VOLUME ONE HUNDRED AND SEVENTEEN...VOLUME ONE HUNDRED AND SEVENTEEN ADVANCES IN IMMUNOLOGY Edited by FREDERICK W. ALT Howard Hughes Medical Institute, Boston, Massachusetts, USA AMSTERDAM

VOLUME ONE HUNDRED AND SEVENTEEN

ADVANCES IN

IMMUNOLOGY

ASSOCIATE EDITORSK. Frank AustenHarvard Medical School, Boston, Massachusetts, USA

Tasuku HonjoKyoto University, Kyoto, Japan

Fritz MelchersUniversity of Basel, Basel, Switzerland

Jonathan W. UhrUniversity of Texas, Dallas, Texas, USA

Emil R. UnanueWashington University, St. Louis, Missouri, USA

VOLUME ONE HUNDRED AND SEVENTEEN

ADVANCES IN

IMMUNOLOGY

Edited by

FREDERICK W. ALTHoward Hughes Medical Institute,Boston, Massachusetts, USA

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CONTENTS

Contributors vii

1. Mechanisms of Epigenetic Regulation of LeukemiaOnset and Progression 1

Panagiotis Ntziachristos, Jasper Mullenders, Thomas Trimarchi, and

Iannis Aifantis

1. Introduction 22. Aberrant DNA Methylation in Leukemia 63. Disruption of Histone-Modifying Complexes Polycomb

and MLL in Leukemia 144. Other Epigenetic Writers, Erasers, and Readers 195. Novel Aspects and Technologies in Epigenetics: Implications

for Leukemia 25Acknowledgments 27References 28

2. Translocations in Normal B Cells and Cancers: Insightsfrom New Technical Approaches 39

Roberto Chiarle

1. Mechanistic Elements that Generate Chromosomal Translocations 402. Novel High-Throughput Methods to Study Chromosomal Translocations 503. New Findings on Translocation Formation Obtained by HTGTS and TC-Seq 524. Landscape of Translocations in Cancers 575. Perspectives 63Acknowledgments 64References 64

3. The Intestinal Microbiota in Chronic Liver Disease 73

Jorge Henao-Mejia, Eran Elinav, Christoph A. Thaiss, and Richard A. Flavell

1. Introduction 742. Role of the Intestinal Microbiota on Chronic Liver Diseases 753. Role of the Interactions Between the Innate Immune System and the Intestinal

Microbiota on Chronic Liver Diseases 814. Probiotics and their Potential Role in Liver Disease Therapy 89

v

5. Conclusions 90References 91

4. Intracellular Pathogen Detection by RIG-I-Like Receptors 99

Evelyn Dixit and Jonathan C. Kagan

1. General Principles of the Antiviral Innate Immune Response 992. RLRs are RNA Sensors 1013. RIG-I Activation and Receptor Proximal Signal Propagation 1094. Regulatory Mechanisms of RIG-I Signaling 1135. Conclusions and Future Directions 117Acknowledgments 118References 118

Index 127Contents of Recent Volumes 133

vi Contents

CONTRIBUTORS

Iannis Aifantis

Howard Hughes Medical Institute; Department of Pathology, New York University School

of Medicine; NYU Cancer Institute, New York University School of Medicine, and Helenand Martin S. Kimmel Stem Cell Center, New York University School of Medicine,New York, USA

Roberto Chiarle

Department of Pathology, Children’s Hospital Boston and Harvard Medical School, Boston,Massachusetts, USA, and Department of Molecular Biotechnology and Health Sciences,

University of Torino, Italy

Evelyn Dixit

Harvard Medical School and Division of Gastroenterology, Boston Children’s Hospital,

Boston, Massachusetts, USA

Eran Elinav

Immunology Department, Weizmann Institute of Science, Rehovot, Israel

Richard A. Flavell

Department of Immunobiology, Yale University School of Medicine, New Haven,Connecticut, and Howard Hughes Medical Institute, Chevy Chase, Maryland, USA

Jorge Henao-Mejia

Department of Immunobiology, Yale University School of Medicine, New Haven,Connecticut, USA

Jonathan C. Kagan

Harvard Medical School and Division of Gastroenterology, Boston Children’s Hospital,Boston, Massachusetts, USA

Jasper Mullenders

Howard Hughes Medical Institute; Department of Pathology, New York University Schoolof Medicine; NYU Cancer Institute, New York University School of Medicine, and Helen

and Martin S. Kimmel Stem Cell Center, New York University School of Medicine,New York, USA

Panagiotis Ntziachristos

Howard Hughes Medical Institute; Department of Pathology, New York University Schoolof Medicine; NYU Cancer Institute, New York University School of Medicine, and Helenand Martin S. Kimmel Stem Cell Center, New York University School of Medicine,

New York, USA

Christoph A. Thaiss

Immunology Department, Weizmann Institute of Science, Rehovot, Israel

Thomas Trimarchi

Howard Hughes Medical Institute; Department of Pathology, New York University Schoolof Medicine; NYU Cancer Institute, New York University School of Medicine, and Helen

and Martin S. Kimmel Stem Cell Center, New York University School of Medicine,New York, USA

vii

Intentionally left as blank

CHAPTER ONE

Mechanisms of EpigeneticRegulation of Leukemia Onsetand ProgressionPanagiotis Ntziachristos*,†,‡,},1, Jasper Mullenders*,†,‡,},1,Thomas Trimarchi*,†,‡,}, Iannis Aifantis*,†,‡,},2*Howard Hughes Medical Institute, New York, USA†Department of Pathology, New York University School of Medicine, New York, USA‡NYU Cancer Institute, New York University School of Medicine, New York, USA}Helen and Martin S. Kimmel Stem Cell Center, New York University School of Medicine, New York, USA1These authors contributed equally to this work2Corresponding author: e-mail address: [email protected]

Contents

1. Introduction 21.1 Leukemia as a heterogeneous and multifactorial disease 21.2 Epigenetic factors and their possible roles in leukemia 4

2. Aberrant DNA Methylation in Leukemia 62.1 The role of DNA methylation in hematopoietic malignancies 62.2 The role of DNMT3A in leukemia 72.3 The biology of TET proteins and their perturbations in leukemia 102.4 IDH1 and IDH2 oncometabolic proteins 12

3. Disruption of Histone-Modifying Complexes Polycomb and MLL in Leukemia 143.1 PRC2 in hematological neoplasms 143.2 Role of PRC1 in leukemia 173.3 MLL function 17

4. Other Epigenetic Writers, Erasers, and Readers 194.1 Arginine methyltransferases 194.2 Lysine demethylases (KDMs) 214.3 Histone demethylases inhibitors (KDMi) 224.4 Histone acetyl transferases 224.5 Histone deacetylases 234.6 Bromodomain-containing proteins 244.7 Plant homeodomain-containing proteins 244.8 Chromatin remodeling complexes 25

5. Novel Aspects and Technologies in Epigenetics: Implications for Leukemia 255.1 Combinatorial epigenetic marks 255.2 Novel aspects of regulation and epigenetic factors in cancer 26

Acknowledgments 27References 28

Advances in Immunology, Volume 117 # 2013 Elsevier Inc.ISSN 0065-2776 All rights reserved.http://dx.doi.org/10.1016/B978-0-12-410524-9.00001-3

1

http://dx.doi.org/10.1016/B978-0-12-410524-9.00001-3

Abstract

Over the past decade, it has become clear that both genetics and epigenetics play pivotalroles in cancer onset and progression. The importance of epigenetic regulation in propermaintenance of cellular state is highlighted by the frequent mutation of chromatin mod-ulating factors across cancer subtypes. Identification of these mutations has created aninterest in designing drugs that target enzymes involved in DNA methylation and post-translational modification of histones. In this review, we discuss recurrent genetic alter-ations to epigenetic modulators in both myeloid and lymphoid leukemias.Furthermore, we review how these perturbations contribute to leukemogenesis andimpact disease outcome and treatment efficacy. Finally, we discuss how the recentadvances in our understanding of chromatin biology may impact treatment of leukemia.

1. INTRODUCTION

1.1. Leukemia as a heterogeneous and multifactorialdisease

Hematopoietic malignancies are a broad category of diseases (Gilliland,

2001). Leukemia is one of the most aggressive among them and is charac-

terized as the abnormal proliferation of immature cells of the hematopoietic

system. Different types of leukemias can arise from lymphocytes (lympho-

cytic leukemia), myeloid cells (myeloid leukemia), erythrocytes (erythro-

cytic leukemia), and others in the bone marrow, lymph nodes, or spleen.

Regardless of the cell type of origin, leukemia generally proceeds in either

a chronic or an acute manner. Chronic disease consists of a long incubation

period, whereas acute leukemia is associated with an abrupt accumulation of

immature blood cells in the peripheral blood, bone marrow, and secondary

lymphoid organs. Certain disorders are marked by both a chronic and acute

phases, which are categorized based on several factors. Among the most

common forms of leukemia are two chronic variants, chronic myeloid

leukemia (CML) and chronic lymphoblastic leukemia (CLL), and two acute

variants, acute lymphoblastic leukemia (ALL) and acute myeloid leukemia

(AML). We briefly review these disease types below.

1.1.1 Chronic myeloid leukemiaCML is a unique case of leukemia that is characterized by the presence of the

Philadelphia chromosome. This reciprocal translocation between chromo-

somes 9 and 22 leads to the formation of a chimeric protein consisting of the

breakpoint cluster region (BCR) gene with the abelson kinase (ABL1) gene.

2 Panagiotis Ntziachristos et al.

The resulting Bcr-Abl oncogene is characterized by constitutive tyrosine

kinase activity leading to activation of downstream targets (Bartram et al.,

1983; Druker, 2008). The current standard of care for CML is the

small-molecule kinase inhibitor Imatinib, a very specific inhibitor of the

Bcr-Abl fusion protein. Treatment with Imatinib results in a 5-year progres-

sion free survival rate of approximately 89% (Druker et al., 2006). Resistance

to Imatinib occurs in certain cases usually through mutations in the Imatinib

binding site in Bcr-Abl (Deininger, Goldman, & Melo, 2000; Holtz,

Forman, & Bhatia, 2005). It is also worth noting that Imatinib does not erad-

icate the disease, as it apparently does not target the CML leukemia-

initiating cells (LICs).

1.1.2 Acute myeloid leukemiaAML is the most common acute leukemia and its incidence increases with

age (Daver &Cortes, 2012). AML can either occur de novo or be preceded by

a premalignant state. Several preleukemic conditions exist (Byrd et al., 2002)

which have the potential to progress to AML. Myelodysplastic syndromes

(MDS) or -myeloproliferative neoplasms (MPN) are characterized by a

block in differentiation leading to accumulation of myeloid progenitor

cells. Included in MDS and MPN are refractory anemia (RA), chronic

myelomonocytic leukemia (CMML), polycythemia vera (PV), essential

thrombocytosis (ET), and myelofibrosis (MF). Around one-third of the

MDS cases progresses and gives rise to AML.

AML is a heterogeneous disease that can be classified in as many as seven

subtypes (de Jonge, Huls, & de Bont, 2011). These subtypes are character-

ized by a variety of cytogenetic and cell surface markers. Unlike CML, there

is no unifying way of treating AML patients. In general, AML is treated with

an array of chemotherapeutic drugs; in some cases, chemotherapy is

followed by bone marrow transplantation. Overall, AML can be very hard

to treat, resulting in a relatively high mortality, which is reported to account

approximately to 10,000 deaths per year in the United States.

1.1.3 Acute lymphoblastic leukemiaALL is an acute disorder of either B-lymphocytes (B-ALL) or

T-lymphocytes (T-ALL). ALL is the most common form of cancer in chil-

dren (Pui & Evans, 2006). The genetics of ALL are quite complex and are

comprised of a variety of chromosome fusions. Similar to AML, these chro-

mosome fusions can be used to distinguish different subtypes of disease,

which are associated with distinct clinical features and outcome.

3Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression

In T-ALL, the most common genetic event is the activation of the

Notch pathway. Mutations leading to enhanced Notch signaling are present

in more than 50% of patients (Aifantis, Raetz, & Buonamici, 2008). This can

be explained by the fact that in thymic development, signaling through the

Notch receptor promotes cell cycle progression and proliferation and

Notch1 therefore acts as a proto-oncogene in this setting.

Treatment of ALL especially in children has become very effective, lead-

ing to cure rates as high as 80% (Chessells et al., 2003; Rivera et al., 2005).

This is mainly achieved by the use of advanced chemotherapy regimen.

Although this is an outstanding clinical achievement, novel less toxic

treatments should still be pursued.

1.1.4 Chronic lymphocytic leukemiaChronic lymphocytic leukemia (CLL) is the most common type of adult

leukemia (Cramer & Hallek, 2012). CLL is a disease of the B-cell lympho-

cytes that is characterized by a very slow progression. The incidence of CLL

increases with aging. Progression of the disease can be at such a low rate that

treatment is sometimes postponed till later stage. As in the leukemias

described above, chromosomal aberrations and gene mutations (including

mutations in the NOTCH pathway) are common in CLL. And, again, these

genetic variants also determine disease outcome.

1.2. Epigenetic factors and their possible roles in leukemiaThe focus of this review is the regulation and deregulation of epigenetic pro-

cesses in different types of leukemia. The term epigenetics was coined by

C.H. Waddington in the 1940s and is a fusion of words “genetics” and

“epigenesis.” The major meaning of epigenesis at that time was that the

embryo gradually changes into the adult organism in contrast to the preva-

iling idea of that era that the adult is preformed at the embryo stage. A more

modern definition of epigenetics has been proposed as “a change in the state

of expression of a gene that does not involve a mutation, but that is never-

theless inherited in the absence of the signal (or event) that initiated the

change” (Ptashne, 2007). The term is used for phenomena such as genomic

imprinting, paramutation, polycomb complex-mediated gene silencing, and

position effect variegation. Model organisms have proven to be incredible

tools to obtain insight in epigenetic phenomena. For instance, Drosophila

development allows the study of stem cells that are responsible for the

formation of adult structures in the fly.


Epigenetic phenomena must fit at least one of the following three criteria

(Bonasio, Tu,&Reinberg, 2010): (i) amechanism for propagation, the signal

must be propagated through DNA replication/cell division; (ii) the signal

must be transmitted to the progeny; and (iii) the signal should affect gene

expression. Among, the modifications that fit these criteria are histone

modifications, histone variants, DNA methylation, relative nucleosomal

position, and occupancy and larger chromatin domains (Margueron &

Reinberg, 2010). To date,DNAmethylation is the only epigeneticmark that

fulfills all three criteria. Many different mechanisms have been proposed that

would explain the propagation and transmission of histone marks, or the

histone variants; however, these processes are not completely understood

currently and require further investigation (Bonasio et al., 2010).

Recently, it has become clear that disruption of epigenetic processes con-

tributes to leukemic transformation. Traditionally, mutations in leukemia

were thought to involve two discreet classes of genes. One class contains genes

whosemutation can give a proliferation or survival advantage to the cell and is

not specific to the hematopoietic system. This would include components of

RAS-MAPK signaling, PI3-kinase/AKT signaling, and others. A second class

of genes mutated in leukemia consists of regulators of hematopoiesis which do

not necessarily give a growth or survival advantage but result in differentiation

defects (Gilliland, 2001; Shih, Abdel-Wahab, Patel, & Levine, 2012).

Although epigenetic regulators often do not belong to either of these two clas-

ses of genes, they are nonetheless frequently mutated in leukemia. This is

exemplified by the translocations that are commonly found in leukemia

and affect mixed lineage leukemia (MLL), polycomb repressive complex 2

(PRC2), or the ten-eleven translocation (TET ) family. It has been proposed

that deregulation of epigenetic factors can provide a tumor cell the plasticity

needed to adapt to different situations. Similarly, it is thought that perturbation

of epigenetic regulators prior to full transformation may be a priming event

that allows a more permissive environment for leukemogenesis upon acqui-

sition of additional mutations (Feinberg, 2007). Apart from the enzymes that

catalyze the histone or DNAmodifications (epigenetic writers), there are pro-

teins that specifically bind modified histone residues (readers), as well as

enzymes that remove covalent modifications (erasers). There are enzymes

containing the appropriate domains for both reading andwriting of the marks.

Mutations that alter enzymatic function can be found in all these types of

chromatin-interacting proteins.

In this review, we will discuss the major perturbations to epigenetic pro-

cesses found in leukemia. For purposes of clarity, we will divide this review


into three sections comprising the following: (1) DNAmethylation; (2) pol-

ycomb andMLL complexes and their roles in physiology and disease; and (3)

other epigenetic modulators, with an emphasis on the ones that are mutated

in leukemia. Moreover, novel therapeutic options will be mentioned

throughout the review, such as inhibitors of epigenetic modulators and their

combinations with current therapies. Finally, emerging technologies and

biological paradigms and how the potential for novel-targeted therapies will

be discussed. Of course, the field is enormous and this review cannot cover

every aspect of epigenetic regulation in leukemia; we thus apologize to our

colleagues for any potential omissions.

2. ABERRANT DNA METHYLATION IN LEUKEMIA

2.1. The role of DNA methylation in hematopoieticmalignancies

DNA methylation is the most common epigenetic modification. Methyla-

tion of CpG islands in the promoters of genes is generally associated with

reduced expression from that locus. CpG islands can be at least 200 bases

in size with a GC content of at least 50%. CpG dinucleotides are quite rare

in mammalian genomes (!1%) (Esteller, 2008), despite which about 60% of

human promoters contain CpG islands. Although the majority of CpG

islands are unmethylated, a small percentage (!6%) becomes methylated

in a tissue-specific manner during early development or in differentiated tis-

sues (Straussman et al., 2009). Besides CpG island methylation in the pro-

moter, DNA methylation of the gene body is common. This is mainly seen

in ubiquitously expressed genes and is positively correlated with gene

expression (Hellman & Chess, 2007). It has been proposed that gene body

DNA methylation might increase elongation efficiency and prevent

spurious initiation of transcription (Zilberman, Gehring, Tran, Ballinger, &

Henikoff, 2007).

Aberrant methylation patterns are considered to be one of the character-

istics of the cancer epigenome (Laird & Jaenisch, 1996). In general, global

DNA hypomethylation is observed which can lead to chromosomal insta-

bility (Eden, Gaudet, Waghmare, & Jaenisch, 2003; Gaudet et al., 2003;

Holm et al., 2005; Nishigaki et al., 2005). This general hypomethylation

can lead to aberrant activation of oncogenes such as cyclin D2 and maspin

(Oshimo et al., 2003). On the other hand, hypermethylation of the pro-

moters of tumor-suppressor genes such as retinoblastoma 1, CDKN2A (also

known as cyclin-dependent kinase inhibitor p16), the von Hippel–Lindau


tumor suppressor, and MutL protein homologue 1 can lead to aberrant

silencing (Esteller, 2007; Herman & Baylin, 2003; Jones & Baylin, 2002).

Therefore, it is not surprising that DNA methyltransferase (DNMT)

enzymes, which catalyze the addition of a methyl group to CpG dinucleo-

tides, play key roles in development and disease. DNMT1 is considered to

be the maintenance methyltransferase and can act on unmethylated DNA.

DNMT3A and DNMT3B are the de novo DNMTs, whereas DNMT3-like

lacks catalytic activity but acts as cofactor for DNMT3A/B and interacts and

colocalizes with them in the nucleus.

Only recently, it became clear that mutations in DNMT3A are common

in AML (Ley et al., 2010; Yan et al., 2011). Moreover, there has been an

advent of specific DNMT inhibitors that are used against MDS with very

encouraging results (Dawson & Kouzarides, 2012).

2.2. The role of DNMT3A in leukemia

2.2.1 DNMT3A mutations in hematopoietic malignanciesMutations in DNMT3A (Fig. 1.1) were reported in approximately 20% of

cases of AML of various subtypes (Ley et al., 2010). Identical mutation per-

centages were found in the AML-M5 subtype that is classified as acute

monocytic leukemia (Yan et al., 2011). In addition, it was reported that

DNMT3A is mutated in other hematopoietic malignancies albeit at a lower

frequency (Thol et al., 2011;Walter et al., 2011).DNMT3Amutations seem

not to be restricted to leukemias from the myeloid lineage, as recently muta-

tions have also been found in T-cell lymphoma and T-ALL (Couronne,

Bastard, & Bernard, 2012; Simon et al., 2012). In pediatric AML, however,

mutations in DNMT3A have not been found, despite the sequencing and

analysis of a cohort consisting of 180 patients (Ho et al., 2011).

2.2.2 Functional consequence of DNMT3A mutationsSo far, mutations identified in DNMT3A are found to be exclusively

heterozygous. Specifically, a very clear hotspot can be identified for

DNMT3A mutations, as around 50% of the mutations occur in residue

R882 (Ley et al., 2010). In vitro experiments showed that AML-linked

mutations in DNMT3A lead to a severe loss of enzymatic activity. How-

ever, as DNMT3A is one of two de novo DNMTs in the human genome,

it is unclear what the molecular consequence of DNMT3A mutations is.

One study compared the DNA methylation status of DNMT3A mutant

versus wild-type AML samples. This revealed that, as expected, some


CpG

CpG CpG CpG

CpG CpG CpG

CpG CpG CpG

IDH1 or IDH2

OO

OHO

OH

OH

OH

Isocitrate

O

O

OH

OH

O

Oxoglutarate O

OOH

OH

OH

MutantIDH1 or IDH2

2-Hydroxyglutarate

N

N

O

H

DNMTs

N

N

O

H

TETs

N

N

NH2

O

H

OH

Oxoglutarate Succinate+ +

A

RNAP2

RNAP2

DNMTDNMT

DNMT

CpG

CpG

RNAP2

TET2TET2 TET2

?Unmodified CpG island

Methylated CpG island

Hydroxy methylated CpG island

B(i)

(ii)

(iii)

NH2

CH3

NH2

X

Figure 1.1 The role of DNA methylation in leukemia. (A) Wild-type IDH convertsisocitrate to oxoglutarate. Mutations in IDH1 and 2 as found in myeloid leukemiaschange the activity of the enzyme. Mutant IDH converts oxoglutarate to2-hydroxyglutarate. Oxoglutarate is a cofactor to dioxygenases like the TET proteins.TET proteins convert 5-methylcytosine to 5-hydroxymethylcytosine. This potentiallyleads to a demethylation of the DNA, which will permit transcription from a previouslysilent locus. (B) Overview of the effect of the different enzymes that regulate DNAmeth-ylation. When CpG islands are unmethylated, transcription can occur from that locus.(i) DNMT enzymes methylate CpG islands in the promoter, this leads to repression oftranscription from this locus. (ii) TET proteins can oxidize the methylcytosine to5-hydroxymethylcytosine. (iii) The outcome of this reaction is not yet fullyunderstood, but it is suggested that this leads to demethylation permits transcription.

CpG islands in promoters indeed become hypomethylated. In AML samples

with mutant DNMT3A, a lower level of methylation of CpG islands in the

HoxA-gene cluster was detected. In addition, there was a clear correlation

with increased expression of the HoxA genes, which leads to a less differen-

tiated phenotype (Yan et al., 2011).

2.2.3 Mouse models of DNMT3 functionInitially, no apparent hematopoietic stem cell (HSC) differentiation defect

was observed in mice mutant for either DNMT3A or DNMT3B

(Tadokoro, Ema, Okano, Li, & Nakauchi, 2007). It was found that cells

deficient forDNMT3A orDNMT3B could still give rise to a variety of pro-

genitors. In addition, it was shown that HSCs depleted for both DNMT3A

and DNMT3B could not reconstitute hematopoiesis of a recipient animal.

After the identification of the DNMT3A mutations in AML, Challen et al.

(2012) further examined theDNMT3A knockout phenotype. In this case, it

was found that loss of DNMT3A led to decreased differentiation of mouse

HSCs. This phenotype could be correlated with higher expression of genes

that are involved in maintaining multipotency of HSCs. Strikingly, when

comparing methylation patterns in wild type and DNMT3A mutant cells,

no significant changes were found in overall DNA methylation. However,

further analysis of specific loci revealed that some genes were hypo- while

others were hypermethylated in DNMT3A knockout animals. Genes that

were found to be hypomethylated and consequently higher expressed

include the well-known HSC homeostasis genes RUNX1 and GATA3.

2.2.4 Is mutant DNMT3A a prognostic marker in myeloid leukemia?The genetics of AML are very complex, but, nevertheless, it has been reported

that themutation status ofDNMT3A by itself is a significant prognosticmarker

for disease outcome in AML (Ley et al., 2010; Marcucci et al., 2012; Ribeiro

et al., 2012). Common genetic lesions co-occurring with mutant DNMT3A

are mutations in NPM1 and FLT3. Especially, the combination of an FLT3-

ITDmutation combined with mutantDNMT3A seems to be associated with

unfavorable outcome in this disease (Patel et al., 2012). Moreover, one report

showed that patients with DNMT3A mutations could benefit from higher

than normal dose of chemotherapy (Daunorubicin) (Patel et al., 2012).

2.2.5 DNMT inhibitorsCurrently, two DNMT inhibitors, vidaza (5-azacytidine) and decitabine

(5-aza-2-deoxycytidine), are approved for the treatment of cancer patients.

Both vidaza and decitabine are analogues of the nucleotide cytosine.


The relatively low side effects make these DNMT inhibitors the drug of

choice for the treatment of MDS. However, in the more advanced

AML, the use of decitabine is debated and is reported to have very little

effect. Nevertheless, combination of inhibitors for histone deacetylases

(HDACs) with DNMTi has given even more very promising outputs

(Gore, 2011).

Another preliminary study used a small cohort of patients in which it

seems that DNMT3A mutant AMLs are more sensitive to the DNA meth-

ylation inhibitor Decitabine (Metzeler et al., 2012). The mechanism behind

these responses is currently unknown.

2.3. The biology of TET proteins and their perturbationsin leukemia

2.3.1 TET proteinsIn a search for proteins that are homologous to the J-binding proteins from

the parasite leishmania, the only homologous proteins identified in the

human genome were the TET proteins (Tahiliani et al., 2009). J-binding

proteins were known for their capacity to bind a modified DNA base, base

J that is unique for the parasite. Base J is a glycosylated derivative of the base

thymidine. This suggested a role for the TET proteins in modifying DNA

directly. Indeed, further studies showed that in TET proteins resides the cat-

alytic activity to modify 5-methylcytosine to 5-hydroxymethylcytosine

(5-hmC) (Tahiliani et al., 2009).

Soon after this finding, Delhommeau et al. (2009) reported frequent

mutations of TET2 in AML again suggesting a key role for DNA methyl-

ation in leukemogenesis. Some of these mutations were later verified to be

true loss-of-function variants (Ko et al., 2010); however, the role of 5-hmC

in tumor development remains to be fully appraised. A variety of technical

issues have hampered the study of TET2 and 5-hmC in leukemia. The lack

of a TET2 antibody, for instance, has made it difficult to study its genomic

occupancy. However, recent technical advances have made genome-wide

5-hmC profiling possible with base-pair resolution (Booth et al., 2012;

Yu et al., 2012).

2.3.2 Mutational status of TET proteins in leukemiaFirst identified as a gene (TET1) in a chromosomal translocation in AML,

it took some time to appreciate the importance of the TET proteins in

leukemia. The initial report described a fusion between chromosomes


10 and 11 in AML that lead to a chimeric protein consisting of the MLL

amino(N)-terminus and the carboxyl(C)-terminus of TET1 (Lorsbach

et al., 2003). In addition, despite the fact that fusions and deletions in

chromosome 4 were detected in a number of AML patients (Viguie

et al., 2005), it was only later understood that a single gene was present

in this locus. The gene product showed a high level of sequence conser-

vation with the previously identified TET1 protein and was therefore

named TET2. Further analysis of the human genome identified one more

protein homologous to both TET1 and TET2, that is, TET3 (Delhommeau

et al., 2009). Fusions of TET1 and deletions of the TET2 locus indicated an

important role of the TET proteins in hematopoietic malignancies. And,

indeed, sequencing efforts confirmed that TET2 (Fig. 1.1) is a commonly

mutated gene in myeloid leukemia and premalignant stages of leukemia. So

far, TET2 mutations have been found in AML, CMML, MDS, and other

myeloid malignancies. The largest studies suggest that TET2 mutations can

be identified in 2–10% of PV and ET patients, and in 10–20% of patients with

primaryMF or post-PV/ETMF (Abdel-Wahab et al., 2010, 2009; Cimmino,

Abdel-Wahab, Levine, & Aifantis, 2011; Tefferi et al., 2009). In addition,

studies of paired MPN and AML samples from individual patients demon-

strated that TET2 mutations are commonly acquired during transformation

to AML from a chronic myeloid neoplasm (Abdel-Wahab et al., 2010). Sur-

prisingly, mutational analysis of bothTET1 andTET3 has not been as fruitful.

Mutations in TET1 and TET3 have been reported in patients with CLL, but

the overall incidence of these mutations is currently unknown (Quesada et al.,

2012). One of the few studies that carefully investigated the status of all

the three TET family members in myeloid malignancies found only TET2

and not TET1 nor TET3 mutated (Abdel-Wahab et al., 2009). Recently,

TET2 has been found to be also mutated in lymphoid neoplasms

(Couronne et al., 2012; Quivoron et al., 2011). Finally, recent studies

point to a role for TET proteins in solid tumors, as sporadic mutations have

been identified in brain (Parsons et al., 2011) and prostate cancers (Grasso

et al., 2012).

2.3.3 Consequence of TET2 mutations in AMLThemajority of our knowledge of the TET proteins comes from studies per-

formed in nonhematopoietic cells. For instance, one study that sheds light on

how TETs could be involved in active DNA methylation was performed in

the brain (Guo, Su, Zhong, Ming, & Song, 2011). The proposed mechanism


involves activation-induced (cytidine) deaminase (AID) and APOBEC

proteins, which promote the conversion of 5-hmC into an unmodified cyto-

sine and thereby lead to active demethylation of the DNA. If this mechanism

were proven to be universal, the consequence of loss of TET2 functionwould

be increased DNA methylation. This does pose some sort of a conundrum as

we have discussed earlier that loss-of-function mutations in DNMT3A are

common in AML. So far, however, it is not clear what happens on the level

of DNA methylation in TET2 mutant cells. There is conflicting evidence in

the literature reporting that TET2 loss could lead to either increased or

decreased DNA methylation (Figueroa et al., 2010; Ko et al., 2010).

2.3.4 TET2 mouse modelsSeveral research groups, including ours, have modeled the loss of TET2 in

the hematopoietic system (Li et al., 2011; Moran-Crusio et al., 2011;

Quivoron et al., 2011). In all cases, the loss of TET2 leads to a decrease

in 5-hmC levels as expected. Deletion of TET2 in the HSC compartment

causes an increase in self-renewal capacity. During the maturation of the

TET2 knockout animals, an increase in the frequency of both myeloid

and lymphoid cells can be observed. This premalignant state develops into

a myeloproliferative neoplasm as the mice become older; this results in

splenomegaly and either an MDS or a CMML-like disease.

2.4. IDH1 and IDH2 oncometabolic proteins

2.4.1 IDH1 and IDH2 mutations in leukemiaThe isocitrate dehydrogenase (IDH) enzymes are NADP-dependent mole-

cules that normally function as homodimers to catalyze the oxidative decar-

boxylation of isocitrate to alpha-ketoglutarate (a-KG) with the concomitant

production of NADPH. Mutations in IDH1 and IDH2 are important for

our discussion for two reasons. First, the mutations occur in a hotspot

resulting in the alteration of the enzymatic activity of the enzyme. Second,

inhibition of TET2 seems to be part of the mechanism by which mutations

in IDH1 and IDH2 cause leukemia (Figueroa et al., 2010). The first indica-

tion that the IDH enzymes were involved in carcinogenesis came from a

study in gliomas (Yan et al., 2009). Strikingly, it was found that nearly all

mutations occur in a couple of residues in either IDH1 (R132) or IDH2

(R140 or R172) (Fig. 1.1). Not much later mutations in IDH1 and

IDH2 were detected in hematopoietic malignancies. Especially, mye-

loid malignancies are reported to have mutations in either IDH1 or


IDH2 at a rate of around 9% (Green & Beer, 2010; Ward et al., 2010). In

particular, mutations have been reported in MDS and MPN (Kosmider

et al., 2010).

2.4.2 Consequence of IDH mutationsAs mentioned above, mutations in the IDH1 and IDH2 proteins occur in

the protein catalytic site. Wild-type IDH enzymes can convert isocitrate

to a-KG. IDH1 is predominantly cytoplasmic, while IDH2 can be found

in the cell mitochondria. So far, only heterozygous IDH mutations have

been found, leaving one allele intact. One very exciting finding was the fact

that mutations in IDH proteins do not abrogate its enzymatic function but

change the outcome of its reaction toward isocitrate. Mutant IDH proteins

have a much higher output of 2-hydroxyglutarate (2-HG) at the expense of

a-KG (Ward et al., 2010). 2-HG is an oncometabolite that can be used as a

marker to distinguish wild-type IDH from mutant IDH cancers. At the

molecular level, this also somehow explains how mutations in an enzyme,

so critical for cellular homeostasis, can be tolerated. Mutations in IDH1 and

IDH2 seem to have similar effects on the enzyme function. It is therefore not

surprising that mutations in IDH1 and IDH2 are mutually exclusive.

Recent studies showed a role for oncometabolites, such as 2-HG, in the

function of epigenetic modulators (Teperino, Schoonjans, & Auwerx, 2010).

