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In vitro and in vivo validation of gene silencing
nanoparticles against alveolar rhabdomyosarcoma
INAUGURALDISSERTATION
zur Erlangung des Doktorgrades
der Fakultät für Chemie und Pharmazie
der Albert-Ludwigs-Universität Freiburg im Breisgau
vorgelegt von
Venkatesh Rengaswamy
aus Madurai
2015
Vorsitzender des Promotionsausschusses: Prof. Stefen Weber
Referent/in: Prof. Regine Süss
Korreferent/in: Prof. Rolf Schubert
Korreferent/in: Prof. Jochen Rößler
Datum der mündlichen Prüfung 23.01.2015
Acknowledgement
I am deeply indebted to the opportunity given by Prof. Regine Süss and Prof. Jochen
Rößler to do my research on gene silencing concept along with siRNA-nanoparticles
against aggressive sarcoma. Specially, I would like to thank Dr. Doris Zimmer for her
time and thoughts in testing several nanoformulations and the excellent co-operation
throughout this study. I humbly express my sincere gratitude for the learning
opportunities provided by Prof. Rolf Schubert and my colleagues at Pharmazeutische
Technologie und Biopharmazie. I would like to thank the members of Pediatric
Hematology and Oncology Laboratory for their assistance, patience and motivation. I
am deeply obliged for the kindness of Marco, Ali, Silvia, Schneider, Alex, Marco and
Karine. I am grateful for the support of Theo for accepting nothing less than
completion from me. This work would not have been accomplished without the
support of Sani who relentlessly helped me with mice and flow cytometry. My
heartfelt thanks to the wonderful people at ZKF and Neuro center animal house. I
humbly dedicate this small work to Dr. Miriam Erlacher and her group for all their
contributions.
Publications
Rengaswamy V, Kontny U, Rössler J.
New approaches for pediatric rhabdomyosarcoma drug discovery: targeting
combinatorial signaling. Expert Opin Drug Discov. 2011;6(10):1103-25.
Submitted
Rengaswamy V, Zimmer D, Süss R, Rössler J.
RGD liposome-protamine-siRNA (LPR) nanoparticles targeting PAX3-FOXO1 for
alveolar rhabdomyosarcoma therapy. Journal of Controlled Release.
Under preparation
Rengaswamy V, Rössler J. Functionalized nanodelivery systems: Effective delivery
mechanisms against aggressive Sarcoma.
Rengaswamy V, Loh C-Khai, Rössler J
Targeting rhabdomyosarcoma.
Rengaswamy V, Rössler J
An update on RNAi design strategies in cancer therapy – from siRNA to miRNA.
In vitro and in vivo validation of gene silencing nanoparticles against alveolar
rhabdomyosarcoma
Due to the therapeutic complexities associated with the aggressive tumor tissues such as
drug resistance, ineffective therapy in advanced stages and relapse, there is a demand to
explore new drug targets and discovery approaches. Recent advancements in the molecular
analysis of PAX3/7-FOXO1 fusion positive alveolar rhabdomyosarcoma have identified
several therapeutic targets. Identification of the associated aberrant genetic alterations that
contribute to the development and progression of the cancerous tissue is relevant for
developing novel anticancer therapeutics.
This study was aimed to evaluate the effect of gene silencing of the fusion transcript PAX3/7-
FOXO1 and its therapeutic significance in vitro and in vivo. By implementing the combination
of siRNA design rules along with different filters, site specific siRNAs were developed for the
PAX3/7-FOXO1 fusion transcript. These siRNAs were validated for their safety and toxicity in
vitro and ensured for non-inflammatory therapeutic applications. Dicer substrate siRNAs
(DssiRNA) and chemically modified siRNAs have proven to have enhanced target down
regulation and stability. They were tested in vitro in this study. Down regulation of PAX3-
FOXO1 and PAX7-FOXO1 targets exhibited direct impact on other over expressed pro-
oncogenic signals. Down regulation of the fusion transcript has shown enhanced inhibition of
cell proliferation without significant apoptotic induction.
RGD targeted lipid protamine siRNA particles showed efficient delivery and down regulation
of the PAX3-FOXO1. ARMS cell lines treated with these LPR particles showed significant
proliferation inhibition. Several RMS cell lines were used for in vitro experiments. Xenograft
tumor generation was done through Rh30 cell lines. With three doses of 20µg of siRNA, the
LPR particles inhibited tumor initiation significantly for three weeks. Tumor growth inhibition
was delayed for a week at 20µg concentration. However, even with 40µg siRNA
concentration tumors were not totally inhibited. Delivering a combination of P3FsiRNA along
with one or more siRNAs against other downstream aberrant signals like CXCR4, FGFR4,
IGF1R, MET, MYCN etc. could eventually enhance the therapeutic significance. However,
effective inhibition of tumor initiation could be exploited in the clinical setting. Introducing
maintenance treatment after “conventional” systemic and local therapy in ARMS with regular
administration of fusion gene specific siRNA-LPR could help to prevent tumor relapse and
secure complete remission. Targeting the integrin receptor of ARMS through RGD tagged
lipid-protamine based nanoparticle delivery system has shown to exhibit a promising
approach in the treatment of residual disease.
Contents Page
1. Introduction
1.1 Rhabdomyosarcoma 1
1.2 Histological and molecular characteristics 2
1.3 Development of Rhabdomyosarcoma 3
1.4 PAX3-FOXO1 and PAX7-FOXO1 fusions in ARMS 5
1.5 Current therapeutic considerations 9
1.6 Initiatives of academia groups in paediatric cancer drug discovery 11
1.7 Need for novel drug development approaches against Rhabdomyosarcoma 13
1.8 RNA interference and Therapeutic gene silencing 14
1.9 Targeted delivery of siRNA 17
1.10 Active targeting of ARMS 17
1.11 In vitro and In vivo model systems 20
2. Objectives and aims 22
3. Materials
3.1 Cell culture 24
3.2 Cell lines 24
3.3 Oligos and siRNAs 24
3.4 Transfection 25
3.5 RNA isolation 25
3.6 Cell assays 25
3.7 Immunotyping 26
3.8 qPCR 26
3.9 Western blot 26
3.10 Utensils and consumables 27
3.11 Instruments 27
3.12 Plasmid vectors 28
3.13 Cell lines and genotype 29
4. Methods
4.1 siRNA design 30
4.2 Primer design 36
4.3 Cell culture 37
4.4 RNase free work environment 38
4.5 siRNA Transfection by HiPerfect 38
4.6 Lipid-Protamine-siRNA nanoparticles 39
4.7 Transfection and treatment by LPR 40
4.8 RNA isolation by TRIzol method 40
4.9 RNA isolation by RNeasy mini kit 41
4.10 RNA quantity and quality measurement
4.11 cDNA Synthesis 42
4.12 Quantitative real time polymerase chain reaction 43
4.13 Protein isolation 46
4.14 Protein concentration measurement 46
4.15 Western Blot 47
4.16 Proliferation inhibition 48
4.17 Apoptosis induction 50
4.18 Transfection of SureSilencing shRNA clones 53
4.19 Transfection of iLenti H1/U6 DssiRNA expression system clones 54
4.20 In vivo Chick Chorioallantoic Membrane (CAM) assay 55
4.21 Experimental animals 56
4.22 In vivo inhibition of tumor initiation 57
4.23 In vivo tumor growth inhibition 57
4.24 In vivo LPR tolerance 57
4.25 Cell viability 58
4.26 Interferon response detection 58
4.27 Quality control and statistical analysis 58
5. Results and Discussion
5.1 siRNA design 59
5.1.1 Designing 21-mer siRNA 61
5.1.2 Designing 27/29-mer PAX3-FOXO1 DssiRNA 64
5.1.3 shRNA and siRNA expression systems for PAX3-FOXO1 65
5.2 Toxicity validation of siRNAs 65
5.3 Specificity of PAX3-FOXO1 siRNAs 67
5.4 Specificity of PAX7-FOXO1 siRNA 68
5.5 Validation for induction of innate immunity 69
5.6 PAX3-FOXO1 target down regulation by different siRNA constructs 71
5.7 Effect of siRNA concentration on PAX3-FOXO1 down regulation 74
5.8 Effect of PAX3-FOXO1 down regulation on other pro-oncogenic signals 75
5.9 Effect of siRNA chemical modification on PAX3-FOXO1 77
5.10 Effect of shRNA constructs on PAX3-FOXO1 down regulation 79
5.11 Effect of shRNA-199 clone 80
5.12 Effect of iLenti H1/U6 siRNA expression system 81
5.13 iLenti H1/U6 clone 199 82
5.14 Effect of siRNA concentration on PAX7-FOXO1 down regulation 83
5.15 Effect of PAX7-FOXO1 down regulation on other pro-oncogenic signals 85
5.16 Effect of siRNA chemical modification on PAX7-FOXO1 86
5.17 Effect of target down regulation on proliferation inhibition 87
5.18 Effect of target down regulation on apoptosis induction 89
5.19 PAX3-FOXO1 target down regulation by P3F-siRNA-LPR 91
5.20 P3F target down regulation on proliferation inhibition by LPR 94
5.21 P3F target down regulation on apoptosis induction by LPR 95
5.22 Down regulation of PAX3-FOXO1 fusion protein 96
5.23 Inhibition of tumor initiation 101
5.24 Tumor growth inhibition with 20µg concentration 102
5.25Tumor growth inhibition with 40µg concentration 103
5.26 In vivo tolerance of LPR 105
6. Conclusion 107
7. Significant outcome 110
8. References 111
1
1. Introduction
1.1 Rhabdomyosarcoma
The survival rate of most paediatric cancers has improved with the development of
effective therapies, including different chemotherapeutic agents that are capable of
destroying proliferating cells. In contrary, for some paediatric cancer entities,
chemotherapy still remains largely ineffective due to relapse, drug resistance and
metastatic spread. Tumors belonging to this category include different types of
sarcomas such as rhabdomyosarcoma (RMS), Ewing‟s sarcoma and osteosarcoma
that reach an overall five year survival rate of 60-65% [Linabery AM and Ross JA
2008]. RMS is a group of heterogeneous sarcomas with ability to invade locally and
metastasize via the lymphatics and the bloodstream. Due to this reason, all RMS
patients should practically be assumed to have micro-metastatic disease already at
the time of their diagnosis [Pappo AS and Shapiro DN 1995]. The outcome for those
patients with metastatic or relapsed disease remains miserable as RMS has a
tendency of chemotherapy resistance.
Intensive chemotherapeutic treatment may result in a variety of long-term
complications in paediatric patients, including impairment of growth and
development, organ dysfunctions and subsequent malignancies, preventing further
intensification of therapy with these drugs [Landier W and Bhatia S 2008]. In children
with advanced stages of RMS, chemotherapy and its combination with surgery and
local radiation usually fail to work, because the cancer cells evolve aggressively to
repair the damage or fail to induce apoptosis. At present, there are no effective
treatments that target the genetic abnormalities in RMS Hence, there is a need to
improve risk stratification and develop effective novel drugs with the understanding of
genetic factors and molecular pathways that are involved in the pathogenesis and
development of RMS. Several signaling pathways that are activated, up-regulated,
down-regulated, co-expressed and over-expressed to promote proliferation and
development of RMS have provided promising strategies for the development of new
therapeutic approaches [Ahn EH, Mercado GE et al. 2013].
2
1.2 Histological and molecular characteristics
The most common soft tissue sarcomas of childhood and adolescence are
rhabdomyosarcomas that share features of skeletal myogenesis with extensive
heterogeneity dependent on age, site of onset. RMS cells bear striking resemblance
to immature skeletal muscle cells, known as myoblasts. These malignancies express
skeletal muscle markers but are originally the result of dysregulated skeletal muscle
differentiation of mesenchymal precursors.
Histological criteria separates RMS into two major types, embryonal (ERMS; 60-70%)
and alveolar RMS (ARMS; 20-30%). Embryonal RMS is associated with a better
prognosis than alveolar. Tumors with embryonal histology arise in the head and neck
region or in the genitourinary tract. Other variants (all considered as subgroups of
ERMS) include the botryoid subtype (represent about 10%), spindle cell variant and
the pleomorphic subtype, which is found mainly in adults [Ognjanovic S, Linabery AM
et al. 2009]. Botryoid tumors arise under the mucosal surface of body orifices and the
spindle cell variant is most frequently observed at the paratesticular site. Most ARMS
resemble lung alveoli and occur in the extremities, such as trunk and
perineum/perianal region and are clinically more aggressive. Patients with ERMS
have a general favorable prognosis, while patients with ARMS do significantly worse,
with a five-year survival rate of less than 50% [Ognjanovic S, Linabery AM et al.
2009].
Nearly 80% of ARMS cases are associated with characteristic chromosomal
translocations, which form a fusion gene between either PAX3 or PAX7 and FOXO1a
arising from t(2;13)(q35;q14) and t(1;13)(p36;q14) chromosomal translocations,
respectively [Barr 2001]. Approximately 60-70% of ARMSs involve PAX3-FOXO1a
[Galili N, Davis RJ et al. 1993; Du S, Lawrence EJ et al. 2005], whereas 20% have
the PAX7-FOXO1a [Davis RJ, D'Cruz CM et al. 1994]. Recognition of these specific
translocations is also prognostically important, as PAX3-FOXO1a positive ARMSs
are significantly more aggressive than PAX7-FOXO1a ARMSs [Sorensen PH, Lynch
JC et al. 2002]. However, the presence of a fusion gene is associated with a poor
prognosis, especially the presence of the PAX3-FOXO1a gene fusion may be
associated with a poorer prognosis compared to PAX7–FOXO1a [Kazanowska B,
Reich A et al. 2007].
3
Approximately 30% of ARMSs fail to exhibit either PAX3-FOXO1a or PAX7-FOXO1a
fusions by routine reverse transcription polymerase chain reaction (PCR) and have
been termed as fusion transcript negative [Barr et al. 2002]. Infrequently, isolated
cases have shown alternate translocation associated with fusion transcripts (PAX3-
AFX t(2;X)(q35;q13), PAX3-NCOA1 and PAX3-NCOA2 t(2;2)(q35;p23) and
t(2;8)(q35;q13)) [Barr FG, Qualman SJ et al. 2002; Wachtel M, Dettling M et al. 2004;
Sumegi J, Streblow R et al. 2010]. Chromosomal translocation is not seen in ERMS,
except loss of heterozygosity (LOH) at 11p15.5 that is also seen in ARMS [Anderson
J, Gordon A, et al. 1999] associated with loss of genes IGF2, H19 and CDKN1C
subject to parental imprinting [De Giovanni C, Landuzzi L et al. 2009] and
dysregulation of IGF2 [Zhan S, Shapiro DN et al. 1994 and Visser M, Sijmons C et al.
1997].
1.3 Development of Rhabdomyosarcoma
Though, the exact origin of RMS is yet to identified, studies have suggested either
mesenchymal stem cells (MSC) or muscle satellite cells might be the site of origin
for RMS (Figure 1.1) [Charytonowicz E, Cordon-Cardo C et al. 2009]. Identifying the
origin of RMS would reveal vital insights into the related requirements of oncogenic
mutations associated with these tumors and would enable new treatments or the
development of novel drugs, to be tailored towards the particular cellular and genetic
requirements [Hettmer S and Wagers AJ 2010]. Looking into the complexity
introduced by these heterogeneous RMS subtypes, additional experimental evidence
suggests that individual RMS subtypes may originate from distinct cellular sources,
including circulating mesenchymal progenitor cells [Charytonowicz E, Cordon-Cardo
C et al. 2009], which are mesodermal in origin and that are not committed to the
myogenic lineage.
4
Figure 1.1 The developmental process of mature muscle from the mesenchymal progenitor
leading to ERMS and ARMS. Depending on the expression of oncogenes, satellite cells and
myoblasts generate ERMS and mesenchymal cells in ARMS. All RMS subtypes express markers of
embryonic or adult myogenic lineage. Myogenic regulatory factors play a vital role in the differentiation
process. PAX3-FOXO1a induction by myogenic factor-6 de-differentiates maturing myoblasts into
ARMS. Identification of the key regulators and their interaction in the developmental process of RMS
would give a better insight in understanding the mechanism of the disease progression [Rengaswamy,
Kontny, Rössler 2011].
Such mesenchymal progenitors are found in many tissues and may circulate
between organs, providing a possible mechanism for the emergence of RMS in non-
muscle tissues [Lisboa S, Cerveira N et al. 2008; Shinkoda Y, Nagatoshi Y et al.
2009] and an explanation for the heterogeneity among RMS subtypes. In the embryo,
mesodermal cells generate myogenic cells that differentiate into skeletal muscle
fibers under the control of myogenic transcription factors, PAX3 and PAX7. However,
subsets of these myogenic cells escape terminal differentiation in the embryo and
instead form a unique population of mononuclear satellite cells that act as myogenic
precursors to support muscle maintenance and growth. During muscle injury, these
cells proliferate, terminally differentiate and fuse into multinucleated myofibers
following a highly regulated process that is controlled by myogenic regulatory factors
[Bober E, Lyons GE et al. 1991].
5
Insights into this fusion-induced development process identify several pro-oncogenic
signals in RMS [Hettmer and Wagers, 2010] pathway modulators and/or genetic
manipulations that promote regular muscle differentiation. High throughput screening
of new drug compounds that enhance muscle differentiation, would arrest cell
proliferation leading to RMS. Induction of PAX3-FOXO1 by myogenic factor-6 (Myf-
6)-Cre results in the development of ARMS [Keller C, Capecchi MR 2005]. As Myf-6
expression is known to be restricted to matured skeletal muscle cells, the
development of ARMS would be PAX3-FOXO1-induced dedifferentiation of maturing
myoblasts [Keller C, Capecchi MR 2005]. However, it is essential to study the well-
defined populations of mesenchymal and muscle-derived cells on a clonal level to
uncover the in vivo cause of RMS tumor-initiating cells from complex heterogeneous
origins [Lisboa S, Cerveira N et al. 2008; Linardic CM, Naini S et al 2007].
1.4 PAX3-FOXO1 and PAX7-FOXO1 fusions in ARMS
The discovery of fusions proteins, FOXO1 with PAX3 and PAX7 by Barr and
colleagues [Galili N, Davis RJ et al. 1993 and Davis RJ, D‟Cruz CM et al. 1994]
initiated several studies on the identification of its transcriptional signature in order to
investigate the origin of ARMS and cancer progression. Expression of these fusion
proteins is more potent than their corresponding wild-type proteins. In these fusion
proteins, an abnormal transcription factor is created that combines the transcriptional
activation domain of FOXO1a with the DNA-binding domains of PAX3 or PAX7
(Figure 1.2), leading to inappropriate activation of the growth promoting genes. PAX3
expression occurs in the neural tube and dermomyotome that is required for the
normal migration of skeletal muscle precursor cells to the limb bud [Daston G, Lamar
E et al. 1996]. PAX7 expression occurs in the myogenic satellite cells in adult skeletal
muscle and is required for regular self-renewal [Oustanina S, Hause G et al. 2004].
FOXO1 is also a transcription factor that plays vital roles in the regulation of
gluconeogenesis and glycogenolysis by insulin signaling [Nakae J, Kitamura T et al.
2003].
6
Figure 1.2 The fusion of PAX3 and PAX7 with FOXO1a. The break point (BP) region for both
fusions is same. The DNAbinding motifs -- paired box domain (PB) and homeobox domain (HB) are
shown in orange. The Forkhead DNAbinding domain (FD) is shown in white that is truncated in the
fusion. Transactivation domain (TAD) is intact in both the fusion types. The fusion gene PAX3-
FOXO1a, resulting from the stable reciprocal translocation of chromosomes 2 and 13, is a signature
genetic change in most ARMS. Identification of the direct effectors of PAX3-FOXO1a might have
crucial roles in delineating its molecular pathogenic mechanism and in identifying new therapeutic
targets.
