microRNAs and cancer · 2015-11-16 · microRNAs and cancer Cellular and Molecular Biology of Cancer (PATH G4500-001) November 9th, 2015 -Katia Basso- Columbia University Katia Basso,

microRNAs and cancer

Cellular and Molecular Biology of Cancer (PATH G4500-001)

November 9th, 2015

-Katia Basso- Columbia University

Katia Basso, PhD

Office: ICRC RM506

E-mail: [email protected]

RNA

DNA

PROTEIN

microRNA

From the “one gene-one enzyme” hypothesis to…

Transcription factors

microRNA discovery

lin-4 discovery

in C. elegans

(Lee et al. Cell

1993; Wightman

et al., Cell 1993)

let-7 discovery in

H. sapiens

(Pasquinelli et al.

Nature 2000)

1993

Identification of a

large class of

small-RNA called

“microRNAs”

(Lagos-Quintana

et al.; Lau et al.;

Lee and Ambros

Science 2001)

microRNA

biogenesis

(Hutvagner et al.

Science 2001; Lee

et al. Nature 2003)

2001 2001-2003

miRBase database

(Griffiths-Jones,

NAR 2004; Griffiths-

Jones, et al. NAR

2006)

2004 2000

The discovery of microRNAs -milestones-

microRNA biogenesis

and function

cytoplasm

Adapted from: Ha, M. and Kim, N.V.: Nature Rev Mol. Cell Biol. (2014)

nu

cle

us

POLII

CROPPING

Transcription

Canonical microRNA biogenesis

RISC ORF AAAA

Target repression

HSC70-HSP90

Substrate recognition by Rnase III endonucleases

Adapted from: Ha, M. and Kim, N.V.: Nature Rev Mol. Cell Biol. (2014)

Microprocessor complex

(Drosha and DGCR8)

tion

on

Dicer

Multifunctional microRNA precursors

Maute R.L. et al.: Wiley Interdiscip Rev RNA (2014)

Ha, M. and Kim, N.V.: Nature Rev Mol. Cell Biol. (2014)

Non-canonical microRNA biogenesis

Drosha and DGCR8-independent Canonical pathway TUTase-dependent Dicer-independent

Possible mechanisms of microRNA-mediated

repression

Filipowicz W. et al.: Nature Rev Genetics (2008)


microRNA-mediated pathways

microRNA nomenclature

hsa-mir-19a

Precursor nomenclature:

hsa-mir-19b-1

organism

hsa-mir-19b-2

family

family member

genomic location precursor

5’

3’

miRNA precursor

5’

3’

miRNA duplex

5’ 3’

hsa-miR-19a-3p hsa-miR-19a-5p

Mature nomenclature:

5’arm or

3’ arm

mature

hsa-miR-19b-3p

hsa-miR-19b-1-5p

hsa-miR-19b-2-5p

mature miRNAs

hsa-miR-19a-3p

hsa-miR-19a-5p

microRNA targets

microRNA-target recognition - site position-

Adapted from: Grimson A. et al.: Mol. Cell (2007)

Binding in the 3’UTR is effective for repression Effective site position in the

target 3’UTR

microRNA-target recognition -seed-


Canonical miRNA complementary sites mRNA changes according to type and

number of sites in the target 3’UTR

microRNA-target recognition -3’ pairing-


Pairing in position 13-16 of the miRNA

increases the response efficiency

microRNA-target recognition -AU content-


Score changes based on the presence

of AU relatively to the site

Nucleotide composition in proximity of

effective and conserved sites

Effectiveness of sites with different local AU content

microRNA-target recognition - summary-

In summary, miRNAs bind to their mRNA targets according to the following rules:

• perfect and contiguous base pairing of miRNA nucleotides 2 to 8 (seed region)

• an A residue in position 1 of the site and/or 3’ complementarity especially at

position 13-16 of the miRNA improve the site efficiency

• bulges or mismatches must be present in the middle of the miRNA-mRNA

duplex, precluding the AGO2-mediated cleavage of mRNA

• AU-rich neighborhood

• position in proximity of the termination codon (except the first 15nt) or of the

poly-A tail

ORF NNNNNNNNNN NNNNNNNNA AAAAAAAA

NNNNNNNNNN NNNNNNNNN 1 8 13 16

miRNA

>15nt

mRNA

seed

Identification of microRNA targets

•TargetScan

•PicTar

•MiRanda

•PITA

• …many others

Target Prediction

Algorithms

•Gene Expression Profiles

•Differential Expression

•Proteomic Profiles

Cell context

specificity

•3’UTR-reporter assay

•AGO-IP

•CLIP (Cross-Link and ImmunoPrecipitation)

Experimental Validation

microRNA-mediated networks

The “competing endogenous RNA”

(ceRNA) hypothesis “All types of RNA transcripts communicate through a “new”

language mediated by miRNA response elements” A ceRNA Hypothesis: The Rosetta Stone of a Hidden Language?