Under normal conditions, a-KG is produced in the trichloroacetic acid (TCA)

cycle from isocitrate and is a cofactor for dioxygenases. Among these

dioxygenases are the Jumonji-domain-containing histone demethylases, as

well as the Tet family of hydroxymethylases. As we have discussed earlier,

mutations in IDH1 and IDH2 lead to the increased production of 2-HG, lead-

ing to reduced catalytic activity of certain dioxygenase enzymes. In an elegant

study, this hypothesis was proven (Figueroa et al., 2010). First, it was shown

that DNA isolated from IDH mutant AMLs is more hypermethylated. Sec-

ond, it was shown that mutations in IDH proteins inhibit the conversion

of 5-mC into 5-hmC by TET proteins. This observation is supported by

the fact that TET2 and IDH mutations are mutually exclusive in AML

(Figueroa et al., 2010). Other enzymes that are affected by IDH mutations

are the histone demethylases, especially the H3K9me3 demethylase KDM4C

(Lu & Thompson, 2012; Lu et al., 2012; Turcan et al., 2012).

Along these lines, it is possible that mutations of other enzymes in the

TCA cycle can cause similar effects. Examples of these are loss-of-function

mutations in the enzymes succinate dehydrogenase and fumarate hydratase

(Kaelin, 2011).


2.4.3 Animal models for IDH gene functionVery recently, the IDH1mutation commonly found in AML (R132H) was

modeled in a mouse (Figueroa et al., 2010). This mutation was created in a

conditional fashion in one of the endogenous IDH1 alleles. This murine

model showed that mutant IDH1 is indeed sufficient to disrupt the hema-

topoietic system homeostasis. IDH1 mutant mice show extra medullary

hematopoiesis and a loss of cells from the bone marrow. This phenotype

is associated with an increase in methylation of both DNA and histones.

3. DISRUPTION OF HISTONE-MODIFYING COMPLEXESPOLYCOMB AND MLL IN LEUKEMIA

Posttranslational modification of N-terminal histone tails is a more

recently appreciated mechanism of regulation of gene expression patterns

in development and disease. Since Jenuwein and Allis (2001) first proposed

the “histone code” hypothesis in 2001, there has been an explosion in

research aimed at cataloging all posttranslational modifications added to

the histones and their distribution across genomes as well as association with

particular transcriptional states (Ernst et al., 2011; Tan, Luo, et al., 2011).

Additionally, many groups have focused on understanding how enzymes

that catalyze or remove these modifications and other proteins with the abil-

ity to “read” histone marks are involved in global regulation of chromatin

states (Shih et al., 2012; Zhou, Goren, & Bernstein, 2011). The importance

of such enzymes in disease development is highlighted by frequent mutation

of many key histone modifiers in human cancer (Abdel-Wahab et al., 2012;

Dawson, Kouzarides, & Huntly, 2012; Ntziachristos et al., 2012; Patel et al.,

2012; Shih et al., 2012; van Haaften et al., 2009; Zhang, Ding, et al., 2012),

including both solid tumors and hematological neoplasms. Deregulation of

mechanisms regulating histone modification seems to have a particularly

important role in leukemic transformation as genetic lesions targeting such

proteins are often considered driver mutations, with potent oncogenic activ-

ity. Here, we will focus on two histone-modifying complexes, the PRC,

including both PRC2 and PRC1, and MLL complexes, which are fre-

quently perturbed in human leukemia of several different blood lineages.

3.1. PRC2 in hematological neoplasmsPRC2 is a large multimeric enzymatic complex that includes the set-

domain-containing methyltransferase EZH2. Other key components

include chromodomain-containing protein EED, SUZ12, and histone


chaperone RBBP4/7 (Margueron & Reinberg, 2011) (Fig. 1.2A). As its

name suggests the main function of this complex is to silence gene expres-

sion at specific loci through catalysis of trimethylation of lysine 27 of histone

3 (H3K27me3). The presence of this mark not only enhances the activity of

PRC2 itself but is also read by the polycomb repressive complex 1 (PRC1),

leading to monoubiquitylation of histone 2A lysine 119 and subsequent

chromatin compaction (Simon & Kingston, 2009). Gene silencing by

PRC2 is critical for establishing proper lineage commitment during devel-

opment by inactivating genes required for alternative cell fates. With a crit-

ical role in nearly every developmental system, it is not surprising that

deregulation of PRC2 function contributes to tumorigenesis (Bracken &

Helin, 2009; Margueron & Reinberg, 2011; Sauvageau & Sauvageau,

2010; Sawarkar & Paro, 2010).

Although components of PRC2 are heavily mutated in many types of

cancer, the consequences of such mutations in leukemia are especially

intriguing with reports of both oncogenic and tumor-suppressor function

A Polycomb repressive complex 2

EZH2

SetEEDJARID2

KDM6BKDM6A

RBBP5

COMPASS-likecomplex

MLL-fusionmethyltransferasecomplex

CDKN2A/BHOXA

ASH2L

WDR5MLL

RNAP2

HOXA

H3K4me3 H3K79me2 H3K27me3

MLLAF9 DOT1L

AF10ENL

CBX8

TIP60

MEIS1

Set

SUZ12

RBBP4/7

EZH2

Nonsense/InDels

MLL protein

MLL-fusion proteins

T-ALLMyeloid disordersDLBCL

Missense

Breakpoint

NH2

ATHooks PHD TACxxC

ATHooks AF-9CxxC

ATHooks AF-4CxxC

ATHooks ENLCxxC

SETNH2

SANT SANT SET

Y64

1

CXC

B

C D

Figure 1.2 Genetic perturbations impacting EZH2 and MLL proteins. (A) EZH2, the cat-alytic subunit of PRC2, represses gene activity by methylation of H3 on lysine 27.(B) Representative distribution of EZH2 mutations reported in T-ALL, myeloid disorders(MDS, MPN, CMML, AML), and DLBCL. (C) The wild-type MLL protein is the catalyticsubunit of mammalian COMPASS-like complexes which enhances gene activitythrough methylation of H3 on lysine 4. MLL-fusion proteins frequently associate withmembers of DotCom to regulatemethylation of H3 on lysine 79. (D) MLL-fusion proteinstypically do not involve the Set methyltransferase domain but rather the N-terminalAT hooks and CxxC domain. Frequent MLL-fusion partners include AF-9, AF-4, and ENL.


of the complex in neoplasms derived from different lineages (Ernst et al.,

2010; Morin et al., 2010) (Fig. 1.2B). Originally suggested to be a

loss-of-function mutation, recurrent mutations in EZH2 residue Y641 have

now been shown to enhance PRC2 activity by cooperating with complexes

containing the wild-type EZH2 protein leading to more efficient catalysis

and hypertrimethylation of lysine 27 of histone 3 (H3K27me3) in follicular

and diffuse large B-cell lymphoma (DLBCL) (McCabe et al., 2012;

Sneeringer et al., 2010; Yap et al., 2011). Conversely, in T-cell acute lym-

phoblastic leukemia (T-ALL), loss-of-function mutations to several PRC2

subunits including EZH2, SUZ12, and EED have been reported to result

in a more aggressive phenotype compared to wild-type tumors

(Ntziachristos et al., 2012; Simon et al., 2012), suggesting a tumor-

suppressor role for the complex in this context. Unlike DLBCL, T-ALL

mutations targeting PRC2 components consist mainly of nonsense muta-

tions upstream of the catalytic domain of EZH2 and larger deletions of

the locus, suggesting a true loss-of-function outcome. Further highlighting

the duality of PRC2 function in hematological tumors, it has been suggested

that within different subtypes of myeloid disease both an oncogenic and a

tumor-suppressor function for this complex exist. Ernst et al. (2010) have

shown loss-of-function EZH2 mutations in MDS and MPN with poorer

overall survival in patients with mutant alleles. However, in mouse models

of MLL-AF9 positive AML, it seems that PRC2 is required for efficient

transformation, suggesting a role for the complex in contributing to aberrant

self-renewal of LICs (Neff et al., 2012; Shi et al., 2012). These results suggest

that proper maintenance of the H3K27me3 modification is critical for

normal cell homeostasis.

Although the results discussed above are compelling, our understanding

of themechanism throughwhich deregulatedH3K27me3might lead to leu-

kemic transformation is very poorly understood. As a tumor suppressor, we

might imagine an antagonistic relationship between PRC2 and oncogenic

transcription factor networks. In diseases driven by transcriptional activators,

we support a model where genes targeted for activation by the oncogenic

factor might in turn be occupied for silencing by PRC2. Thus, loss of

PRC2 function may create a more permissive environment for the activity

of oncogenic transcription factors. As an oncogene, there is evidence that

PRC2 can act to directly repress key tumor-suppressor genes such as the

CDKN1A, CDKN1B (Velichutina et al., 2010), or CDKN2A/CDKN2B

(Chen et al., 2009) loci providing a mechanism of epigenetic silencing in

lieu of genetic inactivation.


Recently, mutations of the protein ASXL1, that is part of the polycomb-

repressive deubiquitylase complex, were identified in human malignancies

(Abdel-Wahab et al., 2012; Shih et al., 2012). This complex catalyzes the

deubiquitination of H2AK119, the modification left by PRC1, suggesting

a possible antagonistic relationship. Surprisingly, inactivation of ASXL1 has

been shown to have a potent effect on PRC2 function leading to global

decreases in H3K27me3 although the mechanism by which this occurs is

unclear. However, loss of ASXL1 and PRC2 function at theHOXA cluster

was shown to correlate with increased HOXA9 expression which is known

to contribute to myeloid transformation (Abdel-Wahab et al., 2012).

3.2. Role of PRC1 in leukemiaLike PRC2, PRC1 has also been suggested to play a role both in mainte-

nance of HSCs and transformation in vivo. However, unlike PRC2, there

are very few reports of mutations in PRC1 complex members in cancer.

Specifically, there are studies showing that PRC1 component BMI1 is

required for normal HSC function and similarly for maintenance of leuke-

mic stem cell function in MLL-rearranged leukemia (Oguro et al., 2012;

Park et al., 2003). It has been proposed in both settings that BMI1 is essential

for maintaining PRC1-mediated suppression of the CDKN2A/CDKN2B

locus, thus allowing cells to evade cellular senescence. Nevertheless, muta-

tions in BMI1 have not been described so far.

3.2.1 Histone methyltransferase inhibitorsChaetocin, deazaneplanocin (DZNep), and BIX-01294 are the best charac-

terized histone methyltransferase inhibitors. All these inhibitors have so far

only been tested in the preclinical environment. However, at this stage,

results are promising; for example, chaetocin has anticancer properties

against multiple myeloma (MM) cells (Greiner, Bonaldi, Eskeland,

Roemer, & Imhof, 2005; Isham et al., 2007). Combination of the PRC2

(EZH2) inhibitor DZNep and a HDAC inhibitor (HDACi) (Panobinostat)

has been shown to kill AML cells in vitro (Fiskus et al., 2009).

3.3. MLL functionTheMLL gene is the human homologue ofDrosophila melanogaster trithorax.

Trithorax was initially described as a regulator of homeotic gene expression

in flies. Now, it has become clear that MLL is a key component of mamma-

lian COMPASS-like complexes, which play critical roles in both embryonic


development and hematopoiesis. COMPASS complexes contain hSET1A

and B, MLL1, MLL2, MLL3, or MLL4 as the catalytic subunit and have

a critical role in activating transcription by catalyzing mono-, di-, and

trimethylation on lysine 4 of histone 3 (H3K3me1, H3K4me2,

H3K4me3). WDR5, RBBP5, and ASH2L are important core subunits that

modulate the action of the methyltransferase (Dou et al., 2006). What

determines the catalytic specificity of the complex regarding the component

constitution is still unknown as deletion of any of the four catalytic subunits

leads to minimal effects in the H3K4me3 levels possibly because of redun-

dancy. However, deletion of the core subunits brings about global loss of

H3K4me3 (Lubitz, Glaser, Schaft, Stewart, & Anastassiadis, 2007;

Wang, Lin, et al., 2009). In this regard, loss of MLL2 in mouse embryonic

stem cells (ESCs) leads to skewed differentiation, but evidence for a

connection to H3K4 methylation is weak (Lubitz et al., 2007). MLL-

deficient ESCs are defective in hematopoiesis (Ernst et al., 2004), but we

do not know if this holds true for MLL3, MLL4, or SET1. Some studies

support the role of the recently characterized DPY-30 protein as a critical

regulator of MLL function (Jiang et al., 2011), although further investigation

is required.

3.3.1 MLL fusions in leukemiaLeukemias harboring 11q23 translocations involving MLL have character-

istic clinical and biological outcomes (Bernt & Armstrong, 2011). MLL-

rearranged leukemias include lymphoid, myeloid, and mixed-phenotype

acute leukemias phenotypes. They are found in >70% of infants with

ALL and in 35–50% of infants with AML. Children with MLL-rearranged

B-ALL exhibit an overall survival of !50% versus an overall survival of

>80% for children that do not harbor the translocation.

MLL rearrangements withmore than 60 translocation partners have been

documented. These translocation partners share no single unifying feature or

functional association. The resulting MLL-fusion proteins contain the

amino-terminal domain of MLL and the carboxy-terminal domain of the

translocation partners. As the fusion proteins no longer contain the MLL

SET domain, the oncogenic action of this chimeric protein is independent

of the H3K4me3 mark. The majority of the MLL-fusion partners are part of

nuclear proteins (Fig. 1.2C). Members of the so-called super elongation

complex (SEC) (AF1, AF9, ENL, ELL, and AF4) are frequent fusion

partners.MLL can also be fused to components of theDot1-containing com-

plex (DotCom) (Mohan, Lin, Guest, & Shilatifard, 2010; Smith, Lin, &


Shilatifard, 2011) such as ENL (Tkachuk, Kohler, & Cleary, 1992) and AF-9

andAF-4 (Gu et al., 1992) (Fig. 1.2D). DOT1L is the catalytic component of

DotCom, which facilitates di- and trimethylation of lysine 79 on histone 3

(H3K79me2, H3K79me3) (Fig. 1.2C). This histone mark is associated with

actively transcribed genes and is essential for transformation by MLL-AF9

(Bernt et al., 2011; Daigle et al., 2011).

Interestingly, cross talk between the MLL-AF9 fusion protein and pol-

ycomb protein CBX8 was recently revealed in leukemia. The essential role

of CBX8 in MLL-AF9-driven leukemia shows that the relationship

between trithorax and polycomb group proteins is not yet fully understood

(Tan, Jones, et al., 2011).

4. OTHER EPIGENETIC WRITERS, ERASERS,AND READERS

Apart from enzymes that directly add or remove epigenetic marks

(writers/erasers), there are proteins that can “read” these marks. These

readers can recruit other proteins that can propagate the signal and subse-

quent repress or activate target genes or bear themselves catalytic activity.

Here, we discuss genetic and posttranslational perturbation of writers,

erasers, and readers and drugs that are used against these proteins in preclin-

ical and clinical settings in leukemia studies (Fig. 1.3A).

4.1. Arginine methyltransferasesThe role of arginine methyltransferases and demethylases in tumorigenesis

is poorly understood and is briefly discussed here. One methyltransferase,

PRMT5, is of particular interest as this protein has been implicated in

myeloproliferative neoplasms (Wysocka, Allis, & Coonrod, 2006;

Zhang & Abdel-Wahab, 2012). It was shown that PRMT5 is

aberrantly phosphorylated by mutant JAK2 (V617F, with increased activ-

ity) leading to decreased methylation of histones H2A and H4 and alter-

ations in gene expression (Liu et al., 2011). Importantly, a specific

inhibitor of the mutant JAK2 (Ruxolitinib) is used against MF. Inversely,

the action of CCND1/CDK4 can lead to increased PRMT5 enzymatic

activity in mouse lymphomas (Aggarwal et al., 2010). A putative role

for PRMTs in cancers is further suggested by the fact that expression levels

of both PRMT1 and 6 have been found to be elevated in different types of

cancer (Yoshimatsu et al., 2011).


PRC2

KDM

Sirtuins HDACs

CpG

CpGCpG CpG

HATs

SIRTiKDMi

KMTi

HDACivorinostat

romidepsin

Lysine methylation

HATi DNMTividaza

decitabine

A

Lysineacetylation

PRMT5 JAK2

(V617F)

Argininemethylation

phosphorylation

JAKiRuxolitinib

Set

DNMT

Nuclear envelope

Alkylating agents

Inhibitors of signal transduction

Cell membrane

Epigenetic inhibitors

Monoclonal antibodies

EGFR

BCR-ABL

DNMTCisplatin

B

Figure 1.3 Major epigenetic modifiers that are genetically affected in leukemia, theirassociated marks and the corresponding inhibitors. (A) Major epigenetic modifiers withthe corresponding inhibitors (marked with the letter i). Inhibitors that are being used forthe treatment of hematopoietic malignancies are shown in red. HDAC (vorinostat andromidepsin) and DNMT inhibitors vidaza (5-azacytidine) and decitabine (5-aza-2-deoxycytidine) are currently used against MDS and CTCL correspondingly. Ruxolitinibis a JAK2 inhibitor used against myelofibrosis. HAT inhibitors, such as curcumin, have


4.2. Lysine demethylases (KDMs)Lysine demethylases are very important for homeostasis and cancer. There

are twomajor families of lysine demethylases. One consists of the amine oxi-

dases and the second of the dioxygenases. Amine oxidation by the LSD fam-

ily of flavin adenine dinucleotide-dependent demethylases (Shi et al., 2004)

represents a type of active demethylation reaction. KDM1A (LSD1), the first

reported histone demethylase (Shi et al., 2004), catalyzes demethylation of

H3K4me1 and H3K4me2 and can also demethylate H3K9me1 and

H3K9me2. KDM1A has also been shown to catalyze the demethylation

of nonhistone targets, such as p53 (Huang et al., 2007) as well as DNMT1

and E2F1 (Wang, Hevi, et al., 2009; Xie et al., 2011).

A second type of demethylation reaction is hydroxylation by

JmjC-domain-containing proteins (Kooistra & Helin, 2012; Tsukada

et al., 2006; Yamane et al., 2006). This broad family contains proteins,

which catalyze demethylation of different histone and nonhistone substrates.

Jumonji (Jarid2), the founding member of this family, lacks catalytic activity

but plays important roles in pluripotency and development by modulating

the PRC2 complex activity. JMJD3 or KDM6B, an H3K27me3

demethylase, has been reported to facilitate transcriptional initiation and

elongation (Chen et al., 2012). UTX (KDM6A) and JMJD3 interact with

the chromatin remodeling complex SWI/SNF (Miller, Mohn, &

Weinmann, 2010), as well as MLL complexes, showing the diversity of

interactions and actions of the group.

The role of lysine demethylases in tumorigenesis has been exemplified by

KDM1A and KDM2B (FBXL10) (Harris et al., 2012; He, Nguyen, &

Zhang, 2011; Schenk et al., 2012). In addition, mutations in the lysine

demethylase UTX, which can remove the H3K27me3 mark, have been

found in human cancers (van Haaften et al., 2009). A recent study focusing

specifically on ALL reported a low frequency of UTXmutations (Mar et al.,

2012). Most of these mutations were found in clinically defined high-risk

patients suggesting possible future therapeutic or prognostic relevance

(Mar et al., 2012).

been used in clinical trials against leukemia and other hematopoietic malignancies.Other inhibitors used in the lab include histone (lysine), methyltransferase (KMTi)and demethylase (KDMi) inhibitors, and sirtuins inhibitors (SIRTi). (B) Recently, differentcombinations of different epigenetic inhibitors, as well as combinations of epigeneticinhibitors with drugs inhibiting signaling transduction pathways, or chemotherapy(such as alkylating agents) are being used in clinical trials.


4.3. Histone demethylases inhibitors (KDMi)The inhibition of histone demethylases as anticancer treatment has great

potential. However, so far, the use of these inhibitors has been restricted to

preclinical studies. For example, recently, it was shown that tranylcypromine

(TCP, a LSD1 inhibitor) has activity against myeloid leukemia cell lines that

are driven by the MLL-AF9 oncogene (Harris et al., 2012).

So far, it has been reported that only acute promyelocytic leukemia

(a subtype of AML) is sensitive to all-trans retinoic acid (ATRA) treatment.

However more recently, in vitro combinatorial use of ATRA and TCP

yielded promising results for other types of AML as well (Schenk et al.,

2012). This further underlines the importance of combinatorial use of drugs

in treatment of leukemia (Fig. 1.3B).

Moreover, it is very encouraging that the advent of new technologies

including high-throughput screens and advanced crystallographic tech-

niques are paving the way to specific drugs, which target structurally similar

molecules that fulfill different functions in the cell. A recent example is the

generation of the first specific inhibitor for the H3K27me3 demethylases

(Kruidenier et al., 2012), which can allow selective pharmacological inter-

vention across the Jumonji family.

4.4. Histone acetyl transferasesThe family of histone acetyl transferases (HATs) consists of epigenetic mod-

ifiers that include CREB-binding protein (CBP), GCN5, and CLOCK.

Mutations that inactivate the action of CBP were recently identified in

ALL (Mullighan et al., 2011) and in B-cell lymphoma (Pasqualucci et al.,

2011). The MOZ (monocytic leukemia zinc-finger protein) and MORF

(MOZ-related factor) HATs are important for different developmental pro-

grams and have been implicated in leukemogenesis and other tumorigenic

processes. In AML, the MOZ gene on chromosome 8p11 is fused to the

CBP gene on 16p13, producing a transcript encoding the fusion protein

MOZ-CBP (Borrow et al., 1996). Interestingly, the MORF gene has been

identified (Champagne et al., 1999) fused to CBP in AML or MDS (Kojima

et al., 2003; Yang & Ullah, 2007).

4.4.1 HAT inhibitorsThree HAT inhibitors (HATi) have been described to date. Curcumin

(Shehzad, Wahid, & Lee, 2010) is broad acting inhibitor that also targets

p300/CBP. Garcinol (Balasubramanyam et al., 2004) and anacardic acid


(Sun, Jiang, Chen, & Price, 2006) are both p300 and KAT2B inhibitors.

These three inhibitors are currently in preclinical development.

4.5. Histone deacetylasesHDACis typically play a repressive role in transcription as they remove the

activating acetylation marks from gene control elements. However, HDACs

have also been detected at the promoters of transcribed genes (Wang, Zang,

et al., 2009). There are four classes of HDACs and three of them depend on

the substrate-Zn chelation in their active site. Sirtuins (Type III HDACs) are

the exception to this rule as they depend on NAD" for their action. No

genetic perturbations affecting HDACs have been described in leukemia

to date. However, differential expression of the HDACs has been associated

with other types of cancer. In the absence of retinoic acid, RARa plays a

suppressive role in transcription through the recruitment of corepressors

such as NcoR, SMRT, Sin3a, and HDACs. The PML-RARa fusion pro-

tein is a stronger repressor than endogenous RARa (Uribesalgo &Di Croce,

2011), thereby warranting the use of HDACis in this scenario.

4.5.1 HDAC inhibitorsHDACis can be chemically classified as short-chain fatty acids, hydroxamic

acids, cyclic peptides, andbenzamidederivatives (Masetti, Serravalle,Biagi,&

Pession, 2011). HDAC inhibition can lead to different outcomes, such as cell

cycle arrest, differentiation, or apoptosis. The most widely used class of

HDACis is the hydroxamic acids,which include trichostatinA and vorinostat

(SAHA). SAHAhas been approved for the treatment of several hematological

malignancies, including cutaneous T-cell lymphoma (CTCL). Another

hydroxamic acid, Panobinostat, is currently being subjected to trials in

CML, refractory CTCL, and MMs (Wolf et al., 2012). Belinostat is another

investigational HDACi and has demonstrated encouraging results in periph-

eral T-cell lymphoma (Copeland, Buglio, & Younes, 2010). In addition,

romidepsin is a cyclic peptide (FK228) approved for CTCL. Benzamide

derivatives (MGCD-0103) are a separate class of investigational drugs, in

clinical development for the treatment of hematological malignancies and

solid tumors. Sirtuin inhibitors have not been comprehensively studied to

date. Cambinol, a sirtuin inhibitor that is structurally unrelated to other

HDACi, has been shown to lead to apoptosis in BCL6-expressing Burkitt’s

lymphoma cells through inhibition of SIRT1 and SIRT2 (Heltweg et al.,

2006). Overall, this is a very big family of inhibitors, having two members

FDA approved for CTCL treatment.


4.6. Bromodomain-containing proteinsAnother family of histone readers is the bromodomain (BRD)-containing

protein family. The BRD recognizes acetylated residues and comprises a

highly conserved, four-helix, left-twisted bundle with a characteristic

hydrophobic cleft between two conserved loops. The BRD is present in

the bromodomain and extra-terminal (BET) proteins as well as in members

of the chromatin remodeling complexes (Snf2), the MLL complex and

members of the SEC (Belkina & Denis, 2012).

Recently, BET domain-containing proteins have been found to play

a key role in the development of MM (Delmore et al., 2011) mainly through

the induction of the c-Myc gene. Another example is MLL-fusion proteins

containing components of the SEC, including PAFc and pTEFb that

contain BET proteins (Dawson et al., 2011). These MLL-fusion proteins

can activate transcription of potent oncogenes, such as BCL2, MYC,

and CDK6.

4.6.1 BRD inhibitorsRecently, James Bradner and his group modified a thienodiazepine mole-

cule so that it inhibited the binding of BRD4 to the acetylated residues

of histone H4 (Filippakopoulos et al., 2010). This so-called JQ1 inhibitor

abruptly inhibits MYC expression and the MYC-associated transcriptional

signatures in MM. InMLL-fusion leukemias (Dawson et al., 2011; Delmore

et al., 2011; Filippakopoulos et al., 2010), inhibition of the BET proteins

with a specific inhibitor (GSK1210151A (I-BET151)) lead to displacement

of BRD3/4 and components of the SEC from chromatin improving the sur-

vival in mouse models of MLL-rearranged leukemia (Dawson et al., 2011).

While BET proteins are involved in broad cellular processes, these two

examples show that their inhibition may actually be feasible as a potential

cancer therapy.

4.7. Plant homeodomain-containing proteinsThe plant homeodomain (PHD) recognizes the various methylation states of

lysine 4 residue on histone 3 (H3K4). In addition, affinity of the PHD for

H3K9me3 has also been documented in the case of JARID1C (Iwase et al.,

2007). JARID1C is a histone demethylase for H3K4me3, which suggests

cross talk between different histone marks.

Translocation of PHD-containing proteins is highly prevalent in hema-

topoietic malignancies (Chi, Allis, &Wang, 2010). Specifically, the PHD of


PHF23 and KDM5A that recognizes H3K4me3/2 has been found to be

fused to the Nucleoporin 98 (NUP98) gene. NUP98 is a nuclear pore

complex component. The NUP98 chimeric protein leads to aberrant

transcriptional activation. The resulting fusion protein inhibits the

removal of H3K4me3 and the repressive action of EZH2 complex

(Wang, Song, et al., 2009).

4.8. Chromatin remodeling complexesIntriguingly, no mutations in chromatin remodeling complexes, such as the

BRG family, have been identified to date in hematopoietic malignancies

(Wilson & Roberts, 2011). This probably suggests that this family has key

roles in cellular physiology and mutations, even heterozygote ones, could

affect key cellular processes.

5. NOVEL ASPECTS AND TECHNOLOGIES INEPIGENETICS: IMPLICATIONS FOR LEUKEMIA

5.1. Combinatorial epigenetic marksRecent progress suggests that the histone marks do not act alone but in

highly concerted combinations. The first example came from studies on

ESCs, where the so-called bivalent domains (Bernstein et al., 2006) consist

of the activating mark H3K4me3 and the repressive mark H3K27me3. Genes

that display these marks are poised for activation or repression and their

levels of transcription are fine-tuned by the relative levels of the two marks

or by other stimuli. During differentiation, these genes are either up- or

downregulated leading to the subsequent removal of the respective mark.

Another example of combinatorial histone marks can be found on active

genes. These genes can display the simultaneous presence of both H3K4me3

and the elongating mark H3K36me3 (Guenther, Levine, Boyer, Jaenisch, &

Young, 2007). There are several other paradigms of cross talk between epige-

netic marks (Zhou et al., 2011). In addition, these marks can occur both on

histone tails and the DNA itself. For example, H3K4me3 is typically

associated with low levels of DNA methylation (Meissner et al., 2008;

Weber et al., 2007).

It is not surprising that cancer cells have aberrations in their combinato-

rial histone marks. For example, Fraga et al. (2005) have reported that loss of

acetylation at Lys16 and trimethylation at Lys20 of histone H4 is a common

hallmark of human cancer. Strikingly, this loss of histone acetylation leads to


a following loss of DNA methylation. This implies that physiological and

cancer histone marks must be interpreted in a combinatorial mode.

One of the challenges has been to define how combinations of epigenetic

marks reflect different chromatin states. One method to establish this is

by studying the genome-wide localization of epigenetic marks. This has

been done, for example, in human cancer cell lines (Ernst et al., 2011),

D. melanogaster (Filion et al., 2010), and mammals (Ram et al., 2011). A

recent study generated by Bernstein and colleagues described the binding

of multiple chromatin modulators and transcription factors in a myeloid cell

line and in ESCs. Analysis of the results revealed six classes of chromatin

modules. These chromatin modules are characterized by different combina-

tions of chromatin regulators. This study showed that although chromatin

regulators might reside at different loci in the genome of different cell types,

they do act on these loci in similar fashion (Ram et al., 2011).

The findings described above provide us with the tools to understand

how mutations of epigenetic regulators in cancer could affect combinatorial

chromatin modules. For instance, there is the fact that a lot of these factors

interact with each other (such as EZH2 and DNMT (Vire et al., 2006),

UTX andMLL (Issaeva et al., 2007; Lee et al., 2007)). Different models have

been used to describe the functional outcome of various epigenetic states

(Ernst & Kellis, 2010; Hon, Hawkins, & Ren, 2009).

5.2. Novel aspects of regulation and epigenetic factorsin cancer

Recently, a novel class of RNAs, termed long noncodingRNAs (lncRNAs)

was discovered. Strikingly, specific lncRNAs, such as HOTAIR, have also

been found to promote cancer metastasis. The effect of HOTAIR has been

reported to be through interaction with the PRC2 complex (Gupta et al.,

2010). Another study by the same group showed that HOTAIR could actu-

ally interact with both PRC2 and LSD1 complexes bridging by this way

H3K27 methylation with H3K4me3 demethylation leading to gene repres-

sion (Tsai et al., 2010). Another lncRNA, HOTTIP, has been found to

mediate activation of the distal HOXA genes through recruitment of and

MLL-containing methyltransferase complex (Wang et al., 2011).

Moreover, a number of studies displayed the importance of chromo-

somal interactions and the integrity of the nuclear architecture in cancer.

For example, Roix, McQueen, Munson, Parada, and Misteli (2003) dem-

onstrated that there is a correlation between the spatial proximity of two loci

in normal cell development and the likelihood of translocation during


carcinogenesis. Specifically, in physiological circumstances, the MYC gene

resides in close proximity to the IGH and IGL loci. These are the exact

translocation partners for Myc as found in leukemia (Chiarle et al., 2011;

Klein et al., 2011). Lieberman-Aiden et al. (2009) capitalized on techniques

such as HiC to map the landscape of inter- and intrachromosomal associa-

tions in myeloid leukemia and lymphoblastoid cell lines. This paved the way

for new studies that assayed the differences in interchromosomal associa-

tions, the translocation landscape, and the transcriptome between normal

and cancer cells. A comprehensive study by Zhang, McCord, et al.

(2012) evaluated the genome-wide correlation between translocations

and chromosomal interactions. This study provided further evidence for

the fact that spatial proximity is positively correlated with the potential to

generate chromosomal translocations. In addition, a recent study by

Hakim et al. (2012) correlated the action of AID, an enzyme that causes

breaks to DNA, to the presence of translocations. This study showed that

stimuli, such as DNA damage, can also affect the frequency of translocations.

The importance of nuclear architecture in the process of tumorigenicity

is further underscored by the fact that lamin, a protein important for the

maintenance of nuclear architecture, is also strongly associated with epige-

netic regulation. Moreover, DNA methylation studies in prostate cancer

showed that lamin-associated areas exhibit local hypermethylation

(Berman et al., 2012). A recent study showed the extent of associations

resulting from RNA polymerase activity in cancer cell lines, and the asso-

ciation between the respective loci and various disease states (Li et al., 2012).

Taken together, it has become clear that in order to understand cancer

we will have to look at the full picture. This includes mutations, epigenetic

changes, transcriptional changes, and possibly larger order chromatin inter-

actions. Nowadays, there is no reliable epigenetic marker that can be used as

a prognostic or diagnostic marker for leukemia. DNA methylation, partic-

ularly of CpG islands of DNA repair enzymes, has been shown a potential to

be a useful prognostic marker in some types of cancer (Van Neste et al.,

2012), but there is a long way to go before this becomes an established prac-

tice. Overview of the cancer’s full properties will allow us to better estimate

its potential. Ultimately, this leads to a better prognosis estimate and poten-

tially it will allow for prediction of treatment outcome.

ACKNOWLEDGMENTSWe thank the members of the Aifantis’ laboratory for critical reading of the chapter and useful

comments on the work. I. A. is a Howard Hughes Medical Institute (HHMI) Early Career


Scientist and is also supported by the National Institutes of Health (RO1CA133379,RO1CA105129, R21CA141399, RO1CA149655, and RO1GM088847), the Leukemia& Lymphoma Society, the V Foundation, the American Cancer Society (RSG0806801),

the Irma T. Hirschl Trust, and the Dana Foundation. P. N. is supported by a fellowshipfrom Lady Tata Foundation for Leukemia. J. M. is financially supported by theNetherlands Organisation for Scientific Research (NWO Rubicon) and by the Dutch

Cancer Society (KWF Fellowship Buit 2012-5358). T. T. is supported by the NIH(training grant T32 CA009161).