Unlike ERMS, most of the aggressive ARMS tumors carry one of the characteristic
chromosomal translocations, such as, t(2;13)(q35;q14) and t(1;13)(p36;q14) that
result in the expression of a PAX3-FOXO1 and PAX7-FOXO1 fusion transcription
factor. The fusion protein of this unique translocation consists of the paired and
homeodomains of the PAX3/7 transcription factor (Paired box family of transcription
factors) along with the potent transcriptional activation domain of FOXO1 (Fork head
family of transcription factors) [Fredericks WJ, Galili N et al. 1995]. The PAX3-
FOXO1 fusion can be detected in about 55% of the ARMS cases, whereas PAX7-
FOXO1 fusion occurs in 22% of the ARMS cases [Sorensen PH, Lynch JC et al.
2002]. The infrequent cryptic fusion variants are thought to be present in up to 10%
of ARMS tumors [Wexler L, Meyer W et al. 2006].
7
Wild-type and fusion gene constructs were transfected and ectopically expressed in
different cell lines to identify the common and unique expression of specific target
genes. Different genes have been identified through microarrays and expression
profiling as downstream candidates that are transcriptionally activated by the fusion
protein. However, the target genes identified were different between the cell lines in
which the fusion gene was ectopically expressed [Kurmasheva R, Hosoi H et al
2010]. PAX-FOXO1 fusion alone was not sufficient for tumorigenesis. A combination
of events such as, p161NK4/p14ARF loss of function, telomere reactivation, MYCN
amplification, mutated p53 and mutated HARS and PAX-FOXO1 fusion promotes
transformation of human myoblasts into ARMS [Naini S, Etheridge KT et al. 2008].
However, silencing the PAX3-FOXO1 with antisense oligonucleotides and siRNA
induces apoptosis [Bernasconi M, Remppis A et al. 1996; Kurmasheva R, Hosoi H et
al. 2010] and repression of malignant phenotype in vitro [Kikuchi K, Tsuchiya K et al
2007]. This suggests that the expression of the PAX3-FOXO1 is a key early step in
the transformation of myoblasts in ARMS. Comparative gene expression profiles of
PAX3-FOXO1 silencing in vitro and in vivo revealed 51 overlapping genes [Wachtel
M, Dettling M et al. 2004] that are involved in signal transduction (CNR1, FGFR2 and
IL4R), secreted proteases (ADAM10 and 19), transcriptional regulation and DNA
binding (MYCN, POU4F1 and TFAP2B) [Ebauer M, Wachtel M et al. 2007]. TFAP2B
is a vital PAX3-FOXO1a target involved in anti-apoptotic activity.
8
Figure 1.3 The gene networks involved in PAX3-FOXO1a regulated rhabdomyosarcoma. Genes
indicated in violet color are the common genes involved in rhabdomyosarcoma (generated based on
published results in the Pubmed database) and the green color genes are up-regulated by the fusion
protein (custom input based on RMS gene expression profile data). Green line indicates up-regulation,
grey line indicates regulation, yellow line indicates interaction, blue line indicates chemical
modification, dotted cyan indicates predicted physical interaction and dotted pink indicates predicted
regulation. Targeting one or more up-regulated signals would be the possible way of developing novel
therapeutics. Only few selected up-regulated signals are shown in the network. (Network interaction
generated in Gene Network Central Pro).
Comparison of the differential expression patterns between ARMS and ERMS with
an inducible PAX3-FOXO1a reveals several shared genes that are up/down-
regulated and function in transcription, signaling (protein kinases) and development
[Mercado GE, Xia SJ et al. 2008]. PAX3-FOXO1a promotes RMS survival through
PTEN (phosphatase and tensin homolog deleted on chromosome ten) down-
regulation [Li HG, Wang Q et al. 2007] and inhibits the host immune system in a
STAT3-dependent mechanism [Nabarro S, Himoudi N et al. 2005]. The increased
expression of VEGFR1 [Onisto M, Slongo ML et al. 2005], MMP2, CXCR4 [Tomescu
O, Xia SJ et al. 2004] and MET [Chen Y, Takita J et al. 2007] observed in fusion-
9
positive ARMS cells might favour tumor growth and contribute to high metastatic
activity. The possible up-regulated network targets that could be further explored for
rational drug discovery is illustrated in Figure 1.3.
Genome-wide analysis of PAX3-FOXO1a binding sites and associated target genes
illustrates a strong association between PAX3 and E-box motifs in DNA, suggestive
of a common co-regulation for many target genes [Cao L, Yu Y et al. 2010]. As
FGFR4 and IGF1R are directly up-regulated by PAX3-FOXO1a, they might serve as
potential targets and biomarkers. The map of PAX3-FOXO1a binding sites provides a
framework for understanding the pathogenic roles of PAX3-FOXO1a, as well as its
molecular targets to allow a systematic evaluation of novel drugs. PAX3-FOXO1a
exerts pleiotropic effects, including driving proliferation, promoting cell survival,
suppressing terminal differentiation, promoting invasion and perhaps supporting
angiogenesis due to the altered regulation of targets of wild-type PAX3 and the
recruitment of new targets to the aggressive fusion protein [Linardic CM, 2008].
However, further work is needed to precisely define the molecular mechanisms
underlying these contributions, and their value as druggable targets.
1.5 Current therapeutic considerations
Based on risk stratification, current treatment for RMS includes chemotherapy,
radiation, and surgery. Combination of the golden standard chemotherapeutic agents
vincristine, actinomycin D and cyclophosphamide (shortly called VAC regimen) are
commonly prescribed based on the cooperative protocol by the Intergroup
Rhabdomyosarcoma Study (IRS) [Maurer and Beltangady et al. 1988]. The VAC
regimen is adopted in the treatment of RMS with slight modifications in administration
modalities and dose intensity. In order to reduce the use of radiation therapy for low-
risk RMS patients, European protocols have more readily incorporated anthracyclines
and ifosfamide. The VAC regimen in Europe has been replaced by IVA (ifosfamide,
vincristine, actinomycin D) as the gold standard for RMS, which differs only in the
choice of alkylating agent. The two schemes are probably equally effective and their
hematological, renal and gonadal toxicity profiles are only slightly different [Casanova
and Ferrari, 2011].
10
Study group Therapeutic drugs
IRS-IV (1991 - 1998) [Crist WM, Anderson JR, et al. 2001; Rany RB, Maurer HM, et al. 2001]
Localized RMS: VA, VAC vs VAI vs VIE Metastatic RMS: melphalan/vincristine vs ifosfamide/etoposide vs ifosfamide/doxorubicin
IRS-V (1999 - 2005) [Raney B, Anderson J, et al. 2008]
Localized RMS: VA, VAC vs VAC + vincristine/topotecan/cyclophosphamide Metastatic RMS: window therapy (topotecan, topotecan/vincristine), VAC
IRS-VI (2006 – Ongoing)
Localized RMS: VAC-VA, VAC vs VAC + irinotecan/vincristine Metastatic RMS: irinotecan/vincristine, dose compression (VDC-IE), VAC ± temozolomide and cixutumumab
SIOP MMT 95 [Oberlin O, Rey A, et al. 1996; Stevens M, Rey A, et al. 2005]
Localized RMS: IVA vs CEVAIE Metastatic RMS: adriamycin, carboplatin (window), CEVAIE, high-dose chemotherapy (cyclophosphamide, etoposide, carboplatin), maintenance VAC
SIOP MMT 98 [McDowell HP, Foot AB, et al. 2010]
Localized RMS: VAI, CEIE, maintenance VAC Metastatic RMS: carboplatin or doxorubicin (window), high-dose chemotherapy(cyclophosphamide+filgrastim, etoposide+filgrastim, cyclophosphamide+filgrastim, carboplatin+filgrastim), maintenance VAC
AIEOP-STSC RMS 96 [Orbach D, Rey A, et al. 2010]
Localized RMS: VA, IVA, VAIA vs CEVAIE Metastatic RMS: CEVAIE/IVADo + high-dose chemotherapy (thiotepa, cyclophosphamide, melphalan), maintenance VAC
CWS 96 [Klingebiel T, Boos J, et al. 2008]
Localized RMS: VAIA vs CEVAIE Metastatic RMS: high-dose chemotherapy or oral maintenance (trofosfamide/etoposide or trofosfamide/idarubicin)
CWS 2007 [Koscielniak and Klingebiel. 2014]
Standard therapy + maintenance chemotherapy with O-TIE (oral etoposide, idarubicin, trofosfamide)
EpSSG (2005 - Ongoing) [Bisogno G, Ferrari A, et al. 2005]
Localized RMS: VA, IVA, IVA vs IVADo ± maintenance therapy (vinorelbine + low-dose cyclophosphamide) Metastatic RMS: IVADo + maintenance therapy ± bevacizumab
Table 1.1 Therapeutic drugs used to treat Rhabdomyosarcoma tested by paediatric oncology
study groups with the standard and new regimens. AIEOP-STSC: Italian Associazione Italiana
11
Ematologia Oncologia Pediatrica - Soft Tissue Sarcoma Committee; CEIE: Carboplatin, epirubicin,
ifosfamide, etoposide; CEVAIE: Carboplatin, epiadriamycin, vincristine, actinomycin D, ifosfamide,
etoposide; CWS: German Soft Tissue Sarcoma Cooperative Group - Cooperative Weichteilsarkomen
Studie; EpSSG: European Pediatric Soft Tissue Sarcoma Study Group; EVAIA: Etoposide, vincristine,
actinomycin D, ifosfamide, adriamycin; IE: Ifosfamide, etoposide; IRS: Intergroup Rhabdomyosarcoma
Study - Children‟s Oncology Group; IVA: Ifosfamide, vincristine, actinomycin D; IVADo: Ifosfamide,
vincristine, actinomycin D, adriamycin; SIOP-MMT: International Society of Pediatric Oncology -
Malignant Mesenchymal Tumour; VA: Vincristine, actinomycin D; VAC: Vincristine, actinomycin D,
cyclophosphamide; VACA: Vincristine, actinomycin D, cyclophosphamide, adriamycin; VADRC:
Vincristine, adriamycin, cyclophosphamide; VAI: Vincristine, actinomycin D, ifosfamide; VAIA:
Vincristine, actinomycin D, ifosfamide, adriamycin; VDC: Vincristine, adriamycin, cyclophosphamide;
VIE: Vincristine, ifosfamide, etoposide.
For low-risk RMS patients, the current goal within Intergroup Rhabdomyosarcoma
Study-Children‟s Oncology Group (IRS-COG) is to decrease the intensity of therapy
in an effort to limit the treatment-related late effects, such as infertility and secondary
cancers. Chemotherapeutic drug combinations with doxorubicin, cisplatin, etoposide,
melphalan, carboplatin and camptothecin derivatives have been used over the years
by different international groups and compared with VAC/IVA in a randomized setting
(Table 1.1). However, all the new regimens have failed to improve the results
achieved by the standard treatment, as there was no improvement in the outcome.
Interestingly, the German CWS-96 trial demonstrated that patients who received oral
maintenance chemotherapy had improved outcome [Klingebiel T, Boss J et al. 2008].
Recent IRS-COG studies have attempted to incorporate various agents, such as
irinotecan, topotecan, doxorubicin, ifosfamide, and etoposide, especially for high-risk
RMS patients [Huh and Skapek, 2010]. Unfortunately, little improvement has been
made for high-risk RMS patients, who have a 3-year overall survival of approximately
30% [Oberlin et al. 2008].
1.6 Initiatives of academia groups in paediatric cancer drug discovery
The Pediatric Preclinical Testing Program (PPTP) founded in 2002 initiated by
National Cancer Institute and Children‟s Oncology Group (COG) in the US
determines whether the panels of childhood cancers can accurately identify novel
and/or combination of agents that will have significant clinical activity. The
identification is characterized through model selection, molecular characterization
and in vivo drug evaluation [Houghton PJ, Morton CL et al. 2007]. Conventional
12
chemotherapeutic agents as well as novel agents have been evaluated for nearly 30
compounds. The clinical development phases of selective agents tested for
Rhabdomyosarcoma are listed in table 1.2. The IRS-COG Phase I Consortium in
cooperation with the Cancer Therapy Evaluation Program of the National Cancer
Institute (NCI) and the Innovative Therapies for Children with Cancer (ITCC) has
played a vital role in the process of identifying new targets and developing new drugs
for Rhabdomyosarcoma [Zwaan CM, Kearns P et al. 2010].
ITCC founded in 2003 aims to coordinate efforts in preclinical and early clinical
development of new anticancer agents for children in Europe [Zwaan CM, Kearns P
et al. 2010]. One of the major objectives of ITCC is to explore the importance of RNA
interference (RNAi) mediated inhibition of druggable target kinases in different cell
lines, which represent major paediatric malignancies. This can be applied to the
preclinical models to select the best candidate drugs for clinical testing. The Kids
Cancer Kinome program of ITCC plans to explore the role of all protein kinase family
members through functional high-throughput kinase-specific viral siRNA screening
and expression profiles. In addition, the proposed objectives include in vitro testing of
the identified protein kinases with the available small molecule inhibitors and LNA
kinase inhibitors along with the mutation analysis of „tumour-driving‟ protein kinases.
ITCC biology consortium is involved in stepwise pre-clinical target identification and
drug evaluation system to select and prioritize anti-cancer compounds.
Therapeutic agent Specific outcome of evaluation Stage
17-DMAG HSP-90 inhibitor
Partial response in ARMS xenograft None
AZD8055 mTOR inhibitor
Survival benefit noted in RMS None
BMS 754807 IGF-1R inhibitor
Intermediate activity noted in RMS None
IMC A12 Monoclonal antibody against IGF-1R
Greater in vitro activity in RMS cell lines. Growth inhibitory activity against in vivo solid tumor models
Phase I
MLN8237 Aurora A kinase inhibitor
Objective response noted in RMS Phase I
PR-104 Hypoxia-activated alkylating agent
Objective response noted in RMS. Broad activity against in vivo xenografts.
None
Rapamycin mTOR inhibitor
Slowly developing responses noted in RMS tumor panels. Xenografts
Phase II
13
responded to rapamycin
Rapamycin Combination with cyclophosphamide or cisplatin or vincristine
Combination therapy worked better than single agent against several tumour models
Phase II
Sunitinib RTK inhibitor for Flt3, PDGFR, VEGFR and kit
Antitumour effect primarily through an anti-angiogenic mechanism of action
Phase I
SVV 001 Oncolytic PicoRNA virus NTX-010
High level in vivo activity in ARMS. Complete response noted.
None
Topotecan (semi synthetic analogue of camptothecin) Topoisomerase – I inhibitor
High activity noted in RMS, comparable to vincristine and better than cisplatin
Phase II
Table 1.2 Pediatric Preclinical Testing Program evaluation of therapeutic agents for
Rhabdomyosarcoma. FLT3: FMS-like tyrosine kinase 3 (also known as FLK2 (Fetal Liver Kinase-2));
HSP: Heat shock protein; IGF1R: Insulin-like growth factor 1 receptor; KIT: Human homolog of the
proto-oncogene c-kit; mTOR: Mammalian target of rapamycin (also known as mechanistic target of
rapamycin); PDGFR: Platelet-derived growth factor receptor; PPTP: Pediatric preclinical testing
program; RMS: Rhabdomyosarcoma; RTK: Receptor tyrosine kinase; SVV: Seneca Valley Virus;
VEGFR: Vascular endothelial growth factor receptor.
1.7 Need for novel drug development approaches against Rhabdomyosarcoma
Treatment for RMS is dependent on a multimodal approach of surgery,
chemotherapy and radiation. This further depends on the type, grade and severity of
RMS. Chemotherapy is usually effective in RMS, especially for the newly diagnosed
cases with the expected post chemotherapy adverse effects that include infertility,
cardiomyopathy, growth retardation and possible secondary malignancies.
Approximately 30% of RMS cases are ineffective to chemotherapy that requires
intensive chemotherapy along with radiotherapy. This could possibly result in a range
of long term sequelae. In addition, treatment options are limited for patients under
high risk with poor prognosis. Drug resistance and relapse are other major setbacks
for the effective treatment that require novel drugs and approaches. This is coupled
with the fact that the present cure rate for children with metastatic RMS is only 20 -
30% [Melcon and de Toledo, 2007].
Due to the heterogeneity of the RMS types, alterations in the molecular pathways
influenced by translocations, the loss of imprinting the drug response and the
treatment outcome varies. Without type specific targeted therapies for genetic
14
abnormalities associated with RMS, the survival outcome may not improve. Unlike
advanced treatment strategies for other types of malignancies, there are no targeted
drug therapies available for RMS that could potentially improve overall cure rates and
reduce morbidity. To overcome the problems associated with non-specificity of the
current therapeutic approaches, the concept of targeted therapy has been developed
to specifically target tumor cells while sparing the normal cells [Wachtel and Schäfer,
2010]. Such an approach requires innovative ways of drug discovery and
development processes.
Over the past two decades, research into the molecular mechanisms of RMS has
identified key genes and signaling pathways involved in disease pathogenesis along
with favorable molecular targets [Crose and Linardic, 2010]. Hence, there is an
urgent need for alternative drug developmental approaches for more effective
targeted treatment. Technological advances in the genome and transcriptome
analysis in the past decade, especially in the gene expression analyses, gene
silencing analyses through RNAi and high-throughput screening/sequencing methods
have accelerated the processes of innovative drug development.
1.8 RNA interference and Therapeutic gene silencing
For the past four decades, researchers have been working on strategies to
selectively silence genes that are responsible for the disease or complement the
genes that are mutated. After the initial discovery of RNAi-mediated gene silencing in
Petunia [Napoli C, Lemieux C, 1990], the therapeutic use of RNAi is gaining
popularity. The pioneering work of Fire et al. (1998) led to the identification of double-
stranded RNAs (dsRNAs) with the potential to selectively and efficiently turn off
genes in Caenorhabditis elegans [Fire A, Xu S et al. 1998] through gene silencing.
However, in vertebrates the dsRNAs were shown to cause cell death by the induction
of the IFN response and the activation of dsRNA-dependent protein kinase R (PKR).
15
Figure 1.4 siRNA-mediated gene silencing and off-target effects. Long dsRNA entering into the
cell is processed into siRNAs by Dicer. These siRNAs assemble into RISCs that unwind the sense
strand. The antisense strand along with the RISC is guided to the complimentary mRNA strand. After
the complimentary binding, RISC cleaves the target mRNA that is further degraded by cellular
nucleases. dsRNA activates the dsRNA-dependent PKR leading to a global inhibition of protein
synthesis. Toll-like receptors present in the endosome recognize double-stranded and single-stranded
siRNAs in a sequence-dependent manner and induce pro-inflammatory cytokines.
Later, Elbashir et al. from Tuschl‟s group (2001) pioneered gene silencing in
mammals by proving that diced dsRNAs can sidestep the IFN pathway and
effectively silence a targeted gene [Elbashir SM, Harborth J et al. 2001]. This
mechanism opened a plethora of opportunities, one among them was the use of
16
small interfering RNAs (siRNA) for gene silencing against a variety of human
diseases through an approach termed „RNAi therapeutics‟.
The RNAi mechanism is initiated by dsRNA that helps in endogenous gene
regulation and controls the expression of cellular DNA. Dicer and Argonaute
containing multiprotein RNA-induced silencing complex (RISC) along with a gene
specific dsRNA are the main players in selective gene silencing. Dicer along with its
associated cofactors, consisting of an N-terminal RNA helicase domain, an RNA-
binding Piwi/Argonaute/Zwille domain, two RNase III domains and a double-stranded
RNA-binding domain (DRBD) process the dsRNA into siRNAs are ~ 21 base pairs
(bp) in length with 2 nucleotide overhangs at both 3`ends. The processed/delivered
siRNAs are then delivered to RISC (Figure 1.4).
Due to the sequence complementarity of the siRNA duplex onto RISC, the Argonaute
unwinds the sense strand through RNA helicase activity. This produces activated
RISC, retaining the anti-sense strand with lower stability at the 5`end, to act as an
RISC-targeting cofactor. The anti-sense strand confers sequence based specificity to
its associated Argonaute containing-RISC complex, allowing recognition and base
pairing with the target mRNA. This reaction is carried out by the Piwi domain in RISC
that folds into an RNaseH like structure. The Argonaute in the RISC complex
contains an endonuclease activity which causes a single-site cleavage of the target
mRNA roughly in the middle of the siRNA binding region [Hutvagner G, Zamore PD
et al. 2002]. The resulting cleaved fragments of the target mRNA have unprotected
ends and are, hence, subsequently degraded by the cellular nucleases.