Salmena, L., Poliseno, L., Tay, Y., Kats, L. and Pandolfi, P.P

Cell (2011)


Effects of microRNA-target perturbation

Steady-state

Competing

miRNA overexpression

Competing

target overexpression

Poliseno L. et al.: Nature (2010); Tay Y. et al.: Cell (2011)

microRNA-mediated modulation of PTEN

microRNAs and cancer

Discovery of

miR-15 and

miR-16 as

onco-

suppressors in

Chronic

Lymphocytic

Leukemia

(Calin et al.,

PNAS 2002)

miRNA &

cancer-

associated

genomic

regions

(Calin et al.,

PNAS 2004)

2002

Oncomir-1 (miR-

17-92 cluster)

(He et al., Nature

2005; O’Donnell et

al., Nature 2005)

microRNA &

metastasis

(Ma et al., Nature

2007; Tavazoie et

al., Nature 2008)

2005 2007

miRNA detection in

serum and plasma

(Chen et al., Cell

Res. 2008; Mitchell

et al., PNAS 2008)

2008 2004

microRNA and cancer research -milestones-

miRNA profiling

classifies tumors

(Lu et al., Nature

2005)

microRNA in cancer

tumor suppressor oncogene

Adapted from: Esquela-Kerscher A. and Slack F.: Nat Rev Cancer (2006)

no miRNA expression

impaired target repression

increased miRNA

expression

enhanced target

repression

microRNAs as tumor suppressors

Chronic Lymphocytic Leukemia (CLL)

• CLL represents the most frequent B-cell malignancy in the elderly

• Characteristically expresses the CD5 cell surface antigen

• It can be divided into cases with somatically mutated (~60%) or unmutated

(~40%) immunoglobulin variable genes

• Most frequent genetic alteration is the deletion of chromosomal region 13q14

Recurrent genetic aberrations in CLL

• Trisomy 12 (16%)

- is thought to affect gene dosage of unknown genes

• Deletion of 11q (18%)

- deletion of the ATM gene; may predispose to genomic instability

and the development of lymphoid malignancy

• Deletion of 17q (7%)

- deletion of the TP53 gene, and in most cases, the remaining

TP53 allele is mutated; predisposes to genomic instability and the

development of lymphoid malignancy

• Deletion of 13q14 (55%)

- ?

DLEU2 DLEU1

Ch13

MDR

miR-15a/16-1

miR-15a/16-1 DLEU2

E1a E2 E3 E4 E5

381bp

DLEU2

Ex 4

miR-16-1 miR-15a

The 13q14 Minimal Deleted Region (MDR)

contains multiple genetic elements q14

Klein, U. et al.: Cancer Cell (2010)

Mouse model of the 13q14 deletion

Mouse 14qC3

Human 13q14

Mouse model #1

MDR conditional knock-out 14qC3

dLeu2

miR-15a/16-1

dLeu5 Kcnrg

loxP loxP

miR-15a/16-1

DLEU5

KCNRG

DLEU2 DLEU1

13q14

MDR

(Minimal Deleted Region)

430 bp

dLeu2

Gapdh

RT-PCR for dLeu2

Mouse model #2

miR-15a/16-1 conditional knock-out

loxP loxP

miR-15a/

miR-16-1

dLeu2

exon 4

dLeu2

exon 5

Lymphoid involvement

Clonal Ig

Spleen

(H&E)

Peripheral

Blood

(FACS)

Spleen

(FACS)

WT

– –

CD5+ MBL in PB

MDR- and miR-15a/16-1-deleted

+ –

CD

5

B220

CD

5

B220

NHL (DLBCL)

+ +

CLL/SLL

+ +

13.2% 1.2%

1.6%

1.5% 1.4% 1.5%

45.0%

66.2%

Malignancies in mouse models of the 13q14 deletion



Malignancies in mouse models of the 13q14 deletion -low penetrance and indolent phenotype-