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CHAPTER TWO

Translocations in Normal B Cellsand Cancers: Insights from NewTechnical ApproachesRoberto Chiarle*,†,1*Department of Pathology, Children’s Hospital Boston and Harvard Medical School, Boston,Massachusetts, USA

†Department of Molecular Biotechnology and Health Sciences, University of Torino, Italy1Corresponding author: e-mail address: [email protected]

Contents

1. Mechanistic Elements that Generate Chromosomal Translocations 401.1 DNA DSB formation 401.2 DNA-repair mechanisms involved in translocations 451.3 Chromosome territories and gene proximity in translocations 471.4 Spatial organization of the genome: Implications for translocations 48

2. Novel High-Throughput Methods to Study Chromosomal Translocations 502.1 High-throughput genomic translocation sequencing 512.2 Translocation-capture sequencing 52

3. New Findings on Translocation Formation Obtained by HTGTS and TC-Seq 523.1 RAG1/2 translocation hotspots in pro-B lymphocytes 533.2 AID hotspots in activated B lymphocytes 533.3 Gene density, transcription, and translocations 543.4 Role of nuclear positioning and chromosomal structure in translocations 55

4. Landscape of Translocations in Cancers 574.1 Distribution of chromosomal translocations in cancers 574.2 Chromothripsis in cancer genomes 584.3 Repetitive patterns and heterogeneity of translocations involving oncogenes 62

5. Perspectives 63Acknowledgments 64References 64

Abstract

Chromosomal translocations are recurrent genetic events that define many types ofcancers. Since their first description several decades ago as defining elements in cancercells, our understanding of the mechanisms that determine their formation as well astheir implications for cancer progression and therapy has remarkably progressed. Chro-mosomal translocations originate from double-strand breaks (DSBs) that are broughtinto proximity in the nuclear space and joined inappropriately by DNA-repair pathways.


39

http://dx.doi.org/10.1016/B978-0-12-410524-9.00002-5

The frequency and pattern of translocations are influenced by perturbations of any ofthese events. DSB formation is heavily determined by physiologic processes, such as theactivity of RAG1/2 and AID enzymes during B-cell development or maturation, or bypathologic factors, such as ionizing radiations, ROS, or fragile sites. Cellular processesof mRNA transcription, DNA replication, and repair can influence the chromosomal ter-ritories andmodify the relative position and proximity of genes inside the nucleus. DNA-repair factors contribute not only to the maintenance of genome integrity but also totranslocations in normal and cancer cells. Next-generation sequencing techniques pro-vide an unprecedented and powerful tool to approach the field of chromosomal trans-locations. Using specific examples, we will explain how genome-wide translocationmapping methods, such as high-throughput genomic translocation sequencing(HTGTS) and translocation-capture sequencing, combined with large-scale methodsto determine nuclear proximity of genes or chromosome domains, such as 4C andHi-C, have changed our view of the factors and the rules governing translocation for-mation in noncancer cells. Finally, we will review chromosomal rearrangements andnewly described findings, such as chromothripsis, in cancer cells based on these novelrules on translocation formation.

1. MECHANISTIC ELEMENTS THAT GENERATECHROMOSOMAL TRANSLOCATIONS

Chromosomal translocations require a series of consecutive events for

their formation (Fig. 2.1). The first event is the generation of at least a pair of

DNA double-strand breaks (DSBs). Then, two DSBs need to find them-

selves within close enough proximity for the DNA-repair machinery to join

them. When appropriate, the ligation of two DSBs restores DNA integrity,

whereas “illegitimate” joining results in a chromosomal rearrangement.

Various types of structural chromosomal rearrangements can be generated,

including inversions, deletions, and intrachromosomal or interchromosomal

translocations. Here, we will quickly review these types of events.

1.1. DNA DSB formationThe generation of DSBs in a cell can result from physiologic or pathologic

mechanisms. Physiologic mechanisms may be defined as those in which

programmed DSBs are introduced within a restricted window during the

development and maturation of B and T cells by specific enzymes, including

recombination-activating genes (RAG) 1 and 2 and activation-induced

cytidine deaminase (AID). In contrast, pathologic DSBs are generated by

external agents, intracellular biochemical agents, or failure of the DNA

replication machinery.

40 Roberto Chiarle

1.1.1 Physiologic breaks induced by RAG1/2 and AID enzymatic activity1.1.1.1 RAG-initiated DSBs and translocationsThe process of V(D)J recombination during B- and T-cell development is

initiated by the activity of the RAG1 and RAG2 proteins (reviewed in Jung,

Giallourakis, Mostoslavsky, & Alt, 2006). The IgH variable (VH), diversity

(D), and joining ( JH) gene segments are assembled into the IgH variable

region exons in a process that starts with RAG1 and RAG2 introducing

DSBs at their borders. RAG1 and RAG2 form a complex that is absolutely

required for V(D)J recombination. The RAG complex recognizes recom-

bination signal sequences (RSSs) that flank V, D, and J segments and contain

nonamers and heptamers flanked separately by 12- or 23-bp spacers

(according to the so-called 12/23 rule). The RAG complex generates DSBs

from a pair of RSS ends in the form of blunt 50-phosphorylated DSBs and

Pathologic DNA doublestrand breaks (DSBs)

Physiologic DNA doublestrand breaks (DSBs)

– ROS– Ionizing radiations– Stalled replication forks– Common fragile sites and ERFSs– Oncogene-induced replication breaks– Topoisomerases– DNA damage in micronuclei– “Off-target” activity of RAG1/2– “Off-target” activity of AID

– RAG1/2 induced V(D)J recombination– AID induced CSR and SHM

Legitimate DNA repair

DNA integrity Translocations–Duplications–Chromothripsis

C-NHEJ (all cell cycle)HR (S/G2 phases)FoSTeS (collapsed replication fork)MMBIR (collapsed replication fork)

Illegitimate DNA repairC-NHEJA-EJFoSTeSMMBIR

DSB

DSB

Figure 2.1 Mechanisms of chromosomal translocation formation. Chromosomal trans-locations are initiated by double-strand breaks (DSBs) formation. DSBs can beprogrammed by physiologic events, or generated by pathologic processes. Onceformed, two DSBs are in large majority correctly repaired to restore chromosome integ-rity. Less frequently, an erroneous joining of DSBs originates chromosomaltranslocations.

41Translocation in Normal and Cancer Cells

hairpin-sealed coding ends (Honjo, Alt, & Neuberger, 2004). The 12/23

rule and additional “beyond 12/23” restrictions (Gostissa, Alt, & Chiarle,

2011) target RAG complex activity to defined segments in the IgH and

TCR loci and limit its “off-target” activity in other sites in the genome.

Themechanisms bywhichRAGactivity is targeted to the correct loci have

been partially elucidated. The binding of RAG1 andRAG2 proteins to target

V(D)J sequences in the Ig andT-cell receptor (TCR) genes requires the precise

orchestrationofprotein–DNAcomplexes tonarrowthepossibilityofoff-target

effects (Schatz & Swanson, 2011). RAG proteins bind DNA in a very focal

pattern, in particular, within small regions of chromatin in the Igk and TCRaJ-gene segments as well as the IgH and TCRb J-gene and J-proximal D-gene

segments. These small regions, called recombination centers, involve multiple

proteins in addition to RAG, such as the high-mobility-group proteins

HMGB1 or HMGB2 (Swanson, 2004), and depend on canonical RSSs for

access to RAG binding. RSSs’ accessibility depends on chromatin confor-

mation that, in turn, is controlled by enhancers and active promoters in the

region. These modifications depend on enzymes that modify and remodel

chromatin structure and promote transcription by allowing for Pol II binding,

thus revealing an essential role for chromatin in RAG activity and specificity

(Krangel, 2007). In this context, RAG1 binds directly to RSSs via domains

that directly interact with the nonamers and heptamers of the RSSs

(Swanson, 2004). In contrast, RAG2 has limited capability for DNA binding

and instead binds to histoneH3 trimethylated at lysine 4 (H3K4me3), amarker

of active and poised promoters (Liu, Subrahmanyam, Chakraborty, Sen, &

Desiderio, 2007; Matthews et al., 2007). Accordingly, in vivoRAG1 binding

sites were found preferentially in regions containing RSSs, whereas bound

RAG2 was found within thousands of H3K4me3-enriched sites across the

genome (Ji et al., 2010).

The mechanisms that regulate RAG DNA binding and cleavage are

exquisitely important for restricting the generation of RAG-mediated DSBs

to their proper sites. Failure of this regulation, or off-target activity, results in

the generation of DSBs that could be improperly repaired and could lead to

the formation of chromosomal translocations. Indeed, off-target RAG activ-

ity is responsible for low-frequency DSBs that are observed throughout the

genome, and the misrepair of DSBs at the Ig and TCR loci causes genomic

instability and translocations in lymphoid cells (Lieber, Yu, & Raghavan,

2006; Mills, Ferguson, & Alt, 2003). Aberrant RAG activity has been impli-

cated in the development of human malignancies (Tsai et al., 2008), whereas

RAG2 integrity is essential to maintain genomic stability and prevent

42 Roberto Chiarle

complex chromosomal translocations, amplifications, and deletions in the

TCR and IgH loci (Deriano et al., 2011).

Translocations found in B- or T-cell acute lymphoblastic leukemia

(B-ALL or T-ALL, respectively), in mouse models of these diseases

(Gladdy et al., 2003; Zha et al., 2010; Zhu et al., 2002) and in humans

(Kuppers, 2005), are thought to be initiated by RAG activity. Other exam-

ples of RAG-mediated translocations are the recurrent translocations

observed in B-cell lymphomas, such as (1) the t(8;14) translocations that

involve IgH and c-myc in endemic Burkitt’s lymphoma (BL); (2) the

t(11;14) translocations found in mantle cell lymphomas (MCL) involving

IgH and the bcl-1 loci; (3) the t(14;18) translocation in follicular lymphoma

(FL) that translocates IgH and bcl-2; and (4) the t(1;14) translocation in

mucosa-associated lymphoid tissue (MALT) lymphomas that involves

IgH and bcl-10 (Kuppers & Dalla-Favera, 2001).

1.1.1.2 AID-initiated DSBs and translocationsAID is a B-cell-specific enzyme required for class switch recombination

(CSR) as well as somatic hypermutation (SHM). It is mostly expressed by

IgM-positive naıve B cells upon antigen stimulation, typically in the germi-

nal center (GC) and to a lesser extent in the extrafollicular areas of secondary

lymphoid organs, such as the spleen and lymph nodes. AID-mediated CSR

generates DSBs in the IgH CH locus that are frequently involved in

translocations, whereas SHM very rarely leads to DSB formation and

translocation (Pasqualucci et al., 2001). AID is a single-strand (ss)-specific

DNA cytidine deaminase that targets repetitive GC-rich sequences within

CSR switch regions and catalyzes dC-to-dU deamination. The presence of

GC-rich sequences induces the formation of stable RNA:DNA complexes,

resulting in displacement of the nontemplate strand as ssDNA (R-loops).

AID targets R-loops in the nontemplate strand, whereas its access to the

template strand depends on the RNA exosome, a cellular RNA-processing/

degradation complex (Basu et al., 2011).Transcription ofmRNA is necessary

for AID activity, as demonstrated by studies showing that AID is directed to

DNAsiteswhereRNApolymerase II (Pol II) activity is stalled (as a result of its

association with Spt5; Pavri et al., 2010). This relationship between AID,

mRNA transcription, and Pol II stalling has likely implications for the

mechanisms of AID-initiated translocations.

AID expression, nuclear localization, and activity are finely regulated in

B cells to limit its genotoxic effects. Indeed, AID expression is transient in B

cells, owing to tight transcriptional control of the promoter as well as by


miR-155 (Teng et al., 2008), as a mutation in the miR-155 binding site in

the AID 30-UTR has been shown to increase cellular AID levels and, con-

sequently, the frequency of IgH-myc translocations (Dorsett et al., 2008).

The protein levels of AID are also tightly regulated. After induction, AID

is quickly degraded (Basu, Franklin, & Alt, 2009), with the majority of

AID being retained in the cytoplasm and only a small amount entering

the nucleus, and its enzymatic activity being controlled by protein

kinase-A-mediated phosphorylation (Basu et al., 2005).

AID off-target activity outside the IgH locus has been implicated in

chromosomal translocations not only in B cells but also in nonlymphoid cells.

Indeed, signs of AIDoff-target activity, in the formof SHM, have been found

in up to 25% of the expressed genes analyzed in GC B cells (Liu et al., 2008),

and AID is required for DSBs generated in the c-myc locus (Robbiani et al.,

2008; Wang et al., 2009). In agreement with these findings, ectopic

expression of AID in mice induces DSBs and tumor formation in

B- and non-B cells (Okazaki, Kotani, & Honjo, 2007; Robbiani et al.,

2009). In human tumors,AID is thought to initiateDSBswhen translocations

involve the IgH switch regions. Typical examples of such translocations

are: (1) IgH and c-myc in sporadic BL, t(8;14); (2) IgH and Bcl-3 in chronic

lymphocytic leukemia (CLL), t(14;19); (3) IgH and Bcl-6 in diffuse, large

B-cell lymphoma (DLBCL), t(3;14); (4) IgH and Pax5 in lymphoplasmacytic

(LP) lymphoma, t(9;14); and (5) the t(4;14), t(14;16), and t(6;14) transloca-

tions that recur in multiple myeloma (MM) (Kuppers & Dalla-Favera,

2001; Mitelman, Johansson, & Mertens, 2007). In some translocations,

such as the t(14;18) found in FL and the t(11;14) in MCL, it is thought that

RAG and AID activity might collaborate in the generation of DSBs at the

Bcl-2 and Bcl-1 loci (Tsai et al., 2008). In non-B cells, AID expression has

been found in gastric (Matsumoto et al., 2007), liver, and colorectal tumors

(Marusawa, 2008), and a role has also been suggested in germ cell

tumors (Okazaki et al., 2007), breast cancer (Pauklin, Sernandez,

Bachmann, Ramiro, & Petersen-Mahrt, 2009), and prostate cancer (Lin

et al., 2009).

1.1.2 Pathologic induction of DSBs in normal and tumor cellsNonprogrammed pathologic DSBs can originate in G1-arrested or cycling

cells by a variety of mechanisms resulting from (1) exposure to physical

agents, such as ionizing radiations; or (2) the malfunctioning of cellular bio-

chemical processes, such as the production of reactive oxygen species (ROS)

or breaks in fragile sites during impaired replication. Ionizing (g!) radiation

44 Roberto Chiarle

can directly induce DSBs in DNA in a dose-dependent manner (Lieber,

2010; Tsai & Lieber, 2010). Oxidative stress generates ROS that can react

with DNA and induce DSB formation by triggering the induction of two

neighboring SSBs (Kryston, Georgiev, Pissis, & Georgakilas, 2011). Fragile

sites are regions of DNA that can generate DSBs when DNA synthesis is

partially inhibited (Durkin & Glover, 2007). Some fragile sites are common

to all cells. In cancer cells, they are implicated in DNA damage associated

with replication stress and were shown to be involved in constitutional

and cancer rearrangements in vivo (Arlt, Durkin, Ragland, & Glover,

2006). As examples, the FRA6E and FRA6F fragile sites are associated with

break points in ALL and acute myelogenous leukemia (AML) (Sinclair,

Harrison, Jarosova, & Foroni, 2005), and some BL show c-myc translocations

close to the FRA8C and FRA8D fragile sites (Sinclair et al., 2005). Interest-

ingly, oncogene-induced replication stress can induce the collapse of stalling

replication forks and DSB formation at fragile sites (Halazonetis, Gorgoulis, &

Bartek, 2008). Early replication fragile sites (ERFSs) have been recently

described to form during cell cycle progression and DNA replication. ERFSs

colocalize with highly expressed gene clusters in B lymphocytes subjected to

replication stress (Barlow et al., 2013). DSBs in ERFSs are relevant, since

greater than 50% of recurrent amplifications/deletions in human diffuse large

B cell lymphoma map to ERFSs (Barlow et al., 2013).

Finally, topoisomerases can induce DSBs. For example, in prostate can-

cer, topoisomerase IIb has been shown to induce DSB formation that results

in the hallmark TMPRSS2-ERG translocation (Haffner et al., 2010). Nota-

bly, this DSB activity has been observed during topoisomerase inhibition by

anticancer drugs (Felix et al., 2006).

1.2. DNA-repair mechanisms involved in translocationsIn response to DSB generation, cells activate an intrinsic DNA-damage-

response (DDR) pathway to resolve DSBs and facilitate DNA repair. Notable

molecular players within the DDR include ATM, the RAD50/MRE11/

NBS1 complex, H2AX, and 53BP1 (for a detailed review, see Lieber,

2010; Alt et al., 2013; Gostissa et al., 2011). The two major DDR pathways

typically operate depending on the sequence homology of the DSB and divi-

sion state of the cell. In dividing diploid cells, sequence homology is used by

the homologous recombination (HR) pathway or by the single-strand

annealing and breakage-induced replication pathways (San Filippo, Sung, &

Klein, 2008). In nondividing cells, or when homology is not present, cells

utilize a form of direct joining called nonhomologous DNA end joining (NHEJ).


Classical NHEJ (C-NHEJ) relies on a series of factors that participate in a

multistep DNA-repair process. First, Ku proteins (Ku70/86) bind to the

DSB to generate a Ku–DNA complex. The Ku–DNA complex serves as

a docking point for other DNA-repair complexes, such as the nuclease com-

plex formed by Artemis and DNA-PKs, the DNA polymerases Pol l and m,and the ligase complex composed of XLF, XRCC4, and DNA Ligase IV

(for a detailed description of these factors, see Lieber, 2010 and Gostissa

et al., 2011). The recruitment and activity of these higher-order complexes

result in the direct joining of DNA or minimal (2–3 base) microhomology

(MH) of the ends. C-NHEJ is considered to be a highly efficient method to

rapidly repair DSBs and restore chromosomal and genomic integrity. In par-

ticular, it is used to repair physiologic DSBs introduced by RAG1/2 during

V(D)J recombination (see above) and most DSBs introduced by AID during

CSR (Gostissa et al., 2011). Also, it shows a predisposition toward repairing

DSBs on the same chromosome (Ferguson et al., 2000).

When one essential core factor (e.g., Ku or Ligase IV) of the C-NHEJ

pathway is missing, such as in knock-out mouse models or in human patients

with specific genetic defects, cells can still join nonhomologous DNA ends

byoneormoremechanismsknowncollectively as the alternative end-joining

(A-EJ) pathway. Many factors have been implicated in A-EJ, among them

Nbs1, Mre11, CtlP, DNA Lig3, Parp1, and XRCC1, but their roles are still

under investigation (Alt et al., 2013; Gostissa et al., 2011; Lieber, 2010). The

signature functionofA-EJ is to repairDSBsvia short sequencesofMHpresent

at the ends of DSBs. However, MH is not absolutely required since A-EJ can

also generate a substantial fraction of direct joins (Boboila et al., 2010b). A-EJ

is considered to be a slower (Han &Yu, 2008) andmore translocation-prone

pathway thanC-NHEJ (Boboila et al., 2010a).The fact that translocations are

also observed in normal cells indicates either that theC-NHEJ can sometimes

mediate inappropriate DNA-repair responses that result in chromosomal

translocation or that A-EJ might work in parallel with the C-NHEJ to repair

some DSBs, possibly when the C-NHEJ is overwhelmed. In this context,

I-SceI was shown to mediate translocation in WT mouse cells in which

C-NHEJ and A-EJ were both intact (Gostissa et al., 2011; Klein et al.,

2011; Weinstock, Elliott, & Jasin, 2006), showing a bias toward MH usage,

possibly indicating a coexistence of C-NHEJ and A-EJ functions. A similar

bias towardMHusage is observed in translocation junctions from cancer cells

(Zhang & Rowley, 2006).

The roleofC-NHEJ in suppressing translocations andmaintaining chromo-

somal integrity is exemplified by knock-out mousemodels of C-NHEJ factors.

46 Roberto Chiarle

B cells deficient for virtually any single C-NHEJ factor, such as Ku70, Ku86,

XRCC4,Lig4,DNA-PKcs,Artemis,orXLF, showincreases inDSBformation

and translocation (Gostissa et al., 2011).When the p53-dependentG1/S check-

pointwasmissing, as inap53!/!background,micedeficient inKu86,XRCC4,

Lig IV or DNA-Pks, or Artemis expression as well as mice deficient in ATM

developed pro-B-cell lymphomas that often carried IgH/c-myc translocations

with c-myc amplifications. In Artemis-deficient mice, IgH/N-myc transloca-

tions were also observed. Medulloblastomas occurred in XLF-deficient mice

and, together with lymphomas, were also found in other C-NHEJ-deficient

mice (Gostissa et al., 2011). Overall, C-NHEJ maintains genome integrity

and suppresses translocation formation, either by promptly repairing DSBs or

by suppressing the translocation-prone repair activity of A-EJ.

1.3. Chromosome territories and gene proximity intranslocations

For a chromosomal translocation to be formed, two DSBs must be in close

proximity to allow the DNA-repair pathways to join them. It is not clear,

however, whether the two loci involved in a translocation should be close to

each other before the DSBs are generated or whether DSBs have some

mobility inside the nucleus.

In classical cytogenetic studies using fluorescence in situ hybridization

(FISH), the nuclear distance between c-myc and IgH, Igk, and Igl directly

correlated with the respective frequency of translocations found in BL. Fur-

thermore, in the interphase nucleus, the IgH locus was found to be proximal

to some of its translocation partners found in lymphomas, such as the

CCND1, Bcl-2, and Bcl-6 genes (Roix, McQueen, Munson, Parada, &

Misteli, 2003). In a mouse model of lymphoma, the IgH locus was found

to frequently colocalize with its translocation partners c-myc and Igl(Wang et al., 2009). This colocalization was tissue specific and limited

to a relatively small portion of the chromosome, as it was lost with the

chromosomal segment located at 15 Mb distance from Igl (Wang et al.,

2009). Chromosomal proximity is similarly thought to influence transloca-

tion frequency in leukemias, including the ABL and BCR genes in chronic

myelogenous leukemia (CML) and the promyelocytic leukemia (PML) and

RARA genes in PML (Neves, Ramos, da Silva, Parreira, & Parreira, 1999),

and in solid tumors such as prostate cancers, where androgen stimulation was

shown to increase proximity in the frequently translocated TMPRSS2 and

ERG genomic loci (Lin et al., 2009; Mani et al., 2009). However, the def-

inition of proximity in such studies was probabilistic and quite arbitrary, as


it was found only in a fraction of the cells examined and was established

based on the limited resolution of confocal microscopes. A more precise

determination of the physical contact between loci has been established

by modern techniques, such as 4C and Hi-C (see Section 3.4).

1.4. Spatial organization of the genome: Implications fortranslocations

The nucleus is a highly dynamic structure where chromosomes as well as many

fundamental cellular processes, including transcription, replication, and DNA

repair, are organized and carried out within defined compartments (Fig. 2.2).

Inside the interphasenucleus, chromosomes, smallergenomic regions, andeven

single genes are not randomly distributed but rather interact within highly

ordered 3D structures known as chromosome territories. Chromosome terri-

tories can bedirectly visualizedby in situhybridization approaches,whichhigh-

light the localization of individual chromosomes in distinct patterns (Bolzer

et al., 2005).Thepatternsof chromosometerritories changewithdifferentiation

and development and are cell-type specific (Cremer et al., 2006;Misteli, 2007).

The functions of chromosome territories are still unclear. Human lym-

phocytes show a strong correlation between the position of chromosomes

and their gene density, with gene-rich chromosomes clustered toward the

nuclear interior (Boyle et al., 2001). Gene-rich regions correlate with

Active A domainInactive B domain

Short chromosomes Long chromosomes

mRNA

mRNA

mRNA

PCNA

mRNA

RNApolymerases

DNApolymerases

C-NHEJ

Chromosome territories Transcription factories Replication factories DNA repair centers

A-EJ

Figure 2.2 Spatial organization of the genome. The nucleus is a highly dynamic struc-ture. Chromosomes are organized in territories. Short chromosomes interact more fre-quently with each other than with long chromosomes. Within each chromosome, activeA domains interact more frequently with other A domains, whereas inactive B domainsare more frequently associated with B domains. Transcription factories are nuclear com-partments (calculated in about 10,000 in HeLa cells) where transcription factors are rec-ruited, assembled, and disassembled within few seconds to achieve efficienttranscription of clustered genes. Replication factories and DNA repair centers are dis-crete compartments of the nucleus where DNA synthesis and DNA repair are achievedthrough the recruitment of specific factors (see text for details).

48 Roberto Chiarle

decondensed chromatin status, whereas gene-poor regions are associated

with condensed chromatin (Gilbert et al., 2004). Chromosomal territories

can also be determined by the size of single chromosomes, with smaller

chromosomes generally located toward the center of the nucleus (Bolzer

et al., 2005). Indeed, very recent data collected with Hi-C mapping in

G1-arrested pro-B cells showed that the longest chromosomes more fre-

quently interact with each other than with smaller chromosomes (Zhang

et al., 2012).

The transcription of mRNA by Pol II polymerases predominantly occurs

in centralized structures called “transcription factories” (Cook, 1999). The

concentration of transcription factors into these factories allows for

efficient transcription, and cotranscribed genes are recruited together by

modifications of chromosome structure and changes in chromatin

conformation (Misteli, 2007). In this process of transcription-driven recruit-

ment, single genes can change their positioning with respect to the

nucleus. For example, in lymphocytes, activated IgH and CD4 relocalize

from the periphery toward the center of the nucleus (Kosak et al., 2002;

Kim et al., 2004).

Similar principles of nuclear compartmentalization and dynamics also

apply to replication and DNA repair. During the S phase, within the so-

called replication factories, multiple factors involved in the replication

machinery are rapidly assembled and disassembled within minutes to

allow for efficient DNA synthesis. DNA repair occurs in “repair centers”

where distinct foci of accumulating factors are recruited to ensure efficient

repair of DSBs (Bekker-Jensen et al., 2006). Taken together, this evidence

shows that the nucleus is a highly dynamic structure in which entire

chromosomes, gene clusters, or even single genes can rapidly change their

position inside the geometry of the nucleus or with respect to other chro-

mosome or gene loci. Therefore, rather than assuming that the proximity

between translocation-prone genes is fixed, their probability of contact

appears to be somewhat fluid in a variable fraction of cells and influenced

by factors such as cell-cycle phase (predominantly G1 or G1/S/G2

phases).

Modern techniques for genome-wide contact analysis, such as 4C and

Hi-C, have improved our understanding of chromosomal organization

within the nucleus. These techniques capture the physical contact made

between gene segments via the formalin-mediated cross-linking of histones

that are in physical contact in the nucleus (Lieberman-Aiden et al., 2009;

Simonis et al., 2006; Zhao et al., 2006). With 4C, it was found that actively

transcribed loci, such as the b-globin locus, preferentially contacted other


actively transcribed loci and that active and inactive genes are involved in

long-range intra- and interchromosomal contacts (Simonis et al., 2006).

Recent studies relied on Hi-C approaches to build spatial proximity maps

of the human genome at 1 Mb resolution. These maps revealed that, in both

cycling cells and G1-arrested cells, chromatin conformation is consistent

with a fractal globule in which intrachromosomal interactions are much

more frequent than interchromosomal interactions, and in each chromo-

some, the probability of contact was directly proportional to genomic dis-

tance (Lieberman-Aiden et al., 2009; Zhang et al., 2012). These physical

data are entirely consistent with the concept of chromosome territories. Fur-

thermore, genomic loci in A domains, characterized by their open chroma-

tin conformation and tendency to correlate with gene-rich areas, showed

higher probability of contact with other loci in A domains than with loci

in the closed and transcriptionally inactive B domains, and vice versa

(Lieberman-Aiden et al., 2009). These concepts—that is, the clustering of

genes during transcription, transcription factories, the higher probability

of contact with regions of the same chromosome, and the segregation of

open and closed chromatin to form two genome-wide compartments—

have profound implications for the interpretation of mechanistic factors that

regulate translocation (Fig. 2.2). These implications will be analyzed below.

2. NOVEL HIGH-THROUGHPUT METHODS TO STUDYCHROMOSOMAL TRANSLOCATIONS

To better study chromosomal translocation formation, the develop-

ment of powerful detection methods in relatively simple assays in vivo is

required. In the past decade, most translocation assays were performed by

a direct PCR approach, a rather simple technique in which a series of

primers were designed to detect translocations between two known genes,

such as c-myc and the IgH locus (Ramiro et al., 2006, 2004; Wang et al.,

2009), or multiple pairs of genes (Jankovic et al., 2010). Although direct

PCR provides reliable quantitative measurements of translocation frequency

between two loci, only defined translocations generated within a few kilo-

bases from where primers are located can be detected, thus limiting its use-

fulness when translocation partners are unknown or larger regions of the

genome are involved. The introduction of next-generation sequencing

techniques has allowed for the development of broader, genome-wide

methods to assay for chromosomal translocation formation.

50 Roberto Chiarle

2.1. High-throughput genomic translocation sequencingHTGTS was recently developed to clone translocation junctions from a

baited DSB end (Chiarle et al., 2011). This bait was provided by DSBs gen-

erated via the homing endonuclease I-SceI that cuts a canonical recognition

sequence of 18 bp (Liang, Romanienko, Weaver, Jeggo, & Jasin, 1996)

targeted into the IgH or c-myc locus (Chiarle et al., 2011; Klein et al.,

2011). Therefore, HTGTS isolates junctions between a chromosomal

DSB introduced at a fixed site and other genic or intergenic regions in

the whole genome. In this study, primary splenic B cells were isolated

and activated in vitro for up to 4 days in conditions that allow for AID expres-

sion and CSR induction (Fig. 2.3). This relatively short time of activation

Mature B cells IgM+

4 days stimulationIL-4 + CD40 or LPS

I-Scel-mediatedDSBs

I-Scel-mediatedDSBs

RAG1/2-induced DSBs and translocations

AID-induced DSBs and translocations

A-MuLV Pro-B cells

STI-571

Next-generationsequencing

DNA isolationLinker-mediated PCR


Translocationmaps

AID induction Translocations

ProliferationCSR to IgG1+ B cells

RAG1/2 induction Translocations

G1 arrest

Figure 2.3 Strategies to generate translocations maps from normal mature B cells andpro-B cells. Mature B cells are freshly isolated from spleens and activated to induce AIDexpression and class switch recombination. I-SceI-mediated DSBs are generated in theIgH and c-myc loci either by retrovirus-mediated I-SceI expression or by hormone-mediated induction of I-SceI–glucocorticoid receptor (GR) fusion. After 4 days, cells arecollected and translocations junctions are cloned as described in the text. For pro-B cells,A-MuLV transformants are generated by Bcr-Abl transduction. In the presence of Bcl2overexpression, the inhibition of Bcr-Abl tyrosine kinase activity by STI-571 induces G1cell-cycle arrest and RAG1/2 induction. DSBs are generated by I-SceI–GR fusion activationand translocations junctions are cloned as for mature B cells.


minimized cellular selection and avoided biases related to the biological con-

sequences of translocations on cell growth and survival. To clone transloca-

tion junctions, genomic DNA was digested into relatively small fragments

by restriction enzymes and ligated to an adapter or, alternatively, to generate

circular fragments. Up to three rounds of nested PCRswere performed with

adapter- and locus-specific primers, and pooled PCR products were then

sequenced by 454 sequencing and aligned to a reference genome after sev-

eral steps of filtering to eliminate nonspecific products and artifacts. The

method proved to be highly specific, with artificial nonspecific junctions

being lower than 1% of detected sequences. By this method, almost

150,000 independent junctions from independent mice and libraries were

generated. All sequences contained the translocation junction, thus allowing

for MH studies (Chiarle et al., 2011).

2.2. Translocation-capture sequencingTranslocation-capture sequencing (TC-Seq) was developed in parallel with

HTGTS based on similar principles (Klein et al., 2011; Oliveira et al., 2012).

Fixed DSBs were generated in activated B cells in the c-myc locus targeted

with the I-SceI recognition sequence. Translocations to I-SceI-c-myc were

cloned with an adapter-based PCR approach. Genomic DNAwas fragmen-

ted by sonication, blunted, ligated to double-stranded asymmetric linkers,

and cut with I-SceI to eliminate native nontranslocated loci. Next, two

rounds of seminested PCR were performed and the fragments assembled

into a paired-end Illumina library. By this method, over 160,000 transloca-

tions were obtained fromWT and AID-deficient B cells (Klein et al., 2011).

3. NEW FINDINGS ON TRANSLOCATION FORMATIONOBTAINED BY HTGTS AND TC-Seq

HTGTS and TC-Seq have greatly expanded our understanding and

interpretation of translocation mechanisms. For example, using these

methods, it was discovered that DSBs generated from fixed loci show a

much wider genomic distribution than previously expected. Chromosomal

translocations were mostly found within the same chromosome where the

original DSB was located, in particular, within a relatively narrow (about

1 Mb) region around the DSB site. This intrachromosomal preference for

DSB joining could be explained by the documented preference for C-NHEJ

to repair DSBs within the same chromosome (Ferguson et al., 2000;

Mahowald et al., 2009; Zarrin et al., 2007) and/or by recent data showing

52 Roberto Chiarle

that regions within the same chromosome are much more likely to be in

physical contact than regions between two different chromosomes

(Lieberman-Aiden et al., 2009; Zhang et al., 2012; see Section 3.4). By

HTGTS, the analysis of SNPs in translocation junctions showed that trans-

locations are 6–10 times more likely to occur within the same allele where

the DSBs are located (Zhang et al., 2012).