Successful gene silencing greatly depends on the selection of the siRNA sequence
design. The most effective siRNAs are above 21 nucleotides, called dicer substrate
siRNA (DsiRNA). These are found as being 100-fold more efficient than the 21-mer
siRNAs without inducing IFN or activate PKR immune reactions [Kim DH, Behlke MA
et al. 2005]. Design rules to develop an efficient siRNA for gene silencing have
proven to be crucial to improve siRNA activity and efficacy along with the site-specific
characteristics of the target sequence. Variety of empirical rule sets and
computational algorithms is available to design potent and efficient siRNAs without
cross reactivity or off-target induction.
17
1.9 Targeted delivery of siRNA
siRNAs are sequence specific but have low stability, poor half-life, improper
biodistribution and cause unintended off-target induction of the host immune
response [Bridge AJ, Pebernard S et al. 2003; Reynolds A, Anderson EM et al. 2006]
at high concentration. Thus, they cannot cross the physiological barriers to initiate
successful gene silencing. Hence, delivering the siRNA into the target cell/tissue is a
major challenge. Most viral vectors are highly effective in delivering siRNAs but
immunogenicity and toxicity are the major risks [Barquinero J, Eixarch H et al. 2004].
Therefore, non-viral delivery systems, especially biodegradable cationic lipids and
polymers, have attracted much attention, as these systems do not have the risks as
associated with the viral systems and in addition have an efficient interaction with
anionic siRNA. To overcome the inherent limitations associated with siRNAs and to
enhance their therapeutic potential as well as systemic application against cancer,
there is a requirement of a type of specific targeted drug delivery system.
By combining the effective and well validated siRNA design strategies along with a
potential nanodelivery system, which enables tumor-specific active targeting, several
barriers like siRNA structural stability, RNAi activity, bioavailability and enhanced
permeability and retention can be optimized to achieve therapeutic significance.
Although several siRNA nanoparticles are effective in vitro, systemic delivery, in vivo
stability and tissue-specific targeting are the ideal features of an optimal nanodelivery
system. In addition it should refrain the induction of host immune response and its
related toxicity, which in most cases are the major obstacles in the development of
nucleic acid based therapeutics. Recent studies have demonstrated rapid
advancements in overcoming the delivery challenges in RNAi-based therapeutics
through functionalized hybrid nanoparticles.
1.10 Active targeting of ARMS
Developing multifunctional nanohybrid drug delivery systems functionalized with
specific surface ligands that are capable of delivering dual or multiple payloads to
cytoplasm and/or nucleus will be an ideal elixir to combat heterogeneous aggressive
tumors. Such a rational approach to co-target the driver signals responsible for
tumorigenesis and drug resistance may enhance proliferation inhibition and induce
18
apoptosis. Most sarcomas have some unique over expressed surface receptors like
IGF1R, PDGFR and VEGFR. However, the tumor heterogeneity adds complexity to
the therapeutic interventions, as in some cases the secondary mutations that develop
in due course of time determine the disease burden, response to therapy, relapse
and survival rate at the later stage. Combinatorial nano-drug delivery systems that
target the surface receptor/s (through ligand neutralization) to deliver the new
generation drugs (siRNA to aberrant signals, miR complementation and epigenetic
drugs for modulation and enhancing apoptosis) along with conventional
chemotherapeutic agents would open a new opportunities in treating aggressive
sarcomas. However, new generation multistage and multifunctional nanohybrid
delivery systems need to be intelligently engineered to overcome the cellular and
physiological barriers.
Members of receptor tyrosine kinase (RTK) family of cell surface receptors have
been characterized through monoclonal antibodies, small molecule inhibitors and
ligand-neutralizing agents. In myogenesis, IGF1R is essential for myoblast
proliferation, and IGF ligands induce a strong proliferative response in myogenic
precursors [Crose and Linardic 2011]. IGF1R was found to be up regulated in ARMS
by the PAX3-FOXO1 fusion gene [Cao L, Yu Y et al. 2010]. Increased expression of
IGF1R and its ligand IGF2 leads to an enhanced mitogenic forward signaling loop. In
RMS, PDGFR α and β receptors show increased expression [McDowell HP, Meco D
et al. 2007; McDermott U, Ames RY et al. 2009]. Also, PAX3-FOXO1 fusion has been
shown to activate transcription of PDGFRα [Epstein JA, Song B et al. 1998]. High
expression of PDGFRs is associated with decreased overall survival, implicating
PDGFR signaling in advanced stages of the disease [Blandford MC, Barr FC et al.
2006; Armistead PM, Salganick J et al. 2007].
Early microarray studies of RMS cell lines and tumors showed overexpression of
FGFR4 [Khan J, Wei JS et al. 2001]. FGFR4 is also a direct transcriptional target of
the PAX3-FOXO1 fusion protein [Cao L, Yu Y et al. 2010]. Amplification and
mutational activation of FGFR4 has been reported in RMS and promotes tumor
progression. Inhibiting FGFR4 expression decreased RMS tumor size, cell migration,
and metastasis [Taylor JC, Cheuk AT et al. 2009]. Therefore, FGFR4 is a tractable
therapeutic target [Li SQ, Cheuk AT et al. 2013]. VEGFR expression is down
19
regulated upon myogenic differentiation, suggesting that prolonged VEGFR signaling
negatively regulates differentiation [Germani A, Di Carlo A et al. 2003]. Inhibition of
VEGFR and its downstream signaling prevents expression of VEGF by RMS cells,
suggesting a feed-forward autocrine loop promoting proliferation [Kurmasheva RT,
Harwood FC et al. 2007]. Multiple isoforms of RTKs, their differential expression
pattern in a heterogenic tumor, resistance to the inhibitors and mutations in kinase
domain are the major limiting factors in targeting RTKs. Since PAX3-FOXO1
promotes the expression of FGFR4, IGF1R, MET, PDGFR and VEGFR1, targeting
these RTKs along with PAX3-FOXO1 could be a promising approach.
Another promising target in ARMS is the fetal type of the nicotinic acetylcholine
receptor (fAChR). During the neuromuscular junction development, a change from
the fetal type (α2βγδ) to the adult type (α2βεδ) of the AChR occurs, with replacement
of the γ-subunit by the ε-subunit [Beeson D, Vincent A et al. 1993]. The γ-subunit of
the fetal acetylcholine receptor (fAChR) is a specific cell surface target in
rhabdomyosarcoma [Gattenloehner S, Vincent A et al. 1998]. The expression of
fAChR is lost in the mature muscle after birth, but maintained in the thymic myoid
cells, in certain extraocular muscle fibers and in denervated muscle [Gattenlohner S,
Schneider C et al. 2002]. In rhabdomyosarcoma fAChRs are highly expressed,
distinguishing them from normal muscle. In addition, chemotherapy increased fAChR
expression on residual tumor cells in rhabdomyosarcoma patients. Human chimeric
fAChRδ-transduced T cells have shown specificity for fAChR of rhabdomyosarcoma
and mediated targeted cell lysis.
Due to this precise tumor specificity of fAChR antibody, such chimeric T cells have a
potential use in primary treatment and as a complementary approach to eradicate
residual tumor cells after chemotherapy [Gattenloehner S, Marx A et al. 2006].
Developing a functionalized nanodelivery system, targeting the fAChR along with
silencing PAX3-FOXO1 through siRNA could be an efficient approach to mitigate the
residual disease. In addition, RVG peptide derived from rabis virus glycoprotein is
capable to deliver siRNA via interaction with the acetylcholine receptor. Chimeric
RVG peptide fused with positively charged polyarginine peptide (9R) to enable siRNA
binding has been tested for transvascular delivery of siRNA [Kumar P, Wu H et al.
2007]. New generation functionalized lipid based nanohybrid delivery systems pose
20
several advantages in tumor targeting with enhanced permeability and retention
along with inter and intra tumoral distribution properties.
1.11 In vitro and in vivo model systems
Human RMS cell lines are extensively used to study alterations in molecular
pathways and their effects in vitro and in vivo in immune-deficient mice. Most studies
conducted so far have used only a few ERMS and ARMS cell lines. PPTP studies are
mainly conducted with ARMS cell lines Rh10, Rh28, Rh30, Rh30R, Rh41, Rh65 and
ERMS cell lines RD, Rh18 and Rh36. Other ARMS cell lines such as, RH4 and
ERMS cell lines such as, CCA and SMS-CTR are not routinely used. Many groups
aim to obtain in vitro engineered models of RMS through the introduction of distinct
gene alterations involved in RMS into recipient cells of different sources and species.
However, of these only few cases have induced tumorigenesis suggesting that there
might be additional mutations that involve other tumor suppressors in the pathway of
RMS development.
In addition, cells being cultured for several passages raise concern about possible
culture-induced changes or pre-selection that influences the experimental results.
Early passage cell lines may model the more rapidly proliferating cells in human
tumors and, thus, retain some of the properties of tumor stem cells. The effects of
anticancer drugs on cell lines should be considered not only with regards to the
induction of apoptosis, but also the induction of senescence or other pathways that
lead to host immune and inflammatory responses [Baguley B, Marshall E, 2008].
Future studies involving comparative genetic and epigenetic analysis of different cell
lines and tumor subtypes may provide a more substantial understanding of the
potential players in RMS development.
The regular in vitro culture platform for cancer drug discovery is the two-dimensional
cell monolayer grown on plastic dishes. However, the monolayer growth of
genetically defined, in vitro human cell models does not mimic the in vivo
environment of real human tumors. Cancers do not grow as a flat monolayer in
human body, but rather as a multicellular three-dimensional mass that interact with
neighbouring cells in three dimensions. As a result, cell-based in vitro assays that
measure proliferation, apoptosis, differentiation or cell death, fail to effectively predict
21
in vivo efficacy. Three-dimensional (ex vivo) cell culture models would be more
representative of physiological conditions in vivo that would represent various
aspects of signalling, gene expression, tumor angiogenesis, invasion, hypoxia and
metastasis [Yamada KM and Cukierman E 2007; Friedrich J, Seidel C et al. 2009].
Thus, the use of short term primary tissue culture and xenografts models would
better to reflect the originating tumor than immortalized cell lines [De Witt Hamer PC,
Van Tilborg AA et al. 2008].
The effect of drug in preclinical cancer models often fails to predict clinical results, as
traditional, subcutaneous xenografting of cell lines onto immunocompromised mice
produce tumors that fail to recapitulate key aspects of human malignancies such as
invasion and metastasis [Hait WN, 2010]. Though, genetically engineered mouse
(GEM) models evade many of these issues, the high cost and relatively low
throughput of preclinical studies are the obvious disadvantages associated with
them. The GEM models have normal immune systems and are genetically modified
for tumors to expand at sites similar to patients. However, the main target of systemic
therapies is metastatic disease, which many models of both types fail to exhibit
[Moreno L, Chesler L et al. 2011].
Xenografts have proven to be useful in studying the antiproliferative effect of most
chemotherapeutic agents. However, the importance of tumor microenvironment plays
an equal key role when identifying the novel drug targets. Thus, accurate modeling of
the tumor host stromal environment is critical, particularly with respect to
maintenance of an intact, native blood supply [Moreno L, Chesler L et al. 2011].
Though, the recent development of constitutive and conditional RNAi and non-
germline-based models [Heyer J, Kwong LN, 2010] are promising for drug target
validation and in vivo functional analysis, the defined limitations are yet to be
addressed. A comprehensive choice of selective GEM and xenograft models is
required based on the RMS type and intended target.
22
2. Objectives and aims
PAX3 and PAX7 transcription factors have distinct and overlapping functions in
various transcription activities. In case of fusion protein positive ARMS, both of the
transcription factors bind to FOXO1. The PAX3/7-FOXO1 fusion products have
altered expression, subcellular localization and function as compared to wild-type
PAX3, PAX7 and FOXO1. In addition, PAX3/7-FOXO1 fusion proteins are expressed
at higher levels than their wild-type PAX counterparts. PAX7-FOXO1 overexpression
results from gene amplification, while PAX3-FOXO1 overexpression occurs by copy
number-independent enhanced transcription [Davis RJ and Barr FG 1997]. These
fusion proteins activate transcription of target genes 10-100 fold more potently than
wild type PAX3 and PAX7 due to transcriptional gain of function [Bennicelli JL,
Edwards RH et al. 1996; Bennicelli JL, Advani S et al. 1999] and hence play a
necessary and fundamental role in ARMS tumorigenesis [Kikuchi K, Tsuchiya K et al.
2008].
Rationale
Without target-specific therapies for genetic abnormalities associated with RMS, the
survival rate will not improve [Crose LE and Linardic CM 2011] especially for high-risk
patients with poor prognosis. In addition, the treatment options are limited in the
advanced stages of RMS due to acquired drug resistance that limits the efficacy of
chemotherapeutics. Hence, an alternative approach, like down regulating the
PAX3/7-FOXO1 fusion was proposed in this study. Targeting PAX3-FOXO1 and
PAX7-FOXO1 was aimed by sequence specific efficient siRNAs. This will
categorically regulate the expression of oncogenic fusion protein and impact the
downstream targets like ALK, CB1R, CXCR4, FGFR4, IGF1R, MET and MYCN that
are involved in tumor development, maintenance, progression and metastasis.
PAX3-FOXO1 depletion anti-tumor effects provide proof-of-principle for therapeutic
strategies designed to abrogate PAX3-FOXO1 expression. Although additional
technological advances are required, siRNA/shRNA approaches targeting the
oncogenic PAX3-FOXO1 fusion may become a viable method for therapy [Olanich
ME, Barr FG, 2013]. Although target specific oncogenic chimeras is a viable
therapeutic approach, delivering the fusion-specific siRNAs though ARMS specific
23
targets like IGF1R, Integrin receptor and fetal acetylcholine receptor will enhance the
therapeutic efficacy due to synergy of dual targets.
Designing of specific siRNAs towards the fusion junction of PAX3-FOXO1 and PAX7-
FOXO1 without cross reactivity and off-target is essential to target the fusion
transcript. In addition, the designed siRNAs should maintain structural stability during
local or systemic delivery. In addition, specific delivery and targeting is another
important challenge. Together with the Department of Pharmaceutical Technology
and Biopharmaceutics, University of Freiburg, we have developed the following
specific aims:
1. Designing specific siRNAs for the fusion junctions of PAX3/7-FOXO1
2. In vitro validation of target specificity and effect of down regulation
3. Developing functionalized siRNA nanodelivery systems to target Integrin
receptor though RGD ligand
4. In vitro and in vivo validation of targeted siRNA-nanodelivery system
5. Evaluating the fusion target for its therapeutic potential by gene silencing
24
3. Materials
3.1 Cell culture
Product Supplier/Manufacturer
RPMI Media 1640 Gibco-Invitrogen Corporation, Karlsruhe
DPBS Gibco-Invitrogen Corporation, Karlsruhe
FCS Biochrom AG, Berlin
Penicillin/Steptomycin Gibco-Invitrogen Corporation, Karlsruhe
Trypsin Gibco-Invitrogen Corporation, Karlsruhe
Trypan blue Biochrom AG, Berlin
DMSO Sigma‐Aldrich Chemie GmbH
Puromycin Biochrom AG, Berlin
3.2 Cell lines
Cell line Type Source
RD Human ERMS Lab collection
RUCH2 Human ERMS B.Schäfer, Uni. Zurich
RUCH3 Human ERMS B.Schäfer, Uni. Zurich
RH30 Human ARMS, PAX3-FOXO1 Lab collection
RMS Human ARMS, PAX3-FOXO1 Lab collection
Rh28 Human ARMS, PAX3-FOXO1 Lab collection
RH4 Human ARMS, PAX3-FOXO1 P.Houghton, St. Jude
RH41 Human ARMS, PAX3-FOXO1 P.Houghton, St. Jude
RMS13 Human ARMS, PAX3-FOXO1 P.Houghton, St. Jude
CW9019 Human ARMS, PAX7-FOXO1 P.Houghton, St. Jude
RMZ-RC2 Human ARMS, PAX7-FOXO1 P.Houghton, St. Jude
3.3 Oligos and siRNAs
Product Supplier/Manufacturer
Scrambled siRNA Qiagen GmbH, Hilden
Cell death control siRNA Qiagen GmbH, Hilden
PAX3-siRNA1 Eurogentec SA, Seraing, Belgium
25
PAX3-siRNA2 Eurogentec SA, Seraing, Belgium
MET-siRNA Eurogentec SA, Seraing, Belgium
MYCN-siRNA Eurogentec SA, Seraing, Belgium
Chemically modified siRNAs Eurogentec SA, Seraing, Belgium
DssiRNAs 27/29nt Eurogentec SA, Seraing, Belgium
qPCR-Primers Eurogentec SA, Seraing, Belgium
Primer assay (for immune response) Qiagen GmbH, Hilden
System Biosciences, CA, USA
3.4 Transfection
Product Supplier/Manufacturer
HiPerfect transfection reagent Qiagen GmbH, Hilden
Attractene transfection reagent Qiagen GmbH, Hilden
RNase free water Sigma-Aldrich Chemie GmbH
3.5 RNA isolation
Product Supplier/Manufacturer
TRIzol reagent Invitrogen Corporation, Karlsruhe
RNeasy kit Qiagen GmbH, Hilden
Propanol Sigma-Aldrich Chemie GmbH
Glycogen Life Technologies, Kahlsruhe
DEPC treated water Promega GmbH, Mannheim
Chloroform Mallinckrodt Baker B.V., Deventer
Ethanol Merck KGaA, Darmstadt
3.6 Cell assays
Product Supplier/Manufacturer
CellTiter-Glo Promega GmbH, Mannheim
WST-1 Cell Proliferation Assay BioVision, Milpitas, CA, USA
Anexin V FITC ImmunoTools GmbH, Friesoythe
7-AAD eBioscience, Frankfurt
Trypan Blue 0.4% Life Technologies, Kahlsruhe
26
3.7 Immunotyping
Product Supplier/Manufacturer
Anti-CD4-PE antibody BD Biosciences, Heidelberg
Anti-CD8-FITC BD Biosciences, Heidelberg
Isotype control BD Biosciences, Heidelberg
3.8 qPCR
Product Supplier/Manufacturer
Quantitect Reverse transcription kit Qiagen GmbH, Hilden
Quantifast SYBR Green kit Qiagen GmbH, Hilden
3.9 Western blot
Product Supplier/Manufacturer
40% Acrylamide Carl Roth GmbH, Karlsruhe
Ammonium per sulphate Sigma - Aldrich Chemie GmbH
Dual colour precision marker Bio Rad, GmbH
N, N, N‟, N‟-Tetramethylethylenediamine-
TEMED
Sigma‐Aldrich Chemie GmbH
Polyvinylidene fluoride
(PVDF) membrane
Millipore, GmbH
BSA Sigma - Aldrich Chemie GmbH
Cell Lysis Buffer (10X) Cell Signaling Technology®, Boston
DPBS Invitrogen Corporation, Karlsruhe
Glycerol Carl Roth GmbH, Karlsruhe
Glycine AppliChem GmbH, Darmstadt
Methanol Prolabo chemicals ,VWR International
Ethanol Merck KGaA, Darmstadt
Sodium Chloride Carl Roth GmbH, Karlsruhe
Nonfat dreid milk powder AppliChem GmbH, Darmstadt
Protease Inhibitor Merck KGaA, Darmstadt
RIPA Lysis Buffer Merck KGaA, Darmstadt
27
SDS SERVA Electrophoresis GmbH
Tris Base Sigma - Aldrich Chemie GmbH
Tris HCl Carl Roth GmbH, Karlsruhe
Tween 20 Sigma‐Aldrich Chemie GmbH
-Mercaptoethanol Merck KGaA, Darmstadt
Bromphenol blue Sigma‐Aldrich Chemie GmbH
Antibody rabbit FOXO1 PolyClonal IgG Proteintech Group, Inc., Chicago
Antibody rabbit PAX3 PolyClonal IgG Proteintech Group, Inc., Chicago
Antibody goat anti rabbit IgG‐HRP Santa Cruz Biotechnology, Inc.