Tumor incidence

Event-free survival

CCND3

CCNE1

CDK6

CDC25A

MCM5

CHK1

CCND2

CDK4

–2.1

–1.5

–1.6

–1.8

–4.9

+0.9

–3.3

CLL-I83E95

EV

Mouse B cells WT

a-IgM 0 24 48 0 24 48 h

miR–/–

miR

b-actin

+2.2

+2.4

+2.0

+5.4

+15.7

+3.8

+3.5

+1.7

–4.9 CCND2 CCND3

CCNE

CDC25A p27

CDK2 CDK4 CDK6

Rb p-Rb

E2F E2F

+

CHK1

MCM5

G0/G1 S-phase

miR-

15a/

16-1

miR-15a/16-1

: miR targets

miR-15a and miR-16 modulate cellular proliferation


microRNAs and host genes:

synergistic and antagonistic functions


microRNAs as oncogenes

Ota, A. et al.: Cancer Res (2004)

13q31-q32 amplification in B cell lymphoma -searching for candidate oncogene(s)-

Olive, V. et al.: The International Journal of Biochemistry & Cell Biology (2010)

mir-17-92 cluster on chr 13q31-q32

and its paralogues

mir-17-92 cluster: oncomir-1

He, L. et al.: Nature (2005)

Over-expression in cancer

Acceleration of MYC-induced lymphomagenesis in mice

Olive, V. et al.: The International Journal of Biochemistry & Cell Biology (2010)

mir-17-92 cluster: function and regulation

MicroRNA Expression in patients Confirmed targets Experimental data Function

miR-15a miR-16-1 downregulated in CLL Bcl-2, Wt-1 induce apoptosis and

decrease tumorigenicity

TS

let-7 (a,-b,-c,-d) downregulated in lung and breast cancer RAS, c-myc, HMGA2 induce apoptosis TS

miR-29 (a,-b,-c) downregulated in CLL, AMLa (11q23), lung

and breast cancers, and

cholangiocarcinoma

TCL-1, MCL1, DNMT3s induce apoptosis and

decrease tumorigenicity

TS

miR-34a-b-c downregulated in pancreatic, colon, and

breast cancers

CDK4, CDK6, cyclinE2,

E2F3

induce apoptosis TS

miR-155 upregulated in CLL, DLBCL, AML, BL, and

lung and breast cancers

c-maf induces

lymphoproliferation, pre-

B lymphoma/leukemia in

mice

OG

miR-17∼92 cluster upregulated in lymphomas and in breast,

lung, colon, stomach, and pancreas

cancers

E2F1, Bim, PTEN cooperates with c-myc to

induce lymphoma in

mice, transgenic miR-17-

92 develop

lymphoproliferative

disorder

OG

miR-21 upregulated in breast, colon, pancreas,

lung, prostate, liver, and stomach cancer;

AML(11q23); CLL; and glioblastoma

PTEN, PDCD4, TPM1 induces apoptosis and

decreases tumorigenicity

OG

miR-372/miR-373 upregulated in testicular tumors LATS2 promote tumorigenesis in

cooperation with RAS

OG

microRNAs in cancer

Garzon R. et al.: Annu Rev Med (2009)

Alterations targeting microRNA

structure and function

Genetic, transcriptional and post-transcriptional

microRNA alterations in cancer

Kasinski A. and Slack F. J.: Nat Rev Cancer (2011)

Genomic Alterations

Transcription & Processing Amplification Deletion Mutation

microRNA deregulated activity induced by

target modifications

Kasinski A. and Slack F. J.: Nat Rev Cancer (2011)

Genetic variation in microRNA networks -SNP in microRNA genes-

Ryan, B.M. et al.: Nat Rev Cancer (2010)

Increased risk of

breast, lung and

gastric cancer

Increased

risk of CLL

Genetic variation in microRNA networks -SNP in microRNA seed or target site-

Adapted from: Ryan, B.M. et al.: Nat Rev Cancer (2010)

increased risk of colorectal cancer increased risk of lung cancer

increased risk of

thyroid and

prostate cancer

Genetic variation in microRNA networks -SNP in microRNA processing machinery-

Ryan, B.M. et al.: Nat Rev Cancer (2010)

Pathways leading to altered microRNA

expression and/or activity

Genomic lesions (gains, losses, rearrangements)

Deregulated transcription

Mutations/SNPs affecting miRNA and/or its processing

TRANSCRIPTION

and

PROCESSING miRNA TARGETS PATHWAYS

Target abundance

Mutations creating/destroying sites

Genomic lesions that change the 3’UTR (i.e. translocations)

Alternative polyadenylation

DNA

RNA

PROTEIN

…the “OMICS” era

microRNA

Transcription factors

(Genome and Epigenome)

(Transcriptome)

(Proteome)

(Transfactome) (miRNome)

Documents

microRNAs and cancer · 2015-11-16 · microRNAs and cancer Cellular and Molecular Biology of Cancer (PATH G4500-001) November 9th, 2015 -Katia Basso- Columbia University Katia Basso,