3.1. RAG1/2 translocation hotspots in pro-B lymphocytesNew translocation-mapping techniques, such as HTGTS, provide a viable

tool to analyze RAG-mediated target and off-target DSB formation. In

pro-B cell lines transformed with Abelson murine leukemia virus

(A-MuLV), RAG expression is induced by cell-cycle arrest mediated by

the inhibition of v-abl activity by the kinase STI571 (Bredemeyer et al.,

2006). In ATM!/! pro-B cell lines, translocations were enriched in the

expected RAG target sites (IgH, Igk, Igl) in TCR loci (TCRa/d, TCRg),which are considered to be inaccessible due to a closed chromatin confor-

mation in pro-B cells. Thus, similar to AID in peripheral B cells, RAG is the

major source of DSBs in pro-B cells, where it largely dictates the landscape

of translocations (Zhang et al., 2012).

3.2. AID hotspots in activated B lymphocytesHTGTS and TC-Seq translocation maps found a strong enrichment of

expected AID targets. A prediction of AID targets for DSBs initiation

was obtained by deep sequencing of genomic AID-binding sites. With this

approach, AID was found to bind preferentially promoter-proximal regions

where stalled polymerases and chromatin-activating marks were enriched

(Yamane et al., 2011). In translocation maps, when B cells were stimulated

with CD40 or LPS and IL-4, AID generated DSBs in the Sm, Sg1, Sg3, andSe regions, as expected. Chromosomal translocations to S regions were up to

20-fold higher than any other recurrent translocation in B cells, revealing the

IgH S region as a major translocation hotspot in B cells and highlighting AID

as the most important DSB-generating enzyme in a normal B cell (Chiarle

et al., 2011; Klein et al., 2011). A series of known and unknown AID targets

were also found to be involved in translocations or deletions. For example,

(1) Pim1, Il21r, and Gas5 all translocate with Bcl6 in DLBCL (Nakamura

et al., 2008; Ueda et al., 2002; Yoshida et al., 1999); (2) Pax5 and Ddx6

are translocated with IgH in DLBCL and in LP lymphoma (Iida, Rao, Ueda,

Chaganti, & Dalla-Favera, 1999; Lu & Yunis, 1992; Yoshida et al., 1999);


(3) c-myc and Pvt1 are repeatedly translocated in human BL and mouse

plasmacytoma (Cory, Graham, Webb, Corcoran, & Adams, 1985;

Einerson et al., 2006; Kuppers, 2005); (4) Aff3 and Grhpr translocate with

Bcl2 and Bcl6, respectively, in FL (Akasaka, Lossos, & Levy, 2003; Impera

et al., 2008); (5) Ccnd2 and Bcl2l11 are translocated or deleted (respec-

tively) in MCL (Bea et al., 2009; Gesk et al., 2006); and (6) Birc3 is

translocated with Malt1 in MALT lymphoma (Murga Penas et al.,

2006) and with mir142 in B-cell prolymphocytic leukemia (Gauwerky,

Huebner, Isobe, Nowell, & Croce, 1989).

3.3. Gene density, transcription, and translocationsBy HTGTS, about 10–20% of translocations were found to be inter-

chromosomal and were widely distributed across all chromosomes

(Chiarle et al., 2011; Klein et al., 2011). Strikingly, translocations strongly

correlated with gene density and gene activity in each chromosome, cluster-

ing at a higher frequency in regions enriched in transcribed genes, and much

less so in regions devoid of active genes (Chiarle et al., 2011). Furthermore,

translocations were enriched in genes with Pol II and marks of active histones,

such as H3K4 trimethylation, H3 acetylation, and H3K36 trimethylation

(Klein et al., 2011). In actively transcribed genes, translocations accumulated

in the promoter region, within a few kilobases of the transcription starting site,

whereas in inactive genes, translocations were evenly dispersed throughout

the gene. The clustering of translocations in the promoter region of WT B

cells was found not only in AID target genes but also in genes not targeted

by AID and in AID-deficient cells (Chiarle et al., 2011).

The observed correlation between gene transcription and translocation is

very intriguing. Transcription generates genetic instability by multiple

mechanisms that are still poorly understood. Transcribed genes likely offer

regions of genomic fragility, owing to the single-strand DNA conformation

of transcribed gene segments, the collision of transcription machinery with

replication forks, and the formation of DNA–RNA hybrids (R-loops)

(Aguilera, 2002; Ruiz, Gomez-Gonzalez, & Aguilera, 2011). In B cells,

CSR (see Section 1.1.1.2) is a recurrent source of DSBs and is heavily

dependent on transcription. Transcription of the switch (S) regions deter-

mines the formation of stable DNA structures, in which the C-rich template

strand forms R-loop intermediates, whereas the G-rich nontemplate strand

generates secondary structures. AID deaminates DNA on the C-rich tem-

plate strand of actively transcribing S regions, to allow for eventual DSB

54 Roberto Chiarle

generation (Chaudhuri et al., 2003; Nambu et al., 2003). Binding of AID to

transcribed regions is mediated by the transcription elongation complex

(Besmer, Market, & Papavasiliou, 2006) and is enhanced by transcriptional

pausing and stalling of Pol II (Canugovi, Samaranayake, & Bhagwat, 2009).

The protein Spt5 is thought to mediate AID binding to stalled transcription

sites (Pavri et al., 2010). Therefore, AID might be recruited not only to

transcriptionally stalled sites in the immunoglobulin (Ig) loci to induce CSR

and SHM but also to non-Ig loci, thus favoring DSBs and translocations in

genes such as c-myc, Bcl6, Pim1, and Pax5 that are repeatedly translocated in

human lymphomas (Pavri & Nussenzweig, 2011). Indeed, TC-Seq studies

showed strongoverlapbetween translocations andAID-andSpt5-binding sites

(Klein et al., 2011; Yamane et al., 2011). In the absence of AID, translocations

were likely to result fromDSB formationduring physiological processes related

to transcription andDNAreplication (Branzei&Foiani, 2010). In this context,

ERFSs could contribute to explainmore than50%of chromosomal aberrations

in human diffuse large B cell lymphomas (Barlow et al., 2013).

3.4. Role of nuclear positioning and chromosomal structure intranslocations

Physical proximity has always been considered a key determinant in chro-

mosomal translocations in cancer. Early DNA–FISH studies in the inter-

phase nuclei of mouse and human B cells showed that loci frequently

involved in lymphoma translocations, such as IgH and c-Myc, or IgH and

Bcl2, were often located in close proximity to each other (Parada,

McQueen, & Misteli, 2004; Roix et al., 2003; see Section 1.3). Similarly,

translocation partners in other hematologic malignancies, such as

BCR–ABL1 in chronic myeloid leukemia, RET–CDC6 in thyroid malig-

nancies, TMPRSS2–ERG/ ETV1 in prostate cancer, and PML–RARA in

acute PML, were frequently proximal in the cells considered to be tumor

precursors (Mitelman et al., 2007). Proximity between loci seems to be dic-

tated, at least in some instances (such as the IgH and c-myc loci), by the

recruitment of a common transcription factory (see Section 1.4; Osborne

et al., 2007).

Pro-B cells undergo V(D)J rearrangements due to the expression of

RAG enzymes that recognize specific sequences in the genome

(see Section 1.1.1). Application of HTGTS translocation-mapping

approaches to pro-B cells revealed high genomic stability in WT cells with

a limited number of cloned translocations. In contrast, in ATM!/! cells,


RAG-mediated breaks dominated the landscape of translocation (see

Section 3.1). Thus, DSB frequency in RAG targets strictly determines

the translocation pattern. In contrast, when DSBs were no longer a limiting

factor, as in cells treated with ionizing radiation, most of the translocations

(between 25% and 40%) were found in the same chromosome where the

bait DSBs were located, supporting a strong influence of chromosomal ter-

ritories on translocation formation (Zhang et al., 2012). Furthermore, trans-

locations on the same chromosome were mostly in cis on the same allele.

Strikingly, by combining HTGTS with Hi-C studies, it was found that

translocations on the same chromosome, as well as translocations in trans

with other chromosomes, strongly correlated with regions with a higher

contact probability (Zhang et al., 2012).

4C-seqmaps generated from genes that are actively transcribed in mature

B cells, such as IgH and c-myc, showed that these genes shared similar

genome-wide interactions, despite being on different chromosomes (chr.

12 for IgH and Chr. 15 for c-myc). The highest frequency of contacts was

found in ciswithin the same chromosome 12 and 15, respectively, consistent

with the data obtained in pro-B cells (see above; Zhang et al., 2012) and with

the concept that chromosomes are organized in defined territories (Cremer

& Cremer, 2010; Lieberman-Aiden et al., 2009). In contrast, trans interac-

tions were likely to be driven by transcriptional activity and chromatin con-

formation, as IgH and c-myc interacted preferentially with loci associated

with activating histone acetylation marks, Pol II binding, and active tran-

scription (Hakim et al., 2012). These findings are consistent with the notion

that chromosomes are organized into areas of compact and open chromatin,

with open chromatin regions having a distinct nuclear organization and

being enriched in genes (Gilbert et al., 2004). Genes within areas of active

or inactive chromatin have a higher probability of contact than do genes

between these areas (Lieberman-Aiden et al., 2009; Simonis et al., 2006).

In mature B cells, in the absence of AID, DSBs are likely to be generated

by common mechanisms associated with transcription and replication. In

this setting, translocation pattern was shown to strictly correlate with

the interaction frequencies between loci. In contrast, in the presence of

AID, translocations correlated not with contact frequency but with DSB

frequency, as determined by RPA binding in 53BP1!/! cells (Hakim

et al., 2012).

Overall, these new genome-wide correlations between translocations,

DSBs, and nuclear proximity indicate that in the presence of a dominant

source of DSBs in B cells (i.e., RAG1/2 in pro-B cells and AID in mature

56 Roberto Chiarle

B cells), the translocation landscape is mainly dictated by the frequency of

DSBs in any given locus. In contrast, in the absence of such DSBs (such

as in AID!/! B cells), the relative nuclear position mainly regulates translo-

cation frequency. Future studies are needed to address these correlations in

non-B cells, where a dominant mechanism for DSB formation is likely

absent.

4. LANDSCAPE OF TRANSLOCATIONS IN CANCERS

The landscape of chromosomal translocation in human cancers varies

from tumors containing minimal structural variations to tumors with highly

complex genomic rearrangements (CGRs). The recurrent presence of such

structural abnormalities in cancers can be interpreted as “driver” events that

are selected and enriched during tumor progression, or “passenger” events

that originate during the life cycle of a tumor without particular selective

forces that fix them in the cancer genome. Typical driver chromosomal trans-

locations are those that define different categories of hematologicmalignancies

or specific subtypes of solid tumors, such as the BCR-ABL translocation in

CML, various translocations in AML, most translocations in human lympho-

mas (see below), and recurrent translocations in solid cancers, such as EWSR1

fusions in Ewing sarcoma (Toomey, Schiffman, & Lessnick, 2010),

ETS fusions in prostate cancer (Rubin, Maher, & Chinnaiyan, 2011), and

anaplastic lymphoma kinase (ALK) fusions in lymphoma, lung carcinoma,

and other cancers (Chiarle, Voena, Ambrogio, Piva, & Inghirami, 2008).

In such tumors, the structural landscape of the tumor genome is dominated

by the driver translocation events, with minimal additional structural varia-

tions in other chromosomes (Mitelman et al., 2007). Driver translocations

were first discovered more than three decades ago with classical cytogenetic

techniques because they are highly recurrent in cancers and, therefore, more

easily identified. In contrast, our understanding of the more elusive nonrecur-

rent passenger chromosomal rearrangements has only recently become

clearer, owing to the development of genome-wide analysis tools such as

next-generation DNA sequencing, RNA sequencing, SNP-array analyses

and, of course, adequate bioinformatics methods.

4.1. Distribution of chromosomal translocations in cancersMany human cancers show complex genomic structural rearrangements.

These rearrangements can be divided into different types and can be intra-

chromosomal or interchromosomal. Intrachromosomal rearrangements are


typically observed as deletions, tandem duplications, inversions, or other

complexnoninverted intrachromosomal rearrangements. Interchromosomal

rearrangements are translocations between different chromosomes that

account for less than 10% of all the structural variations in cancers with

complex genomic structural rearrangements (Pleasance et al., 2010). Next-

generationDNAsequencing allows for the improvedcharacterizationof such

complex cancer genomes. Strikingly, in many cancer types, highly CGRs

are confined to one or few chromosomes, where tens or hundreds of

chromosomal rearrangements are clustered. Such events have been termed

“chromothripsis” (Stephens et al., 2011).

4.2. Chromothripsis in cancer genomesThe first evidence of chromothripsis came from whole-genome sequencing

of CLL patients. In this series, it was found that chromosomal rearrangements

generally clustered within one entire chromosome and more frequently in

smaller regions, such as an entire chromosomal arm or even in segments just

a few tens of megabases or kilobases in length (Stephens et al., 2011). In these

regions of chromothripsis, chromosomal rearrangements were both inverted

and noninverted in orientation. Strikingly, there was an equal representation

of the four major possible patterns of intrachromosomal rearrangements,

that is, deletions, head-to-head and tail-to-tail inversions, and tandem

duplications (Stephens et al., 2011).

Chromothripsis has been found in a range (3–25%) of other cancer types,

such as neuroblastoma (Molenaar et al., 2012); medulloblastoma (Northcott

et al., 2012; Rausch et al., 2012); bone cancers (Stephens et al., 2011); MM

(Magrangeas, Avet-Loiseau, Munshi, & Minvielle, 2011); and lung, renal,

and thyroid cancers (Forment, Kaidi, & Jackson, 2012). Chromothripsis

can also be characterized in terms of its limited copy-number state, where

the rearranged regions vary between one or two copies, with segments

exhibiting a loss of heterozygosity alternating with segments with retained

heterozygosity (Kloosterman et al., 2011; Stephens et al., 2011).

These extensive chromosomal rearrangements that occur during chro-

mothripsis are thought to originate from a single catastrophic event rather

than as a consequence of progressive sequential rearrangements. In the

progressive rearrangement model, complex, localized clustering of

rearrangements originates during many cell cycles, generating increasing

complexity in genomic structure. This is the mechanism typically thought

to cause genomic amplifications. As an example, amplifications of the c-myc

58 Roberto Chiarle

locus are thought to derive from the so-called breakage–fusion–bridge cycle,

where regional weakness of the DNA structure may lead to repeated cycles

of DNA breakage and repair (Gostissa et al., 2011; Zhang et al., 2010). In

contrast, during chromothripsis, the entire chromosome or chromosomal

regions are shattered into several fragments in a narrow window of time

and then joined. The minimal or absent sequence homology between

the translocated pieces favors mechanisms of repair based on C-NHEJ or

other end-joining pathways (Forment et al., 2012). The fact that tens to

hundreds of pieces of chromosomal DNA can be rejoined within the same

chromosome suggests that chromothripsis could occur when chromosomes

are in a condensed state, such as during mitosis. Alternatively, it might be the

result of the organization of chromosomes into territories where DNA

repair, mostly C-NHEJ, favors joining within the same chromosome

(Gostissa et al., 2011; Zhang et al., 2010). Indeed, mouse models of

translocations indicate that, in the presence of a catastrophic event, such

as ionizing radiations, rejoining of DSBs and translocations are preferentially

clustered in cis within the same chromosomal allele (Zhang et al., 2012).

Alternatively, other repair mechanisms could be involved, such as

replication fork stalling and template switching (Branzei & Foiani,

2010) or microhomology-mediated break-induced replication (MMBIR)

(Liu et al., 2011).

The question on how such catastrophic events are generated is still open

(Fig. 2.4). The fact that DNA shattering involves only a limited number of

chromosomes, or limited segments within chromosomes, suggests that the

DNA-damaging event should occur when chromosomes are at a condensed

stage, such as mitosis. DSBs could be caused by an environmental stimulus,

such as exposure to free radicals or ionizing radiation (Tsai & Lieber, 2010),

or by DNA replication stress with premature termination of replication forks

and DSB formation at potentially fragile sites (Halazonetis et al., 2008).

Recently, it was shown that aberrant and persistent DNA replication within

micronuclei can generate DNA damage and chromosome pulverization

(Crasta et al., 2012). Additional catastrophic DNA-damaging events could

occur during telomere attrition (Sahin & Depinho, 2010) or apoptotic

events that would kill a normal but not a cancerous cell (Tubio &

Estivill, 2011). Interestingly, germ line and somatic TP53 mutations were

associated with chromothripsis both in medulloblastoma and AML

(Rausch et al., 2012). This finding indicates that defects in checkpoint path-

ways designed to repair DNA damage predisposes to chromothripsis, likely

by facilitating cell-survival mechanisms that operate during catastrophic


events, such as the favoring of low-fidelity repair or bypassing of G2/M cell-

cycle checkpoints (Maher & Wilson, 2012).

Chromothripsis could have important implications in the evolution of

cancers. First, because regions of heterozygosity are conserved inside clusters

of rearrangements, chromothripsis is thought to occur early in cancer cell

development (Forment et al., 2012; Stephens et al., 2011), suggesting that

such rearrangements might themselves influence the progression of cancer

cells. Second, a particular cancer cell undergoing chromothripsis could derive

some selective advantages. Chromosomal segments generated during massive

chromosomal fragmentation might not be reincorporated into the derivative

chromosome but instead might form double-minute chromosomes. In this

Mitosis

Micronucleuspulverization

RadiationMMBIR

Predisposition to cancer due tooncogenes and oncosuppressors’

alterations

Postmitotic cell withchromothripsis

Mitosis exit

DNA repairChromosome territory

P53 deficiency

NHEJMMBIR

Chromosome shattering

Figure 2.4 Proposed mechanisms of chromothripsis in normal and cancer cells. Duringmitosis, chromosomes are condensed and focal DNA damage can be induced byradiation, microhomology-mediated break-induced replication (MMBIR), or chromo-some lagging, micronuclei formation, and pulverization due to inappropriate chro-mosome segregation. After chromosome shattering, DNA fragments are joined byNHEJ within chromosomal territories. Repaired chromosomes contain chromosomalrearrangements such as deletions, head-to-head and tail-to-tail inversions, and tandemduplications. With mitosis exit, the chromothriptic chromosome can be reincorporatedinto the nucleus. Deficiency of DNA-damage checkpoints, such as P53 deficiency, facil-itates the survival of cells during the chromothriptic process. As a result, chromothripsiscan induce oncogene activations by translocations or duplications as well as lossof oncosuppressor genes by deletions or locus disruptions, thus facilitating cancerprogression.

60 Roberto Chiarle

context, one case of bone cancer chromothripsis was shown to generate one

double-minute chromosome approximately 1.1 Mb in length that contained

multiple amplified copies of c-myc (Stephens et al., 2011), likely giving a

selective advantage to the cell. Alternatively, the catastrophic event could

simultaneously disrupt multiple tumor-suppressor genes, as in the case of a

chordoma sample in which the cyclin-dependent kinase inhibitor 2A

(CDKN2A), the F-box andWD-40 domain containing protein 7 (FBXW7),

and the Werner syndrome ATP-dependent helicase (WRN) genes were

disrupted as a consequence of one single chromothriptic event (Forment

et al., 2012).

Interestingly, the pattern of intrachromosomal rearrangements resulting

from chromothripsis in cancer cells has been faithfully reproduced in normal

B cells in mouse models of induced translocations. In these models, a dom-

inant source of DSBs is generated by the targeting of I-SceI substrate

sequences in the IgH locus or in the c-myc locus. Those I-SceI-induced

DSB loci are embedded in regions with a high density of spontaneous DSBs,

generated in B cells by either AID in the IgH switch regions flanking the

I-SceI site, or by AID-dependent and -independent mechanisms in the

closely localized c-myc and Pvt1 genes. Indeed, the Pvt1 gene is frequently

translocated not only in BL but also in nonlymphoid cancers such as lung

cancer and medulloblastoma (Northcott et al., 2012; Pleasance et al.,

2010). Therefore, these models show that a high density of synchronous

DSBs generated in normal cells, within a chromosomal region of few kilo-

bases, might simulate a chromothriptic event. Remarkably, normal cells

react to these localized chromothriptic events by generating a pattern of

chromosomal rearrangements highly similar to cancer cells, with deletions,

head-to-head and tail-to-tail inversions represented in approximately equal

frequency (Chiarle et al., 2011; Klein et al., 2011). Similarly, in human

medulloblastoma, an approximately 200-kb region flanking the Pvt1 locus

was found to be frequently involved in chromothriptic events, with frequent

oncogenic rearrangements occurring with the c-myc locus upstream or the

NDRG1 locus downstream of Pvt1 (Northcott et al., 2012).

Additionally, events similar to chromothripsis can be observed in some

genomic disorders where CGRs are identified (Zhang, Carvalho, & Lupski,

2009). These genomic disorders are thought to originate from germ line

rearrangements during gametogenesis or early postzygotic development.

In these conditions, multiple copy-number changes can be found, including

deletions, duplications, and extensive translocations and inversions. To

explain these events, a MMBIR model has been proposed for complex


rearrangements, where copy gains or losses involve the generation and repair

of DSBs in regions with domains of MH (Hastings, Lupski, Rosenberg, &

Ira, 2009). It is speculated that MMBIR and subsequent replication-

mediated repair by C-NHEJ could explain both CGRs in genomic

disorders as well as chromothripsis in cancer cells (Kloosterman et al.,

2012; Liu et al., 2011). Thus, the structural similarities between chromo-

somal rearrangements observed in normal B cells, CGR genomic disorders,

and chromothripsis strongly argue in favor of similar mechanisms for DSB

repair operating in normal and cancer cells.

4.3. Repetitive patterns and heterogeneity of translocationsinvolving oncogenes

In human patients, some translocations are recurrently found in specific sub-

types of tumors. The IgH-c-myc translocations are typically found in BL and

DLBCL, IgH-Bcl-2 translocations in B-cell lymphomas (mainly FL, CLL,

and DLBCL), IgH-Bcl-1 translocations in MCL and MM, and Bcl-6 trans-

locations in DLBCL. It is thought that these translocations are generated

from the joining of one physiologic DSB in the IgH locus with one patho-

logic DSB in the oncogene as consequence of off-target activity of B-cell-

specific genes such as RAG and AID (see Section 1.1). However, some

oncogenes have much more heterogeneous patterns of translocations. For

example, PAX5 is involved in the t(9:14) translocation with IgH in PL

and other more aggressive lymphomas (Poppe et al., 2005), but 2.6% of

pediatric B-ALL patients show multiple different translocation partners

for PAX5. PAX5-ETV6 translocation was the first to be reported

(Cazzaniga et al., 2001), but many others were subsequently discovered,

including translocations of PAX5 with the transcription factors ETV6,

FOXP1, ZNF521, PML, DACH1, DACH2, the chromatin regulators

NCoR1, BRD1, the protein kinases JAK2, HIPK1, and others (Coyaud

et al., 2010; Medvedovic, Ebert, Tagoh, & Busslinger, 2011). Similarly,

the Bcl-6 oncogene is frequently involved in translocation events with many

non-IgH genes in lymphoma, including CIITA, Pim-1, eif4AII, TFRC,

RHOH, Ikaros, and up to 20 different partners (Ohno, 2006). The explana-

tion for how such non-IgH translocations in lymphoid cells occur is not

totally clear. Some are likely to be off-target AID translocation partners.

Pax5, Pim-1, and RHOH frequently show SHM in B cells as a result of

AID activity (Liu et al., 2008) and are found as hotspots in translocation-

mapping experiments (see Section 2). However, a clear role for AID or

RAG has not yet been proved for many other genes, and other mechanisms

62 Roberto Chiarle

for DSB formation could still be responsible for initiating such translocation.

Even more compelling, specific cell-type mechanisms likely occur when the

same oncogene translocates with specific partners in different tumor types.

The ALK oncogene was first discovered as a partner of the Nucleophosmin

1 (NPM1)-ALK translocation in anaplastic-large-cell lymphoma (Morris

et al., 1994). In the past 20 years, at least 20 different ALK translocation part-

ners were discovered in lymphoma and recently also in solid tumors, such as

myofibroblastic inflammatory tumors and lung, colorectal, and renal carci-

noma (Chiarle et al., 2008; Kohno et al., 2012; Lipson et al., 2012; Soda

et al., 2007; Takeuchi et al., 2012). For such translocations, the initiating

events are very poorly understood. Strikingly, some translocations are highly

tumor specific. For example, the NPM-ALK translocation, by far the most

frequent translocation in lymphoma, is never encountered in solid tumors.

In contrast, the EML4-ALK translocation that is predominant in lung carci-

noma is never observed in lymphoma. Similarly, differential tissue-specific

patterns are also found in other recurring oncogene translocations, such as

RET, which is involved in translocations in thyroid and lung cancers

(Lipson et al., 2012;Nikiforov&Nikiforova, 2011). Therefore, tissue-specific

differences in translocation patterns do exist. Factors such as tissue-specific

DSB formation, transcriptional activity of the implicated genes, or nuclear

conformation and chromosome distribution must be investigated to explain

the tissue specificity of translocation patterns.

5. PERSPECTIVES

Recent breakthroughs in technology have critically advanced our

ability to investigate the mechanisms that regulate translocation formation.

We are now able to move on from studies focusing on a few specific genes to

studies that can generate genome-wide maps of translocations and contacts

in both normal and neoplastic cells. From these maps, we can rank the rel-

ative specific weight of the different factors required for translocation forma-

tion. DSB frequency seems to largely determine the pattern of translocations

in normal cells and likely in cancer cells as well, but more studies are needed

to prove this. In the absence of a dominant source of DSBs (i.e., in the

absence of RAG or AID in B cells), translocations seem to follow the rules

dictated by the proximity of chromosomal regions where the DSBs occur.

The active transcription characteristics of genes influence their frequency of

translocation, but it remains to be determinedwhether this effect depends on

the increased probability of DSBs in transcribed genes or on increased


proximity due to clustering in transcription factors, or both. Defects in

DNA-repair pathways increase the overall frequency of translocation, but

the exact roles of the various NHEJ—and possibly HR—factors in translo-

cations remain to be fully elucidated. Finally, other important questions

await answers.What is the role of chromatin conformation in translocations?

Is there a tissue specificity in translocations of the same oncogene found in

different tumor types? Are the translocation mechanisms identical in normal

or cancer cells? The new combination of system-level tools and techniques

for mining genomic data will likely allow us to answer most of these ques-

tions in the near future.

ACKNOWLEDGMENTSThe work was supported by grants from the Associazione Italiana per la Ricerca sul cancro(AIRC), from the International Association for Cancer Research (AICR), and Grant FP7

ERC-2009-StG (Proposal No. 242965—“Lunely”).Disclosure Statement. The author is not aware of affiliations, memberships, funding, or

financial holdings that might affect the objectivity of this review.

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CHAPTER THREE

The Intestinal Microbiota inChronic Liver DiseaseJorge Henao-Mejia*,1, Eran Elinav†,1, Christoph A. Thaiss†,1,Richard A. Flavell*,‡,2*Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut, USA†Immunology Department, Weizmann Institute of Science, Rehovot, Israel‡Howard Hughes Medical Institute, Chevy Chase, Maryland, USA1Equal contributors2Corresponding author: e-mail address: [email protected]

Contents

1. Introduction 742. Role of the Intestinal Microbiota on Chronic Liver Diseases 75

2.1 Nonalcoholic fatty liver disease 752.2 Cirrhosis and associated comorbidities 782.3 Hepatocellular carcinoma 802.4 Autoimmune liver disease 80

3. Role of the Interactions Between the Innate Immune System and the IntestinalMicrobiota on Chronic Liver Diseases 813.1 Toll-like receptors 823.2 Inflammasomes 843.3 C-type lectins 863.4 Dysbiosis associated with innate immune deficiency and its implications for

liver disease 874. Probiotics and their Potential Role in Liver Disease Therapy 895. Conclusions 90References 91

Abstract

Recent evidence indicates that the intestinal microflora plays a critical role in physiolog-ical and pathological processes; in particular, it is now considered a key determinant ofimmune pathologies and metabolic syndrome. Receiving the majority of its blood sup-ply from the portal vein, the liver represents the first line of defense against food anti-gens, toxins, microbial-derived products, and microorganisms. Moreover, the liver iscritically positioned to integrate metabolic outcomes with nutrient intake. To accom-plish this function, the liver is equipped with a broad array of immune networks. It isnow evident that, during pathological processes associated with obesity, alcohol-intake,or autoimmunity, the interaction between these immune cell populations and the


73

http://dx.doi.org/10.1016/B978-0-12-410524-9.00003-7

intestinal microbiota promotes chronic liver disease progression and therefore they rep-resent a novel therapeutic target. Herein, we highlight recent studies that have shednew light on the relationship between the microbiome, the innate immune system,and chronic liver disease progression.

1. INTRODUCTION

The human gastrointestinal tract contains 10–100 trillion bacteria and

approximately 500–1500 different bacterial species (Lozupone, Stombaugh,

Gordon, Jansson, & Knight, 2012). These microorganisms have critical func-

tions in multiple aspects of human physiology such as regulation of metabolic

processes, education of the immune system, and promotion of epithelial cell

responses that are essential to maintain mutualism (Maynard, Elson, Hatton, &

Weaver, 2012; Tremaroli & Backhed, 2012). The intestinal microflora differs

quantitatively and qualitatively among species and individuals. Life style, age,

dietary habits, exposure to antibiotics, and host genotype play essential roles in

the composition of the intestinal microflora (Claesson et al., 2012; Turnbaugh

et al., 2009); moreover, disruption of the delicate balance that represents the

ecosystem of bacterial communities of the gastrointestinal tract can lead to

severe metabolic and inflammatory pathologies.

The close functional relationship between the liver and the gastrointes-

tinal tract (gut–liver axis) is highlighted by multiple important physiological

processes that intimately interconnect these organs. The liver, the largest

organ in the body, has a dual blood supply. The hepatic artery, which arises

from the celiac artery, supplies oxygenated blood to the liver, and the portal

vein conducts venous blood from the intestines and the spleen. Approxi-

mately 75% of hepatic blood flow is derived from the hepatic portal vein

(1000–1200 mL/min), and therefore, the liver is constantly exposed to

nutrients, toxins, food-derived antigens, microbial products, and microor-

ganisms derived from the intestinal tract (Miyake & Yamamoto, 2013). This

strategic location confers critical metabolic, immunologic, and detoxifying

roles to the liver and stresses the crucial role of the intestinal microbiota on

hepatic pathophysiology.

In this review,weexamine the impactof gutmicrobiotaonhepatic diseases,

focusing on how dysbiosis and immune responses triggered by microbiota-

derived products shape the progression of chronic liver pathologies.

74 Jorge Henao-Mejia et al.

2. ROLE OF THE INTESTINAL MICROBIOTA ON CHRONICLIVER DISEASES

2.1. Nonalcoholic fatty liver diseaseNonalcoholic fatty liver disease (NAFLD) is the leading cause of chronic

liver disease in Western societies, with a prevalence ranging from 20% to

40% in the general population and up to 75–100% in obese individuals

(Ludwig, Viggiano, McGill, & Oh, 1980; Sheth, Gordon, & Chopra,

1997). NAFLD is considered the hepatic manifestation of metabolic

syndrome (Marchesini et al., 2003), with many patients developing other

comorbidities including insulin resistance, hyperlipidemia, cardiovascular

disease, polycystic ovary syndrome, and obstructive sleep apnea (Cerda

et al., 2007; Tolman, Fonseca, Dalpiaz, & Tan, 2007). While most patients

with NAFLD remain asymptomatic, 20% progress to develop chronic

hepatic inflammation (nonalcoholic steatohepatitis, NASH), which in turn

can lead to cirrhosis, portal hypertension, hepatocellular carcinoma (HCC),

and increased mortality (Caldwell et al., 1999; Propst, Propst, Judmaier, &

Vogel, 1995; Shimada et al., 2002). NASH can be classified as primary

NASH (associated with obesity, type 2 diabetes (T2DM), and hyperlipemia)

and secondary NASH (occurring after pharmacological interventions,

parenteral nutrition, jejunoileal bypass surgery, or Wilson’s disease). Despite

its high prevalence, factors leading to progression from NAFLD to NASH

remain poorly understood and no treatment has proved effective (Charlton,

2008; Hjelkrem, Torres, & Harrison, 2008).

A “two-hit” mechanism is proposed to drive NAFLD/NASH pathogen-

esis (Day & James, 1998). The first hit, hepatic steatosis, is closely associated

with lipotoxicity-induced mitochondrial abnormalities that predispose the

liver to additional proinflammatory insults (second hits) that promote disease

progression. Second hits include increased generation of reactive oxygen spe-

cies, increased lipid peroxidation, and gut-derived factors. Most likely, the

parallel action of these hepatic tissue insults is required for the development

of steatohepatitis (Sanyal et al., 2001). In the past decade, a growing body

of research functionally links the intestinal microbiota with the development

of steatosis (first hit) and with the progression to NASH (second hit).