3.10 Utensils and consumables
Product Supplier/Manufacturer
15ml/50ml Falcons BD Biosciences, Erembodegem, Belgium
Costar 5ml, 10ml, 25ml Strippett Corning Incorporated, Corning, NY
Reaction tubes 1,5ml , 0,5ml Greiner Bio‐One GmbH, Frickenhausen
SafeGuard Filter Tips,1000μl, 200μl,
100μl, 20μl, 10μl
PegLab Biotechnologie GmbH, Erlangen
Cell culture flask 75cm2, 175cm2 BD Labware Europe, Le Pont De Claix,
France
Cell culture plates 6 well, 12 well, 24 well BD Labware Europe, Le Pont De Claix,
France
Cryoware freezing tubes, 1,8ml Nalgene Fisher Scientific GmbH,
Dreieich
Disposable cell scraper BD Biosciences, Heidelberg
96, 384 Well Reaction plate BioRad Laboratories, Hercules, GB
Biopur Safe‐Lock Reaction Tubes Eppendorf AG, Hamburg
Microseal PCR Plates Bio‐Rad Laboratories, Hercules, GB
Extra thick Filter Paper Bio‐Rad Laboratories, Hercules, GB
3.11 Instruments
Product Supplier/Manufacturer
C1000 Thermal Cycler CFX96/384 Real BioRad Laboratories GmbH, München
28
Time System
Molecular Imager ChemiDoc
XRS System
BioRad Laboratories GmbH, München
TransBlot SD Semidry Tranfer Cell BioRad Laboratories GmbH, München
Mini‐PROTEAN 3Cell BioRad Laboratories GmbH, München
1,5mm SDS gel cells BioRad Laboratories GmbH, München
All rage of micro pipettes Eppendorf AG, Hamburg
Eppendorf Thermomixer 5436 Eppendorf AG, Hamburg
Biofuge fresco Heraeus Thermo Fisher Scientific, Waltham
Mulitfuge 3S‐R Heraeus Thermo Fisher Scientific, Waltham
HERA Safe Heraeus Thermo Fisher Scientific, Waltham
HERA cell240 Heraeus Thermo Fisher Scientific, Waltham
NanoDrop ND‐1000 Spectrophotometer PegLab Biotechnologie GmbH, Erlangen
Axiovert 40C Microscope Zeiss Micro Imaging GmbH, Oberkochen
AxioCam ICc 1 Zeiss Micro Imaging GmbH, Oberkochen
Axiovert 200M Microscope Zeiss Micro Imaging GmbH, Oberkochen
AxioObserver A1 Zeiss Micro Imaging GmbH, Oberkochen
Tecan Sunrise Microplate reader Tecan, Mainz-Kastel
BD FACSCalibur Flow cytometer BD Biosciences, Heidelberg
3.12 Plasmid vectors
Product Supplier/Manufacturer
SureSilencing Qiagen GmbH, Hilden
iLenti siRNA expression system Applied Biological Materials Inc, Canda
29
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4. Methods
4.1 siRNA design
Due to the fusion of two transcription factors, the PAX-3FOXO1 and PAX7-FOXO1
need to be analyzed for the siRNA target accessibility especially based on the fusion
junction point without having any cross reactivity with any of the candidate genes
involved in the fusion. The sequences of siRNAs were analyzed through RNAfold and
Sfold for structural prediction of optimal secondary structure of the PAX3-FOXO1 and
PAX7-FOXO1 sequences with minimum free energy and thermodynamics properties
in order to confirm the target accessibility for different siRNA constructs. siRNAs were
designed based on the fusion junction.
The optimal secondary structure in dot-bracket notation with a minimum free energy
of -39.80 kcal/mol for PAX3-FOXO1 sequence is given below.
GUGUCAGAUCCCAGCAGCACCGUUCACAGACCUCAACCGCUUCCUCCAAGCACUGUACACCAA
AGCACGAUUCCUUCCAACCCAGACAGCAGCUCUGCCUACUGCCUCCCCAGCACCAGGCAUGGA
UUUUCCAGCUAUACAGACAGCUUUGUGCCUCCGUCGGGGCCCUCCAACCCCAUGAACCCCAC
CAUUGGCAAUGGCCUCUCACCUCAGAAUUCAAUUCGUCAUAAUCUGUCCCUACA
(((((((.....(((......)))..............((((.....)))).))).))))........................(((((......(((((..(((.......)))..)))))((((...))))(((........)))...
.((((...((.((((.................))))))....))))(((((......................)))))...)))))......
The free energy of the thermodynamic ensemble is -44.67 kcal/mol. The frequency of
the MFE structure in the ensemble is 0.04 %. The ensemble diversity is 61.73. The
centroid secondary structure in dot-bracket notation with a minimum free energy of -
12.60 kcal/mol is given below.
GUGUCAGAUCCCAGCAGCACCGUUCACAGACCUCAACCGCUUCCUCCAAGCACUGUACACCAA
AGCACGAUUCCUUCCAACCCAGACAGCAGCUCUGCCUACUGCCUCCCCAGCACCAGGCAUGGA
UUUUCCAGCUAUACAGACAGCUUUGUGCCUCCGUCGGGGCCCUCCAACCCCAUGAACCCCAC
CAUUGGCAAUGGCCUCUCACCUCAGAAUUCAAUUCGUCAUAAUCUGUCCCUACA
......................................((((.....))))............................................(((((..(((.......)))..)))))((((...))))((..........)).........
......................................................................................
Based on the base-pairing probabilities, the structure below was generated and
optimized for PAX3-FOXO1 mRNA to see the secondary structure accessibility for
different siRNA constructs.
31
A
B
C
32
Figure 4.1 Secondary structure prediction of the PAX3-FOXO1 target site. A. Minimal free energy
(MFE) secondary structure (left) and centroid secondary structure (right). B. Optimized structures. C.
specific target region of the PAX3-FOXO1 mRNA (left) and the DNA counterpart (right).
The optimal secondary structure in dot-bracket notation with a minimum free energy
of -409.10 kcal/mol for PAX7-FOXO1 is given below.
GGGCUCGGAUGUGGAGUCGGAACCUGACCUCCCACUGAAGCGCAAGCAGCGACGCAGUCGGA
CCACAUUCACGGCCGAGCAGCUGGAGGAGCUGGAGAAGGCCUUUGAGAGGACCCACUACCCA
GACAUAUACACCCGCGAGGAGCUGGCGCAGAGGACCAAGCUGACAGAGGCGCGUGUGCAGGU
CUGGUUCAGUAACCGCCGCGCCCGUUGGCGUAAGCAGGCAGGAGCCAACCAGCUGGCGGCG
UUCAACCACCUUCUGCCAGGAGGCUUCCCACCCACCGGCAUGCCCACGCUGCCCCCCUACCA
GCUGCCGGACUCCACCUACCCCACCACCACCAUCUCCCAAGAUGGGGGCAGCACUGUGCACC
GGCCUCAGCCCCUGCCACCGUCCACCAUGCACCAGGGCGGGCUGGCUGCAGCGGCUGCAGC
CGCCGACACCAGCUCUGCCUACGGAGCCCGCCACAGCUUCUCCAGCUACUCUGACAGCUUCA
UGAAUCCGGCGGCGCCCUCCAACCACAUGAACCCGGUCAGCAACGGCCUGUCUCCUCAGAAU
UCAAUUCGUCAUAAUCUGUCCCUACACAGCAAGUUCAUUCGUGUGCAGAAUGAAGGAACUGGA
AAAAGUUCUUGGUGGAUGCUCAAUCCAGAGGGUGGCAAGAGCGGGAAAUCUCCUAGGAGAAG
AGCUGCAUCCAUGGACAACAACAGUAAAUUUGCUAAGAGCCGAAGCCGAGCUGCCAAGAAGAA
AGCAUCUCUCCAGUCUGGCCAGGAGGGUGCUGGGGACAGCCCUGGAUCACAGUUUUCCAAAU
GGCCUGCAAGCCCUGGCUCUCACAGCAAUGAUGACUUUGAUAACUGGAGUACAUUUCGCCCU
CGAACUAGCUCAAAUGCUAGUACUAUUAGUGGGAGACUCUCACCCAUUAUGACCGAACAGGAU
GAUCUUGGAGAAGGGGAUGUGCAUUCUAUGGUGUACCCGCCAUCUGCCGCAAAGAUGGCCUC
UACUUUACCCAGUCUGUCUGAGAUAAGCAAUCCCGAAAACAUGGAAAAUCUUUUGGAUAAUCU
CAACCUUCUCUCAUCACCAACAUCAUUAACUGUUUCGACCCAGUCCUCACCUGGCACCAUGAU
GCAGCAGACGCCGUGCUACUCGUUUGCGCCACCAAACACCAGUUUGAAUUCACCCAGCCCAAA
CUACCAAAAAUAUACAUAUGGCCAAUCCAGCAUGAG
(((((.((((((((.(((((...))))).(((.((((...(((.....)))...)))).))))))))).((.(((((((.((((((((((((((.....((((((((...((........))..............(((.((...
)).))))))))).)).(((((..((.((((((((.((((((.((((((.....((((.(((((....)))))..)).))...))))))))).(((((.((.((.......((((((...))))))......)))).))))).)
)).))))).)))...))..)))))((.((.((((................((((((....))))))((((((..(((((...((((..(((((.((((..((((((.((.((...)).)).)))).))..)))).)))))..))
))....)).)))..))))))..)))))).))..)))))))))))))).))(((((...((((((.....((.((...)).)).....))))))....)))))...)))))))........((((((((...........((((...
...))))....(((((((.......)))))))((((((......))))))(((((....(((......)))((((((..(((((((...((((....))))...((((((((.((((....(((.(((....(((((.((((((
(..((...((.((((.......((((((.((((..........)))))))))).(((....)))((((.........))))..))))..))..))..)))))))...))))).....))))))...(((((.((.....(((....)
))((((((......)))))).....(((((((.((...)).)))))))....(((((((((((((.((((((((((((..(((((((....)))))))))(((((((.......)))))))....(((......))).....((
((((.....((((.(((.............))).)))).)))))).)))))).......)))).))))))..))).)))))))))))((......))..)))))))))))).............)))))))..))))))...)))
))..)))))))).)).))))).................(((.(((.....)))..)))..
The free energy of the thermodynamic ensemble for PAX7-FOXO1 is -427.46
kcal/mol. The frequency of the MFE structure in the ensemble is 0.00 %. The
ensemble diversity is 245.44 (due to the length of the sequence). The centroid
33
secondary structure in dot-bracket notation with a minimum free energy of -336.22
kcal/mol is given below.
GGGCUCGGAUGUGGAGUCGGAACCUGACCUCCCACUGAAGCGCAAGCAGCGACGCAGUCGGA
CCACAUUCACGGCCGAGCAGCUGGAGGAGCUGGAGAAGGCCUUUGAGAGGACCCACUACCCA
GACAUAUACACCCGCGAGGAGCUGGCGCAGAGGACCAAGCUGACAGAGGCGCGUGUGCAGGU
CUGGUUCAGUAACCGCCGCGCCCGUUGGCGUAAGCAGGCAGGAGCCAACCAGCUGGCGGCG
UUCAACCACCUUCUGCCAGGAGGCUUCCCACCCACCGGCAUGCCCACGCUGCCCCCCUACCA
GCUGCCGGACUCCACCUACCCCACCACCACCAUCUCCCAAGAUGGGGGCAGCACUGUGCACC
GGCCUCAGCCCCUGCCACCGUCCACCAUGCACCAGGGCGGGCUGGCUGCAGCGGCUGCAGC
CGCCGACACCAGCUCUGCCUACGGAGCCCGCCACAGCUUCUCCAGCUACUCUGACAGCUUCA
UGAAUCCGGCGGCGCCCUCCAACCACAUGAACCCGGUCAGCAACGGCCUGUCUCCUCAGAAU
UCAAUUCGUCAUAAUCUGUCCCUACACAGCAAGUUCAUUCGUGUGCAGAAUGAAGGAACUGGA
AAAAGUUCUUGGUGGAUGCUCAAUCCAGAGGGUGGCAAGAGCGGGAAAUCUCCUAGGAGAAG
AGCUGCAUCCAUGGACAACAACAGUAAAUUUGCUAAGAGCCGAAGCCGAGCUGCCAAGAAGAA
AGCAUCUCUCCAGUCUGGCCAGGAGGGUGCUGGGGACAGCCCUGGAUCACAGUUUUCCAAAU
GGCCUGCAAGCCCUGGCUCUCACAGCAAUGAUGACUUUGAUAACUGGAGUACAUUUCGCCCU
CGAACUAGCUCAAAUGCUAGUACUAUUAGUGGGAGACUCUCACCCAUUAUGACCGAACAGGAU
GAUCUUGGAGAAGGGGAUGUGCAUUCUAUGGUGUACCCGCCAUCUGCCGCAAAGAUGGCCUC
UACUUUACCCAGUCUGUCUGAGAUAAGCAAUCCCGAAAACAUGGAAAAUCUUUUGGAUAAUCU
CAACCUUCUCUCAUCACCAACAUCAUUAACUGUUUCGACCCAGUCCUCACCUGGCACCAUGAU
GCAGCAGACGCCGUGCUACUCGUUUGCGCCACCAAACACCAGUUUGAAUUCACCCAGCCCAAA
CUACCAAAAAUAUACAUAUGGCCAAUCCAGCAUGAG
(((((.((((((((.(((((...))))).(((.((((...(((.....)))...)))).)))))))))....(((((((.((((((((((((((.....((((((...)))).))....................((....))..
((((.(((..((((...........((((..((((((((................((.(((((....)))))..)).....((((((...(((((..........................................................
..........)))))..)).))))................((((((....))))))........))))))))..))))..............))))....))).))))((((.((.((((((((...)))))))))).........((
(((....)))))..)))).)))))))))))))).))(((((...((((((.....((.((...)).)).....))))))....)))))...)))))..........((((((((...........((((......))))....(((
((((.......)))))))((((((......))))))....((((.....))))....((((((..(((((((...((((....))))...((((((((.((((........(((....(((((.(((((((..((...((.((((
.......((((...((((..........))))..))))..(......).((((.........))))..))))..))..))..)))))))...))))).....)))......(((((........(((....)))((((((......)))
))).....(((((((.((...)).)))))))....(((((((((((((.((((((((((((..((((((......))))))))(((((((.......))))))).....................((((((......(.........
................)..)))))).)))))).......)))).))))))..)))).)))..)))))((......))..)))))))))))).............)))))))..))))))..........)))))))).)).))))).
................(((.(((.....)))..)))..
Based on the base-pairing probabilities, the structure below was generated and
optimized for PAX7-FOXO1 mRNA to see the secondary structure accessibility for
suitable siRNA construct.
34
A
B.1
B.2
35
Figure 4.2 Secondary structure prediction of the PAX7-FOXO1 target site. A. Minimal free energy
(MFE) secondary structure (left) and centroid secondary structure (right). B1 and B2 Optimized
structures. C. Specific target region of the PAX7-FOXO1 mRNA(left) and the DNA counterpart (right).
Figure 4.3 Interaction of various siRNA constructs at the target sites of PAX3-FOXO1 mRNA.
Although fusion junction specific siRNAs were selected out, every single selected siRNA candidates
were tested further for their target accessibility in silico to confirm the expected RNAi activity in vitro
and in vivo. In addition, the possible cross reactivity and immune stimulatory motifs of the optimal
candidates were checked independently. Empirical rule sets of Ui-Tei were opted for the best hits that
were further filtered by Reynold‟s and Amarzguioui‟s rule sets.
B
36
Figure 4.4 siRNA empirical rules based on the sequence positions and their interrelationship.
A. Positional preferences of the bases in siRNA proposed by empirical rules. B. The rule sets differ
themselves in selecting efficient siRNA candidates as only 3.7% of the siRNAs match with all three
rule sets. The siRNAs selected for PAX3-FOXO1 and PAX7-FOXO1 were sorted for further refinement
to match with all these three rule sets.
The following tools were used for the secondary structure analysis, sequence
analysis and siRNA design.
RNAFold: http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi
Sfold: http://sfold.wadsworth.org/cgi-bin/index.pl
Sfold-Srna: http://sfold.wadsworth.org/cgi-bin/srna.pl
siDirect 2: http://sidirect2.rnai.jp/
CLUSTALW: http://www.genome.jp/tools/clustalw/
Nucleotide BLAST: http://blast.ncbi.nlm.nih.gov/Blast.cgi
4.2 Primer design
The primers were designed by several online tools. Melting temperature (Tm) of the
primers was selected between 65 °C and 75 °C, and within 5 °C of each other. GC
content was opted up to 50%. Different primer couples developed were checked with
the target gene at different concentrations and optimized based on their Ct value
limits.
Two primer pairs were optimized for PAX3-FOXO1:
F: 5-AGACAGCTTTGTGCCTCCAT-3 R: 5-CTCTTGCCTCCCTCTGGATT-3
F: 5-ACCAGCTGTCGGAGACCTCTTA-3 R: 5-CTGTGGATTGAGCATCCACC-3
37
Two primer sets were optimized for PAX7-FOXO1:
F: 5-GGCTGGACGAGGGCTCGG-3 R:5-CATGGATGCAGCTCTTCTCCT-3
F: 5-CCGACACCAGCTCTGCCTAC-3 R:5-ATGAACTTGCTGTGTAGGGACAG-3
Figure 4.5 Validation of primer pairs by qPCR. A. Optimized primer pairs were checked at different
concentrations from 150, 100, 50, 10 and 1 ng by qPCR. Efficiency should be similar in both target
and reference gene. The regularity of the curves was checked by comparative delta-delta-Ct method.
B. Ct values for different primers were checked and higher Ct value pairs were not chosen.
The following tools were used for the primer design for the targets.
Primer Blast: http://www.ncbi.nlm.nih.gov/tools/primer-blast/
Primer 3 Plus: http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi
PrimerDesigner:http://www.lifetechnologies.com/de/de/home/life-science/sequencing/sanger-
sequencing/pre-designed-primers-pcr-sanger-sequencing.html
4.3 Cell culture
All ARMS and ERMS cell lines were cultured in RPMI-1640 medium supplemented
with 10% FCS and 1% Penicillin+Streptomycin at 37 °C in a humidified incubator with
5% CO2 concentration. Depending on the growth rate medium was replaced every
third or fourth day. Culturing ensued either in 75cm2, 175cm2 or in plates of 6, 12 or
24 wells. Depending on the growth density the cells were split every 4-5 days. Cells
were seeded into culture dish, when a confluence of 80-85% was reached using
trypsin/EDTA (0.05%/0.02% (w/v) in PBS) solution. All cell lines were checked
A B
38
routinely for mycoplasma contamination by PCR in regular interval. Biosafety level S1
and S2 were adopted throughout the experiment.
4.4 RNase free work environment
All RNA related work was done based on RNase free working procedures. All the tips
and tubes used were RNase free certified. The work bench, pipette and centrifuge
rotors were wiped with RNaseZap reagent before and after the experiment.
Diethylpyrocarbonate (DEPC) treated water was used to inactivate RNases in water
and buffers and to store the RNA samples. cDNA synthesis was performed mostly
after the total RNA isolation in order to avoid accidental RNA degradation. RNase
free work practice was also adapted in all transfection procedures.
4.5 siRNA Transfection by HiPerfect
Transfections of several Rhabdomyosarcoma cell lines with siRNA were done with
HiPerfect transfection agent. Different siRNA transfecting agents were tested for
optimal transfection efficiency with less toxicity for RMS cell lines. In addition, the
siRNA+transfection agent complex was also analyzed for the possible immune
induction with Rh30 cell lines to confirm optimal transfection and RNAi activity. Cells
were seeded on 24-well plates, using 20,000-25,000 cells per well. Within 24 hours,
the required cell density was achieved. To prepare the cells for the transfection the
media containing FCS and P/S was removed and replaced by RPMI media without
antibiotic (in a volume of 600 µl less the volume, which then was added through the
siRNA-transfection complex mix. Antibiotics were avoided in order to prevent any
influences on the transfecting agent-siRNA complex formation. Before seeding the
cells were put on synchronization for optimal intake of the siRNA.