Obesity is considered the most common risk factor for NAFLD in

humans (Younossi et al., 2011). Several lines of evidence unequivocally link

the intestinal microflora with body weight and body fat composition

75The Intestinal Microbiota in Chronic Liver Disease

(Fig. 3.1). In animal studies, germ-free mice have a lower body fat content

than conventionally raisedmice; moreover, the inoculation of germ-free mice

with microbiota from wild-type mice results in a significant increase in body

fat accumulation (Turnbaugh et al., 2006). The phyla Bacteroidetes

and Firmicutes represent a large proportion of the intestinal microbiota com-

position in mice and humans; however, their relative abundance profoundly

affects the body composition of individuals (Ley et al., 2005; Ley, Turnbaugh,

Klein, & Gordon, 2006). Genetically obese mice (ob/ob) have a significant

increase in the Bacteroidetes to Firmicutes ratio when compared with lean

littermate controls, but perhaps more importantly, germ-free mice colonized

with microbiota from genetically obese mice gained weight faster and harvest

calories more efficiently than mice colonized with intestinal microflora from

lean mice (Turnbaugh et al., 2006). These findings indicate that the compo-

sition of the microbiota directly influences calorie extraction, body fat com-

position, and body weight.

In humans, several lines of evidence now correlate the composition

of the intestinal microbiota with multiple metabolic and inflammatory

parameters as well as dietary habits (Claesson et al., 2012; Ley et al.,

2006; Muegge et al., 2011). Similar to mice, obese individuals have

increased levels of Bacteroidetes and the reduction of this phylum in the

intestinal microflora is significantly associated with weight loss either by

Type 2 diabetes• Endotoxemia

SteatosisIntestinal microbiota

• Insulitis• Insulin resistance

Obesity

Decreased cholinemetabolism

• Increased calorie extraction• Cleavage of dietary polysaccharides• Dyslipidemia

Figure 3.1 Effects of the intestinal microbiota on the risk factors that promote NAFLDdevelopment. The microbiota can regulate the progression of multiple associated com-orbidities that are associated with NAFLD pathogenesis such as choline metabolism,obesity, and diabetes mellitus.


fat- or carbohydrate-restricted diets, suggesting that Bacteroidetes may be

responsive to calorie intake (Ley et al., 2006).Metagenome-wide association

studies have recently demonstrated that T2DM patients are characterized by

gut microbial dysbiosis, a decrease in the abundance of butyrate-producing

bacteria and an increase in various opportunistic bacterial pathogens. More-

over, these gut microbial markers can be useful for classifying T2DM, indi-

cating that specific conformations of the intestinal microbiota play critical

roles in the pathogenesis of T2DM and associated disorders (Qin et al.,

2012). Calorie intake of Western society diets is a key determinant of met-

abolic syndrome. Long-term dietary habits have a profound effect on the

human gut microbiota and therefore on potential deleterious metabolic out-

comes. It has been proposed that the human gut microbiota should be

divided into three compositions (enterotypes), yet this notion is still debated

and merits further validation. Each suggested enterotype is dominated by a

different genus—Bacteroides, Prevotella, or Ruminococcus—(Arumugam et al.,

2011). Interestingly, enterotypes dominated by Bacteroides are associated

with diet rich in protein and animal fat (Western diet), while Prevotella-

dominated enterotypes are associated with the consumption of a diet rich

in carbohydrates/fiber (De Filippo et al., 2010; Wu et al., 2011), suggesting

that the gut microbiota is shaped by the different diets to maximize energy

extraction. Taken together, these studies show that the composition of the

microbiota is a critical player in the metabolic status of the host and its dis-

turbance is associated with metabolic abnormalities that are associated with

the “first hit” (steatosis) during NAFLD pathogenesis.

Although it is now clear that the intestinal microflora plays critical roles

in body fat accumulation and weight gain, the role of gut-derived factors

on NAFLD progression has just begun to be elucidated. Progression from

steatosis to steatohepatitis is mainly an inflammatory process that likely

reflects the concerted deleterious effects of multiple noxious stimuli. Several

lines of evidence now suggest that intestinal bacterial communities might

play an important part in this process. Jejunoileal bypass, small intestinal

diverticulosis, total parenteral nutrition, and intestinal failure are associated

with NASH progression (Carter & Karpen, 2007; Corrodi, 1984; Nazim,

Stamp, & Hodgson, 1989; Quigley, Marsh, Shaffer, & Markin, 1993;

Vanderhoof, Tuma, Antonson, & Sorrell, 1982); interestingly, small intes-

tinal bacterial outgrowth (SIBO) as a consequence of low intestinal motility

has been proposed as a key determinant factor for NAFLD progression in

these conditions in humans (Carter & Karpen, 2007; Pappo et al., 1992;

Quigley et al., 1993). In concordance with this, antibiotic treatment or


surgical removal of the bypassed section of the intestine reverses SIBO

and steatohepatitis. Similarly, rats fed under total parenteral nutrition are

characterized by severe liver injury secondary to bowel hypomotility,

which leads to the expansion of Gram-negative bacterial populations and

increased hepatotoxic mediators such as endotoxin or tumor necrosis factor

(Pappo et al., 1992).

The role of the intestinal microbiota in the more highly prevalent pri-

mary NASH is less clear. The prevalence of SIBO is significantly increased

in obese individuals as compared with healthy lean subjects (Sabate et al.,

2008), but its role in NAFLD progression has largely been overlooked. Nev-

ertheless, a recent study conducted byMiele et al. (2009) evaluated intestinal

permeability, SIBO, and NAFLD disease stage. Interestingly, patients with

NAFLD were reported to have significantly increased gut permeability and

SIBO when compared with healthy individuals, suggesting that overgrowth

of the intestinal bacterial flora gut could lead to bacterial translocation, portal

endotoxemia, and ultimately hepatic injury (Miele et al., 2009). In concor-

dance with this possibility, multiple studies have found high levels of SIBO

prevalence in different cohorts of NASH patients (Sajjad et al., 2005; Wigg

et al., 2001); moreover, we recently demonstrated that inflammasome-

mediated dysbiosis characterized by an expansion of the Prevotellaceae and

Porphyromonadaceae families as well as the TM7 taxa promotes NAFLD pro-

gression in different mouse models (Henao-Mejia, Elinav, Jin, et al., 2012).

Collectively, these studies indicate that different compositions of the bacte-

rial communities of the intestines might regulate NAFLD progression in

humans and therefore represent a novel therapeutic target. Characterization

of the bacterial communities at different stages of NAFLD and the exact role

of metabolites derived from the bacterial microflora in disease progression

should shed some light on the precise role of the microbiome in liver disease

in the context of metabolic syndrome.

2.2. Cirrhosis and associated comorbiditiesCirrhosis is the final clinical–histopathological stage of a wide array of liver

diseases. The intestinal microbiota is a common denominator of the major

complications of liver cirrhosis, including spontaneous bacterial peritonitis,

hepatic encephalopathy (HE), and esophageal variceal bleeding (Basile &

Jones, 1997; Campillo et al., 1999; Guarner & Soriano, 1997; Husova

et al., 2005; Thalheimer, Triantos, Samonakis, Patch, & Burroughs,

2005). The process of liver fibrogenesis promotes dysbiosis and intestinal


barrier dysfunction through multiple pathological processes. Cirrhotic

patients have decreased blood flow through the portal vein and intestinal

vascular congestion, which results in increased gut permeability (Bauer

et al., 2001; Gunnarsdottir et al., 2003). Moreover, impaired liver function

promotes changes in bacterial communities in the gut through decreased bile

acid production and defective intestinal motility that leads to SIBO (Sung,

Shaffer, & Costerton, 1993). Thus, it is now well recognized that impaired

fluid/liver physiology and innate immunity in combination with dysbiosis

are key pathological processes that promote bacterial translocation to the

peritoneum.

HE is a broad term that encompasses a constellation of neuropsychiatric

abnormalities observed in patients with liver dysfunction (Bajaj, 2010).

Overt HE is diagnosed in up to 45% of patients with cirrhosis, while

minimal HE is observed in 60–80% of the patients (Bajaj, 2010). In healthy

individuals, the liver protects the brain from ammonia by converting it to

urea, which is then excreted by the kidneys. In the context of severe liver

dysfunction, ammonia becomes the critical driver of HE pathogenesis and

the intestinal microbiota is by far its predominant source (Williams, 2007).

In particular, Urease-producing bacteria such as Klebsiella and Proteus spe-

cies seem to play a critical role in increased ammonia production and HE

development (Basile & Jones, 1997). In concordance with the concept of

HE being a bacterial-driven disease, treatment with nonabsorbable antibi-

otics such as Neomycin and Rifaximinis is associated with a significant

decrease in the risk of breakthrough episodes of HE, relapses, or hospital-

ization due to this neuropsychiatric complication (Bajaj et al., 2011; Bass

et al., 2010; Sidhu et al., 2011).

Recently, the role of specific bacterial families in cirrhosis has begun to be

addressed. Two studies have performed nonculture-based methods

to determine the composition of the microbiota in patients with cirrhosis

and HE. Both studies found a higher concentration of Streptococcaceae and a

negative correlation between cirrhosis and the abundance of Lachnospiraceae

(Bajaj et al., 2012; Chen et al., 2011). Interestingly, Bajaj et al. (2012) found

that in addition to changes in the intestinal microbiota between healthy and

cirrhotic individuals, there was a significant increase in the abundance of dif-

ferent bacterial families (Enterobacteriaceae, Alcaligenaceae, and Streptococcaceae) in

patients with confoundedHE.Moreover, a positive correlation between cog-

nitive dysfunction and the presence of Alcaligenaceae and Porphyromonadaceae

was observed by standardized cognitive testing (Bajaj et al., 2012). The inves-

tigation of the gut microbiome in cirrhosis and its correlation to severe clinical


complications is still in its early stages, but identification of bacterial species

that specifically drives disease progression will greatly improve our under-

standing of the pathogenesis of these complex human diseases.

2.3. Hepatocellular carcinomaHCC is one of the most frequent human cancers worldwide. Approximately

80–90% of HCCs are preceded by chronic liver disease, hepatic fibrosis, and

cirrhosis (Nordenstedt, White, & El-Serag, 2010). Therefore, it has been

speculated that microbial-derived products are essential determinants of

HCC progression. Indeed, recent studies performed using a mouse model

of HCC showed that hepatocarcinogenesis in chronically injured livers

depended on the intestinal microbiota and Toll-like receptor 4 (TLR4)

activation in non-bone-marrow-derived resident liver cells. Importantly,

TLR4 and the gut microbiota are not required for HCC initiation but

for HCC progression as intestinal sterilization restricted late stages of

hepatocarcinogenesis (Dapito et al., 2012). The role of the microbiome

on human HCC is an unexplored area that warrants further investigation

in the following years.

2.4. Autoimmune liver diseasePrimary sclerosing cholangitis (PSC) is a chronic liver disease characterized

by inflammation and eventual obstruction of biliary ducts (Levy & Lindor,

2006). Although the pathogenesis of PSC remains undetermined, intestinal

microbiota is considered to be a major factor in its etiology. The role of

intestinal bacterial communities in ulcerative colitis (UC) pathogenesis is

well characterized. Interestingly, approximately 75% of patients with PSC

have UC and nearly 3% of patients with UC have PSC as a concomitant

comorbidity (Bambha et al., 2003; Bergquist et al., 2008; Hashimoto

et al., 1993; Joo et al., 2009; O’Toole et al., 2012; Sano et al., 2011; Ye

et al., 2011). Moreover, PSC is more frequent in UC patients with total

colonic involvement suggesting a strong positive correlation between

intestinal inflammation and PSC development (Joo et al., 2009; O’Toole

et al., 2012).

Several lines of evidence point to the microbiota as a common denom-

inator driving liver and intestinal inflammation in this condition. In the bile

of PSC patients, Candida and enteric bacteria such as Escherichia coli are

frequently detected (Rudolph et al., 2009). End-stage PSC liver shows


significantly increased expression and activation of critical genes involved

in innate immune pathways (Miyake & Yamamoto, 2013). Finally, serum

atypical perinuclear antineutrophil cytoplasmic antibodies (pANCA) are

frequently found in patients with PSC (Mulder et al., 1993; Terjung

et al., 1998). Recently, the autoantigen of this atypical pANCA has been

reported to be b-tubulin, but perhaps more importantly, pANCA cross-

reacts with FtsZ, a bacterial cytoskeletal protein present in all intestinal

bacteria (Terjung et al., 2010). Thus, identifying the specific bacterial species

that trigger PCS is a clinically relevant problem that deserves further

investigation.

Primary biliary cirrhosis (PBC) affects approximately 40 per 100,000 peo-

ple in the United States. PBC is an autoimmune liver disorder characterized

by immune cell activation and directed damage of cholangiocytes, which

results in cholestasis that ultimately leads to hepatic fibrogenesis and liver fail-

ure in 26% of patients within 10 years of diagnosis (Washington, 2007). The

presence in the serum of antimitochondrial antibodies (AMAs) is the hallmark

of PBC. AMAs are detected in approximately 95% of PBC patients and their

cross-reaction with bacterial components is proposed as a critical event for the

early pathogenesis of PBC (Bogdanos et al., 2004; Hopf et al., 1989). AMAs

have been reported to react with proteins of E. coli isolated from PBC patients

(Bogdanos et al., 2004; Hopf et al., 1989). Moreover, IgG3 antibodies in

approximately 50% of PBC patients cross-react with b-galactosidase of Lacto-bacillus delbrueckii, and in 25% of PBC patients, the serum reacts specifically

with proteins of Novosphingobium aromaticivorans from stool specimens

(Bogdanos et al., 2005; Selmi et al., 2003). Given this association, further study

is warranted to determine if modulation of gut microbiota might aid in the

treatment of this catastrophic disease.

3. ROLE OF THE INTERACTIONS BETWEEN THE INNATEIMMUNE SYSTEM AND THE INTESTINAL MICROBIOTAON CHRONIC LIVER DISEASES

The complex interplay between the host and its indigenous microflora

is mediated by a large array of pattern-recognition receptors (PRRs) of the

innate immune system (Carvalho, Aitken, Vijay-Kumar, & Gewirtz, 2012).

Originally mainly appreciated for their role in recognizing invading patho-

genic microbes and for the initiation of adaptive immune responses, these

receptors and their downstream signaling cascades are increasingly regarded


as pivotal for the recognition of the commensal microbiota. This microbial

recognition plays an important role under homeostatic conditions, and dys-

function in innate signaling in the intestine has been associated with aberrant

development of the intestinal immune system, failure in maintenance of

intestinal epithelial homeostasis and barrier function, and exacerbated intes-

tinal injury (Michelsen & Arditi, 2007). Importantly, this innate sensing

function also serves to locally contain the microbiota and to exclude intes-

tinal microorganisms from the systemic circulation (Slack et al., 2009).

The innate receptors expressed in the gastrointestinal tract represent the

first line of defense against invasion of microorganisms. However, in cases

of increased microbial translocation through the gastrointestinal barrier,

the liver as first line of defense requires the expression of innate PRRs in order

to set in place a secondary surveillance system of microbial products poten-

tially draining from the gastrointestinal tract. Indeed, intrahepatic expression

of innate immune receptors has been described for Kupffer cells (Visvanathan

et al., 2007), liver sinusoidal endothelial cells (Hosel et al., 2012), hepatic

stellate cells (Wang et al., 2009), biliary epithelial cells (Yokoyama et al.,

2006), and hepatocytes (Wang et al., 2005). Consequently, the liver has to

master a delicate balance between its ability to induce systemic tolerance

toward innocuous food particles and occasional translocation of commensal

microbial products and its role in promoting inflammation when a persistent

microbial stimulus caused by intestinal breech is indicative of systemic

microbial spread. In the following sections, we will discuss how hepatic

PRR signaling mediates host–microbial interactions in this vital organ, and

howaberrations inPRRexpression and signaling contribute to themolecular

etiology of liver disease.

3.1. Toll-like receptorsTLRs were the first class of PRRs discovered. They recognize a wide range

of microbial ligands, ranging from bacterial and fungal cell wall components

to nucleic acid (Kawai & Akira, 2010). TLRs are expressed in a wide variety

of liver cells and have long been recognized to be involved in the path-

ogenesis of liver diseases. In particular, Kupffer cells express high levels of

TLR2, TLR3, and TLR4, and respond to LPS stimulation with the produc-

tion of TNF-a, IL-6, and IFN-g. Moreover, the expression of TLRs has

been found on hepatocytes, biliary epithelial cells, hepatic stellate cells,

and liver sinusoidal endothelial cells (Miyake &Yamamoto, 2013) (Fig. 3.2).

TheTLR4–MyD88–NF-kB signaling axis has been found to play a critical

role in various pathophysiological settings in the liver, including cirrhosis,


fibrosis, viral hepatitis, HCC, and fatty liver disease. For instance, in mice on a

high-fat diet, TLR4 deficiency ameliorates hepatic steatosis (Li et al., 2011). In

addition, signaling through TRIF downstream of TLR4 in Kupffer cells has

been shown to promote alcoholic liver disease (Gao et al., 2011). Further,

hepatic TLR4 expression is increased in animal models of NASH (Thuy

et al., 2008), PSC (Mueller et al., 2011), and PBC (Wang et al., 2005). These

animal studies have been supported by genetic data from humans. A polymor-

phism in the gene encoding TLR4, which attenuates the signaling down-

stream of the receptor in response to LPS stimulation, has been associated

with a decreased risk to develop cirrhosis (Figueroa et al., 2012; Huang

et al., 2007).

Another TLRwhich has been repeatedly associated with enhanced sever-

ity of inflammatory liver disease is TLR9, which signals through IRF-7 to

induce the expression of type I interferons (IFNs). Interestingly, type I IFNs

Steatosis

Inflammatory responsein the liver

Flux of PRR ligands

Intestinal dysbiosis

Enterocytes: NLRP6

Hepatocyte: TLR2-4

TNFIL-6

LSEC: TLR2

Kupffer cell: TLR2-4

Stellate cell: TLR1-9

Figure 3.2 Multiple layers of pattern-recognition receptor involvement in the patho-genesis of liver disease. Functional expression of the NLRP6 inflammasome in the intes-tine is necessary to avoid dysbiosis. Chronic intestinal inflammation is associated withincreased translocation of microbes across the gastrointestinal tract and influx of micro-bial products into the liver. There, TLR expression on a variety of cell types mediates anaberrant respond to the increased microbial load, initiating an exaggerated inflamma-tory response that can lead to hepatitis.


were recently described to protect from TLR9-associated liver damage,

and this effect was mediated by the endogenous IL-1 receptor antagonist

(Petrasek, Dolganiuc, Csak, Kurt-Jones, & Szabo, 2011). The same authors

also found a protective role for type I IFNs in a TLR4-driven model of

alcoholic liver disease (Petrasek, Dolganiuc, Csak, Nath, et al., 2011).

The involvement of TLRs in a multitude of liver pathologies clearly

implied a role for increased microbial translocation across the gastrointestinal

tract and hepatic recognition of microbial products (Fig. 3.2), but direct evi-

dence for this notion has been lacking until recently. First insight came from

a study by Seki et al. who showed an involvement of the microbiota in the

development of hepatic fibrosis. Antibiotic treatment, as well as TLR4- or

MyD88-deficiency, reduced fibrosis after bile duct ligation. TLR4 expression

on hepatic stellate cells led to enhanced TGF-b signaling and recruitment

of Kupffer cells to the fibrotic liver (Seki et al., 2007).

As detailed below, we recently described that, under conditions of

intestinal inflammation, the influx of microbial products into the liver pro-

motes the development and progression of NAFLD in a TLR4- and

TLR9-dependent manner (Henao-Mejia, Elinav, Jin, et al., 2012). In con-

cordance with these results, Lin et al. recently used the concanavalin A

(ConA) model of fulminant liver injury to demonstrate that the intestinal

microbiota is critically involved in TLR4-mediated hepatitis. Treatment of

mice with broad-spectrum antibiotics as well as TLR4 deficiency greatly

ameliorated liver damage, as evidenced by reduced release of aminotrans-

ferases into the blood, dampened production of proinflammatory cyto-

kines, and decreased hepatic cell death (Lin et al., 2012). In contrast,

administration of purified LPS potentiated liver pathology in the ConA

model. Adoptive transfer experiments using TLR4-deficient or sufficient

splenocytes revealed that immune cells contribute to disease progression

through TLR4 expression.

3.2. InflammasomesInflammasomes are a group of cytosolic multiprotein complexes, classically

consisting of an upstream sensor protein of the NOD-like receptor (NLR)

family, the adaptor protein ASC, and the downstream effector caspase-1

(Henao-Mejia, Elinav, Strowig, & Flavell, 2012). To date, the NLR pro-

teins NLRP1, NLRP2, NLRP3, NLRP6, NLRP7, NLRC4, and the

HIN-200 family member AIM2 have been reported to initiate the forma-

tion of an inflammasome. Upon stimulation with a diverse set of microbial


or damage-associated molecular patterns, inflammasome assembly leads to

the autocatalytic cleavage of caspase-1 and processing of pro-IL-1b and

pro-IL-18 into their mature and bioactive forms (Strowig, Henao-Mejia,

Elinav, & Flavell, 2012). Inflammasome activity is thought to require two

sequential stimuli. The first stimulus drives transcription of the proforms

of IL-1b and IL-18, while the second stimulus is required for the formation

of the inflammasome complex (Latz, 2010). Inflammasomes fulfill a dual

role, recognizing both endogenous damage-associated substances such as

ATP or crystal particles and initiating immune responses in reaction to

pathogen-associated molecular patterns during bacterial, viral, fungal, and

parasitic infections (Elinav, Strowig, Henao-Mejia, & Flavell, 2011). In

addition, the inflammasomes are critically involved in the complex interplay

between the intestinal immune system and the gut microbiota, which will be

covered in more detail below.

Recently, inflammasomeswere identified to play a role in the pathogenesis

of liver disease. Inflammasome components are expressed by various cell types

in the liver. Kupffer cells and sinusoidal endothelial cells express high level of

NLRP1,NLRP3, and AIM2, and hepatocytes upregulate NLRP3 expression

in an LPS-dependent manner (Boaru, Borkham-Kamphorst, Tihaa, Haas, &

Weiskirchen, 2012). Imaeda et al. (2009) initially demonstrated an in-

volvement of the NLRP3 inflammasome in the development of

acetaminophen-induced hepatotoxicity and showed reduced mortality in

acetaminophen-treated mice lacking any component of the NLRP3

inflammasome, although others could not find a role for NLRP3 in

acetaminophen-mediated liver failure (Williams, Farhood, & Jaeschke,

2010). Watanabe et al. (2009) revealed expression of inflammasome compo-

nents in hepatic stellate cells and demonstrated an involvement of the

inflammasome in a mouse model of liver fibrosis using carbon tetrachloride

or thioacetamide. Similarly, knockdown of NLRP3 ameliorated liver inflam-

mation and protected ischemia–reperfusion injury in mice by preventing

excessive production of inflammatory cytokines and NF-kB activity (Zhu

et al., 2011).

These early studiesmainly focused on the role of the inflammasome in the

response against tissue damage in sterile injury-mediated models of liver dis-

ease. Subsequent reports, however, have also demonstrated an involvement

of the inflammasome in liver pathology caused by microbial components or

live microorganisms, such as in a model of Propionibacterium acnes-induced

sensitization to LPS-induced liver injury (Tsutsui, Imamura, Fujimoto, &

Nakanishi, 2010) and in Schistosoma mansoni infection (Ritter et al., 2010).


In these studies, a cooperative behavior of TLR signaling and inflammasome

activation was noticed to be a driving force in the development of overt liver

inflammation, suggesting concerted recognition events of microbial- and

damage-associated molecules.

Interestingly, Csak et al. (2011) recently showed an involvement of the

NLRP3 inflammasome in the development and progression of NASH.

Upon induction of a mouse model of NASH, expression of inflammasome

components was upregulated in the liver and inflammasome activation

occurred in isolated hepatocytes. Mechanistically, palmitic acid, a saturated

fatty acid, was found to activate the inflammasome and sensitized hepato-

cytes to IL-1b secretion in response to LPS. The results from this study indi-

cated that both microbial and nonmicrobial PRR ligands act in concert to

induce pathogenic inflammasome responses in the liver. A later study

confirmed NLRP3 activation in the liver and showed that LPS stimulation

alone is sufficient to drive hepatic production of inflammatory cytokines

downstream of NLRP3 inflammasome activation (Ganz, Csak, Nath, &

Szabo, 2011).

3.3. C-type lectinsC-type lectin (CTL) receptors and their downstream adaptor molecules are

mediating recognition of glycosylated ligands on microorganisms (Sancho &

Reis e Sousa, 2012). Dectin-1 and 2 are two CTLs involved in the immune

response against fungal pathogens. The recognition of fungal-associated

molecular patterns elicits a downstream cascade through the signaling mol-

ecules caspase recruitment domain-containing protein 9 (CARD9) and Syk

(Kerrigan & Brown, 2011). A recent study found hepatic mRNA expression

in humans of many factors involved in CTL signaling, including Dectin-1,

Syk, and CARD9 (Lech et al., 2012). Interestingly, CARD9, which is

known as a susceptibility locus in inflammatory bowel disease (IBD), has

recently been associated with PSC, along with Rel and IL-2, two other

IBD risk loci (Janse et al., 2011). Rel is a member of the NF-kB family

of transcription factors, CARD9 induces NF-kB signaling, and IL-2 is an

NF-kB target gene, potentially combining all three susceptibility loci into

one pathway.

The involvement of three members of a fungal recognition pathway in

PSC implies a functional role of innate immune recognition of fungal micro-

organisms in the pathogenesis of this disease. CARD9 is essential for the

control of fungal infection, and CARD9-deficient mice show high rates of


early mortality after infection with Candida albicans (Gross et al., 2006).

As mentioned above, Candida is detected in the bile fluid of 1 in every

10 PSC patients. In most cases, the detection of fungi in the bile negatively

influences the prognosis on disease severity (Rudolph et al., 2009).

Functional studies are needed in the future to delineate the mechanisms

and the importance of host–fungal interactions in the pathophysiology

of liver disease. Intriguingly, the recently suggested link between alter-

ations in commensal fungal sensing and susceptibility to IBD may poten-

tially provide a mechanistic explanation for the substantial susceptibility for

PSC among chronic IBD patients (Iliev et al., 2012).

Taken together, the involvement of PRRs of the innate immune

system in the pathogenesis of inflammatory liver disease has so far been

interpreted in the context of local responses to endogenous signal of dam-

age. While PRR-mediated recognition of damage-associated molecular

patterns certainly plays a critical role in disease development and progres-

sion, recent evidence indicates that one should also consider microbial

ligands as drivers in hepatic inflammatory disorders.

3.4. Dysbiosis associated with innate immune deficiencyand its implications for liver disease

The cases described above are examples of a liver-intrinsic role of microbial

recognition and its association with disease pathogenesis. Recent studies,

however, point to a new role of extrahepatic innate immune-microbial cross

talk in the initiation and progression of liver disease. First evidence came

from a report demonstrating that mice lacking TLR5, the receptor recog-

nizing bacterial flagellin, develop features of metabolic syndrome as a con-

sequence of altered microbial composition in the gut (Vijay-Kumar et al.,

2010). Although a recent study has argued that familial transmission, rather

than genetic deficiency, might be the dominant driver of dysbiosis in mice

(Ubeda et al., 2012), the intriguing notion that defective host–microbiome

interactions in the intestine might have consequences that are not limited to

regulating inflammation in the gastrointestinal tract, but rather affect sys-

temic metabolism and liver disease, has prompted further investigation.

We recently found that the intestinal tracts of mice deficient in the

inflammasome components NLRP3, NLRP6, ASC, and Caspase-1, as well

as mice lacking the downstream effector cytokine IL-18, harbor an aberrant

microbial community which is characterized by the overrepresentation of

anaerobic bacterial species of the Prevotellaceae family and the candidate

phylum TM7 (Elinav, Strowig, Kau, et al., 2011). This indicates that


inflammasomeactivity in the intestine is required for themaintenanceof a stable

microflora composition, partially through the secretion of IL-18. The altered

microbiota found in inflammasome-deficient mice was transferable to wild-

type mice upon cohousing in the same cage, demonstrating a dominant pop-

ulation effect, andwas reversible upon antibiotic treatment. The biogeograph-

ical niche enabling theoutgrowth ofPrevotellaceae seemed tobe the area close to

the colonic epithelial layer and the colonic crypts, an areawhich is normally less

densely colonized with microbes due to mechanisms involving antimicrobial

peptide production and mucus secretion. This altered intestinal flora leads to

mild chronic inflammation and greatly predisposes to experimental colitis.

Mechanistically, the colitogenic bacteria present in inflammasome-deficient

mice leads to enhanced epithelial production of the chemokine CCL5, which

in turn recruits proinflammatory immunecell populations to the intestinal lam-

ina propria (Elinav, Strowig, Kau, et al., 2011).

Most importantly, however, we found that the inflammatory processes

regulated by the colitogenic flora were not limited to the regulation of

local immune responses. When inflammasome-deficient mice were fed a

methionine/choline-deficient diet, a model commonly used to induce

NAFLD, they featured a dramatic outgrowth of bacterial species of the

Porphyromonadaceae family and enhanced translocation of microbial products,

in particular, TLR4 and TLR9 ligands, to the portal circulation (Henao-

Mejia, Elinav, Jin, et al., 2012). Again, this increased microbial translocation

across the gastrointestinal tractwas dependent on dysbiosis-inducedCCL5 pro-

duction and intestinal inflammation. In the liver, the increased stimulation of

TLR4 and TLR9 led to augmented production of TNF-a via MyD88/TRIF

signaling, which initiated an inflammatory process leading to the development

ofNASH.Thealteredmicrobiota alone,when transferred frominflammasome-

deficient or IL-18-deficient mice to wild-type recipients, was able to enhance

susceptibility to NASH in a CCL5-, TLR4-, TLR9-, MyD88/TRIF-, and

TNF-dependentmanner, demonstrating thatdysbiosis, rather thangeneticdefi-

ciency, was responsible for increased disease susceptibility and that metabolic

disease might feature infectious, that is, transmissible microbial, components.

Correspondingly, antibiotic treatment of inflammasome-deficient mice fed

anMCD diet not only amelioratedNASH severity but also inhibited transmis-

sion of the phenotype to wild-type recipients.

Moreover, the abnormal microflora also influenced other manifestations

of metabolic syndrome in other mouse models of disease. Genetically

obese leptin receptor-deficient mice gained markedly more weight when

cohoused with inflammasome-deficient mice and so did ASC-deficient


mice and cohoused wild-type mice fed a high-fat diet. Antibiotic treatment

reversed not only weight gain but also fasting plasma insulin amounts and

glucose intolerance to normal levels, showing the strong influence of the

microbial component on systemic metabolic parameters (Henao-Mejia,

Elinav, Jin, et al., 2012).

These results demonstrated that homeostatic extrahepatic expression of

PRRs is necessary to prevent the development of dysbiosis in the gastroin-

testinal tract, which in turn predisposes to liver disease via the tight anatom-

ical connection between both organ systems (Fig. 3.2). They also provide an

example where multistage host–microbial interactions via different kinds of

PRRs and their downstream signaling are involved in disease progression,

both at distal (in this case, inflammasomes) and proximal sites (in this case,

TLRs). The changes induced by the colitogenic microflora affect inflamma-

tory processes locally (induction of CCL5 and leukocyte recruitment to the

intestine), at the most proximal sites draining the intestine (inflammatory

cytokine production in the liver), and even beyond (multiorgan regulation

of weight gain and insulin sensitivity).

4. PROBIOTICS AND THEIR POTENTIAL ROLE IN LIVERDISEASE THERAPY

The recognition of the importance of dysbiosis in the development

and progression of liver disease opens new avenues for the development of

therapeutic approaches. Similar to diseases in which a contribution of

dysbiosis has long been appreciated, such as IBD, therapeutic intervention

with the aim of adjusting the composition of the intestinal microflora

might prove a valuable tool in the treatment of liver diseases. Probiotics

and prebiotics are actively exploited for their therapeutic effects in IBD

(DuPont & DuPont, 2011). Probiotics are live microorganisms given as

dietary supplements to modify their relative representation in the intestinal

ecosystem, while prebiotics are nondigestible dietary substances which pro-

mote the growth of one or more types of microorganisms in the gut, with

the aim of increasing their relative abundance in the intestinal microflora.

The benefits of pro- and prebiotics include direct effects, such as the

increased release of metabolic products, and indirect effects, in particular,

through microbe–microbe interactions and changes in population dynam-

ics of intestinal microbial communities.

Interestingly, the initial studies have demonstrated beneficial effects of

probiotic interventions in liver disease. In a rat model of liver damage


provoked by ischemia–reperfusion, intestinal dysbiosis was observed,

including the outgrowth of Enterobacteriaceae and a decrease in Bacteroides

spp., Lactobacillus spp., and Bifidobacter spp. These changes could be reversed

by dietary supplementation with Lactobacillus paracasei, which remarkably led

to reduced liver inflammation, as evidenced by ameliorated production of the

proinflammatory cytokines IL-1b, IL-6, and TNF-a (Nardone et al., 2010).

Similarly, after chemical liver injury, probiotic therapy with Lactobacillus spp.

reduced hepatic inflammation by supporting intestinal barrier function and

reducing microbial translocation across the gastrointestinal tract (Osman,

Adawi, Ahrne, Jeppsson, &Molin, 2007). Interestingly, in our inflammasome

dysbiosismousemodel, representation ofLactobacilluswas significantly reduced

(Elinav, Strowig, Kau, et al., 2011), pointing toward potential involvement of

this commensal family in prevention of local mucosal inflammation and the

related tendency toward systemic metabolic complications. Indeed, probiotic

interventions were shown to influence hepatic metabolism, as was demon-

strated in a rat model of high-cholesterol diet, in which Lactobacillus spp.

supplementation in the food reduced the levels of cholesterol and triglycerides

in the liver (Xie et al., 2011). Further, HE in cirrhotic patients was ameliorated

by probiotic therapy leading to decreased representation of E. coli and reduced

blood ammonia levels (Liu et al., 2004).

Future studies are clearly needed to understand the mechanisms by

which dietary manipulation of the intestinal ecosystem exerts its effects

on liver metabolism. Gnotobiotic mice represent an excellent tool to study

the contribution of individual microorganisms and their metabolic pathways

to liver function.

5. CONCLUSIONS

The mesenteric lymph node is the “first pass” organ for nutrients and

microbial substances entering the lymph fluid in the intestinal lamina

propria. As such, it serves as a key site for tolerance induction to food

particles but at the same time acts as a firewall to prevent systemic spread

of microorganisms. Similarly, the liver is exposed to all substances leaving

the gastrointestinal tract via the portal blood circulation and faces similar

challenges balancing tolerance to innocuous particles draining from the

intestine and barrier function to potentially harmful microbial substances.

In contrast to the mesenteric lymph node, the liver is the body’s prime

metabolic organ, and any aberrations from the homeostatic state of

host–microbial interactions in the liver may affect its metabolic functions.


We are convinced that the realization that both intrahepatic and extra-

hepatic host–microbial interactions, and in particular, innate immune

system–microflora interactions, drastically influence systemic physiologic

and pathophysiologic processes will guide future efforts to exploit this

new insight in preclinical and clinical settings.

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CHAPTER FOUR

Intracellular Pathogen Detectionby RIG-I-Like ReceptorsEvelyn Dixit, Jonathan C. Kagan1Harvard Medical School and Division of Gastroenterology, Boston Children’s Hospital, Boston,Massachusetts, USA1Corresponding author: e-mail address: [email protected]

Contents

1. General Principles of the Antiviral Innate Immune Response 992. RLRs are RNA Sensors 101

2.1 Common and distinct features of RLRs and their signaling capabilities 1012.2 Structural characteristics of synthetic RLR ligands 1042.3 Viruses 1062.4 Bacteria 108

3. RIG-I Activation and Receptor Proximal Signal Propagation 1094. Regulatory Mechanisms of RIG-I Signaling 113

4.1 Regulators of RLR signaling 1134.2 Regulation of RLR signal transduction by subcellular compartmentalization 115

5. Conclusions and Future Directions 117Acknowledgments 118References 118

Abstract

The RIG-I-like receptors (RLRs) RIG-I, MDA5, and LGP2 trigger innate immune responsesagainst viral infections that serveto limitvirus replicationandto stimulateadaptive immunity.RLRsarecytosolic sensors forvirus-derivedRNAandthus responsible for intracellular immunesurveillance against infection. RLR signaling requires the adapter protein MAVS to inducetype I interferon, interferon-stimulated genes, and proinflammatory cytokines. This reviewfocuses on the molecular and cell biological requirements for RLR signal transduction.

1. GENERAL PRINCIPLES OF THE ANTIVIRAL INNATEIMMUNE RESPONSE

Viruses are obligate intracellular parasites and thus depend strictly on

the biosynthetic machinery of the host in order to replicate and spread. As a

result, the virus-driven exploitation of the host cell’s metabolic pathways and


99

http://dx.doi.org/10.1016/B978-0-12-410524-9.00004-9

reprogramming of cellular processes often lead to cell death. The struggle for

survival between virus and host is ancient and as a consequence both have

evolved multiple strategies to antagonize each other. While mammalian

hosts developed sophisticated mechanisms of antiviral immunity, viruses

acquired strategies to evade the immune response. Therefore, it is critical

for the host to mount an effective innate and adaptive immune response

immediately upon infection in order to successfully combat the pathogen.

The innate immune response constitutes the earliest phase of the host’s

defense against pathogens and will stimulate and modulate the later onset

adaptive response (Palm & Medzhitov, 2009). It operates through a set of

germ line-encoded pattern recognition receptors (PRRs) that recognize

pathogen-associated molecular patterns (PAMPs) of viruses, bacteria, fungi,

and protozoa. PAMPs are conservedwithin broad classes of pathogens. They

are typically products of biosynthetic pathways that are essential for the sur-

vival of the pathogen and thus lack the potential for immune evasion

through genetic variability (Medzhitov, 2007). Owing to the panel of

PAMPs that is recognized by PRRs, the innate immune system achieves

an impressively complete coverage of pathogens despite the genetically lim-

ited number of available receptors. Engagement of antiviral PRRs by their

cognate PAMPs activates signaling pathways that lead to the production of

defense factors such as proinflammatory cytokines, type I interferons (IFN-aand IFN-b), or interferon-stimulated genes (ISGs). ISGs induced by IFN

secretion or cell-autonomously upon viral infection collectively establish

an antiviral state that limits viral replication and prevents further spread of

the infection (Katze, He, & Gale, 2002).

Detection of viruses poses a particular challenge to the host as they lack

features in line with the postulated characteristics of PAMPs, that is, invari-

ant structures required for survival. With few exceptions, viral proteins are

highly variable without being functionally compromised by mutation.

Moreover, viruses are obligate parasites relying on the host metabolism

for their replication. The evolutionary solution to this problem is to recog-

nize viral nucleic acids, either virus genomes or replication intermediates.

Undoubtedly, nucleic acid is not a PAMP that is unique to viruses and thus

virus detection comes at the cost of the potential for autoimmunity (Barton

& Kagan, 2009). Nucleic acid detection is accomplished by a growing list of

PRRs, namely, the cytosolic RIG-I-like receptors (RLRs) RIG-I and

MDA5 (Yoneyama et al., 2005, 2004); the endosomal Toll-like receptors

TLR3, TLR7/8, TLR9, and TLR13 (Kawai & Akira, 2010); the Ifi16/

cGAS/STING axis (Ishikawa, Ma, & Barber, 2009; Sun, Wu, Du, Chen, &

100 Evelyn Dixit and Jonathan C. Kagan

Chen, 2012; Unterholzner et al., 2010; Wu et al., 2012); and the AIM2

inflammasome (Burckstummer et al., 2009; Fernandes-Alnemri, Yu, Datta,

Wu, & Alnemri, 2009; Hornung et al., 2009; Roberts et al., 2009). This

review will focus on virus-induced signaling by RLRs; nucleic acid sensing

by other receptor families is reviewed elsewhere (Barbalat, Ewald,

Mouchess, & Barton, 2011).

2. RLRs ARE RNA SENSORS

2.1. Common and distinct features of RLRs and theirsignaling capabilities

RLRs detect RNA derived from RNA viruses and in some instances DNA

viruses. In terms of specificity and signaling output, RLRs aremost similar to

TLR3, as both detect viral RNA and induce ISGs, type I IFN, and

proinflammatory cytokines (Alexopoulou, Holt, Medzhitov, & Flavell,

2001; Matsumoto et al., 2003; Schulz et al., 2005). However, there is a fun-

damental conceptual difference in nucleic acid detection between TLRs and

RLRs. The nucleic acid-specific endosomal TLRs TLR3, TLR7/8, and

TLR9 recognize extracellular nucleic acids having reached the endosomes

through endocytosis (Takeda & Akira, 2005), whereas RLRs are cytosolic

receptors required for detection of intracellular viral RNA from actively

replicating viruses (Kawai & Akira, 2006). As such, RLRs represent an indis-

pensable means for determining if a given cell is infected or not. In line with

this key role in antiviral immunity, RLR signaling operates in most cell

types. In contrast, TLR expression is restricted to specialized immune cells

such as macrophages and dendritic cells. Even thoughRLRs are expressed in

plasmacytoid dendritic cells, TLRs but not RLRs are required for IFN-aproduction in this cell type (Kato et al., 2005).

Three highly related proteins constitute the family of RLRs: the

founding member RIG-I, MDA5, and LGP2. They are characterized by

a central ATPase containing DExD/H box helicase domain. RIG-I and

MDA5 contain N-terminal tandem CARD domains that mediate down-

stream signaling, whereas LGP2 lacks a CARD (Yoneyama et al., 2005,

2004). RIG-I and LGP2 also harbor a repressor domain (RD) in their

C-terminal regulatory domains (CTDs) (Fig. 4.1). Due to the presence of

the RD in RIG-I, its overexpression in the absence of an activating ligand

does not result in signaling, whereas MDA5 overexpression is sufficient to

activate the pathway. In accordance with their domain architecture, RLRs

lacking the CARDs have a dominant negative phenotype. RIG-I devoid of

101RIG-I-Like Receptor Signaling

the CTD or the N-terminal fragment comprising solely the CARDs signal

constitutively (Cui et al., 2008; Saito et al., 2007; Takahasi et al., 2008). All

RLRs are present at low levels in resting cells, but their expression is strongly

induced by type I IFN creating a feed forward loop for a robust antiviral

response (Kang et al., 2004; Yoneyama et al., 2005, 2004).

Despite different ligand specificities for viral RNA, both RIG-I and

MDA5 rely on the same signaling cascade to trigger the expression of type

I IFNs, ISGs, and proinflammatory cytokines (Yoneyama et al., 2005). The

adapter protein MAVS (also known as IPS-1, VISA, and Cardif ) (Kawai

et al., 2005; Meylan et al., 2005; Seth, Sun, Ea, & Chen, 2005; Xu et al.,

2005) acts immediately downstream of the receptors and represents a node

from which RLR signaling branches in several directions in order to pro-

mote the activation of NF-kB through the canonical IKKs, IKK-a,IKK-b, and IKK-g, of ATF2/c-jun through MAPK activation and most

importantly of members of the interferon regulatory factor (IRF) family

of transcription factors (Kawai et al., 2005; Meylan et al., 2005;

Mikkelsen et al., 2009; Poeck et al., 2010; Seth et al., 2005; Xu et al.,

2005). IRF3 and IRF7 are the essential transcription factors for IFN-b gene

transcription, as activation of NF-kB and ATF-2/c-Jun alone is not suffi-

cient for IFN-b induction. Interestingly, in dendritic cells, IRF5 can also

function to promote IFN-b expression (Lazear et al., 2013). They reside

in the cytosol in their latent forms until viral infection activates the non-

canonical IKKs, TBK1 and IKK-i. Phosphorylation of IRF3 and IRF7

by these kinases causes hetero- or homodimerization and nuclear trans-

location. IRF3 and/or IRF7, NF-kB, and ATF-2/c-Jun together with

RIG-I1

7

11

10 77 103 153 514 534 540

476 678

97 110 190 316 882 1025

87 92 172 251 735 925CARD CARD

CARD

CARD Pro

CARD

RD/CTD

RD-like

RD/CTD

TM

ATPase/helicase

ATPase/helicase

ATPase/helicase

MDA5

LGP2

MAVS

Figure 4.1 Domain architecture of RLRs and MAVS. Domain boundaries are indicatedfor human RIG-I, MDA5, LGP2, and MAVS proteins according to www.uniprot.org. Notethat MDA5 harbors an RD-like domain in the C-terminus that does not participate inautoregulation.


http://www.uniprot.org

the transcriptional coactivator CBP/p300 and the architectural protein

HMG I(Y) assemble in an enhanceosome to direct IFN-b transcription

(Hiscott, 2007; Honda, Takaoka, & Taniguchi, 2006) (Fig. 4.2).

Once IFN-b is secreted, it binds to the IFN-a/b receptor (IFNAR) in an

autocrine and paracrine manner resulting in JAK-STAT signaling and thus

expression of several hundred ISGs by the ISGF3 transcription factor, which

consists of STAT1, STAT2, and IRF9 (Platanias, 2005). However, despite

their namesake, ISGs may also be induced independent of a preceding secre-

tion of type I IFN (Collins,Noyce,&Mossman, 2004;Mossman et al., 2001).

Influenza virus WNVDengue virus

EMCVTheiler’s virus

ReovirusNDVSeVVSVHCVJEV

RIG-I MDA-5

P P P

TRIM25Riplet

Cytoplasm

RNF125PKC-a/b

NLRX1 MAVS

IKK-iTBK1

IKK-aIKK-bIKK-g

MAPKs

ATF2/c-Jun

NucleusISGsCytokinesType I IFN

NF-kBIRF3/7

?

Figure 4.2 RLR signaling on a glance. The repertoire of viruses detected by RIG-I andMDA5, respectively, reflects their different ligand specificities. Both receptors use com-mon signaling components to activate three sets of transcription factors required forexpression of type I IFN, proinflammatory cytokines, and ISGs.


Many ISGs function as direct antiviral effectors, acting to prevent viral

genome replication, viral particle assembly, or virion release from infected

cells. Others encode components of signaling pathways such as receptors

for pathogen recognition or transcription factors resulting in a stronger

IFN response and thereby creating a positive feedback loop.

The role of LGP2 in antiviral immunity is less clear. LGP2 lacks a

CARD domain (Fig. 4.1). Devoid of a signaling domain, LGP2 was pro-

posed to be a negative regulator of RLR signaling. Overexpression of

LGP2 does not activate IFN-b induction. On the contrary, reduced

IRF3 activation was observed when LGP2 overexpressing cells were

infected with Newcastle disease virus (NDV) (Rothenfusser et al., 2005;

Yoneyama et al., 2005). In vivo experiments with different lines of

LGP2-deficient mice strongly contradict the previous data generated by

in vitro studies and implicate LGP2 as a positive regulator (Satoh et al.,

2010; Venkataraman et al., 2007). In the absence of LGP2, both RIG-I

and particularly MDA5-dependent responses to RNA virus infection are

impaired, whereas responses to synthetic ligands of these RLRs are

unaffected (Satoh et al., 2010). Presumably, LGP2 facilitates binding of viral

RNA—potentially in complex with protein—to its cognate receptor,

whereas the affinity of RIG-I and MDA5 is sufficiently strong to bind to

“naked” synthetic agonists. Structural analysis of the binding interface of

RNA with the CTD of RIG-I supports this model, as it predicts weaker

affinity of MDA5 than RIG-I to its ligand (Takahasi et al., 2009). In

addition to confirming the role of LGP2 as a positive, yet nonessential reg-

ulator of RLR signaling, a recent report implicates LGP2 as a cell-intrinsic

regulator of virus-specific CD8! T cell survival and effector functions.

CD8! T cells are crucial for controlling West Nile virus (WNV) pathology

in the brain. LGP2-deficient mice displayed higher viral burden and signif-

icantly lower WNV-specific CD8! T cells in the brain leading to increased

mortality as compared to wild-type animals (Suthar et al., 2012). Nonethe-

less, further clarification is required to determine the role of LGP2 in RLR

signaling.

2.2. Structural characteristics of synthetic RLR ligandsThe two best characterized RLRs, RIG-I and MDA5, recognize structur-

ally distinct RNA species that have reached the cytosol by infection or by

means of transfection. Being cytosolic receptors, RIG-I and MDA5 do

not respond to extracellular nucleic acid.


The RIG-I ligand comprises an RNA molecule with two features: (i) a

50-triphosphate (Hornung et al., 2006; Pichlmair et al., 2006) and (ii) base

pairing at the 50-end due to secondary RNA structures such as hairpin or

panhandle conformations (Schlee et al., 2009; Schmidt et al., 2009). Studies

aimed at the characterization of molecular features of the RIG-I ligand largely

rely on in vitro transcripts. In vitro-transcribed RNA by all knownRNA poly-

merases leaves a triphosphate at the50 endof the transcript (pppRNA)(Schlee&

Hartmann, 2010). Transfection of pppRNA intomonocytes resulted in robust

IFN-a secretion,whereasRNA lacking a triphosphate didnot (Hornunget al.,

2006).Similarly, highly immunogenicRNAextracted frominfluenza-infected

cellswas rendered nonstimulatory after phosphatase treatment (Pichlmair et al.,

2006). However, a 50-triphosphate alone is not sufficient to mark a single-

stranded (ss) RNA molecule as nonself and to render it immunogenic. In

support of this notion, synthetic 50-triphosphate-ssRNA did not activate

RIG-I signaling. In contrast, when the same ssRNA molecule was generated

by in vitro transcription, it was stimulatory. Reverse cloning and sequencing of

the latter RNA species revealed the presence of sequences generated by self-

coding intramolecular 30-extension leading to blunt-ended RNA with com-

plementary 50- and 30-ends. Thus, aberrant in vitro transcription products are

responsible for the immunostimulatory properties of such preparations. The

minimal length of the 50-base paired region was found to be 19 bp. Further-

more, a 30-overhang of 2 nt reduced the stimulatory activity by 70%, while

no 50-overhang was tolerated (Schlee et al., 2009). Alternative to 50-base

pairing, sequence composition may contribute to the stimulatory potential

of pppRNA. Hepatitis C virus (HCV) genomic ssRNA is characterized by

polyuridine motifs with interspersed C nucleotides (referred to as poly-U/

UCmotifs) anda50-triphosphate.Deletionof thepoly-U/UCmotif abrogated

the stimulatory activity of HCV genomic RNA (Saito, Owen, Jiang,

Marcotrigiano, & Gale, 2008; Uzri & Gehrke, 2009). Thus, both panhandle

structures and poly-U/UC may serve as a secondary PAMP for pppRNA.

However, short synthetic double-stranded (ds) RNA without a 50-

triphosphate was reported to activate RIG-I as well (Kato et al., 2008;

Takahasi et al., 2008).Notably, the antiviral proteinRNaseLcancleave ssRNA

of virus or host origin and thereby generate short (200 nt) ligands devoid of a

50-triphosphate for RIG-I and MDA5 (Malathi, Dong, Gale, & Silverman,

2007). The structural features responsible for the immunogenicity of

RNaseL-generated ligands have not been identified.

The molecular nature of the MDA5 ligand remains poorly charac-

terized. The stereotypic MDA5 agonist is polyI:C (Gitlin et al., 2006;


Kato et al., 2006), a synthetic RNAmolecule lacking 50-triphosphates that is

generated by the annealing of poly-inosine strands to poly-cytidine strands

of various lengths. Thus, polyI:C contains an ill-defined mix of ramified ds

and ssRNA. Size fractionation of polyI:C revealed that MDA5 responds to

high-molecular-weight (HMW) polyI:C, whereas polyI:C shorter than

1000 nucleotides acts as a RIG-I agonist (Kato et al., 2008). Size fraction-

ation of total RNA isolated from encephalomyocarditis virus (EMCV)-

infected cells yielded a prominent dsRNA fraction of 11 kb and an even

larger-molecular-weight RNA aggregate with variable ss and dsRNA con-

tent. Of note only the RNA aggregate, but not the dsRNA, stimulated

MDA5 activity. Furthermore, this fraction required its intact secondary

and tertiary structure to remain fully active (Pichlmair et al., 2009). Thus,

MDA5 preferentially binds to HMW dsRNA that presumably adopts a

web-like conformation much like the synthetic RNA analog polyI:C.

2.3. VirusesThe structural features of viral RNA that are displayed by a given virus

depend on its replication cycle. As a consequence, the different ligand

specificities of RIG-I and MDA5 are reflected by the largely non-

overlapping pattern of virus susceptibility of mice deficient in either of

the two RLRs. RIG-I is required for innate responses to many ssRNA

viruses. The best-studied examples among these are the negative-stranded

viruses of the orthomyxoviridae, for example, influenza A and B virus,

paramyxoviridae, for example, NDV, Sendai virus (SeV), respiratory

syncytial virus, and measles virus, and rhabdoviridae, for example, vesic-

ular stomatitis virus (VSV) and rabies virus (Hornung et al., 2006; Kato

et al., 2006; Loo et al., 2008; Plumet et al., 2007). Moreover, detection of

positive-stranded flaviviruses including HCV and Japanese encephalitis

virus is RIG-I dependent (Kato et al., 2006; Saito et al., 2007;

Sumpter et al., 2005). In addition, recognition of cytoplasmic DNA

can also feed into the RIG-I pathway. RIG-I does not detect DNA

directly but can do so after RNA polymerase III-mediated transcription

of AT-rich DNA. IFN induction in response to infection with DNA

viruses such as adenovirus, herpes simplex virus-1, and Epstein–Barr virus

relies on this pathway (Ablasser et al., 2009; Chiu, Macmillan, & Chen,

2009; Samanta, Iwakiri, Kanda, Imaizumi, & Takada, 2006). MDA5 is

required for protection against picornaviruses such as EMCV, Theiler’s

virus, mengovirus, murine norovirus, and murine hepatitis virus (Gitlin


et al., 2006; Kato et al., 2006; McCartney et al., 2008; Roth-Cross,

Bender, & Weiss, 2008). Similar to RIG-I, MDA5 has also been impli-

cated in DNA virus detection. Vaccinia virus, a dsDNA virus of the

poxvirus family, activates MDA5 via a yet-to-be-characterized mechanism

(Pichlmair et al., 2009). Someviruses such asWNV,Denguevirus, reovirus,

and lymphocytic choriomeningitis virus (Fredericksen, Keller, Fornek,

Katze, & Gale, 2008; Loo et al., 2008; Zhou et al., 2010) trigger both

RIG-I- and MDA5-dependent innate immune responses. RLR depen-

dence of the aforementioned viruses was determined by infection of

different RLR-deficient cell types or mice with purified virions and is

summarized in Table 4.1.

Table 4.1 RIG-I and MDA5 detect different sets of viruses

Viruses detected by RIG-I

Orthomyxoviridae(") ssRNA, NS

Influenza A virus Kato et al. (2006)

Influenza B virus Loo et al. (2008)

Paramyxoviridae(") ssRNA, NS

Sendai virus Kato et al. (2006)

Newcastle disease virus Kato et al. (2006)

Respiratory syncytialvirus

Loo et al. (2008)

Measles virus Plumet et al. (2007)

Rhabdoviridae (")ssRNA, NS

Vesicular stomatitisvirus

Kato et al. (2006)

Rabies virus Hornung et al. (2006)

Flaviviridae (!)ssRNA NS

Hepatitis C virus Saito et al. (2007) and Sumpter et al.(2005)

Japanese encephalitisvirus

Kato et al. (2006)

dsDNA-viruses Epstein–Barr virus Ablasser et al. (2009), Chiu et al.(2009), and Samanta et al. (2006)

Herpes simplex virus-1 Chiu et al. (2009)

Adenovirus Chiu et al. (2009)

Continued


2.4. BacteriaVarious bacteria including Francisella tularensis,Mycobacteria tuberculosis, Brucella

abortis, group B streptococcus (GBS), Listeria monocytogenes, and Legionella

pneumophila have been shown to induce type I IFN in a TLR-independent

manner (Charrel-Dennis et al., 2008; Henry, Brotcke, Weiss, Thompson,

& Monack, 2007; O’Riordan, Yi, Gonzales, Lee, & Portnoy, 2002; Opitz

et al., 2006; Roux et al., 2007; Stanley, Johndrow, Manzanillo, & Cox,

2007; Stetson &Medzhitov, 2006). While it is well appreciated that viral rep-

lication is inhibited by type I IFN, the role of IFN in bacterial infections is less

clear; for example, IFNhas a protective effect duringGBS infection (Mancuso

et al., 2007), whereas it is disadvantageous during Listeria infection (Auerbuch,

Brockstedt, Meyer-Morse, O’Riordan, & Portnoy, 2004; Carrero, Calderon,

& Unanue, 2004; O’Connell et al., 2004). Even less clear is which bacterial

ligands and host receptors trigger IFN secretion.

Table 4.1 RIG-I and MDA5 detect different sets of viruses—cont'd

Viruses detected by MDA5

Picornaviridae (!)ssRNA, NS

Encephalomyocarditisvirus

Gitlin et al. (2006) and Kato et al.(2006)

Theiler’s virus Kato et al. (2006)

Mengovirus Kato et al. (2006)

Caliciviridae (!)ssRNA, NS

Murine norovirus-1 McCartney et al. (2008)

Coronaviridae (!)ssRNA NS

Murine hepatitis virus Roth-Cross et al. (2008)

Viruses detected by RIG-I and MDA5

Flaviviridae (!)ssRNA, NS

Dengue virus Loo et al. (2008)

West Nile virus Fredericksen et al. (2008) andLoo et al. (2008)

ReoviridaedsRNA S

Reovirus Loo et al. (2008)

Arenaviridae (")ssRNA, S

Lymphocyticchoriomeningitis virus

Zhou et al. (2010)

RLR dependence to various viruses is listed according to virus families. The respective genome type isindicated as single-stranded (ss) or double-stranded (ds) RNA or DNA with negative (") or positive (!)genome orientation featuring segmentation (S) or nonsegmentation (NS).


The intracellular gram-negative bacterium L. pneumophila infects macro-

phages and causes Legionnaires’ disease. IFN-b induction in lung epithelial

cells and macrophages depends on MAVS (Monroe, McWhirter, & Vance,

2009; Opitz et al., 2006). However, the signaling events upstream of MAVS

activation are a matter of debate. Chiu et al. propose that AT-rich DNA

reaches the host cytosol and is transcribed into an RNA ligand for RIG-I

in an RNA polymerase III-dependent manner (Chiu et al., 2009). In con-

trast, Monroe et al. argue that the IFN response to Legionella genomic DNA

does not require MAVS in mouse macrophages as MAVS-deficient and

wild-type macrophages display comparable levels of IFN. Instead, their data

support a model where Legionella RNA is directly detected by both RIG-I

and MDA5 as macrophages deficient in either receptor display a partial

phenotype (Monroe et al., 2009).

Shigella flexneri, the causative agent of bacillary dysentery, infects macro-

phages of the colonic epithelium and rapidly induces cell death by

pyroptosis. Escaping bacteria invade colonic epithelial cells where they rep-

licate in the cytosol. Type II IFN-g is critical for inhibiting S. flexneri cyto-

solic growth. It is at this stage that IFN-g exerts its antimicrobial effect

through RIG-I signaling in nonmyeloid cells. Both RIG-I- and MAVS-

deficient mouse embryonic fibroblasts (MEFs) failed to restrict IFN-g-dependent S. flexneri replication. Inhibition of RNA polymerase III also

reduced the antimicrobial effect of IFN-g suggesting that RIG-I signaling

is triggered by RNA polymerase III-generated RNA mediates. Interest-

ingly, type I IFN induction is not required for this effect as IFNAR-deficient

MEFs that are completely unresponsive to type I IFNs do not impair IFN-g-mediated growth inhibition of S. flexneri. In contrast, in primary macro-

phages, RIG-I signaling is dispensable for IFN-g-mediated growth arrest

( Jehl, Nogueira, Zhang, & Starnbach, 2012). These findings underscore

the importance of the interplay of distinct innate immunity pathways in

order to successfully combat pathogens.

3. RIG-I ACTIVATION AND RECEPTOR PROXIMAL SIGNALPROPAGATION

RLR activation is a multistage process that requires a well-coordinated

interplay of receptor, ligand, and several accessory proteins. In contrast to

RIG-I, the specific requirements for efficient MDA5 activation are unclear,

but it stands to reason that both proinflammatory RLRs follow a similar

mechanism. As exemplified by RIG-I, our current understanding of this


process involves the following sequence of events: (1) In resting cells, RIG-I

adopts a closed conformation resulting in an autoinhibited (nonsignaling)

state. (2) pppRNA binding to RIG-I induces conformational changes that

lead to dimerization and exposure of CARDs in the open conformation.

(3) Dephosphorylation of RIG-I and TRIM25-dependent ubiquitination

events fully activate the signaling capability of RIG-I. (4) RIG-I associates

with MAVS in a CARD-dependent manner. (5). MAVS accumulates in

signaling aggregates by a prion-like mechanism.

In the absence of infection, RIG-I is kept in an autoinhibited state by

intramolecular interactions between the CARDs and the helicase domain,

which sterically hinders RNA binding to the helicase domain and prevents

the CARDs from signaling (Kowalinski et al., 2011; Saito et al., 2007).

Accordingly, the N-terminus of RIG-I comprising the two CARDs has

a constitutively active phenotype when overexpressed (Yoneyama et al.,

2004). Furthermore, phosphorylation of threonine 170 (and serine 8 in pri-

mate orthologs) by PKC-a and PKC-b suppresses RIG-I activity at steady

state (Gack, Nistal-Villan, Inn, Garcia-Sastre, & Jung, 2010; Maharaj, Wies,

Stoll, & Gack, 2012; Nistal-Villan et al., 2010).

Only upon ligand binding does the closed conformation open up to

facilitate downstream signaling by the CARDs. Biochemical studies have

identified the CTD as the sensor for pppRNA. Receptor–ligand interac-

tions were examined by measuring ATPase activity of purified deletion

mutants of RIG-I lacking the CARDs (DCARD), the CTD (DCTD), or

both (helicase) in response to treatment with a panel of RNA ligands derived

from the rabies virus leader (RVL) sequence, that is, pppRNA (pppRVL),

nonphosphorylated ssRNA (ssRVL), as well as dsRNA (dsRVL). ssRVL did

not activate ATPase activity in any of the RIG-I variants. pppRVL strongly

stimulated ATPase activity of wild-type RIG-I. Deletion of the CARDs did

not interfere with pppRVL-stimulated ATPase activity. Neither the helicase

domain alone nor RIG-I lacking the CTD displayed ATPase activity in

response to pppRVL. dsRNA weakly stimulated wild-type RIG-I and

the isolated helicase domain. Of note, dsRNA activatedDCARDmore effi-

ciently than pppRVL achieving ATPase activity levels comparable to wild-

type RIG-I in complex with pppRVL. These findings suggest that the

CARDs inhibit dsRNA binding in an inactive conformation, while CTD

promotes pppRVL binding in an active conformation. Further binding

studies clearly demonstrated that the pppRNA binding site resides within

the CTD. X-ray crystallography of the CTD revealed two features that

are required for pppRNA binding: (1) A zinc coordination site comprising


four highly conserved cytidine residues (C810, C813, C864, C869). These

cytidines are conserved in a paralogous and orthologous manner within

the family of RLRs. (2) A conserved groove with a positively charged

patch at the center of which an RIG-I invariant lysine is located (K888)

(Cui et al., 2008).

Crystallographic structures of RIG-I give detailed insight into the con-

formational changes triggered by ligand binding and required for signal ini-

tiation. The structural data suggest a model where in the autorepressed state

the CTD is devoid of intramolecular interactions and thus can freely engage

in pppRNA binding. This initial event increases the local RNA concentra-

tion and leads to cooperative binding of RNA and ATP to the helicase

domain resulting in dramatic rearrangements within the helicase domain

that are orchestrated by the pincher domain that connects the helicase

domain with the CTD. The helicase domain and the CTD completely sur-

round the RNA clasping onto the helix by numerous intermolecular inter-

actions. This channel covers 9–10 bp along the RNA. Longer RNA

molecules allow the binding of two RIG-I monomers simultaneously.

However, this apparent dimerization is devoid of a protein–protein interface

but much rather reflects an RNA-guided oligomerization (Kowalinski et al.,

2011; Luo et al., 2011). In line with the structural data of RNA-bound

RIG-I, full-length RIG-I but not the DCTD mutant or MDA5 eluted as

dimers after gel filtration when incubated with pppRNA (Cui et al., 2008).

Downstream signaling by ligand-activated RIG-I is achieved by the

N-terminal tandem CARDs. Deletion of the CARDs results in a dominant

negative phenotype of RIG-I (Yoneyama et al., 2004). Huh7.5 cells, a sub-

population of the hepatocyte cell line Huh7 that is characterized by a thre-

onine to isoleucine mutation at position 55 (T55I) in the first CARD of

RIG-I, fail to respond to HCV infection. As a consequence, the absence

of a functional antiviral response creates conditions permissive for HCV rep-

lication in Huh7.5 (Sumpter et al., 2005). The T55I mutant interferes with

the binding of the TRIM25 E3 ubiquitin ligase that is required for activation

of RIG-I signaling. Gack et al. demonstrated that TRIM25 binds to the first

CARD domain via its SPRY domain. Prerequisite for TRIM25 binding is

dephosphorylation of RIG-I at T170 (and S8 in primates) by an unidentified

phosphatase. The phosphomimetic mutation T170E abrogated binding of

TRIM25 to RIG-I and interfered with downstream signaling events and

antiviral activity of RIG-I (Gack et al., 2010). TRIM25 transfers K63-linked

ubiquitin moieties to the lysine 172 residue (K172) within the second

CARDusing its RING domain. Oligomerization of RIG-I with the adapter


protein MAVS critically depends on this modification. Accordingly,

TRIM25-deficient MEFs do not secrete IFN-b after SeV infection. The

absence of antiviral defenses is reflected by markedly higher viral titers upon

VSV infection (Gack et al., 2007). Although TRIM25 does not attach

ubiquitin moieties to MDA5, polyubiquitin binding by MDA5 is required

for its signaling functions ( Jiang et al., 2012).

The requirement for ubiquitination of RIG-I for initiation of downstream

signalingwas challenged by a study using a cell-free system to identify themin-

imal components for RIG-I signal transduction. The RIG-I pathway was

reconstituted in a mixture containing affinity-purified RIG-I, crude mito-

chondria and peroxisomes (containing the adapter MAVS), cytosolic extracts

(containing TBK1), in vitro-synthesized transcription factor IRF3, and ATP.