Depending on the concentration, siRNA was mixed with 3–6 µl of HiPerfect. After
letting the transfecting agent-siRNA complex to form for about 5 minutes at room
temperature, the siRNA-transfection mix was added to the wells containing RPMI
media without antibiotics to get a total volume of 600µl. To ensure a reliable
dispersion of the siRNA the 24well plates were carefully pivoted for proper diffusion
throughout the well surface. The plates were kept in the incubator to enable the
siRNA to invade the cells for 6 hours. Afterwards the media with transfection complex
was replaced by RPMI media containing 10% FCS and 1% P/S to prevent the cells
39
from transfection induced cell death. Transfection was successful in most of the cell
lines within 6 hours. After 48 and 72 hours of incubation the cells were harvested to
extract the RNA or the protein.
4.6 Lipid-Protamine-siRNA nanoparticles
Liposome-Protamine-siRNA (LPR) naoparticles have been demonstrated to be an
effective delivery vehicle for siRNA among the lipid-based carrier systems [Chono et
al., 2008]. Cationic peptide protamine is complexed with siRNA and hyaluronic acid
to form a complex which is then coated with cationic lipids allowing for PEGylation of
the carrier surface and further modification for active targeting [Chen Y, Wu JJ et al.
2010]. Integrin αVβ3 is highly expressed in HUVEC and Rh30. RGD-modified
liposomal formulations of patupilone were effectively delivered to rhabdomyosarcoma
tumors [Scherzinger-Laude K, Schönherr C et al. 2013]. In this study, targeting
rhabdomyosarcoma integrin receptors through RGD based siRNA nanoparticles
specific to PAX3-FOXO1 fusion transcript was evaluated in vitro in different RMS cell
lines and in vivo xenograft model. These nanohybrid siRNA delivery systems were
developed and characterized at the Department of Pharmaceutical Technology and
BioPharmacy [Zimmer DY, 2013] as described below.
Liposomes were prepared by the film hydration method using a lipid film of DOTAP
and DOPE in a molar ratio of 1:1. Lipid films were prepared by dissolving the lipids in
chloroform followed by solvent removal in a vacuum centrifuge. Films were hydrated
with HEPES saccharose buffer for 30 minutes to obtain a liposomal dispersion with a
concentration of 40mM. The liposomes were treated with a sonication tip operated in
pulse mode (6 cycles of 30 sec) to reduce size and lamellarity of the vesicles. siRNA
and hyaluronic acid were mixed in 1:1 (w/w) ratio and diluted to a volume of 150 µL
with HS buffer. An equal volume of protamine solution (200 µg/mL in HS buffer) was
added drop wise, yielding a final ratio of siRNA/hyaluronic acid to protamine of 0.7
(w/w). The mixture was incubated for 10 minutes at room temperature to allow
complex formation. Addition of 40 µL of the preformed liposomes was followed by
incubation of the particles with mPEG-DSPE or RGD-/RAD-PEG-DSPE micelles at
60 °C for 1 h for surface modification via post-insertion technique. RGD-/RAD-PEG-
DSPE micelles were obtained by hydrating a lipid film of Mal-PEG-DSPE with the
respective peptide solution (1mg/mL) in a molar lipid/peptide ratio of 1:1 and
40
incubated for 10 hours. The amount of PEGylated lipid in the film was 15 mol%
related to the total lipid [Zimmer DY, 2013].
4.7 Transfection and treatment by LPR
Lipid protamine siRNA nanoparticles were made with scrambled siRNA and PAX3-
FOXO1 specific siRNA along with RGD targeting moiety and a non-targeted RAD.
Optimal concentration of 60nM siRNA was used for all the in vitro experiments. Along
with mock transfected control, RGD-Scr-LPR, RAD-P3F-LPR, RAD-Scr-LPR were
used as multiple controls in parallel with the targeted RGD-P3F-LPR. ARMS cell lines
were used as positive targets and ERMS cell lines were used as negative targets.
The efficacies of these particles on PAX3-FOXO1 target down regulation,
proliferation inhibition, apoptosis induction, inhibition of tumor initiation and tumor
growth inhibition were evaluated for a possible targeted therapy of alveolar
rhabdomyosarcoma. 20-40µg of siRNA concentration was used for the xenograft
treatment along with mock control.
4.8 RNA isolation by TRIzol method
The cells were prepared for the RNA extraction by TRIzol or enzyme digestion. After
washing the adherent cells twice with cold PBS they were trypsinized. Cells, which
were harvested in a tube after inactivating the trypsin with FCS containing media.
The media-cell-trypsin suspension was then pipetted up and down in the wells to
ensure a proper harvest and to separate the cell aggregates formed in the
inactivation process. The harvested cells were put into the centrifuge for 10 minutes
at 4 °C and 325xg-relative centrifugal force. The resulting pellet was washed with
PBS for two more times followed by another centrifugation step. In one step RNA
isolation, the cell pellet was re-suspended in PBS, which was left in the tube after
discarding the supernatant and transferred to a 1.5ml Biopur reaction tube. Later, the
suspension was carefully mixed with 1ml of TRIzol reagent by pipetting.
Trizol is a ready to use monophasic solution of phenol and the active ingredient
guanidine isothiocyanate, which is designed to isolate separate fractions of RNA,
DNA and proteins from cells [Chomczynski P, Sacchi N, 2006]. The guanidine
isothiocyanate is responsible for the cell disruption and inactivates RNases present in
the cells, while the phenol contained in the reagent is responsible to bring RNA, DNA
41
and proteins into solution. For RNA purification, the pH needs to be maintained
around 4, to retain the RNA in the aqueous phase. The 10 minutes incubation time
was followed by adding chloroform to each tube and vortexing this solution
thoroughly before placing the tubes into centrifuge at 4 °C for at least 15 minutes at
16060xg-force.
After centrifugation the aqueous phase at the top, containing the RNAs, was
transferred into a new RNase free Biopur tube containing Isopropanol and Glycin.
Isopropanol is important for the precipitation of the nucleic acid. This requires a
minimum concentration of monovalent cations to neutralize the charge on the nucleic
acid backbone to reduce the hydorphilicity of the RNA. Glycine is an inert co-
precipitant. The tubes were further centrifuged at 4 °C and 1606 g-force for 15min
after checking for a visible pellet. The supernatant was discarded and the pellet was
washed in 70% of ethanol. These steps were performed on ice, to enhance the
formation of RNA complexes to prevent the RNA from degradation. After
centrifugation for 5 minutes the ethanol was removed carefully and completely. The
pellet was air dried and later dissolved in DEPC water whereby the volume correlated
with the size of the pellet. Quantity and quality of RNA was detected with photometric
measurement and then stored at -20 °C.
4.9 RNA isolation by RNeasy mini kit
The RNeasy procedure combines the selective binding properties of a silica-based
membrane with the speed of microspin technology. A specialized high-salt buffer
system allows up to 100μg of RNA longer than 200 bases to bind to the RNeasy
silica membrane. The cells are lysed and homogenized in the presence of a highly
denaturing guanidine-thiocyanate–containing buffer, which immediately inactivates
RNases to ensure purification of intact RNA. Further, ethanol is added to provide
appropriate binding conditions, and the sample is then applied to an RNeasy Mini
spin column, where the total RNA binds to the membrane and contaminants are
efficiently washed away. High quality RNA is then eluted in 30-100 μl water. With the
RNeasy procedure, all RNA molecules longer than 200 nucleotides are purified. Total
RNA from the cell lines were purified using spin technology method.
42
4.10 RNA quantity and quality measurement
To detect the RNA concentration of a sample the absorbance of the nucleic acid
solution was detected via spectrophotometry by NanoDrop. The detection of the
optical density (OD) was measured at wavelengths of λ = 260 and λ = 280nm
(Equation 1).
nm
nm
OD
ODOD
280
260 Equation 1
40factor delutional][ 260 nmODml
gc
Equation 2
Equation 2 allows the calculation of the RNA concentration, while equation 1 results
in an item which is indicative of the quality. In NanoDrop standardized method, a
260/280 ratio between 1.8 to 2.0 is generally accepted as “pure”, as phenol absorb
strongly at 280nm, a ratio lower than 1.8 indicates an impurity, mostly caused by not
drying the RNA pellet properly before adding DEPC water.
4.11 cDNA Synthesis
The complementary DNA (cDNA) of the mRNAs in the samples was synthesized with
the Quantitect Reverse Transcription Kit from Qiagen, following the protocol of the
manufacturer. Similar to RNA isolation, RNase free tubes were used in cDNA
synthesis step. gDNA wipeout buffer was used to ensure the quality of isolated RNA.
This step was done to remove potential genomic DNA. DEPC water was used to refill
this solution to a total volume of 14µl. This premix was set into the Incubator at 47 °C
for two to three minutes and then put on ice. The remaining components of the Kit: 5x
Quantiscript RT Buffer, RT Primer Mix and Quantitect Reverse Transcriptase were
mixed in the ratio 4:1:1. This master mix was added to the RNA solution to reach a
total RNA concentration of 0.05µg/µl. After setting the tubes back into the incubator
at 47 °C for 15 minutes the synthesized cDNA was heated to 95 °C for three minutes
to inactivate the reverse transcriptase and cooled down to room temperature for
another 3 minutes before freezing it till further usage at -20 °C. Due to the method
used in nanodrop analysis, it is not possible to detect the cDNA concentration and
quality because the primers added with the master mix do interfere with the optical
density of the nanodrop instrument. Hence, the concentration of cDNA is assumed as
the concentration of RNA used in the reaction at 0.05µg/µl.
43
4.12 Quantitative real time polymerase chain reaction (qRT-PCR)
The qRT-PCR based analysis of the gene expression based on mRNA level was
used for the genes/transcripts of PAX3-FOXO, PAX3, FOXO1, MET, MYCN, ALK,
GAPDH and B-actin. GAPDH and B-actin were used as housekeeping reference
genes to enable the calculation of the % relative expression. RNase free water was
used as a negative control. The RNA, isolated from the cells via TRIzol which was
later reverse transcripted to cDNA was used to quantify the gene expressions by
qRT-PCR. QuantiFast SYBR Green PCR Kit of Quiagen was used for the
amplification measurement of 2.5µl respectively 12.5ng of cDNA. Due to faster
amplification in two step qRT-PCR, QuantiFast SYBR Green method was used over
other reagents. Ct values in late amplification cycles were not considered to minimize
false positive results.
Components of 2x QuantiFast Probe PCR Kit:
Component Features Benefits
HotStarTaq Plus
DNA Polymerase 3 min activation at 95ºC
Set-up of qPCR reactions at room
temperature
QuantiFast Probe
PCR Buffer
Balanced combination of
NH4+ and K+ ions
Specific primer annealing
ensures reliable PCR results
Unique Q-Bond additive
Faster PCR run times, enabling
faster results and more reactions
per day
ROX dye†
Normalizes fluorescent
signals on Applied
Biosystems and, optionally,
Agilent instruments
Precise quantification on cyclers
that require ROX dye. Does not
interfere with PCR on any real-
time cycler
Also contains dNTP mix (dATP, dCTP, dGTP, and dTTP).†
ROX dye is either present in the master
mix or as a separate solution. ROX based reference run was done only for initial assessments.
The PCR reaction was performed in a 384well plate on ice. The master mix for the
PCR consists of QuantiFast SYBR Green, forward + reverse primers and
RNase/DNase free water in varying ratios, depending on the primers.
44
PAX3-FOXO, PAX3, FOXO1, MET, MYCN, ALK, FGFR4, B-actin, GAPDH
Components Ratio
SYBR GreenI 10
Forward Primer 1-2.5
Reverse Primer 1-2.5
Rnase free Water 0-3
This master mixes were added to the cDNA to reach a total volume of 10µl per well.
The plate was afterwards carefully sealed with micro seal film, which should be kept
clean for precise measurement without any interference. After short centrifugation the
384well plate was set into the C1000 Thermal Cycler CFX38 Real-Time System.
The standard PCR – cycle protocol was used, consisting of the following phases:
1. Initial denaturation and activation of the enzyme: 15 minutes at
95 °C
2. Denaturation phase:
The denaturation phase is important to separate the
double – stranded cDNA, making an annealing of the
primers possible.
15 seconds at
95 °C
3. Annealing phase:
The adequate temperature to ensure specific primer
hybridization at the cDNA single strands.
30 seconds at
60 °C
4. Elongation phase:
A daughter strand is formed on each of the two original
cDNA strands, which serve as matrixes.
30 seconds at
72 °C
5. Melt curve:
The measurement of the melt curve proves the specific
primer annealing and elongation of only one target strand.
5 seconds at
65 °C
5 minutes at
95 °C
The phases 2, 3 and 4 are the actual cycling phases as those are repeated for 39
times according to the program template. The annealing temperature is an average
45
temperature calculated of the specific temperatures for all the primer pairs. This is an
uncommon method to save time and materials, and it does only work because the
primers annealing temperatures are close to each other. After the qRT-PCR run
some samples were randomly stained with GelRed Nucleic Acid Gel Stain and
loaded to a 2% agarose gel. The gel was made with and run in 1 x TAE buffer, at
100V voltage the amplified cDNA samples were electrophoretically separated. A 100
base pair DNA ladder was loaded and run simultaneously as a marker to see the
PCR product. To make a qualified statement, whether and in which quantity the
siRNA was able to down regulate its target mRNA, cells transfected with scrambled
siRNA in the analogous concentrations 40nm and 60nM parallel to the target siRNA
were used. Plain cells were tested as well, but not used as a control, as they would
not normalize for the effect resulting from the transfecting method and transfecting
reagent.
Using the relative gene expression analysis 2-ΔΔCT method ( Schmittgen TD and Livak
KJ 2008 ), all samples were checked for their B-actin expression (or GAPDH) in three
technical replicates as well. The average of the Ct values of the technical replicates
deducing the most discordant value was calculated for the gene of interest GOI
tC
and for the house – keeping gene HKG
tC . B-actin/GAPDH was used as endogenous
reference, in accord with the formula:
HKG
t
GOI
t
T
t CCC
(T - Target; GOI - Gene of interest; HKG - Housekeeping Gene)
Subsequently the ΔCtNC (negative control like scrambled siRNA) is used as a
calibrator:
NC
t
T
t
T
t CCC
The amount of target, normalized to an endogenous reference and relative to a
calibrator is given by the following equation:
TtC
targetAmount of
2
The Standard deviations were calculated in the following way
46
)1(
)( 2
n
CCSD
tt
22 )()( HKG
t
GOI
t
T
t SDSDCSD
22 )()( NC
t
T
t
T
t CSDCSDCSD
To prove the biological sample consistency the whole transfection experiment was
repeated for three times. The averages of all three biological replicates are shown in
the results as graphs. The significance level was set at 5% (0.05). This means that a
test of significance with a p-value lower than the significance level allows a rejection
of the null hypothesis and by association a reference of the result as statistically
significant.
4.13 Protein isolation
The adherent cells were washed with cold PBS twice in order to remove media and
the protein contaminations from used FKS. After that, all the steps were performed
on ice to protect the protein integrity and enhance the precipitation. After
centrifugation at 100xg force and 4 °C for 5 minutes the supernatant was removed
and carefully wiped off at a cellulose tissue to remove remaining supernatant. The
remaining cell pellet was carefully mixed with 1x Lysis buffer containing protease
inhibitor. Protease inhibitor stock was freshly added to the lysis buffer prior to the
use. Lysis buffer was mixed with the cells by pipetting to enhance faster cell lysis and
protein release. Later, the dilution was vortexed for three times at every 10 minutes
before setting it into the centrifuge at 16060xg (13,000 rpm with 1.5ml tubes) force
and 4 °C for 20 minutes. The protein lysate containing supernatant was transferred to
a new reaction tube and kept at -20 °C till further usage.
4.14 Protein concentration measurement
The concentration of the isolated proteins was measured by BioRad Protein assay,
which is a modified Lowry assay method. The quantification was made by means of a
standard column with gradient concentrations of BSA (bovine serum albumin)
(0μg/μl; 0.25μg/μl; 0.5μg/μl; 0.75μg/μl; 1.0μg/μl; 1.5μg/μl; 2μg/μl). This gradient of
protein concentration was measured always parallel to the protein samples of the
47
transfected and control cells. 5μl of every sample as well as the BSA samples were
prepared as duplicates and complimented with 2500μl of a premix of Reagent A and
Reagent S in a 1:20 ratio. After adding additional 200μl of reagent B the plate was
incubated at room temperature under constant shaking for 15 minutes. The
absorbance was subsequently measured at 750nm in the spectrophotometer. Taking
the absorbance of the BSA gradient and the standard graph best fit, the analogous
concentrations of the samples were calculated.
4.15 Western Blot
Denaturing one dimensional electrophoresis was performed to resolve the proteins
based on their molecular weights. The proteins were boiled in 2x (or) 6x-Lämmeli
depending upon the expression levels of proteins to be investigated prior loading.
Lämmeli buffer contains 0.1% sodium dodecyl sulphate, an anionic detergent that
overcomes weak, non-covalent interactions. Strong covalent bonds are disturbed by
boiling the samples at 95° C for 5min. Disulphide bonds that preserve the tertiary
structure of proteins are reduced by supplementing DTT or β-mercaptoethanol with
Lämmeli buffer.
To prepare two 10% SDS-PAGE gels that contain a stacking gel and separating gel
the following components are mixed and poured.
10% - Separation gel
5% - Stacking gel
3ml of deionised H2O 3.8ml of deionised H2O
6ml of separation gel buffer 5ml of stacking gel buffer
3ml acrylamide / bisacrylamide 1.2ml of acrylamide / bisacrylamide
120µl 10 % APS 100µl 10% APS
15µl TEMED 15µl TEMED
After solidification the proteins were loaded onto the wells up to a maximum volume
of 30µl per well. The gel was allowed to run at 70V for 30min till the dye front reaches
the border, which separates the stacking and separating gel. Then the proteins were
48
separated by running the gel at 30mA for at least 120min till the dye front reaches the
bottom of the gel. Dual colour protein marker from Bio-Rad was used as a molecular
weight marker. Once the run was over, the gel was washed in transfer buffer.
Proteins were transferred to a PVDF membrane, which was washed already with
methanol and transfer buffer for 40min at 12V in a semidry transfer. After the
completion of transfer, the membrane was washed with wash buffer once and
blocked with 5% BSA prepared in wash buffer on a shaker. This is to avoid unspecific
binding of antibody to the membrane.
After blocking at room temperature for 1hr the membrane was washed three times
with wash buffer for 10min each time. After washing, the membrane was incubated
with the chosen primary antibody for 1hour at room temperature. To remove excess
antibody, the membrane was washed with wash buffer for three times. After washing,
the secondary antibody coupled with horseradish peroxidase was added at a dilution
of 1:10000 and incubated for 30 minutes. After removing excessive secondary
antibody, 1ml of ECL substrate A and substrate B was added to the membrane to
detect horseradish peroxidase activity. The luminescent signal was detected with Fuji
super Rx-X-ray film.
4.16 Proliferation inhibition
Tetrazolium salts are used extensively in cell proliferation and cytotoxicity assays in
drug discovery and optimization experiments. Tetrazolium salts are reduced
metabolically into colored formazans by the enzymes of the endoplasmic reticulum.
Mostly, MTT assay is widely used in cell proliferation and cytotoxicity assays. The
cellular reaction of MTT is associated with the reduced pyridine nucleotides NADH
and, to a lesser extent, NADPH. Here, succinate is a weak electron donor for
mitochondrial MTT reduction. New tetrazolium salt assays like WST-1 uses
intermediate electron acceptors to facilitate reduction. Unlike MTT, WST-1 is
efficiently reduced by NADH and NADPH as their reduction involves superoxide.
Quick Cell Proliferation WST-1 assay was used in accessing the inhibition of cell
proliferation. The reduction of light red WST-1 to dark red formazan (Figure 4.6) is
directly proportional to the number of living and proliferating cells which can be
quantified by multi-well micro titer plate reader by measuring the absorbance of the
49
dye solution at 440-450nm. In addition, this assay correlates well with the 3H-
thymidine incorporation assay.
Figure 4.6 Reduction of WST-1 into Formazan. Electrochemical reaction of WST-1 reduction is
faster than MTT and XTT. The color formation can be measured after 30 minutes of the reaction.