RIG-I activation was quantified by measuring dimerization of IRF3, a read-

out for its activation. With this in vitro assay in place, the authors recapitulated

key aspects ofRIG-I signaling and revealed new regulatorymechanisms. IRF3

activation required MAVS and TRIM25 as depletion of these proteins by

RNAi interfered with IRF3 dimerization. RIG-I needed to be isolated from

virus-infected cells, be activated by RNA ligand in vitro, or be present as an

N-terminalCARD fragment for IRF3 activation to occur. The ubiquitination

machinery responsible for RIG-I activation was shown to be comprising E1,

the E2 Ubc5 and Ubc13, and the E3 TRIM25, as the mitochondrial fraction

of virus-infected cells depleted from Ubc5 (isoform b and c) and Ubc13 no

longer elicited IRF3dimerization. In linewith thenotion thatUbc13 is specific

for synthesis of lysine 63 (K63)-linked ubiquitin and previous findings on the

importance of K63-linked polyubiquitin for RIG-I activation, ubiquitin

proteins with a sole lysine residue at position 63 were capable to activate the

pathway in the cell-free in vitro system (Zeng et al., 2010).

Thus, a requirement for both TRIM25 and K63-linked ubiquitin for

IFN-b induction by RIG-I were confirmed in this experimental setup.

The major discrepancy between the studies by Gack et al. and Zeng et al.

is the attachment of polyubiquitin. While in the former study covalent link-

age to the K172 residue of RIG-I was proposed, the latter study suggested

that unanchored polyubiquitin chains serve as essential cofactors for RIG-I

activation. Two major lines of evidence support this proposition: (1) RIG-I

CARDs isolated from E. coli that lack an ubiquitination system-activated

IRF3 when ubiquitin polymers were added to the cell-free system. (2)

Endogenous polyubiquitin was coprecipitated with RIG-I CARDs from

mammalian cells and subsequently recovered from the complex by selective

heat denaturation. This preparation promoted IRF3 dimerization, but lost


its activity when treated with the deubiquitination enzyme IsoT. Even

though the K172 residue is not required as an acceptor for ubiquitination

in this situation, its relevance for RIG-I signaling remains undisputed as it

is critical for the binding affinity to polyubiquitin (Zeng et al., 2010).

Both RIG-I and MDA5 signaling depends on the adapter protein MAVS

to link receptor activity to the downstream kinases TBK1 and IKK-i

(Fig. 4.2). MAVS is a 540 aa protein comprising an N-terminal CARD

domain, a central proline-rich region (Pro), and a C-terminal transmembrane

domain (Seth et al., 2005) (Fig. 4.1).While the transmembrane domain targets

the adapter to its proper subcellular locations (mitochondria, peroxisomes, and

mitochondria-associated membranes (MAM); see Section 4.2), the CARD

domain is required for signaling (Dixit et al., 2010; Horner, Liu, Park,

Briley, & Gale, 2011; Seth et al., 2005). WhenMAVS was initially character-

ized as an RLR signaling adapter, the authors noted that viral infection results

in the formation of detergent-resistant aggregates (Seth et al., 2005). Recent

studies by the same group defined these aggregates as highly organized, self-

propagating prion-like fibrils. Using the cell-free system for in vitro reconsti-

tution of RLR signaling as described earlier, complexes of MAVS larger than

the 26S proteasome were detected 9 h after SeV infection which coincided

with IRF3 dimerization. These complexes displayed several features charac-

teristic for prions: (1) The MAVS CARD is necessary and sufficient for for-

mation of fiber-like structures as determined by electron microscopy. (2)

These fibrils are resistant to protease K treatment and detergent solubilization.

(3) Protease-resistant fibrils convert MAVS on mitochondria that were

extracted from uninfected cells into functional aggregates leading to IRF3

activation. Interestingly, however, these MAVS aggregated did not stain with

Congo Red, a dye that typically stains “classic” prion structures (chen prion

paper). Conversely, mitochondria depleted of MAVS by RNAi prior to

extraction did not result in IRF3 dimerization. Importantly, MAVS aggre-

gates form within minutes upon activation of RLR signaling in the cell-fee

reconstitution assay indicating that prion-like MAVS fibrils are a bona fide

determinant of the MAVS activation status (Hou et al., 2011).

4. REGULATORY MECHANISMS OF RIG-I SIGNALING4.1. Regulators of RLR signaling

Several proteins regulate RLR signaling along the pathway in order to tailor

the response. Various E3 ubiquitin ligases regulate RIG-I activity. TRIM25

as discussed in Section 3 and Riplet (also known as RNF135 or REUL)


positively regulate RIG-I activity through K63-linked ubiquitination at its

N- or C-terminus, respectively (Gack et al., 2007; Gao et al., 2009;

Oshiumi, Matsumoto, Hatakeyama, & Seya, 2009; Oshiumi et al., 2010).

In contrast, RNF125 mediates K48-linked ubiquitination that targets

RIG-I for degradation and thus acts as a negative regulator (Arimoto

et al., 2007). Recently, ZAPS was identified as a cofactor for RIG-I signal-

ing. ZAPS is a member of the poly (ADP-ribose) polymerase (PARP) family

but lacks the PARP-like domain present in ZAPS due to alternative splicing.

ZAPS was shown to directly associate with RIG-I in a ligand-dependent

manner and to amplify downstream signaling events such as activation

of the transcription factors IRF3 and NF-kB and induction of type I

IFN. As a result, ZAPS inhibited viral replication after infection with

RIG-I-dependent viruses such as influenza virus or NDV (Hayakawa

et al., 2011). While a continuously growing number of accessory proteins

that modify RIG-I signaling activity emerges, the interplay between these

proteins, the order in which they act upon RIG-I, and their relative signif-

icance for signaling output remain elusive until further systematic studies are

done to address these questions.

NLRX1 (also known as Nod9) was proposed to control RLR signal

transduction at the level of MAVS; however, its role is a matter of debate.

NLRX1 was reported to reside at the outer mitochondrial membrane from

where it physically disrupts the virus-induced RLR–MAVS interaction

(Moore et al., 2008) (Fig. 4.2). Alternatively, NLRX1was found to be local-

ized within the mitochondrial matrix which deems impossible the proposed

function as a direct interactor of MAVS to modulate its activity. Rather, it

was shown that NLRX1 promotes the generation of reactive oxygen species

(ROS) (Arnoult et al., 2009; Tattoli et al., 2008). Interestingly, several lines

of evidence implicate ROS as modulators of RLR signaling. Cells deficient

in autophagy accumulate dysfunctional mitochondria which entails

increased ROS levels and display enhanced RLR signaling. Treatment with

antioxidant reverses the effect (Tal et al., 2009). Conversely, mitochondrial

uncoupling—a process by which ROS generation is decreased—reduced

RLR signaling (Koshiba, Yasukawa, Yanagi, & Kawabata, 2011). Addi-

tional research is required to delineate the mechanism by which ROS reg-

ulate RLR-dependent antiviral responses.

STING (also known as MITA, MPYS, or ERIS) (Ishikawa & Barber,

2008; Jin et al., 2011; Sun et al., 2009; Zhong et al., 2008) was originally

identified as a regulator of RIG-I signaling owing to its ability to directly

bind to RIG-I, MAVS, and TBK1 and to its knockout phenotype.


Overexpression of the constitutively active fragment of RIG-I failed to

induce IFN in STING-deficient MEFs. Moreover, VSV infection of

STING-deficient mice resulted in significantly poorer survival rates and

lower type I IFN serum levels relative to control littermates. It is of note that

the response to transfected polyI:C remained unchanged in the absence of

STING (Ishikawa et al., 2009). While STING was shown to play an

undisputed role in the IFN response to cytosolic DNA from viruses or syn-

thetic agonists, its implication in RLR signaling may not be essential.

4.2. Regulation of RLR signal transduction by subcellularcompartmentalization

All three receptorsof theRLRfamily are cytosolic proteins, and theyhavenot

been found to be associated with any subcellular structure at steady state.

However, several signaling components downstream of the receptors are

membrane proteins whose functional domains project into the cytosol from

the surfaceof the respectiveorganelles.More importantly, proper localization

of these proteins is a prerequisite for their biological activity. The best char-

acterized example is the adapter protein MAVS. MAVS resides on the outer

mitochondrial membrane (Seth et al., 2005), peroxisomes (Dixit et al., 2010)

andMAMs (Horner et al., 2011), a specialized subdomainof theER that con-

nects mitochondria and peroxisomes (Hayashi, Rizzuto, Hajnoczky, & Su,

2009; Vance, 1990). Both peroxisomal and mitochondrial MAVS signal to

induce ISG expression in MEFs. While mitochondrial MAVS induces type

I IFN and as a consequence ISG expression in response to reovirus and influ-

enza virus infection, peroxisomal MAVS directly induces ISG expression

which creates a transient yet functional antiviral state. The lack of type I

IFN induction by peroxisomal MAVS was also observed in macrophages.

Unlike MEFs, macrophages upregulate not only expression of ISGs but also

proinflammatory cytokines after reovirus infection (Dixit et al., 2010). A dif-

ferent study confirms the localization ofMAVS onmitochondria and perox-

isomes, and adds MAMs to the list of subcellular pools of MAVS.Moreover,

the authors propose the MAM as an innate immune synapse for antiviral

responses that coordinates MAVS-dependent signaling from mitochondria

and peroxisomes (Horner et al., 2011). HCV-infected Huh7 hepatocytes

are unable to induce IFN expression due to MAVS cleavage by the viral

protease NS3/4A (Loo et al., 2006; Meylan et al., 2005). Others and we

have shown that cytosolic MAVS is unable to signal (Dixit et al., 2010;

Seth et al., 2005). Given that NS3/4A cleaves MAM-localized MAVS, but

not mitochondrial MAVS, the authors conclude that—at least for HCV


infections—mitochondrial MAVS is dispensable for RIG-I signaling.

This notion is further supported by the finding that RIG-I is recruited

specifically to MAM-resident MAVS upon HCV infection (Horner et al.,

2011). In fact, a ternary complex consisting of active open-conformation

RIG-I, TRIM25, and the chaperone 14-3-3e is redistributed to MAMs

upon infection (Liu et al., 2012). MFN2 tethers the ER to mitochondria

and thus maintains the MAM mitochondrial contacts (de Brito &

Scorrano, 2008). Depletion of MFN2 by RNAi destabilizes the antiviral

synapse, which shifts MAVS to peroxisomes and thereby increases RIG-

I-mediated signaling in response to SeV, VSV, and HCV (at early time

points before MAVS cleavage by NS3/4A) infection (Horner et al., 2011).

It would be interesting to test the effect of MFN2 on the organelle-specific

outcome of RLR signaling using cells with organelle-restricted MAVS

expression.

In addition toMFN2,MFN1 has been implicated in regulation of RIG-I

signaling as well. Activation of RLRs by infection with SeV, NDV, influ-

enza virus, VSV, Sindbis virus, or EMCV and by transfection with pppRNA

resulted in redistribution of mitochondrial MAVS. While some mitochon-

dria accumulate MAVS, others become devoid of it during a process that

depends on MFN1. RIG-I is evenly distributed throughout the cytosol

in uninfected cells but is concentrated in foci upon infection. However,

no colocalization between RIG-I and MAVS was observed. On the con-

trary, RIG-I colocalized with viral nucleocapsid. As a consequence, type

I IFN induction after NDV infection was completely abolished in

MFN1-deficient MEFs. These findings led the authors to propose a model

where RIG-I is recruited to virus factories to maximize the chances of rec-

eptor–ligand interaction. Mitochondria serve as vehicles that position

MAVS. Some mitochondria enrich MAVS through repeated fission and

fusion events and surround the foci of active viral replication in order to

enable IFN induction (Onoguchi et al., 2010). While this model outlines

how mitochondrial signaling is optimized to perpetuate IFN induction

for the duration of infection and to establish a sustained antiviral immune

response, it leaves two important questions unanswered. First, what are

the kinetics of this process? The earliest time point presented in the study

is 9 h postinfection. Second, what triggers mitochondrial remodeling and

accumulation ofMAVS? Regardless of whether activation of RLR signaling

or a different stimulus initiates the rearrangement, this model does not

explain RNA detection at the very first instance of virus encounter. Much

rather it demands additional and disparate means of RLR signaling that


ensure an immediate antiviral response until MAVS-enriched mitochondria

are recruited to the periphery of virus factories.

5. CONCLUSIONS AND FUTURE DIRECTIONS

RLR signaling is a crucial pathway for detection of intracellular

viruses and mounting protective antiviral defenses. Since the identification

of RIG-I and its related proteinsMDA5 and LGP2, tremendous progress has

been made in terms of the core components of this pathway and the regu-

latory mechanisms. Still, many open questions remain on the pathogen as

well as the host side. What are the biological ligands that arise during a given

viral infection? Viral genomes, viral transcripts, or replication intermediates

are likely candidates. Do these naturally occurring ligands match the postu-

lated structural features that were identified in vitro? Baum, Sachidanandam,

and Garcia-Sastre (2010) sought to characterize such ligands by immunopre-

cipitation of endogenous RIG-I/RNA complexes from SeV and influenza

virus-infected cells and subsequent deep sequencing. Copy-back defective

interfering particles were identified as the natural ligand of both SeV and

influenza virus. RIG-I also bound to (preferentially short segments of) geno-

mic RNA of influenza virus. This study confirms the requirement for both a

50 triphosphate and a panhandle structure for RIG-I activation during SeV

and influenza virus infection (Baum et al., 2010). How accessible are these

ligands during infection? In the light of coevolution of virus and host, it

stands to reason that viral PAMPs are spatially segregated from the respective

PRRs. Is RLR-mediated virus detection merely possible by accidental

escape of PAMPs or are mechanisms in place that actively sample sites of viral

replication?

Regarding the host factors required for an effective antiviral response,

our understanding of the spatiotemporal control of this pathway is very

limited. Despite the designation of RLRs as cytosolic receptors, the signal

transduction cascade initiated upon ligand engagement is certainly not cyto-

solic, but strictly dependent on proper subcellular localization of many

components of this pathway. The adaptor protein MAVS resides on and

signals distinctively from peroxisomes, MAM, and mitochondria (Dixit

et al., 2010; Horner et al., 2011; Seth et al., 2005). The negative regulator

NLRX1 is also localized onmitochondria (Moore et al., 2008). In the course

of infection, mitochondria are rearranged to surround sites of viral replica-

tion in an MFN1-dependent manner. Failure to do so severely abrogates an

antiviral response (Onoguchi et al., 2010). What is the benefit for the host of


such an elaborate subcellular arrangement of a signal transduction pathway?

Perhaps, recruitment of molecules concentrated on an organelle might

be faster and more energy efficient than recruiting every single molecule

independently. Considering the different responsesmediated by peroxisomal

and mitochondrial MAVS, distribution of this pathway on two organelles

might facilitate targeting of factors specifically required for each of the

responses. A similar situation can be found with TLR4, the receptor for the

prototypical PAMP lipopolysaccharide. Perhaps, a positive regulator of direct

ISG induction is only targeted toperoxisomesor an inhibitorof such a signaling

pathway is located onmitochondria. The TLR4 pathway exemplifies how the

spatial distribution of signaling components governs the signaling output.

While plasma membrane-bound TLR4 induces cytokine expression in an

MyD88-dependent manner (Medzhitov, Preston-Hurlburt, & Janeway,

1997;Medzhitov et al., 1998), endocytosis ofTLR4 induces type I IFN induc-

tion in aTRIF-dependentmanner (Kagan et al., 2008;Yamamotoet al., 2002).

For TLR4 signaling, TRAF3 was proposed to be limited in its mobility. The

inability of TRAF3 to be recruited to TLR4 at the plasma membrane neces-

sitates TLR4 to be endocytosed. It is at the endosome that the TRAM–TRIF

adaptor pair is recruited to engage TRAF 3 and to enable type I IFN signaling

(Kagan et al., 2008). Similarly, an essential factor for direct ISG induction may

be available exclusively at peroxisomes. Experimental evidence for the

organelle-specific presence of regulators of RLR signaling comes from

NLRX1. Overexpression of NLRX1 inhibits signaling mediated by mito-

chondrial MAVS, but not by peroxisomal MAVS (Dixit et al., 2010). The

spatial regulation may also be indicative of RLR signaling being a multistage

process, wherein in an initial wave a nascent infection is sensed, and in a later

phase the process is optimized for a robust response during infection and finally

is turned off. In order to address this possibility, kinetic studies rather than late

end points after infection would be helpful.

ACKNOWLEDGMENTSE. D. is supported by the Erwin Schrodinger Fellowship ( J3295-B22) of the Austrian ScienceFund (FWF). The National Institutes of Health grants AI093589 and P30 DK34854 support

the work performed in the laboratory of J. K. Dr. J. K. holds an Investigators in thePathogenesis of Infectious Disease Award from the Burroughs Wellcome Fund.

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Zeng, W., Sun, L., Jiang, X., Chen, X., Hou, F., Adhikari, A., et al. (2010). Reconstitutionof the RIG-I pathway reveals a signaling role of unanchored polyubiquitin chains ininnate immunity. Cell, 141, 315.

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INDEX

Note: Page numbers followed by “f ” indicate figures, and “t” indicate tables.

AActivation-induced cytidine deaminase

(AID)

binding, 54–55DSBs and translocationsdescription, 43

expression, 43–44off-target activity, 44transcription of mRNA, 43

expression and CSR induction, 51–52HTGTS and TC-Seq translocation, 53–54in oncogene, 62–63physiologic mechanisms, 40

Acute lymphoblastic leukemia (ALL)and B-ALL, 3, 43description, 3

and T-ALL, 4, 15–16, 43treatment, 4

Acute myeloid leukemia (AML)

chromosomal translocations, 57description, 3DNMT3A mutations, 7MOZ gene, 22

myelodysplastic syndromes(MDS)/-neoplasms (MPN), 3

subtypes, 3

TET proteins, 10–12AID. See Activation-induced cytidine

deaminase (AID)

ALL. See Acute lymphoblastic leukemia(ALL)

AML. See Acute myeloid leukemia (AML)

Antiviral immunityhost cell’s metabolic pathways, 99–100innate immune response, 100LGP2 role, 104

nucleic acid detection, 100–101PRRs and PAMPs, 100

Arginine methyltransferases, 19–20

Autoimmune liver diseasePBC, 81PSC, 80–81

BB lymphocytes

AID targets for DSBs initiation, 53–54

leukemia, 3, 43RAG1/2 translocation, 53

Bromodomain (BRD)-containing protein

familydescription, 24development of MM, 24

inhibitors, 24

CChromatin

epigenetic marks, 26

in RAG activity, 42remodeling complexes, 25

Chromosomal translocations

DNA DSB formation (see DNAdouble-strand breaks (DNA DSBs))

DNA-repair mechanisms

C-NHEJ, 46–47DDR pathway, 45NHEJ, 45

high-throughput methodsHTGTS, 51–52TC-Seq, 52

HTGTS and TC-Seq

AID targets, B cells, 53–54gene density, transcription, andtranslocations, 54–55

nuclear positioning and chromosomalstructure, 55–57

RAG1/2 translocation, pro-B cells, 53

mechanisms, 40spatial organization of the genomechromosome territories, 48–49description, 48, 48f

and DNA repair, 49genome-wide contact analysis, 49–50“transcription factories”, 49

structural landscapechromothripsis, 58–62

127

Chromosomal translocations (Continued )driver translocations, 57intra/interchromosomal

rearrangements, 57–58oncogenes, 62–63

territories (see Chromosome territories)

TET proteins, 10–11Chromosome territoriesfunctions of, 48–49and gene proximity, 47–48

in situ hybridization approaches, 48Chromothripsiscancer types, 58

chromosomal rearrangements, 57–58genomic disorders, 61–62implications, 60–61

mechanisms, in normal and cancer cells,59–60, 60f

progressive rearrangement model, 58–59

Chronic liver disease. See Intestinalmicrobiota, chronic liver disease

Chronic lymphocytic leukemia (CLL), 4, 58Chronic myeloid leukemia (CML)

chromosomal proximity, 47–48description, 2–3treatment with Imatinib, 2–3

Cirrhosis, intestinal microbiotadescription, 78–79and HE, 79–80

liver fibrogenesis, 78–79Classical NHEJ (C-NHEJ)in knock-out mouse models/in human

patients, 46

multistep DNA-repair process, 46sequence homology, 58–59in translocations and chromosomal

integrity, 46–47CLL. See Chronic lymphocytic leukemia

(CLL)

CML. See Chronic myeloid leukemia(CML)

C-type lectin (CTL) receptors, 86–87

DDNA-damage response (DDR) pathway, 45

DNA double-strand breaks (DNA DSBs)AID-initiated DSBs and translocations,

43–44

fragile sites, 44–45nonprogrammed pathologic DSBs, 44–45physiologic/pathologic mechanisms, 40

RAG-initiated DSBs and translocations,41–43

topoisomerases, 45

DNA methylationaberrant methylation patterns, 6–7CpG islands, 6hypomethylation, 6–7

IDH1 and IDH2 proteins, 12–14mutations, DNMT3a, 7PHD-containing proteins, 24–25

TET proteins, 10–12DNA methyltransferase (DNMT)

DNMT3A mutations

in hematopoietic malignancies, 7, 8fmolecular consequence, 7–9mouse models, 9

prognostic marker, 9inhibitors, 9–10

DNMT. See DNA methyltransferase(DNMT)

Dysbiosiswith innate immune deficiency, 87–89probiotic interventions, 89–90

EEpigenetic modulators

arginine methyltransferases, 19–20BRD-containing protein family, 24

chromatin remodeling complexes, 25DNAmethylation (seeDNAmethylation)HATs, 22–23

HDACs, 23histone demethylases inhibitors

(KDMi), 22

histone-modifying complexes and MLL,14–19

lysine demethylases (KDMs), 21

HHATs. See Histone acetyl transferases

(HATs)HCC. SeeHepatocellular carcinoma (HCC)

HDACs. See Histone deacetylases (HDACs)Hematopoietic malignancies.

See also Leukemia

128 Index

DNA methylation, 6–7DNMT3A mutations, 7

Hepatic encephalopathy (HE)

intestinal microbiota, 78–79nonculture-based methods, 79–80pathogenesis, 79

Hepatocellular carcinoma (HCC), 80High-throughput genomic translocation

sequencing (HTGTS)AID targets, 53–54

analysis of SNPs, 52–53application, 55–56clone translocation junctions, 51–52

gene density, transcription, andtranslocations, 54–55

normal mature B cells and pro-B cells,

51–52, 51fRAG1/2 translocation, 53TC-Seq, 52

Histone acetyl transferases (HATs)family, 22inhibitors (HATi), 22–23monocytic leukemia zinc-finger protein

(MOZ), 22MOZ-related factor (MORF), 22

Histone deacetylases (HDACs)

classes, 23inhibitors (HDACi), 23transcription role, 23

Histone demethylases inhibitors (KDMi), 22Histone-modifying complexes, leukemiadescription, 14–17MLL function, 17–19

PRC1, 17PRC2, 14

HTGTS. See High-throughput genomic

translocation sequencing (HTGTS)

IIDH. See Isocitrate dehydrogenase (IDH)IFN. See Interferon (IFN)Inflammasomes

components, 85intestinal tracts of mice deficient, 87–88NLRP3, 86

NLR proteins, 84–85response against tissue damage, 85–86sequential stimuli, 84–85

InhibitorsBRD, 24DNMT, 9–10

HAT (HATi), 22–23HDAC, 23histone methyltransferase, 17

KDMi, 22Innate immunity

and intestinal microbiotaCTL receptors, 86–87

dysbiosis, 87–89inflammasomes, 84–86PRRs, 81–82

receptors expression, 82TLRs, 82–84

PRRs and PAMPs, 100

Interferon (IFN)IFN-a, 101IFN-bIRF3 and IRF7, 102–103LGP2 role, antiviral immunity, 104

IRF (see Interferon regulatory factor(IRF))

type I IFNs, TLR9-associated liverdamage, 83–84

Interferon regulatory factor (IRF)

dimerization, 112–113IRF3 and IRF7, 102–103LGP2 role, antiviral immunity, 104

ubiquitination system-activated IRF3,112–113

Intestinal microbiota, chronic liver diseaseautoimmune liver disease, 80–81

cirrhosis and associated comorbidities,78–80

gastrointestinal tract, 74

HCC, 80hepatic artery, 74and innate immune system (see Innate

immunity)liver (see Liver)NAFLD (see Nonalcoholic fatty liver

disease (NAFLD))probiotics, 89–90

IRF. See Interferon regulatory factor (IRF)Isocitrate dehydrogenase (IDH)

animal models, 14as homodimers, 12–13

129Index

Isocitrate dehydrogenase (IDH) (Continued )2-hydroxyglutarate (2-HG), 13IDH1 and IDH2 mutations, 12–13

oncometabolites, role, 13wild-type, 13

LLeukemia

ALL, 3–4AML, 3B-ALL/T-ALL, chromosomal

translocations, 43chromosomal proximity, 47–48chronic variants, 2

CLL, 4CML, 2–3DNA methylation, 6–14epigenetic modifiers, 19, 20f

epigeneticsbivalent domains, 25classes of genes, 5

combinatorial chromatin marks, 26combinatorial histone marks, 25–26definition, 4

DNA methylation, 5long noncoding RNAs (lncRNAs), 26modulators (see Epigenetic modulators)

nuclear architecture, 26–27perturbations, 5–6phenomena, 4, 5

histone-modifying complexes, 14–19

IDH1 and IDH2 proteins, 12–14TET proteins, 10–12types, 2

Liverchronic disease (see Intestinal microbiota,

chronic liver disease)

and gastrointestinal tract, 74Lysine demethylases (KDMs)amine oxidation and dioxygenases, 21

hydroxylation, 21in tumorigenesis, 21

MMicrobiota. See Intestinal microbiota,

chronic liver diseaseMitochondriaIDH mutations, leukemia, 13

MAM, 113, 115–116, 117–118

MAVS signal, 115–117NLRX1, 114ubiquitination, RIG-I activation, 112

Mitochondria-associated membranes(MAM), 113, 115–116, 117–118

Mixed-lineage leukemia (MLL)

COMPASS complexes, 17–18description, 17–18fusion proteins, 18–19genetic perturbations, 14–15, 15f

MLL-rearranged leukemias, 18role of CBX8, 19

MLL. See Mixed-lineage leukemia (MLL)

NNAFLD. SeeNonalcoholic fatty liver disease

(NAFLD)NHEJ. See Nonhomologous DNA end

joining (NHEJ)NOD-like receptor (NLR) proteins

development and progression, NASH, 86

Kupffer cells and sinusoidal endothelialcells, 85

types, 84–85

Nonalcoholic fatty liver disease (NAFLD)calorie intake, Western society diets,

76–77

obesity, 75–76prevalence, 75prevalence of SIBO, 78primary and secondary, 75

for progression, gut-derived factors, 77–78regulation, 75–76, 76f“two-hit” mechanism, 75

Nonhomologous DNA end joining (NHEJ)C-NHEJ (see Classical NHEJ (C-NHEJ))description, 45

PPAMPs. See Pathogen-associated molecular

patterns (PAMPs)Pathogen-associated molecular patterns

(PAMPs)detection of viruses, 100–101innate immune system, 100

Pattern recognition receptors (PRRs)homeostatic extrahepatic expression, 89host and indigenous microflora, 81–82

innate immune response, 100

130 Index

innate receptors expression, 82nucleic acid detection, 100–101TLRs, 82

PBC. See Primary biliary cirrhosis (PBC)PeroxisomesMAVS, 113, 115–116

RIG-I pathway, 112Plant homeodomain (PHD)-containing

proteinsJARID1C, 24

translocation, 24–25Polycomb repressive complex 1 (PRC1)histone methyltransferase inhibitors, 17

HSCs maintenance and transformationin vivo, 17

Polycomb repressive complex 2 (PRC2)

components, 14–15EZH2, 14–15, 15fgene silencing, 14–15

loss-of-function mutation, 15–16mutations, protein ASXL1, 17and PRC1, 17T-ALL mutations, 15–16

as tumor suppressor, 16PRC1. See Polycomb repressive complex 1

(PRC1)

PRC2. See Polycomb repressive complex 2(PRC2)

Primary biliary cirrhosis (PBC)

antimitochondrial antibodies (AMAs), 81autoimmune liver disorder, 81TLR4 expression, 82–83

Primary sclerosing cholangitis (PSC)

CARD9, 86–87microbiota, 80–81pathogenesis, 80

TLR4 expression, 82–83Probioticsdescription, 89

interventions, 89–90and prebiotics, 89

PRRs. See Pattern recognition receptors

(PRRs)PSC. SeePrimary sclerosing cholangitis (PSC)

RRAG. See Recombination-activating genes

(RAG)

Recombination-activating genes (RAG)

DSBs and translocationsaberrant RAG activity, 42–43mechanisms, 42

off-target RAG activity, 42–43recurrent translocations, B-celllymphomas, 43

V(D)J recombination, 41–42in pro-B lymphocytes, 53, 55–56

RIG-I-like receptors (RLRs)activation

adapter protein MAVS, 113ATPase activity, 110–111CARDs and helicase domain, 110

crystallographic structures, 111description, 109–110downstream signaling, 111–112

TRIM25 and K63-linked ubiquitin,112–113

ubiquitination, 112

adapter protein MAVS, 102–103domain architecture, 101–102, 102fIFN-b transcription, 102–104IFN role, bacterial infections, 108

IRF family, 102–103, 103fLGP2 role, 104ligand specificities, 102–103

MDA5, 104nucleic acid detection, 100–101nucleic acid-specific endosomalTLRs, 101

regulators, RLR signalingadapter protein MAVS, 115–116MFN2 and MFN1, 115–117NLRX1, 114

STING, 114–115ZAPS, 113–114

RIG-I, MDA5, and LGP2, 101–102

structural characteristics, 104–106type II IFN-g, Shigella flexneri, 109viruses detection, 106–107, 107t

RLRs. See RIG-I-like receptors (RLRs)

TT-cell acute lymphoblastic leukemia

(T-ALL) mutations, 15–16Ten-eleven translocation (TET) proteins

J-binding proteins, 10mutations analysis, TET1, 10TET2 mouse models, 12

TET2 mutations, 11–12

131Index

TLRs. See Toll-like receptors (TLRs)Toll-like receptors (TLRs)concanavalin A (ConA) model, 84

expression, 82microbial translocation, 84nucleic acid detection, 100–101

PRRs, 82

and RLRs, 101TLR9, 83–84TLR4–MyD88–NF-kB signaling, 82–83

TLR4 pathway, 117–118Translocation-capture sequencing (TC-Seq)

AID targets, 53–54

description, 52

132 Index

CONTENTS OF RECENT VOLUMES

Volume 85

Cumulative Subject Index Volumes 66–82

Volume 86Adenosine Deaminase Deficiency:

Metabolic Basis of Immune

Deficiency and PulmonaryInflammation

Michael R. Blackburn and

Rodney E. Kellems

Mechanism and Control of V(D)JRecombination Versus Class SwitchRecombination: Similaritiesand Differences

Darryll D. Dudley, Jayanta Chaudhuri,Craig H. Bassing, and Frederick W. Alt

Isoforms of TerminalDeoxynucleotidyltransferase:

Developmental Aspects andFunction

To-Ha Thai and John F. Kearney

Innate Autoimmunity

Michael C. Carroll and V. Michael Holers

Formation of Bradykinin: A Major

Contributor to the InnateInflammatory Response

Kusumam Joseph and Allen P. Kaplan

Interleukin-2, Interleukin-15, and

Their Roles in Human NaturalKiller Cells

Brian Becknell and Michael A. Caligiuri

Regulation of Antigen Presentation and

Cross-Presentation in the DendriticCell Network: Facts, Hypothesis,and Immunological Implications

Nicholas S. Wilson and Jose A. Villadangos

Index

Volume 87Role of the LAT Adaptor in T-Cell

Development and Th2 Differentiation

Bernard Malissen, Enrique Aguado, andMarie Malissen

The Integration of Conventional andUnconventional T Cells thatCharacterizes Cell-Mediated Responses

Daniel J. Pennington, David Vermijlen,Emma L. Wise, Sarah L. Clarke,Robert E. Tigelaar, and Adrian C. Hayday

Negative Regulation of Cytokine and TLR

Signalings by SOCS and OthersTetsuji Naka, Minoru Fujimoto, HirokoTsutsui, and Akihiko Yoshimura

Pathogenic T-Cell Clones in AutoimmuneDiabetes: More Lessons from the NOD

MouseKathryn Haskins

The Biology of Human LymphoidMalignancies Revealed by Gene

Expression ProfilingLouis M. Staudt and Sandeep Dave

New Insights into Alternative Mechanismsof Immune Receptor Diversification

Gary W. Litman, John P. Cannon, and

Jonathan P. Rast

The Repair of DNA Damages/Modifications During the Maturation ofthe Immune System: Lessons from

Human Primary ImmunodeficiencyDisorders and Animal Models

Patrick Revy, Dietke Buck, Francoise le Deist,

and Jean-Pierre de Villartay

Antibody Class Switch Recombination:Roles for Switch Sequences andMismatch Repair Proteins

Irene M. Min and Erik Selsing

Index

133

Volume 88CD22: A Multifunctional Receptor That

Regulates B Lymphocyte Survival andSignal Transduction

Thomas F. Tedder, Jonathan C. Poe, and

Karen M. Haas

Tetramer Analysis of Human AutoreactiveCD4-Positive T Cells

Gerald T. Nepom

Regulation of Phospholipase C-g2Networks in B Lymphocytes

Masaki Hikida and Tomohiro Kurosaki

Role of Human Mast Cells and Basophils inBronchial Asthma

Gianni Marone, Massimo Triggiani, Arturo

Genovese, and Amato De Paulis

A Novel Recognition System forMHC Class I Molecules Constitutedby PIR

Toshiyuki Takai

Dendritic Cell BiologyFrancesca Granucci, Maria Foti, andPaola Ricciardi-Castagnoli

The Murine Diabetogenic Class IIHistocompatibility Molecule I-Ag7:

Structural and Functional Properties andSpecificity of Peptide Selection

Anish Suri and Emil R. Unanue

RNAi and RNA-Based Regulation of

Immune System FunctionDipanjan Chowdhury and Carl D. Novina

Index

Volume 89Posttranscriptional Mechanisms Regulating

the Inflammatory Response

Georg Stoecklin Paul Anderson

Negative Signaling in FcReceptor Complexes

Marc Daeron and Renaud Lesourne

The Surprising Diversity of Lipid Antigensfor CD1-Restricted T Cells

D. Branch Moody

Lysophospholipids as Mediatorsof Immunity

Debby A. Lin and Joshua A. Boyce

Systemic MastocytosisJamie Robyn and Dean D. Metcalfe

Regulation of Fibrosis by the

Immune SystemMark L. Lupher, Jr. andW. Michael Gallatin

Immunity and Acquired Alterations in

Cognition and Emotion: Lessons fromSLE

Betty Diamond, Czeslawa Kowal,Patricio T. Huerta, Cynthia Aranow,

Meggan Mackay, Lorraine A. DeGiorgio,Ji Lee, Antigone Triantafyllopoulou,Joel Cohen-Solal Bruce, and T. Volpe

Immunodeficiencies with

Autoimmune ConsequencesLuigi D. Notarangelo, Eleonora Gambineri,and Raffaele Badolato

Index

Volume 90Cancer Immunosurveillance and

Immunoediting: The Roles of

Immunity in Suppressing TumorDevelopment and Shaping TumorImmunogenicity

Mark J. Smyth, Gavin P. Dunn, and

Robert D. Schreiber

Mechanisms of Immune Evasion by TumorsCharles G. Drake, Elizabeth Jaffee, andDrew M. Pardoll

Development of Antibodies and

Chimeric Molecules for CancerImmunotherapy

Thomas A. Waldmann and John C. Morris

134 Contents of Recent Volumes

Induction of Tumor ImmunityFollowing Allogeneic Stem Cell

TransplantationCatherine J. Wu and Jerome Ritz

Vaccination for Treatment and Preventionof Cancer in Animal Models

Federica Cavallo, Rienk Offringa,

Sjoerd H. van der Burg, Guido Forni,and Cornelis J. M. Melief

Unraveling the Complex RelationshipBetween Cancer Immunity and

Autoimmunity: Lessons fromMelanoma and Vitiligo

Hiroshi Uchi, Rodica Stan, Mary Jo Turk,

Manuel E. Engelhorn, GabrielleA. Rizzuto, Stacie M. Goldberg,Jedd D. Wolchok, and Alan N. Houghton

Immunity to Melanoma Antigens:From Self-Tolerance to

ImmunotherapyCraig L. Slingluff, Jr.,Kimberly A. Chianese-Bullock,

Timothy N. J. Bullock, WilliamW. Grosh,David W. Mullins, Lisa Nichols, WalterOlson, Gina Petroni, Mark Smolkin, and

Victor H. Engelhard

Checkpoint Blockade in CancerImmunotherapy

Alan J. Korman, Karl S. Peggs, andJames P. Allison

Combinatorial Cancer

ImmunotherapyF. Stephen Hodi and Glenn Dranoff

Index

Volume 91A Reappraisal of Humoral Immunity Based

on Mechanisms of Antibody-MediatedProtection Against Intracellular

PathogensArturo Casadevall andLiise-anne Pirofski

Accessibility Control of V(D)JRecombination

Robin Milley Cobb, Kenneth J. Oestreich,Oleg A. Osipovich, and EugeneM. Oltz

Targeting Integrin Structure and Functionin Disease

Donald E. Staunton, Mark L. Lupher,Robert Liddington,and W. Michael Gallatin

Endogenous TLR Ligands and

AutoimmunityHermann Wagner

Genetic Analysis of InnateImmunity

Kasper Hoebe, Zhengfan Jiang,Koichi Tabeta, Xin Du,Philippe Georgel, Karine Crozat,and Bruce Beutler

TIM Family of Genes in Immunity

and ToleranceVijay K. Kuchroo, Jennifer Hartt Meyers,Dale T. Umetsu, and

Rosemarie H. DeKruyff

Inhibition of Inflammatory Responses byLeukocyte Ig-Like Receptors

Howard R. Katz

Index

Volume 92Systemic Lupus Erythematosus: Multiple

Immunological Phenotypes in a

Complex Genetic DiseaseAnna-Marie Fairhurst,Amy E. Wandstrat, and

Edward K. Wakeland

Avian Models with SpontaneousAutoimmune Diseases

Georg Wick, Leif Andersson, Karel

Hala, M. Eric Gershwin,Carlo Selmi,Gisela F. Erf, Susan J. Lamont, andRoswitha Sgonc

135Contents of Recent Volumes

Functional Dynamics of NaturallyOccurring Regulatory T Cells in Health

and AutoimmunityMegan K. Levings, Sarah Allan, Evad’Hennezel, and Ciriaco A. Piccirillo

BTLA and HVEM Cross TalkRegulates Inhibition and Costimulation

Maya Gavrieli, John Sedy,Christopher A. Nelson, andKenneth M. Murphy

The Human T Cell Response to Melanoma

AntigensPedro Romero, Jean-Charles Cerottini, andDaniel E. Speiser

Antigen Presentation and the

Ubiquitin-Proteasome System inHost–Pathogen Interactions

Joana Loureiro and Hidde L. Ploegh

Index

Volume 93Class Switch Recombination: A

Comparison Between Mouse

and HumanQiang Pan-Hammarstrom, Yaofeng Zhao,and Lennart Hammarstrom

Anti-IgE Antibodies for the Treatment of

IgE-Mediated Allergic DiseasesTse Wen Chang, Pheidias C. Wu,C. Long Hsu, and Alfur F. Hung

Immune Semaphorins: Increasing Membersand Their Diverse Roles

Hitoshi Kikutani, Kazuhiro Suzuki, andAtsushi Kumanogoh

Tec Kinases in T Cell and MastCell Signaling

Martin Felices, Markus Falk, Yoko Kosaka,and Leslie J. Berg

Integrin Regulation of LymphocyteTrafficking: Lessons from Structural andSignaling Studies

Tatsuo Kinashi

Regulation of Immune Responses andHematopoiesis by the Rap1 Signal

Nagahiro Minato, Kohei Kometani, andMasakazu Hattori

Lung Dendritic Cell MigrationHamida Hammad and Bart N. Lambrecht

Index

Volume 94Discovery of Activation-Induced Cytidine

Deaminase, the Engraver of AntibodyMemory

Masamichi Muramatsu, Hitoshi Nagaoka,

Reiko Shinkura, Nasim A. Begum, andTasuku Honjo

DNADeamination in Immunity: AID in theContext of Its APOBEC Relatives

Silvestro G. Conticello, Marc-Andre Langlois,Zizhen Yang, and Michael S. Neuberger

The Role of Activation-Induced Deaminasein Antibody Diversification andChromosome Translocations

Almudena Ramiro, Bernardo ReinaSan-Martin, Kevin McBride,Mila Jankovic, Vasco Barreto,

Andre Nussenzweig, andMichel C. Nussenzweig

Targeting of AID-Mediated SequenceDiversification by cis-ActingDeterminants

Shu Yuan Yang and David G. Schatz

AID-Initiated Purposeful Mutations inImmunoglobulin Genes

Myron F. Goodman, Matthew D. Scharff,

and Floyd E. Romesberg

Evolution of the ImmunoglobulinHeavy Chain Class SwitchRecombination Mechanism

Jayanta Chaudhuri, Uttiya Basu, Ali Zarrin,Catherine Yan, Sonia Franco, ThomasPerlot, Bao Vuong, Jing Wang,Ryan T. Phan, Abhishek Datta,

John Manis, and Frederick W. Alt


Beyond SHM and CSR: AID and RelatedCytidine Deaminases in the Host

Response to Viral InfectionBrad R. Rosenberg andF. Nina Papavasiliou

Role of AID in TumorigenesisIl-mi Okazaki, Ai Kotani, and

Tasuku Honjo

Pathophysiology of B-Cell IntrinsicImmunoglobulin Class SwitchRecombination Deficiencies

Anne Durandy, Nadine Taubenheim,Sophie Peron, and Alain Fischer

Index

Volume 95Fate Decisions Regulating Bone Marrow

and Peripheral B Lymphocyte

DevelopmentJohn G. Monroe and Kenneth Dorshkind

Tolerance and Autoimmunity:Lessons at the Bedside of Primary

ImmunodeficienciesMagda Carneiro-Sampaio and AntonioCoutinho

B-Cell Self-Tolerance in HumansHedda Wardemann and Michel

C. Nussenzweig

Manipulation of Regulatory T-CellNumber and Function withCD28-Specific Monoclonal

AntibodiesThomas Hunig

Osteoimmunology: A View fromthe Bone

Jean-Pierre David

Mast Cell Proteases

Gunnar Pejler, Magnus Abrink,Maria Ringvall, and Sara Wernersson

Index

Volume 96New Insights into Adaptive Immunity

in Chronic NeuroinflammationVolker Siffrin, Alexander U. Brandt,Josephine Herz, and Frauke Zipp

Regulation of Interferon-g During Innate

and Adaptive Immune ResponsesJamie R. Schoenborn and ChristopherB. Wilson

The Expansion and Maintenance of

Antigen-Selected CD8! T CellClones

Douglas T. Fearon

Inherited Complement Regulatory ProteinDeficiency Predisposes to Human

Disease in Acute Injury and ChronicInflammatory States

Anna Richards, David Kavanagh,

and John P. Atkinson

Fc-Receptors as Regulators of ImmunityFalk Nimmerjahn and Jeffrey V. Ravetch

Index

Volume 97T Cell Activation and the Cytoskeleton:

You Can’t Have One Withoutthe Other

Timothy S. Gomez and Daniel

D. Billadeau

HLA Class II Transgenic Mice MimicHuman Inflammatory Diseases

Ashutosh K. Mangalam, Govindarajan

Rajagopalan, Veena Taneja, andChella S. David

Roles of Zinc and Zinc Signaling inImmunity: Zinc as an Intracellular

Signaling MoleculeToshio Hirano, Masaaki Murakami,Toshiyuki Fukada, Keigo Nishida,Satoru Yamasaki, and

Tomoyuki Suzuki


The SLAM and SAP Gene Families ControlInnate and Adaptive Immune

ResponsesSilvia Calpe, Ninghai Wang, Xavier Romero,Scott B. Berger, Arpad Lanyi, Pablo Engel,

and Cox Terhorst

Conformational Plasticity and Navigation of

Signaling Proteins in Antigen-ActivatedB Lymphocytes

Niklas Engels, Michael Engelke, and Jurgen

Wienands

Index

Volume 98Immune Regulation by B Cells and

Antibodies: A View Towardsthe Clinic

Kai Hoehlig, Vicky Lampropoulou, Toralf Roch,Patricia Neves, Elisabeth Calderon-Gomez,Stephen M. Anderton, Ulrich Steinhoff, and

Simon Fillatreau

Cumulative Environmental Changes,

Skewed Antigen Exposure, and theIncrease of Allergy

Tse Wen Chang and Ariel Y. Pan

New Insights on Mast Cell Activation

via the High Affinity Receptorfor IgE

Juan Rivera, Nora A. Fierro, Ana Olivera,

and Ryo Suzuki

B Cells and Autoantibodies in thePathogenesis of Multiple Sclerosis andRelated Inflammatory DemyelinatingDiseases

Katherine A. McLaughlin andKai W. Wucherpfennig

Human B Cell SubsetsStephen M. Jackson, Patrick C. Wilson,

Judith A. James, and J. Donald Capra

Index

Volume 99Cis-Regulatory Elements and Epigenetic

Changes Control GenomicRearrangements of the IgH Locus

Thomas Perlot and Frederick W. Alt

DNA-PK: The Means to Justify the Ends?

Katheryn Meek, Van Dang, and SusanP. Lees-Miller

Thymic Microenvironments for T-CellRepertoire Formation

Takeshi Nitta, Shigeo Murata, Tomoo Ueno,Keiji Tanaka, and Yousuke Takahama

Pathogenesis of Myocarditis and DilatedCardiomyopathy

Daniela Cihakova and Noel R. Rose

Emergence of the Th17 Pathway and Its

Role in Host DefenseDarrell B. O’Quinn, Matthew T. Palmer,Yun Kyung Lee, and Casey T. Weaver

Peptides Presented In Vivo by HLA-DR in

Thyroid AutoimmunityLaia Muixı, Inaki Alvarez, and DoloresJaraquemada

Index

Volume 100Autoimmune Diabetes Mellitus—Much

Progress, but Many ChallengesHugh O. McDevitt and Emil R. Unanue

CD3 Antibodies as Unique Tools to RestoreSelf-Tolerance in EstablishedAutoimmunity: Their Mode of Action

and Clinical Application in Type 1Diabetes

Sylvaine You, Sophie Candon, Chantal

Kuhn, Jean-Francois Bach, and LucienneChatenoud

GAD65 Autoimmunity—Clinical StudiesRaivo Uibo and Ake Lernmark


CD8! T Cells in Type 1 DiabetesSue Tsai, Afshin Shameli, and Pere

Santamaria

Dysregulation of T Cell PeripheralTolerance in Type 1 Diabetes

R. Tisch and B. Wang

Gene–Gene Interactions in the NODMouse Model of Type 1 Diabetes

William M. Ridgway, Laurence B. Peterson,John A. Todd, Dan B. Rainbow, BarryHealy, and Linda S. Wicker

Index

Volume 101TSLP in Epithelial Cell and Dendritic

Cell Cross TalkYong-Jun Liu

Natural Killer Cell Tolerance: Licensingand Other Mechanisms

A. Helena Jonsson and Wayne M. Yokoyama

Biology of the Eosinophil

Carine Blanchard and Marc E. Rothenberg

Basophils: Beyond Effector Cells of AllergicInflammation

John T. Schroeder

DNA Targets of AID: Evolutionary

Link Between Antibody SomaticHypermutation and Class SwitchRecombination

Jason A. Hackney, Shahram Misaghi,Kate Senger, Christopher Garris,Yonglian Sun, Maria N. Lorenzo,and Ali A. Zarrin

Interleukin 5 in the Link Between the

Innate and Acquired ImmuneResponse

Kiyoshi Takatsu, Taku Kouro, and Yoshinori

Nagai

Index

Volume 102Antigen Presentation by CD1: Lipids,

T Cells, and NKT Cells in MicrobialImmunity

Nadia R. Cohen, Salil Garg, and Michael

B. Brenner

How the Immune System AchievesSelf–Nonself DiscriminationDuring Adaptive Immunity

Hong Jiang and Leonard Chess

Cellular and Molecular Mechanisms inAtopic Dermatitis

Michiko K. Oyoshi, Rui He, Lalit Kumar,

Juhan Yoon, and Raif S. Geha

Micromanagers of Immune Cell Fate

and FunctionFabio Petrocca and Judy Lieberman

Immune Pathways for Translating ViralInfection into Chronic Airway

DiseaseMichael J. Holtzman, Derek E. Byers,Loralyn A. Benoit, John T. Battaile,

Yingjian You, Eugene Agapov, ChaehoPark, Mitchell H. Grayson, Edy Y. Kim,and Anand C. Patel

Index

Volume 103The Physiological Role of Lysyl tRNA

Synthetase in the Immune SystemHovav Nechushtan, Sunghoon Kim,Gillian Kay, and Ehud Razin

Kill the Bacteria … and Also Their

Messengers?Robert Munford, Mingfang Lu, and AlanVarley

Role of SOCS in Allergic and Innate

Immune ResponsesSuzanne L. Cassel and PaulB. Rothman


Multitasking by Exploitation of IntracellularTransport Functions: The Many Faces

of FcRnE. Sally Ward and Raimund J. Ober

Index

Volume 104Regulation of Gene Expression in

Peripheral T Cells by RunxTranscription Factors

Ivana M. Djuretic, Fernando Cruz-Guilloty,and Anjana Rao

Long Noncoding RNAs: Implicationsfor Antigen Receptor Diversification

Grace Teng and F. Nina Papavasiliou

Pathogenic Mechanisms of AllergicInflammation: Atopic Asthma as aParadigm

Patrick G. Holt, Deborah H. Strickland,Anthony Bosco, and Frode L. Jahnsen

The Amplification Loop of theComplement Pathways

Peter J. Lachmann

Index

Volume 105Learning from Leprosy: Insight into the

Human Innate Immune ResponseDennis Montoya and Robert L. Modlin

The Immunological Functions of SaposinsAlexandre Darmoise, Patrick Maschmeyer,

and Florian Winau

OX40–OX40 Ligand Interaction in

T-Cell-Mediated Immunity andImmunopathology

Naoto Ishii, Takeshi Takahashi,

Pejman Soroosh, andKazuo Sugamura

The Family of IL-10-Secreting CD4!

T Cells

Keishi Fujio, Tomohisa Okamura,and Kazuhiko Yamamoto

Artificial Engineering of SecondaryLymphoid Organs

Jonathan K. H. Tan and

Takeshi Watanabe

AID and Somatic HypermutationRobert W. Maul and PatriciaJ. Gearhart

BCL6: Master Regulator of the

Germinal Center Reaction andKey Oncogene in B CellLymphomagenesis

Katia Basso and RiccardoDalla-Favera

Index

Volume 106The Role of Innate Immunity in

B Cell Acquisition of AntigenWithin LNs

Santiago F. Gonzalez, Michael

P. Kuligowski, Lisa A. Pitcher,Ramon Roozendaal, and MichaelC. Carroll

Nuclear Receptors, Inflammation,

and NeurodegenerativeDiseases

Kaoru Saijo, Andrea Crotti, and

Christopher K. Glass

Novel Tools for Modulating Immune

Responses in the Host—Polysaccharides from the Capsuleof Commensal Bacteria

Suryasarathi Dasgupta andDennis L. Kasper


The Role of Mechanistic Factors inPromoting Chromosomal

Translocations Found in Lymphoidand Other Cancers

Yu Zhang, Monica Gostissa, Dominic

G. Hildebrand, Michael S. Becker, CristianBoboila, Roberto Chiarle, Susanna Lewis,and Frederick W. Alt

Index

Volume 107Functional Biology of the IL-22-IL-22R

Pathway in Regulating Immunity

and Inflammation at BarrierSurfaces

Gregory F. Sonnenberg, Lynette A. Fouser,

David Artis

Innate Signaling Networks in Mucosal IgAClass Switching

Alejo Chorny, Irene Puga, and Andrea

Cerutti

Specificity of the Adaptive ImmuneResponse to the Gut Microbiota

Daniel A. Peterson and Roberto A. JimenezCardona

Intestinal Dendritic Cells

Maria Rescigno

The Many Face-Lifts of CD4 T HelperCells

Daniel Mucida and Hilde Cheroutre

GALT: Organization and Dynamics

Leading to IgA SynthesisKeiichiro Suzuki, Shimpei Kawamoto,Mikako Maruya, and SidoniaFagarasan

Bronchus-Associated Lymphoid Tissue

(BALT): Structure and FunctionTroy D. Randall

Host–Bacterial Symbiosis in Health andDisease

Janet Chow, S. Melanie Lee, Yue Shen, AryaKhosravi, and Sarkis K. Mazmanian

Index

Volume 108Macrophage Proinflammatory Activation

and Deactivation: A Question of

BalanceAnnabel F. Valledor, Monica Comalada, LuisSantamarıa-Babi, Jorge Lloberas, and

Antonio Celada

Natural Helper Cells: A New Player in theInnate Immune Response againstHelminth Infection

Shigeo Koyasu, Kazuyo Moro, MasanobuTanabe, and Tsutomu Takeuchi

Mapping of Switch RecombinationJunctions, a Tool for StudyingDNA Repair Pathways during

Immunoglobulin Class SwitchingJanet Stavnezer, Andrea Bjorkman,Likun Du, Alberto Cagigi, and Qiang

Pan-Hammarstrom

How Tolerogenic Dendritic Cells InduceRegulatory T Cells

Roberto A. Maldonado and Ulrich H.

von Andrian

Index

Volume 109Dynamic Palmitoylation and the Role of

DHHC Proteins in T Cell Activationand Anergy

Nadejda Ladygina, Brent R. Martin, andAmnon Altman


Transcriptional Control of NaturalKiller Cell Development and Function

David G. T. Hesslein and Lewis. L. Lanier

The Control of Adaptive Immune Responsesby the Innate Immune System

Dominik Schenten and Ruslan Medzhitov

The Evolution of Adaptive Immunity inVertebrates

Masayuki Hirano, Sabyasachi Das,Peng Guo, and Max D. Cooper

T Helper Cell Differentiation: Morethan Just Cytokines

Beata Zygmunt and Marc Veldhoen

Index

Volume 110AID Targeting in Antibody DiversityRushad Pavri and Michel C. Nussenzweig

The IgH Locus 30 Regulatory Region:

Pulling the Strings from BehindEric Pinaud, Marie Marquet, Remi Fiancette,Sophie Peron, Christelle Vincent-Fabert,Yves Denizot, and Michel Cogne

Transcriptional and Epigenetic Regulation

of CD4/CD8 Lineage ChoiceIchiro Taniuchi and Wilfried Ellmeier

Modeling a Complex Disease: MultipleSclerosis

Florian C. Kurschus, SimoneWortge, and AriWaisman

Autoinflammation by Endogenous DNAShigekazu Nagata and Kohki Kawane

Index

Volume 111Early Steps of Follicular Lymphoma

PathogenesisSandrine Roulland, Mustapha Faroudi,Emilie Mamessier, Stephanie

Sungalee, Gilles Salles, and Bertrand Nadel

“A Rose is a Rose is a Rose,” butCVID is Not CVID: Common Variable

Immune Deficiency (CVID),What do we Know in 2011?

Patrick F. K. Yong, James E. D.

Thaventhiran, and Bodo Grimbacher

Role of Activation-Induced Cytidine

Deaminase in Inflammation-AssociatedCancer Development

Hiroyuki Marusawa, Atsushi Takai,

and Tsutomu Chiba

Comparative Genomics and Evolutionof Immunoglobulin-EncodingLoci in Tetrapods

Sabyasachi Das, Masayuki Hirano,Chelsea McCallister, Rea Tako, andNikolas Nikolaidis

Pax5: A Master Regulator of B CellDevelopment and Leukemogenesis

Jasna Medvedovic, Anja Ebert,Hiromi Tagoh, and MeinradBusslinger

Index

Volume 112Stability of Regulatory T-cell Lineage

Shohei Hori

Thymic and Peripheral Differentiation ofRegulatory T Cells

Hyang-Mi Lee, Jhoanne Lynne Bautista,and Chyi-Song Hsieh

Regulatory T Cells in Infection

Rick M. Maizels and KatherineA. Smith

Biological Functions of Regulatory T CellsEthan M. Shevach

Extrathymic Generation of Regulatory

T Cells—Chances and Challengesfor Prevention of Autoimmune Disease

Carolin Daniel, and Harald von Boehmer

Index


Volume 113Studies with Listeria monocytogenes Lead the

WayEmil R. Unanue and Javier A. Carrero

Interactions of Listeria monocytogeneswith theAutophagy System of Host Cells

Grace Y. Lam, Mark A. Czuczman,Darren E. Higgins and John H. Brumell

Virulence Factors That Modulate the CellBiology of Listeria Infection and the

Host ResponseSerge Mostowy and Pascale Cossart

Dendritic Cells in Listeria monocytogenesInfection

Brian T. Edelson

Probing CD8 T Cell Responses with Listeria

monocytogenes InfectionStephanie A. Condotta, Martin J. Richer,Vladimir P. Badovinac and John

T. Harty

Listeria monocytogenes and Its Products asAgents for Cancer Immunotherapy

Patrick Guirnalda, Laurence Wood and

Yvonne Paterson

Monocyte-Mediated Immune Defense

Against Murine Listeria monocytogenesInfection

Natalya V. Serbina, Chao Shi and

Eric G. Pamer

Innate Immune Pathways Triggered byListeria monocytogenes and Their Rolein the Induction of Cell-Mediated

ImmunityChelsea E. Witte, Kristina A. Archer,Chris S. Rae, John-Demian Sauer,Josh J. Woodward and

Daniel A. Portnoy

Mechanisms and Immunological Effects ofLymphocyte Apoptosis Caused byListeria monocytogenes

Javier A. Carrero, and Emil R. Unanue

Index

Volume 114Nucleic Acid Adjuvants: Toward an

Educated VaccineJasper G. van den Boorn, Winfried Barchet,and Gunther Hartmann

Structure-Based Design for High-Hanging

Vaccine FruitsJaap W. Back and Johannes P. M. Langedijk

Mechanisms of Peptide Vaccination inMouse Models: Tolerance, Immunity,

and HyperreactivityThorbald van Hall and Sjoerd H. van der Burg

Experience with Synthetic Vaccines forCancer and Persistent Virus Infectionsin Nonhuman Primates and Patients

Esther D. Quakkelaar and Cornelis J. M.Melief

Malaria Vaccine Development UsingSynthetic Peptides as a Technical

PlatformGiampietro Corradin, Nora Cespedes,Antonio Verdini, Andrey V. Kajava,

Myriam Arevalo-Herrera, and SocratesHerrera

Enhancing Cancer Immunotherapy byIntracellular Delivery of Cell-PenetratingPeptides and Stimulation of Pattern-

Recognition Receptor SignalingHelen Y. Wang and Rong-Fu Wang

TLR Ligand–Peptide ConjugateVaccines: Toward Clinical Application

Gijs G. P. Zom, Selina Khan, DmitriV. Filippov, and Ferry Ossendorp

Behavior and Function of Tissue-ResidentMemory T cells

Silvia Ariotti, John B. Haanen, and Ton

N. Schumacher

Rational Design of Vaccines: Learning fromImmune Evasion Mechanisms ofPersistent Viruses and Tumors

Ramon Arens

Index


Volume 115The Immunobiology of IL-27Aisling O’Hara Hall, Jonathan S. Silver, andChristopher A. Hunter

Autoimmune Arthritis: The InterfaceBetween the Immune System

and JointsNoriko Komatsu and Hiroshi Takayanagi

Immunological Tolerance DuringFetal Development: From Mouse

to ManJeff E. Mold and Joseph M. McCune

Mapping Lupus SusceptibilityGenes in the NZM2410Mouse Model

Laurence Morel

Functional Heterogeneity in the BasophilCell Lineage

Mark C. Siracusa, Elia D. Tait Wojno, and

David Artis

An Emerging Role of RNA-BindingProteins as Multifunctional Regulatorsof Lymphocyte Development and

FunctionMartin Turner and Daniel J. Hodson

Active and Passive Anticytokine ImmuneTherapies: Current Status andDevelopment

Helene Le Buanec, Armand Bensussan,Martine Bagot, Robert C. Gallo, andDaniel Zagury

Index

Volume 116Classical and Alternative End-Joining

Pathways for Repair ofLymphocyte-Specific and GeneralDNA Double-Strand Breaks

Cristian Boboila, Frederick W. Alt, andBjoern Schwer

The Leukotrienes: Immune-ModulatingLipid Mediators of Disease

Antonio Di Gennaro andJesper Z. Haeggstrom

Gut Microbiota Drives Metabolic Disease inImmunologically Altered Mice

Benoit Chassaing, Jesse D. Aitken,Andrew T. Gewirtz, andMatam Vijay-Kumar

What is Unique About the IgE Response?Huizhong Xiong, Maria A. Curotto de

Lafaille, and Juan J. Lafaille

Prostanoids as Regulators of Innate andAdaptive Immunity

Takako Hirata and Shuh Narumiya

Lymphocyte Development: Integration of

DNA Damage Response SignalingJeffrey J. Bednarski and Barry P. Sleckman

Index


CpG

CpG CpG CpG

CpG CpG CpG

CpG CpG CpG

IDH1 or IDH2

OO

OHO

OH

OH

OH

Isocitrate

O

O

OH

OH

O

Oxoglutarate O

OOH

OH

OH

MutantIDH1 or IDH2

2-Hydroxyglutarate

N

N

O

H

DNMTs

N

N

O

H

TETs

N

N

NH2

O

H

OH

Oxoglutarate Succinate+ +

A

RNAP2

RNAP2

DNMTDNMT

DNMT

CpG

CpG

RNAP2

TET2TET2 TET2

?Unmodified CpG island

Methylated CpG island

Hydroxy methylated CpG island

B(i)

(ii)

(iii)

NH2

CH3

NH2

X

Chapter 1, Figure 1.1 (See page 8 of this volume.)

A Polycomb repressive complex 2

EZH2

SetEEDJARID2

KDM6BKDM6A

RBBP5

COMPASS-likecomplex

MLL-fusionmethyltransferasecomplex

CDKN2A/BHOXA

ASH2L

WDR5MLL

RNAP2

HOXA

H3K4me3 H3K79me2 H3K27me3

MLLAF9 DOT1L

AF10ENL

CBX8

TIP60

MEIS1

Set

SUZ12

RBBP4/7

EZH2

Nonsense/InDels

MLL protein

MLL-fusion proteins

T-ALLMyeloid disordersDLBCL

Missense

Breakpoint

NH2

ATHooks PHD TACxxC

ATHooks AF-9CxxC

ATHooks AF-4CxxC

ATHooks ENLCxxC

SETNH2

SANT SANT SET

Y64

1

CXC

B

C D


PRC2

KDM

Sirtuins HDACs

CpG

CpGCpG CpG

HATs

SIRTiKDMi

KMTi

HDACivorinostat

romidepsin

Lysine methylation

HATi DNMTividaza

decitabine

A

Lysineacetylation

PRMT5 JAK2

(V617F)

Argininemethylation

phosphorylation

JAKiRuxolitinib

Set

DNMT

Nuclear envelope

Alkylating agents

Inhibitors of signal transduction

Cell membrane

Epigenetic inhibitors

Monoclonal antibodies

EGFR

BCR-ABL

DNMTCisplatin

B


Pathologic DNA doublestrand breaks (DSBs)

Physiologic DNA doublestrand breaks (DSBs)

– ROS– Ionizing radiations– Stalled replication forks– Common fragile sites and ERFSs– Oncogene-induced replication breaks– Topoisomerases– DNA damage in micronuclei– “Off-target” activity of RAG1/2– “Off-target” activity of AID

– RAG1/2 induced V(D)J recombination– AID induced CSR and SHM

Legitimate DNA repair

DNA integrity Translocations–Duplications–Chromothripsis

C-NHEJ (all cell cycle)HR (S/G2 phases)FoSTeS (collapsed replication fork)MMBIR (collapsed replication fork)

Illegitimate DNA repairC-NHEJA-EJFoSTeSMMBIR

DSB

DSB


Active A domainInactive B domain

Short chromosomes Long chromosomes

mRNA

mRNA

mRNA

PCNA

mRNA

RNApolymerases

DNApolymerases

C-NHEJ

Chromosome territories Transcription factories Replication factories DNA repair centers

A-EJ


Mature B cells IgM+

4 days stimulationIL-4 + CD40 or LPS

I-Scel-mediatedDSBs

I-Scel-mediatedDSBs

RAG1/2-induced DSBs and translocations

AID-induced DSBs and translocations

A-MuLV Pro-B cells

STI-571

Next-generationsequencing



Translocationmaps

AID induction Translocations

ProliferationCSR to IgG1+ B cells

RAG1/2 induction Translocations

G1 arrest


Mitosis

Micronucleuspulverization

RadiationMMBIR

Predisposition to cancer due tooncogenes and oncosuppressors’

alterations

Postmitotic cell withchromothripsis

Mitosis exit

DNA repairChromosome territory

P53 deficiency

NHEJMMBIR

Chromosome shattering


Type 2 diabetes• Endotoxemia

SteatosisIntestinal microbiota

• Insulitis• Insulin resistance

Obesity

Decreased cholinemetabolism

• Increased calorie extraction• Cleavage of dietary polysaccharides• Dyslipidemia


Steatosis

Inflammatory responsein the liver

Flux of PRR ligands

Intestinal dysbiosis

Enterocytes: NLRP6

Hepatocyte: TLR2-4

TNFIL-6

LSEC: TLR2

Kupffer cell: TLR2-4

Stellate cell: TLR1-9


RIG-I1

7

11

10 77 103 153 514 534 540

476 678

97 110 190 316 882 1025

87 92 172 251 735 925CARD CARD

CARD

CARD Pro

CARD

RD/CTD

RD-like

RD/CTD

TM

ATPase/helicase

ATPase/helicase

ATPase/helicase

MDA5

LGP2

MAVS


Influenza virus WNVDengue virus

EMCVTheiler’s virus

ReovirusNDVSeVVSVHCVJEV

RIG-I MDA-5

P P P

TRIM25Riplet

Cytoplasm

RNF125PKC-a/b

NLRX1 MAVS

IKK-iTBK1

IKK-aIKK-bIKK-g

MAPKs

ATF2/c-Jun

NucleusISGsCytokinesType I IFN

NF-kBIRF3/7

?


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VOLUME ONE HUNDRED AND SEVENTEEN...VOLUME ONE HUNDRED AND SEVENTEEN ADVANCES IN IMMUNOLOGY Edited by FREDERICK W. ALT Howard Hughes Medical Institute, Boston, Massachusetts, USA AMSTERDAM