The lyophilized WST reagent was dissolved into 5ml with the electro coupling
solution (ECS). Aliquots of 1ml were prepared in light protecting black tubes. These
aliquots were stored at –20 °C. For each experiment 5x103 cells per well were
seeded in 96-well plates. After 24 hours, RPMI-1640 media was added to each well.
After 4 hours of settling time cells were transfected at a concentration of 60nM siRNA
per well with different LPR formulations along with mock transfected control cells.
Media alone was used as a blank control. The effect of target down regulation on
proliferation inhibition was analyzed at 24, 48 and 72 hours.
Prior to the reading, 10μl per well WST reagent was added to each well without
introducing any bubbles to the wells. After 45 minutes to one hour of incubation, the
plates were shaken for a minute and the readings were taken at 450nm using a micro
plate reader for the control, treated and untreated wells. Reference wavelength
650nm was used to cross validate the experiment. 10μl of the Stop Solution was
added for stable readouts. All the plates were protected from direct light after the
addition of WST-1. Unlike MTT, there was no toxicity observed that has interfered the
readouts.
50
4.17 Apoptosis induction
Since the fusion transcript is the driving factor for alveolar rhabdomyosarcoma
tumorigenesis, the effect of apoptotic induction upon target down regulation was
analyzed with HiPerfect based siRNA transfection as well as with LPR particles.
Damage of plasma membrane of the treated cells were measured by Annexin V
based assay along with 7-AAD. In apoptotic cells, the membrane phospholipid
phosphatidylserine (PS) is translocated from the inner to the outer leaflet of the
plasma membrane, thereby exposing the membrane to external cellular environment.
Annexin V is a 35-36 kDa Ca2+ dependent phospholipid-binding protein that has a
high affinity for phosphatidylserine and binds to cells with exposed PS. Annexin V
may be conjugated to fluorochromes like FITC. Since externalization of PS occurs in
the earlier stages of apoptosis, Annexin V coupled with FITC can identify apoptosis at
an earlier stage.
Staining with Annexin V is typically used in combination with a vital dye such as 7-
Amino-Actinomycin (7-AAD) to identify early apoptotic cells (7-AAD negative,
Annexin V positive). Viable cells are negative for both Annexin V and 7-AAD. Early
apoptotic cells are positive for Annexin V but negative for 7-AAD. Late apoptotic or
dead cells are positive for both. Annexin V+7-AAD assay does not differentiate
between cells that have undergone induced apoptotic death versus cells died as a
result of a necrotic pathway or due to any other damage (Figure 4.7-4.9). 3x104 cells
per well were seeded in 24-well plates. After 24 hours, cells were transfected at a
concentration of 60nM siRNA+LPR per well. The effect of target down regulation on
apoptosis induction was assessed after 48 and 72 hours by double-staining by flow
cytometery. For HiPerfect based transfection, 40nM siRNA was used for the
optimization studies.
51
Figure 4.7 Control Rh30 cells after 48 hours of mock transfection. Unstained control Rh30
(sample id: 0.001) has not shown any cell death but stained samples have shown un-induced cell
death induction at the upper right quadrant (sample id: RH30-0.002 and 0.003). Such an un-induced
population was observed in the range of 7-11%.
52
Figure 4.8 Treated Rh30 cells after 48 hours of transfection with P3F-siRNA+HiPerfect (40nM).
Down regulation of PAX3-FOXO1 enhanced apoptotic induction up to 50% (sample id: RH30-T.005
and .006).
Figure 4.9 Treated Rh30 cells after 72 hours of transfection with P3F-siRNA+HiPerfect (40nM).
Down regulation of PAX3-FOXO1 enhanced apoptotic induction with lower efficiency. (sample id:
RH30-T.007 and .008).
53
4.18 Transfection of SureSilencing shRNA clones
SureSilencing shRNA plasmids were designed for scrambled siRNA and the siRNAs
at position 199 and 200. Along with these constructs, empty vector was also used as
an additional control. This vector expresses a short hairpin RNA under U1 promoter
with a selective marker of puromycin resistance and/or GFP gene. Puromycin
selection permits the selection of stably transfected Rh30 cells. GFP helps to
estimate transfection efficiencies, tracks transfected cells by fluorescence microscopy
and permits FACS-based enrichment of transiently transfected cells (Figure 4.10).
Figure 4.10 SureSilencing plasmid with GFP. Selected segments of validated siRNA 27/29mer
were cloned at shRNA insert site. Scrambled clone and empty vector were used as controls.
Rh30 cells were allowed to grow 35-45 % confluence in 500µl RPMI media with FKS
for 24 hours in 24 well plates. 1 μg/μl concentration of each shRNA plasmid was
mixed with 3µl of Attractene transfection reagent along with 60µl of plain RPMI
media. 15 minutes incubation was given to this mix for the complex formation. This
mixture then was added into the wells containing cells and normal growth medium.
For proper dispersal of shRNA-Attractene complex, the plates were mixed gently.
The plates were incubated at 37 °C in a CO2 incubator for 48 hours. After transfection
the cells were re-plated at a low density (<10% confluence) along with fresh medium
54
containing 10µg/ml puromycin. Untransfected cells were killed by puromycin
selection. Media was replaced every two days and the cells were re-plated every six
days. The stable transfectants of Rh30 were obtained after third cycle of re-plating.
The stable transfectants of empty vector, scrambled vector, siRNA-199 and siRNA-
200 were stored at -70 oC in DMSO-FKS vials.
4.19 Transfection of iLenti H1/U6 DssiRNA expression system clones
iLenti expression system has H1 and U6 promoters with dual selection markers. The
long dicer substrate siRNS (DssiRNA) coding sequences can be cloned under these
promoters. Unlike shRNA, the long DssiRNA is directly transcribed from these
promoters. These convergent promoters avoid hairpin loop structure design and
unwanted processing of shRNA by host machinery. The unique single BbsI restriction
enzyme site in the multiple cloning site of this vector allows efficient, directional
cloning of siRNA target sites, where one strand comes from H1 and another strand
from U6 promoter (Figure 4.11). GFP selection along with puromycin enrichment is
possible to make stable clones. The GFP reporter gene incorporated under the CMV
promoter enables simultaneous tracking of expressed siRNAs in vitro and in vivo.
DssiRNAs of position 199, 200, 202, 205 and scrambled were cloned at the
restriction site. Empty vector was also used as an additional control. iLenti vectors
were transfected into Rh30 cells by Attactene transfecting agent. The selection
process is similar to that of SureSilencing shRNA vector transfection. Unlike shRNA
vectors, iLenti vectors were enriched within two weeks with one cycle time lesser.
The stable transfectants were stored at -70 oC in DMSO-FKS vials. Although the
iLenti vectors can be used for lentiviral based transduction of the cloned DssiRNA,
only puromycin enrichment based stable transfectants were selected.
55
Figure 4.11 iLenti H1/U6 DssiRNA expression system. iLenti vector allows direct transcription of
long siRNAs without loop structures.
4.20 In vivo Chick Chorioallantoic Membrane (CAM) assay
The CAM is composed of a multilayer epithelium, ectoderm at the air interface,
mesoderm (or stroma) and endoderm at the interface with the allantoic sac [Valdes
TI, Kreutzer D et al. 2002]. In addition, CAM contains extracellular matrix proteins
(ECM) such as fibronectin, laminin, collagen type I and integrin ανβ3, which mimics
the physiological cancer cell environment [Giannopoulou E, Katsoris P et al. 2001].
Fertilized White Leghorn chick eggs were incubated at 37 °C with 80% relative
humidity. At day 6 the egg shells were cut precisely to make a window. A tiny plastic
ring was inserted on the CAM membrane. The shell was then closed with parafilmM
along with cellotape. At day 12, one million cells were loaded on the plastic ring well
and ensured the contact with the CAM. After loading control and test cells, the eggs
were incubated for another 5 days. The growth of the tumor was observed from 17th
day onwards. At day 20-21 the tumors were removed and stored in tissue freezing
medium at LN2.
56
4.21 Experimental animals
Immunodeficient Fox Chase SCID/Beige mice with an average weight of 18.5 grams
were used for all the Xenograft experiments. This mouse genotype was developed by
an intercross of C.B-17 SCID/SCID to C57BL/6 bg/bg mice [Greenwood JD and Croy
BA 1993]. The mouse strain possesses both autosomal recessive mutations SCID
(Prkdcscid) and beige (Lystbg) and are severe combined immunodeficient. The beige
mutation results in defective natural killer (NK) cells. The first two batches of mice
were obtained from Charles River. The last two batches were obtained from animal
breeding facility of ZKF. Each mouse was tested for the CD4/8 count before and after
the experiment. The immune cell population was checked by anti-antibodies of CD4-
PE and CD8-FITC along with mouse isotype immunoglobulins. The immune cell
population was calculated by the total count with CD4/8 subtracted by the value of
total mouse isotype count by flow cytometry (Figure 4.12).
Figure 4.12 Overlay of flow cytometry readings of CD4 and CD8 (AK) along with mouse isotype
reading (ISO). Although the mice are SCID, due to leakiness of the mutation, few mice have shown
higher CD4/8 counts (mouse id: 143) beyond the accepted limit of 10%.
5-6 week old immune deficient female mice were used in all batches. All the mice
were screened for the immune cells before and after the experiment. Only those mice
with no or low immune cells were taken for further experiments. Mice with higher
immune cell count were sacrificed. 20×106 Rh30 cells were grafted by subcutaneous
57
injection into the lower back, right flank region to induce Xenograft tumor. All animals
were sacrificed at around 1500mm3 tumor size. Body weight and fecal consistency
were monitored at regular intervals throughout the experiment. Animal experiments
were performed using protocols and conditions approved by the animal care and use
committee at Freiburg University Medical Center 35-9185.81/G-12/20.
4.22 In vivo inhibition of tumor initiation
The effect of LPR nanoparticle mediated PAX3-FOXO1 down regulation on inhibiting
the tumor initiation was analyzed by simultaneous grafting of Rh30 cells followed by
tail vain injection of LPR particles. The grafted cells were allowed to settle for 90
minutes prior to tail vain injection. The mice were divided in five groups of 8-10
animals. One group was treated with RNase-free water, the others with LPR particles
prepared with P3F or scrambled siRNAs and targeted with RGD or RAD,
respectively. For all the groups, except the water control group, the administered
siRNA concentration was 1 mg/kg bodyweight. Administration was repeated twice on
days 3 and 5 after the first injection. The tumor size was monitored every 3-6 days
after the third dose. When the tumor sizes reached 1500mm3 the mice were
sacrificed.
4.23 In vivo tumor growth inhibition
Effective tumor targeting and delivery capabilities of LPR particles and the impact of
PAX3-FOXO1 down regulation was accessed after generating the tumor xenograft up
to the size of 250mm3. The animals were treated with tumor targeted P3F-RGD-LPR
along with Scr-RAD-LPR, Scr-RGD-LPR and P3F-RAD-LPR. The mock water control
was avoided as there was no significant difference found among the control groups.
20 and 40µg concentration (1 and 2mg/kg body weight) of siRNA-LPR particles were
used. All the animals were given three doses in the interval of three days. The tumors
were measured periodically.
4.24 In vivo LPR tolerance
All the mice were weighed in the interval of every three days to ensure the possible
side effect of LPR in weight loss/gain. The fecal consistency was checked randomly
in every group. Tail vain blood analysis was done initially. At the final stage, blood
was collected by cardiac puncture under anesthesia. Collected blood samples were
58
used to check the total count, CD4/8 immune cells, aspartate amino transferase
(AST) and alanine amino transferase (ALT) (for liver function), creatinine and urea
(for kidney function) measurement. All these tests were done at ZKF animal facility.
4.25 Cell viability
Trypan blue exclusion assay was performed to determine cell viability after
transfection. Cell viability was calculated as the number of viable cells divided by the
total number of cells within the grids on the hemacytometer. To ensure the healthy
log phase 95% viability was set as a cut-off. In addition, CellTiter-Glo viability assay
was also performed to cross verify the viable count method as this method detect
metabolically active cells based on quantification of ATP. After transfection in 96 well
plate, 100µl of CellTiter-GLo reagent was added to mock control cells along with
transfected cells. The plates were kept on shaker for 2 minutes to ensure proper
mixing and cell lysis. After 10 minutes incubation, the plates were read two times in
order to confirm the stable luminescent signals.
4.26 Interferon response detection
Primer assay was performed to detect siRNA and/or siRNA+carrier induced non-
specific inflammatory responses. Induction of interferons may affect metabolic
expression levels of the cell and can interfere the outcome of gene silencing
experiment. Relative expression levels were checked for IFNB1, IFITM1, IL61, MX1,
OAS1, OAS2 and STAT1SG. Along with mock and scrambled transfected cells, the
test siRNA and LPR particles were evaluated by qRT-PCR.
4.27 Quality control and statistical analysis
All the cell lines were tested for mycoplasma before and after the experiments.
Graphs and Statistical analyses were carried out with GraphPad Prism Version 6
(GraphPad Software, CA). The data were analyzed using one way ANOVA among
the groups. Between two groups, only unpaired t-test was performed (P values <
0.05 were considered statistically significant; *< 0.05, ** < 0.01, *** < 0.001, **** <
0.0001).
59
5. Results and Discussion
5.1 siRNA design
Designing target specific siRNAs is a crucial step, especially for the fusion targets of
two different transcription factors. The siRNA need to react only at the specific
junction point of the translocation of PAX3-FOXO1. Sequence specificity of the
siRNA is very stringent, as even a single base pair mismatch between the siRNA and
its target mRNA dramatically reduces the efficacy of silencing. In addition, due to
partial homology, there is a possibility that the siRNA may cross react with
unintended mRNA transcripts, a process called off-target effect. The incidence of this
nonspecific targeting is dependent on the concentration of the siRNA, with a higher
concentration leading to a greater off-target effect. This is a major barrier to the
success of effective siRNA design and therapeutic gene silencing. Using sub
nanomolar concentrations of siRNAs minimizes off-target effects [Jackson AL, Bartz
SR 2003; Persengiev SP, Zhu X et al. 2004] but however, compromises the efficacy
of gene silencing due to faster intracellular degradation.
Various online software tools exist, which try to find an effective siRNA for the query
target mRNA sequence. These tools are based on siRNA design principles proposed
by several groups like Ui-Tei (2004), Reynolds (2004), Amarzguioui (2004) and
Tuschl (2006). But, these rules themselves are a result of limited data validation
without considering rare oncogenic fusion targets like PAX3/7-FOXO1. Hence, the
tools designed with the help of these empirical rules cannot be claimed to be effective
for most of the translocation fusion targets like PAX3/7-FOXO1. An effective
algorithm has to combine different rule sets and align them with physico-chemical
properties of siRNA and its functional mechanism inside the cell to avoid the flaws in
the design and enhance its efficacy. In addition, that would reduce the siRNAs cross
reactivity and non-specificity, filter out off-targets and yield refined siRNAs which are
highly efficient in degrading the target mRNA.
Most computational algorithms designed for making specific and efficient siRNA with
minimized or no off-target effects are not completely effective as they produce more
false positives as compared to true positives. As a consequence, varying results are
produced for the same input sequence. Hence, all the factors related to the off-target
60
activity have to be taken into the consideration in designing a better algorithm by
combining the goodness of rules and checking all the responsible factors. We have
taken set of rules based on frequently occurring patterns in the already existing
validated siRNAs. Along with the rules, we have applied several selection filters to
enhance the predictability of the siRNA effectiveness. The rules generated from
Apriori have been used to train the Support Vector Machine using entire siRNA data
in order to classify any unseen siRNA into effective or non-effective against the fusion
target, but not the individual genes of the translocation. To filter off-target effects, the
siRNA predicted as effective by the SVM were BLASTed with online databases
Unigene and Refseq. Also, the basic biological constraints like GC%, AU differential
frequencies, immune stimulatory motif screen, target accessibility of the secondary
structure have been applied to screen out the most effective and specific siRNAs for
the PAX3-FOXO1 and PAX7-FOXO1 (Figure 5.1).
Figure 5.1 Selection criteria algorithm for the siRNA candidates.
Parse the sequence generating many siRNAs (n)
P3F/P7F sequence
AUGCAUGCAUGC
Filter (Criteria A-U
Differential)
Filter
(Criteria GC %)
Filters (Criteria Remove sequences with Poly
NNNN)
Predict the output class label for these siRNAs using
already trained SVM model (*)
BLAST with local database
RefSeq and Unigene
Output the final
siRNAs left
61
Such analysis was performed for both 21-mer as well as 27-mer dicer substrate
siRNAs. The flow diagram (Figure 5.1) depicts the important steps in the selection
criteria used. The combined empirical rules of Amarzguioui, Reynolds and Ui-Tei
were taken into consideration for selecting the best fit for 21-mer siRNAs as well as
27/29-mer DssiRNAs. Although certain most effective siRNAs predicted by this
method integration, they were found fully at the target sequence region of either
PAX3/7 or FOXO1 but not at the fusion junction point. Such candidates were omitted
as there will be a cross reaction due the target accessibility. Both PAX3-FOXO1 and
PAX7-FOXO1 transcripts are devoid of splice variants, the fusion target could be a
perfect target for sequence specific gene silencing for siRNA mediated transient
silencing as well as shRNA/siRNA expression based long term silencing.
5.1.1 Designing 21-mer siRNA
PAX3-FOXO1 fusion junction sequence details were retrieved from GenBank ID:
U02368.1 (Human), and GenBank ID: AF178854.1 (Mouse). The below (partial)
sequence in red indicates PAX3 region and blue FOXO1 region. Highlighted area (in
yellow) is the fusion junction point.
PAX3………GTGTCAGATCCCAGCAGCACCGTTCACAGACCTCAACCGCTTCCTCCAAGCACTGTA
CACCAAAGCACGATTCCTTCCAACCCAGACAGCAGCTCTGCCTACTGCCTCCCCAGCACCAGGC
ATGGATTTTCCAGCTATACAGACAGCTTTGTGCCTCCGTCGGGGCCCTCCAACCCCATGAACCCC
ACCATTGGCAATGGCCTCTCACCTCAGAATTCAATTCGTCATAATCTGTCCCTACA.........FOXO1
PAX7-FOXO1 fusion junction sequence details was retrieved from GenBank ID:
HQ824715.1. In the below sequence red indicates PAX7 region and blue FOXO1
region. Highlighted area (in yellow) is the fusion junction point.
PAX7………GGGCTCGGATGTGGAGTCGGAACCTGACCTCCCACTGAAGCGCAAGCAGCGACGC
AGTCGGACCACATTCACGGCCGAGCAGCTGGAGGAGCTGGAGAAGGCCTTTGAGAGGACCCAC
TACCCAGACATATACACCCGCGAGGAGCTGGCGCAGAGGACCAAGCTGACAGAGGCGCGTGTG
CAGGTCTGGTTCAGTAACCGCCGCGCCCGTTGGCGTAAGCAGGCAGGAGCCAACCAGCTGGCG
GCGTTCAACCACCTTCTGCCAGGAGGCTTCCCACCCACCGGCATGCCCACGCTGCCCCCCTACC
AGCTGCCGGACTCCACCTACCCCACCACCACCATCTCCCAAGATGGGGGCAGCACTGTGCACCG
GCCTCAGCCCCTGCCACCGTCCACCATGCACCAGGGCGGGCTGGCTGCAGCGGCTGCAGCCG
CCGACACCAGCTCTGCCTACGGAGCCCGCCACAGCTTCTCCAGCTACTCTGACAGCTTCATGAA
TCCGGCGGCGCCCTCCAACCACATGAACCCGGTCAGCAACGGCCTGTCTCCTCAGAATTCAATT
CGTCATAATCTGTCCCTACACAGCAAGTTCATTCGTGTGCAGAATGAAGGAACTGGAAAAAGTTC
62
TTGGTGGATGCTCAATCCAGAGGGTGGCAAGAGCGGGAAATCTCCTAGGAGAAGAGCTGCATCC
ATGGACAACAACAGTAAATTTGCTAAGAGCCGAAGCCGAGCTGCCAAGAAGAAAGCATCTCTCCA
GTCTGGCCAGGAGGGTGCTGGGGACAGCCCTGGATCACAGTTTTCCAAATGGCCTGCAAGCCCT
GGCTCTCACAGCAATGATGACTTTGATAACTGGAGTACATTTCGCCCTCGAACTAGCTCAAATGC
TAGTACTATTAGTGGGAGACTCTCACCCATTATGACCGAACAGGATGATCTTGGAGAAGGGGATG
TGCATTCTATGGTGTACCCGCCATCTGCCGCAAAGATGGCCTCTACTTTACCCAGTCTGTCTGAG
ATAAGCAATCCCGAAAACATGGAAAATCTTTTGGATAATCTCAACCTTCTCTCATCACCAACATCAT
TAACTGTTTCGACCCAGTCCTCACCTGGCACCATGATGCAGCAGACGCCGTGCTACTCGTTTGCG
CCACCAAACACCAGTTTGAATTCACCCAGCCCAAACTACCAAAAATATACATATGGCCAATCCAGC
ATGAG………FOXO1
For the in silico analysis from secondary structure analysis to siRNA design
prediction the above sequences were used. The resulted siRNA candidates were
further checked for:
1. thermodynamic asymmetry for the stability
2. selected empirical rules and guidelines to avoid unwanted motifs
3. known immune-stimulatory motifs to avoid inflammatory response
4. homology analysis for the precise specificity and to avoid cross reactivity
5. seed region frequency to minimize off-target effects by eliminating common
seed regions
6. siRNA target site secondary structure predictions to confirm functional mRNA
structures from non-functional sites, capable of forming an A-helix for correct
positioning of the scissile phosphate bond for cleavage by siRNA and
7. stringent filtering through Smith-Waterman algorithm for off-targets as a final
quality control step.
Out of several candidates only seven sequences were selected for the in vitro
validation by qRT-PCR. However, two optimal siRNAs were predicted as best fit for
PAX3-FOXO1 and one candidate for PAX7-FOXO1 due to their specificity and
efficacy status analyzed through in silico tools. In addition, all these siRNAs were
having most of the features suggested by Ui-Tei, Reynolds and Amarzguioui. Further
in vitro transfection experiments followed by qRT-PCR have confirmed the in silico
optimized sequences for their physiological RNAi efficacy in down regulating the
intended targets.
63
Seven siRNA constructs were optimized for PAX3-FOXO1 and later tested with qRT-
PCR
199-221: GGCCTCTCACCTCAGAATTCAAT
200-222: GCCTCTCACCTCAGAATTCAATT
201-229: CCTCTCACCTCAGAATTCAATTC
202-225: CTCTCACCTCAGAATTCAATTCG
203-225: TCTCACCTCAGAATTCAATTCGT
204-225: CTCACCTCAGAATTCAATTCGTC
205-225: TCACCTCAGAATTCAATTCGTCA
Unlike PAX3-FOXO1, only one siRNA was optimized for PAX7-FOXO1.
551-573: CAGAATTCAATTCGTCATAATCT
The selected siRNAs have the fusion junction point at the right side for PAX3-FOXO1
siRNA candidates and left side for PAX7-FOXO1 siRNA. Target sequence position
includes 21nt target + 2nt overhang. The 3‟ over hangs were made into TT for higher
intra cellular and in vivo stability as per Tuschl‟s guidelines for all in vitro and in vivo
experiments. To ensure the target accessibility of the siRNAs on PAX3-FOXO1 and
PAX7-FOXO1 fusion junction mRNA structure, secondary structure prediction
analysis was performed to confirm functional mRNA structures for precise positioning
of the siRNA accessibility (Figure 5.2). Structural prediction was based on RNAfold
and Sfold secondary structure data.
64
Figure 5.2 Structural accessibility of PAX3-FOXO1 (left) and PAX7-FOXO1 (right) target regions.
Fusion region (Red) is accessible to siRNA target for 21-mer as well as 27/29-mer (only the core
motifs are shown from the whole structure).
5.1.2 Designing 27/29-mer PAX3-FOXO1 DssiRNA
Based on the structural accessibility and the position of fusion junction, dicer
substrate siRNAs were designed for the purpose of evaluating the efficacy
enhancement in target down regulation. The positions of the siRNAs were validated
with 21-mer siRNAs by qRT-PCR without any cross reaction either with PAX3 or
FOXO1.
199-221: GGCCTCTCACCTCAGAATTCAATTCGTCA
200-228: GCCTCTCACCTCAGAATTCAATTCGTCAT
201-229: CCTCTCACCTCAGAATTCAATTCGTCATA
202-225: CTCTCACCTCAGAATTCAATTCGTCATAA
203-225: TCTCACCTCAGAATTCAATTCGTCATAAT
204-225: CTCACCTCAGAATTCAATTCGTCATAATC
205-225: TCACCTCAGAATTCAATTCGTCATAATCT
65
Target sequence position includes 27nt target + 2nt overhang. The 3‟ over hangs
were made into TT for higher stability as per Tuschl‟s guidelines for in vitro
experiments.
5.1.3 shRNA and siRNA expression systems for PAX3-FOXO1
Based on in silico structural analysis and the qRT-PCR results of 29-mer DssiRNA,
two sequences (199-221 and 200-228) were selected for SureSilencing shRNA
expression system and four sequences were selected for iLenti H1/U6 based siRNA
expression system (as given below). Clones of the plasmids were constructed by
Qiagen (SABiosciences) and Applied Biological Materials in-house facility. Based on
in silico structural stability analysis, the clone of position 202 was modified with a
nonspecific GGGGG segment in the end in order to enhance the stability and efficacy
as this DssiRNA has shown significant target down regulation with 27-mer DssiRNA.
199-221: GGCCTCTCACCTCAGAATTCAATTCGTCA
200-228: GCCTCTCACCTCAGAATTCAATTCGTCAT
202-225: CTCTCACCTCAGAATTCAATTCGTGGGGG
205-225: TCACCTCAGAATTCAATTCGTCATAATCT
5.2 Toxicity validation of siRNAs
The in vivo grades of 21nt siRNAs were used for all the experimental purposes. More
than 96% purity and endotoxin free certification was assured by Eurogentec quality
check. In order to check the toxicity to RMS cell lines, the siRNAs were transfected
with HiPerfect in 96 well plates and the viability was checked after 48 and 72 hours.
Rh30 cell lines were transfected with 40nM of Scr-siRNA, P3F-siRNA1, P3F-siRNA2
and P7F-siRNA for 48 and 72 hours. The control cells were added only with buffer.
HiPerfect alone was taken as an additional mock control.
The viability was evaluated with CellTiter-Glo assay. The same experiment was also
conducted and the viability was accessed through trypan blue staining. More than
95% cell viability was observed with siRNA+HiPerfect combination when compared
to the control after 48 hours. The viability has increased slightly after 72 hours.
HiPerfect alone has compromised the cell viability.
66
Cells+b
uffe
r
Scr
-siR
NA
P3F
siRNA1
P3F
siRNA2
P7F
siRNA
Hi-P
erfe
ct
70
80
90
100
48 h
72 h
Via
bili
ty o
f R
h30 a
fter
transfe
ctio
n (
%)
Figure 5.3 Rh30 cell lines after 48 hours of transfection. Viability was accessed by CellTiter-Glo
assay. (M ± SEM, n=3)
Cells+b
uffe
r
Scr
-siR
NA
P3F
siRNA1
P3F
siRNA2
P7F
siRNA
Hi-P
erfe
ct
70
80
90
100
48 h
72 h
Via
bili
ty o
f R
h30 a
fter
transfe
ctio
n (
%)
Figure 5.4 Rh30 cell lines after 48 hours of transfection. Viability was accessed by trypan blue
viable counting. (M ± SEM, n=3)
This could be possibly due to ionic toxicity of the component which was not
neutralized by siRNA complexation. However, after 72 hours the viability has
67
increased. The cell viability assay by trypan blue viable counting coincided well with
the result of CellTiter-Glo assy. In both methods the toxicity with plain HiPerfect was
observed after 48 and 72 hours (Figure 5.3 and 5.4).
5.3 Specificity of PAX3-FOXO1 siRNAs
The PAX3-FOXO1 specific siRNAs designed based on position 199 (P3F-siRNA1)
and 200 (P3F-siRNA2) were evaluated for their specificity to independent counterpart
of PAX3 and FOXO1 along with housekeeping genes by qPCR. 40nM of siRNA was
transfected with HiPerfect into Rh30 cell line and the results were checked after 48
and 72 hours. All the expression data were normalized with the mock transfected
Rh30 (Figure 5.5 and 5.6).
P3F
PAX
3
FOXO1
GAPD
H
B-A
ctin
0
50
100
15048 h
72 h
***
***
***
***
Rela
tive e
xpre
ssio
n (
%)
Figure 5.5 Relative expression of candidate genes in Rh30 after transfection with P3F-siRNA1.
(M ± SEM, n=3)
P3F-siRNA1 has no significant cross reactivity with PAX3. However, the FOXO1 was
down regulated 12.5% after 48 hours and 10% after 72 hours. No significant impact
on the expression of B-actin and GAPDH was noted. The cross reactivity with
FOXO1 could be due to sequence similarity. However, at 40nM concentration such
partial cross reactivity is expected.
68
P3F
PAX
3
FOXO1
GAPD
H
B-A
ctin
0
50
100
15048 h
72 h
***
***
***
***R
ela
tive e
xpre
ssio
n (
%)
Figure 5.6 Relative expression of candidate genes in Rh30 after transfection with P3F-siRNA2.
(M ± SEM, n=3)
Similar to P3F-siRNA1, P3F-siRNA2 has no significant cross reactivity with PAX3.
FOXO1 was down regulated 12.8% after 48 hours and 10% after 72 hours. There
was no significant impact noted on the expression of B-actin and GAPDH. Although
P3F-siRNA1 and P3F-siRNA2 sequence region covers 15 and 14 bases respectively
with the PAX3 sequence and 8 and 9 bases respectively with FOXO1 sequence, the
cross reactivity of the siRNAs are more towards FOXO1 region. Possibly, the
cleavage site of the fusion protein mRNA sequence is oriented right from the fusion
junction point. There was no impact seen on GAPDH and B-actin expression by both
the siRNAs, indicating that these siRNAs have no interference on housekeeping
genes. In a higher concentration of siRNA like 40nM, 12.5-12.8% cross reactivity is
not unusual, especially when the siRNAs are designed to target a region of sequence
specific translocation.
5.4 Specificity of PAX7-FOXO1 siRNA
With several in silico optimization steps, finally one siRNA was designed for PAX7-
FOXO1 fusion from the position 551. Only 3 bases are from PAX7 region and 20
bases are from FOXO1 region. 40nM of siRNA was transfected with HiPerfect in
CW9019 cell line. The expression profile was checked after 48 and 72 hours for
PAX7, FOXO1 along with housekeeping genes. There was no impact observed on
housekeeping genes and PAX7 expression. However, FOXO1 was down regulated
69
16.1% after 48 hours and that has increased 3% further after 72 hours (Figure 5.7).
There was no effect observed on the expression of B-actin and GAPDH.
P7F
PAX
7
FOXO1
GAPD
H
B-A
ctin
0
50
100
15048 h
72 h
***
***
***
***
Rela
tive e
xpre
ssio
n (
%)
Figure 5.7 Relative expression of candidate genes in CW9019 after transfection with P7F-
siRNA. (M ± SEM, n=3).
5.5 Validation for induction of innate immunity
siRNAs can induce non-specific immune induction as the toll-like receptors present in
the endosome recognize double-stranded and single-stranded siRNAs in a
sequence-dependent manner and induce pro-inflammatory cytokines. Sometimes,
the resulting cell death may be due to the inflammatory responses and not because
of sequence specific mRNA target down regulation. Hence, all the siRNAs were
checked with Interferon beta 1 (IFNB1), Interferon induced transmembrane protein 1
(IFITM1), Interleukin 6 (IL6), Interferon induced GTP-binding protein Mx1 (MX1), 2'-
5'-oligoadenylate synthetase 1 and 2 (OAS1 and 2) enzymes induced by interferons
and Signal transducers and activators of transcription (STAT1). STAT1 is involved in
up regulating genes due to a signal either by type I, type II or type III interferons.
Although such issues can be filtered by the siRNA design steps in silico, it is
necessary to check them experimentally.
Especially after interacting with the carrier and cationic-anionic interactions, the
surface chemistry of the siRNA delivery system and their interaction with the toll like
70
receptor of the cells cannot be evaluated by any of the in silico methods. Apart from
siRNA sequence properties, such pro-inflammatory induction depends on cell/tissue
type, mode of delivery, chemical components of the delivery system and the overall
surface properties.
Relative expressions of inflammatory genes were measured by qPCR after 48 hours.
Rh30 cells were not showing any pro-inflammatory cytokine response after 48 hours
of transfection. Compared with the Scr-siRNA controls, no significant expression was
noted (Figure 5.8). The mild expression noted could be due to the native expression
that coincides with the scrambled control. However, the longtime effect of oligos like
siRNAs and their impact on inducing the innate immunity has to be evaluated in vivo
for therapeutic safety. During the intra cellular siRNA processing, the unwound sense
strand is generally degraded due to the free ends of the single strand. Through
effective design algorithms, immune stimulatory motifs in the siRNA sequence can be
filtered out in the sense strand. Despite there is no assurance that such free single
strand may not bind with toll like receptors. Since most of the siRNA-nanoparticles
are delivered through endosomal release (escape), it is crucial to ensure that the
endosomal bound toll like receptors (TLR3, 7, 8 and 9) are not activated to induce
pro-inflammatory cytokines.
Also P7F-siRNA has not shown any inflammatory effect on CW9019 cell line (Figure
5.9). Although the long term effect of these siRNAs on the inflammatory signals was
not tested in vitro owing the fact that such innate immune inflammatory response
bursts out within 24 hours of transfection and lasts for several days until the cell
death occurs as a host innate immune response that is evolutionally conserved
against RNA viral infections. There was no significant difference between scrambled
siRNA and target siRNA in Rh30 as well CW9019.
71
IFNB1
IFIT
M1
IL61
MX1
OAS1
OAS2
STA
T1 SG
0
10
20
30
40
50
Scr-siRNA
P3F-siRNA1
Immune induction genes
Rela
tive e
xpre
ssio
n (
%)
Figure 5.8 Relative expressions of different pro-inflammatory genes in Rh30 cells after
transfected with 40nM P3F-siRNA along with HiPerfect. (M ± SEM, n=3)
IFNB1
IFIT
M1
IL61
MX1
OAS1
OAS2
STA
T1 SG
0
10
20
30
40
50
Scr-siRNA
P7F-siRNA
Immune induction genes
Rela
tive e
xpre
ssio
n (
%)
Figure 5.9 Relative expressions of different pro-inflammatory genes in CW9019 cells after
transfected with 40nM P7F-siRNA along with HiPerfect. (M ± SEM, n=3)
5.6 PAX3-FOXO1 target down regulation by different siRNA constructs
Initially seven different siRNAs were designed based on the fusion junction of the
PAX3-FOXO. Their efficacy was validated with 21nt siRNA as well as 27nt siRNA
72
(Dicer substrate siRNA) at 40nM concentration by HiPerfect transfection on Rh30 cell
lines. Up to 57% target down regulation was achieved after 48 hours with 21-mer
siRNAs however, with 27-mer siRNAs up to 67% down-regulation was achieved.
Since 27-mer siRNAs are processed by Dicer, their half-life and bioavailability is
more than that of 21-mer siRNAs which are readily used as a processed siRNA by
the host RNAi machinery. siRNAs with the target position at 199, 200 and 205 seems
to be more effective for 21-mer as well as 27-mer. siRNA target position 199 has
shown 56.9% target down regulation for 21-mer and 66.7% for 27-mer. Target
position 200 has shown 55.3% target down regulation for 21-mer and 67.4% for 27-
mer.
Although the target down regulation effect of 27-mer siRNA is optimal even after 48
hours, the production synthesis yielded after purification is low and hence the costs
are high. siRNAs of position 199 and 200 have nearly the same effect. These two
candidates (named P3FsiRNA1 and P3FsiRNA2) were taken for further experiments.
The 27-mer siRNA of position 205 has given 65% target down regulation unlike
position 201, 202, 203 and 204 27-mers (Figure 5.10). Since DssiRNAs are
processed by the Dicer of the host RNAi machinery, several 21-mer siRNAs are
generated from 27-mer and the effect of higher target down regulation efficiency is
due to this fact in addition to higher intracellular half-life and delayed processing time
to generate siRNAs systemically, without over saturating the host RNAi machinery.
Similar results were observed with Rh4 cell line (Figure 5.11).
73
siRNA-1
99
siRNA-2
00
siRNA-2
01
siRNA-2
02
siRNA-2
03
siRNA-2
04
siRNA-2
05
0
20
40
60
80
10021-mer siRNA
27-mer siRNA
Rela
tive e
xpre
ssio
n o
f P
3F
(%
)
Figure 5.10 Expression of PAX3-FOXO1 after transfection with different siRNA sequences in
Rh30 cells. siRNAs at position 199 and position 200 showed better target down regulation. (M ± SEM,
n=3)
siRNA-1
99
siRNA-2
00
siRNA-2
01
siRNA-2
02
siRNA-2
03
siRNA-2
04
siRNA-2
05
0
20
40
60
80
10021-mer siRNA
27-mer siRNA
Rela
tive e
xpre
ssio
n o
f P
3F
(%
)
Figure 5.11 Expression of PAX3-FOXO1 after transfection with different siRNA sequences in
Rh4 cells. (M ± SEM, n=3)
74
5.7 Effect of siRNA concentration on PAX3-FOXO1 down regulation
The highly effective siRNAs against the target position 199 and 200 (P3FsiRNA1 and
P3FsiRNA2) were taken for further validation to access the effect of concentration on
target down regulation. siRNA concentration from 20-120 nM in the increment of
20nM were transfected in Rh30 cells with HiPerfect. The down regulation was
accessed after 48 hours. siRNAs with 40nM and above concentration were capable
of down regulating the PAX3-FOXO1 target significantly. However, the concentration
above 60nM has not shown any significant effect. The optimal concentration for the
effective down regulation is ranging from 40-60 nM (Figure 5.12).
Con
trol
20nM
40nM
60nM
80nM
100n
M
120n
M
0
20
40
60
80
100
120 P3F-siRNA1
P3F-siRNA2
Rela
tive e
xpre
ssio
n (
%)
Figure 5.12 Relative expression of PAX3-FOXO1 target after transfected with P3F-siRNA 1 and
2 at different concentration in Rh30 cells. (M ± SEM, n=3)
Both of the siRNA candidates expressed nearly the same level of target down
regulation although P3FsiRNA1 was slightly better (2% more efficient) than
P3FsiRNA2. Based on these results, 60nM concentration of siRNA of P3F-siRNA1
(that was down regulating up to 65% PAX3-FOXO1a target) was preferred for the
siRNA-nanoparticle formulation and further in vitro and in vivo validation. Although
higher concentrations of siRNAs directly impact the efficacy of target down
regulation, they do enhance the cell death. This could be possible as such high
concentration of siRNA over utilize the host RNAi machinery and deplete the RNAi
resources rapidly. Under such conditions, the unprocessed siRNA duplex may mimic
75
like viral RNA and activate a major host innate immune response leading to cell
death.
5.8 Effect of PAX3-FOXO1 down regulation on other pro-oncogenic signals
Due to the shrewd translocation of two effective transcriptional factors, the PAX3-
FOXO1 and PAX7-FOXO1 mediate the transcription of target genes several folds. In
addition, the nuclear localization of the fusion protein enables the mediation of
transcriptional gain function of this without any regulatory barriers. Due to this
hapless fact, lots of pro-oncogenic signals are over expressed and augmenting tumor
development and metastasis. Down regulating the fusion protein may possibly have a
direct impact on these candidate genes. Few of the over expressed downstream
factors were checked to evaluate the influence of PAX3-FOXO1 down regulation in
Rh30. Down regulation of the PAX3-FOXO1 has a direct impact on the lower
expression of these aberrant signals. 23% of ALK, 20% of FGFR4, 22.4% of MET
and 25.2% MYCN expressions were lowered after 48 hours. The impact is also seen
up to 72 hours although not significantly (Figure 5.13).
The impact of P3F target down regulation on other downstream targets is not
significant after 72 hours of transfection except FGFR4 that shows a stable impact of
22.4 to 17.4% (Figure 5.13). Similar results were observed in other ARMS cell lines
Rh4 and RMS (Figure 5.14 and 5.15). The interrelation of PAX3-FOXO1 with FGFR4
was seen in Rh4 and RMS cell lines too. Such impact indicates that the downstream
targets are not exclusively enhanced by PAX3-FOXO but hold their self-regulatory
induction independent of PAX3-FOXO1. Especially, due to the copy number
amplification of MYCN, the PAX3-FOXO1 down regulation may not have a significant
direct impact on the expression. Hence, co-targeting PAX3-FOXO1 along with one or
more downstream targets would be a rational approach in mitigating ARMS. In
addition, whether such an impact has any effect on the migration and metastasis in
vivo, needs to be evaluated in a metastatic model system.
76
P3F
ALK
FGFR
4M
ET
MYCN
0
20
40
60
80
10048 h
72 h
Rh30 aberrant signals
Rela
tive e
xpre
ssio
n (
%)
Figure 5.13 Impact of the PAX3-FOXO1 target down regulation on co-regulated signals in Rh30
cells. (M ± SEM, n=3)
P3F
ALK
FGFR
4M
ET
MYCN
0
20
40
60
80
10048 h
72 h
Rh4 aberrant signals
Rela
tive e
xpre
ssio
n (
%)
Figure 5.14 Impact of the PAX3-FOXO1 target down regulation on co-regulated signals in Rh4
cells. (M ± SEM, n=3)
77
P3F
ALK
FGFR
4M
ET
MYCN
0
20
40
60
80
10048 h
72 h
RMS aberrant signals
Rela
tive e
xpre
ssio
n (
%)
Figure 5.15 Impact of the PAX3-FOXO1 target down regulation on co-regulated signals in RMS
cells. (M ± SEM, n=3)
5.9 Effect of siRNA chemical modification on PAX3-FOXO1
Several studies reveal that some chemical modifications can improve the properties
of siRNAs but certain chemical modifications have insignificant influence on the
efficacy of the siRNA. Sometimes, chemical modifications may create toxicity to the
cell instead of target gene silencing. However, position specific chemical
modifications can greatly increase the specificity and stability of the siRNAs,
subsequently resulting in prolonged effect of gene-silencing activity [Malhotra M,
Nambiar M, 2011]. P3FsiRNA was modified by 3`O-Methyl, 2`-Fluoro, locked and
unlocked nucleic acid bases.
Since these chemical modifications enhances the stability of the siRNA, the RNAi
activity was observed significantly up to 72 hours without any major difference when
compared to the effects at 48 hours (Rh30-Figure 5.16 and Rh41-Figure 5.17).
Compared to un-modified siRNA all the modified siRNAs has shown significant P
values both at 48 and 72 hours (***P<0.001). Unmodified siRNA was not that
effective after 48 hours due to intracellular degradation. Among all the chemically
modified siRNAs, UNA modified siRNA showed higher target down regulation. There
was a distinct reduction in post transfection cell death of Rh30 with chemically
modified siRNAs. Possibly, this effect could be due to higher nuclease resistance of
78
the chemical modification hence less utilization of siRNA processing and not
saturating the host RNAi machinery.
Con
trol
3' O
-Met
hyl
2' F
luor
oUNA
LNA
Un-
mod
ified
0
20
40
60
80
100 48 h
72 h
***
*
******
***
Rh30
Rela
tive e
xpre
ssio
n o
f P
3F
(%
)
Figure 5.16 Relative expression of PAX3-FOXO1 target after transfection with chemically
modified siRNA in Rh30 cells. (M ± SEM, n=3)
Con
trol
3' O
-Met
hyl
2' F
luor
oUNA
LNA
Un-
mod
ified
0
20
40
60
80
100 48 h
72 h
***
*
******
***
Rh41
Rela
tive e
xpre
ssio
n o
f P
3F
(%
)
Figure 5.17 Relative expression of PAX3-FOXO1 target after transfection with chemically
modified siRNA in Rh41 cells. (M ± SEM, n=3)
79
5.10 Effect of shRNA constructs on PAX3-FOXO1 down regulation
The validated PAX3-FOXO1 specific siRNA target sequences were further tested
with SureSilencing shRNA expression plasmid. Four constructs were used to analyze
the shRNA based P3F-siRNA induction in RH30 cell lines. Along with a scrambled
control shRNA and empty vector control, two shRNA plasmids were constructed for
the sequences 199-221 and 200-228. Empty shRNA vector and scrambled shRNA
were compared with plain Rh30 cells for the target down regulation. shRNA vector
199 and 200 were compared with scrambled vector. After puromycin induction for 48
and 72 hours the down regulation was analyzed by qRT-PCR for all the clones along
with Rh30 cells. Plain vector and scrambled shRNA vector has shown similar
insignificant PAX3-FOXO1 target down regulation (4.5 and 3.7% after 48 hours and
3.7 and 3.2% after 72 hours). Compareed with scrambled vector, shRNA-199 vector
showed 71.3 and 57.5% down regulation at 48 and 72 hours respectively. shRNA-
200 vector showed 65 and 53.4% down regulation at 48 and 72 hours respectively.
shRNA-199 vector showed higher effect similar to its 21-mer siRNA. When compared
to Rh30 cells all the vector cloned Rh30 cells exhibited cell death due to puromycin
induction (Figure 5.18).
Con
trol
Scr
-shR
NA
shRNA-1
99
shRNA-2
00
shRNA v
ecto
r
0
50
100
48 h
72 h***
***
******
Rela
tive e
xpre
ssio
n o
f P
3F
(%
)
Figure 5.18 Down regulation of PAX3-FOXO1 by shRNA vectors in Rh30 cell lines. Compared
with scrambled shRNA shRNA 199 and shRNA-200 showed ***P<0.001 at both time points. (M ± SD,
n=3)
80
5.11 Effect of shRNA-199 clone
The shRNA-199 clone was further tested for its biological effect. The morphology of
the Rh30 shRNA-199 clone changed after the induction with puromycin that has
initiated the shRNA expression in multiple folds. Although the Rh30-shRNA-199
clones were differentiating, the cells were eventually lysed after 72 hours (Figure
5.19). Complete differentiation was not observed with any of the shRNA clones. The
gap closure test indicated effective inhibition on migration of the Rh30-shRNA-199
cells (Figure 5.20) when compared to Rh30-shRNA-scr control cells. Furthermore,
the CAM assay also confirmed the reduction of the tumor in the Rh30-shRNA-199 but
not in the scrambled control (Figure 5.21). However, none of these methods have
proven the expression of the P3F-siRNA induced total cell differentiation or cell
death. The expression of the most effective P3F-siRNA in the Rh30-shRNA-199
clone has only shown effective inhibition of proliferation and migration.
Figure 5.19 Rh30 cells with shRNA-199 clone. The cell morphology showed the initiation of
differentiation after the shRNA expression but unable to differentiate fully.
Figure 5.20 Migration assay with Rh30-shRNA-199 clone. Effective inhibition of migration (left) after
48 hours of the scratch assay was observed. Rh30-shRNA-scr clone exhibited faster migration (right).
81
Figure 5.21 CAM assay with Rh30-shRNA-scr and Rh30-shRNA-199 clones. The scrambled
control shRNA clone showed tumor initiation (left). Rh30-shRNA-199 clone exhibited a rudimentary
tumor (right).
5.12 Effect of iLenti H1/U6 siRNA expression system on PAX3-FOXO1 down
regulation
Four validated PAX3-FOXO1 specific siRNA target sequences were further tested
with iLenti H1/U6 siRNA expression system plasmid along with a scrambled control
vector and a plain vector. Rh30 cells were taken as additional control to see the
difference with Scr-Vector and Plain vector. All the vectors were transfected and
selected for puromycin and the PAX3-FOXO1 target down regulation was checked
after 48 and 72 hours. iLenti vector-199 showed 80 and 69% target down regulation
after 48 and 72 hours respectively. Scrambled iLenti and plain iLenti did not display
any significant difference in Rh30 cells. Similar to the Suresilencing vector, iLenti
vector 199 and 200 were more effective in target down regulation but with better
efficacy. iLenti 202 and 205 have exhibited minor variations after 48 hours but all the
vectors have nearly performed similar after 72 hours (Figure 5.22). Out of all
constructs iLenti-199 dicer substrate siRNA expression system showed higher
efficacy with limited cell death. Unlike the Suresilencing vector, iLenti vectors have
not induced cell death upon the induction of siRNA expression. All iLenti vectors
exhibited ***P<0.001 at 48 and 72 hours when compared with Scr-iLenti.
82
Con
trol R
h30
Scr
-iLen
ti
199-
iLen
ti
200-
iLen
ti
202-
iLen
ti
205-
iLen
ti
Plain-iL
enti
0
20
40
60
80
100
120 48 h
72 h************
************
Rela
tive e
xpre
ssio
n o
f P
3F
Figure 5.22 Down regulation of PAX3-FOXO1 by iLenti H1/U6 based siRNA expression system
in Rh30 cells. (M ± SEM, n=3).
5.13 iLenti H1/U6 clone 199
Similar to P3F-siRNA expressing shRNA clones, the iLenti clones have also exhibited
morphological differentiation upon the expression induction of the DssiRNA by
puromycin. However, the cell death is limited with iLenti vectors. With the initial
induction, Rh30 cells with iLenti-199 differentiated quickly after 24 hours and became
static. Second induction after 72 hours has induced cell death with few differentiated
cells. Such cell death could be due to excessive siRNA induction that might have
saturated the host RNAi machinery but not due to the silencing of PAX3-FOXO1.
Once after stopping the puromycin induction, the dormant Rh30 has shifted from the
static condition and grow back normally (Figures 5.23 and 5.24).
83
Figure 5.23 Rh30 with iLenti-199 – after induction. After the induction of DssiRNA specific to PAX3-
FOXO1expression by puromycin, the Rh30 cells started differentiating. Considerable cell death was
observed after 48 hours (right).
Figure 5.24 Rh30 with iLenti-199 – prolonged induction. Expression of DssiRNA specific to PAX3-
FOXO1 after 72 hours resulted static cell growth (left). Further induction by puromycin resulted in cell
death (right).
5.14 Effect of siRNA concentration on PAX7-FOXO1 down regulation
The PAX7-FOXO1 positive cell lines RMZ-RC2 and CW9019 were transfected with
different concentrations of P3F-siRNA and P7F-siRNA (Figure 5.25 and 5.26). Since
the junction point of the fusion is similar, it is inquisitorial to check whether there is
any activity of P3F-siRNA on PAX7-FOXO1 fusion. The P7F-siRNA down regulates
the target effectively at 40-60nM siRNA concentration but at higher concentration
there is no great significance. The results are more similar to P3F-siRNA on its
target. Although the PAX7-FOXO1 fusion has homologous sequence similarity with
PAX3-FOXO1 fusion, the P3F-siRNA cross reacts with PAX7-FOXO1 target in a
minimal level.
84
Even at high concentrations like 60nM, P3F-siRNA has the down regulation of PAX7-
FOXO1 target only 23.7% however, 66% target down regulation was observed by the
specific P7F-siRNA (in RMZ-RC2). At an extremely high level concentration of
120nM 45.5% target down regulation was observed. Since the junction point followed
by the FOXO1 region is similar for both the PAX3-FOXO1 and PAX7-FOXO1, such
cross reactivity cannot be avoided. At higher concentrations of siRNA from 80nM
onwards, cell death was observed invariably of P3FsiRNA or P7FsiRNA. Similar
results were observed with CW9019 (Figure 5.26). However, the specific target down
regulation of the PAX7-FOXO1 was better in all concentrations of P7F-siRNA.
Con
trol
20nM
40nM
60nM
80nM
100n
M
120n
M
0
20
40
60
80
100
120P7F-siRNA
P3F-siRNA
Rela
tive e
xpre
ssio
n (
%)
Figure 5.25 Down regulation of P7F by siRNA in RMZ-RC2 cell line. P3F-siRNA cross reacted with
the PAX7-FOXO1 target. (M ± SEM, n=3)
85
Con
trol
20nM
40nM
60nM
80nM
100n
M
120n
M
0
20
40
60
80
100
120P7F-siRNA
P3F-siRNA
Rela
tive e
xpre
ssio
n (
%)
Figure 5.26 Down regulation of P7F by siRNA in CW9019 cell line. (M ± SEM, n=3)
5.15 Effect of PAX7-FOXO1 down regulation on other pro-oncogenic signals
Like PAX3-FOXO1, PAX7-FOXO1 enhances the expression of other pro-oncogenic
signals that are involved in migration and metastasis. However, the impact of PAX7-
FOXO1 target down regulation is higher than the PAX3-FOXO1 down regulation.
48% of ALK, 59% of FGFR4, 68.3% of MET and 69% MYCN expressions were
decreased after 48 hours in CW9019 cell line. Although only 53.5% down regulation
was seen on PAX7-FOXO1, the impact on other signals was higher. Surprisingly, the
impact is also seen up to 72 hours especially for MET and MYCN. In contrary to the
effect of PAX3-FOXO1 target down regulation, PAX7-FOXO1 target down regulation
has significant effect on the co-expressed signals, especially on MYCN, where the
effect is seen even at 72 hours (Figure 5.27).
However, similar effects were not reproduced with another PAX7-FOXO1 cell line,
RMZ-RC2, when 40nM of P7F-siRNA was transfected with HiPerfect. With this cell
line the effect is more similar with the down regulation of PAX3-FOXO1 in RH30 cell
line. With the impact of 52% target down regulation, 23% of ALK, 30% of FGFR, 31%
of MET and 25.6% of MYCN was reduced after 48 hours. Such contrary results in
different cell lines of the same PAX7-FOXO1 fusion could be due to differential
pattern of gene network axis or heterogeneity in the cell lines. However, the FGFR4
signal was down regulated considerably that correlated with the impact of PAX3-
FOXO1 down regulation on FGFR4 (Figure 5.28).
86
P7F
ALK
FGFR
4M
ET
MYCN
0
20
40
60
8048 h
72 h
Rela
tive e
xpre
ssio
n (
%)
Figure 5.27 Down regulation of pro-oncogenes by P7F siRNA in CW9019 cells. Down regulation
of PAX7-FOXO1 has significant impact on co-regulated signals. (M ± SEM, n=3)
P7F
ALK
FGFR
4M
ET
MYCN
0
20
40
60
80
10048 h
72 h
Rela
tive e
xpre
ssio
n (
%)
Figure 5.28 Down regulation of pro-oncogenes by P7F siRNA in RMZ-RC2 cells. The impact of
fusion down regulation on other signals was not significant compared to cell line CW9010. (M ± SEM,
n=3)
5.16 Effect of siRNA chemical modification on PAX7-FOXO1
Similar chemical modifications used for P3FsiRNA were also considered for the
P7FsiRNA as there was an optimal down regulation seen even up to 72 hours.
Comparable results were observed as all of the modified P7FsiRNAs exhibited
87
enhanced stability. Once again, UNA modification exhibited better down regulation
due to a possible enhancement of RNAi activity that was observed after 72 hours
also (Figure 5.29). Position specific UNA modifications of both P3FsiRNA and
P7FsiRNA need to be further evaluated for their RNAi activity along with long term
stability. In several studies, chemical modification of the siRNAs has been shown to
improve the siRNA function by enhancing its stability, reducing the off-target effects
and avoiding the stimulation of the innate immune system [Bramsen JB, Laursen MB,
2009]. Compared with un-modified siRNA, all the siRNAs showed ***P<0.001 after
72 hours. LNA and UNA showed ***P<0.001 at 48 hours.
Con
trol
3' O
-Met
hyl
2' F
luor
oUNA
LNA
Un-
mod
ified
0
20
40
60
80
100 48 h
72 h
****
******
***
Rela
tive e
xpre
ssio
n o
f P
7F
(%
)
Figure 5.29 Expression analysis of P7F after transfection with chemically modified siRNAs.
Chemical modification of P7FsiRNA enhances the half-life and also the RNAi activity for a long time.
(M ± SEM, n=3)
5.17 Effect of target down regulation on proliferation inhibition
Since the target down regulation of PAX3-FOXO1 and PAX7-FOXO1 was effective in
down regulating co-expressed signals like FGFR4, MET and MYCN, the impact
needed to be evaluated on proliferation inhibition by WST assay. 40nM of P3F-siRNA
and P7F-siRNA were transfected with HiPerfect in two cell lines harboring the PAX3-
FOXO1 (Rh30 and Rh4) and PAX7-FOXO1 fusion (CW9019 and RMZ-RC2). The
impact on proliferation inhibition was seen after 24, 48 and 72 hours (Figure 5.30 and
5.31).
88
Con
trol R
h30
P3F
-Rh3
0
Scr
-Rh3
0
Con
trol R
h4
P3F
-Rh4
Scr
-Rh4
0.0
0.2
0.4
0.6
0.8
1.024 h
48 h
72 h******
**
******
**
%A
b a
t 450 n
m
Figure 5.30 Proliferation inhibition in PAX3-FOXO1 ARMS cell lines. (M ± SEM, n=6)
Con
trol
P7F
-CW
9019
Scr
-CW
Con
trol R
MZ
P7F
-RM
Z-RC2
Scr
-RM
Z
0.0
0.2
0.4
0.6
0.8
1.024 h
48 h
72 h******
*
******
**
%A
b a
t 450 n
m
Figure 5.31 Proliferation inhibition in PAX7-FOXO1 ARMS cell lines. (M ± SEM, n=6)
Proliferation was effectively inhibited after 24 and 48 hours in all cell lines and
moderately inhibited after 72 hours eventually due to utilization of siRNAs. Scrambled
control showed a mild inhibitory effect when compared to untreated control cells due
89
to the transfection induced stress. Both Rh30 and Rh4 showed ***P<0.001 after 24
and 48 hours compared to Scr-controls. After 72 hours, **P<0.01 was observed
because of utilization of siRNA (Figure 5.30). With PAX7-FOXO1 ARMS cell lines,
after 24 and 48 hours, ***P<0.001 was observed compared to Scr-controls. RMZ-
RC2 showed **P after 72 hours and CW9019 showed *P (Figure 5.31).
5.18 Effect of target down regulation on apoptosis induction
Since the fusion target down regulation had significant impact on proliferation
inhibition, it was decided to evaluate the impact of down regulation on the induction
of apoptosis. Since the expression level of the co-expressed signals like MET and
MYCN were also negatively influenced, the possibility of apoptotic induction at 40nM
siRNA concentration needs to be significant. Overall induction of apoptosis was
tested with Scr-siRNA and P3F-siRNA on PAX3-FOXO1 harboring cell lines Rh30
and Rh4 along with a negative control RD. There was no difference observed in RD
cell line with Scr-siRNA and P3F-siRNA after 48 and 72 hours.
The observed insignificant apoptosis induction 11.2-11.8% after 48 hours and 16.3-
16.9% after 72 hours was due to the HiPerfect-siRNA induced stress as RD cells do
not harbor PAX3-FOXO1 fusion. When compared to Scr-siRNA, the apoptotic
induction seen in Rh30 for P3F-siRNA was 41.7% after 48 hours that has reduced
into 19% after 72 hours. Similar results were found with Rh4 cell line, where 42.9%
apoptotic induction was seen after 48 hours and 12.8% after 72 hours. The down fall
in apoptotic induction after 72 hours was not coinciding with the scrambled control
(Figure 5.32).
Similarly, in PAX7-FOXO1 harboring cells, 40nM Scr-siRNA and P7F-siRNA were
transfected with HiPerfect. RD cell line was used as a negative control and CW9019
and RMZ-RCZ were used to see the impact on PAX7-FOXO1 down regulation on
apoptosis induction. RD cell line showed no significant apoptotic induction with both
siRNAs. After 48 hours, CW9019 showed 37.2% apoptotic induction and RMZ-RC2
showed 35.6%. The apoptotic induction was reduced after 72 hours (Figure 5.33).
90
RD -
Scr
-siR
NA
RD-P
3F-s
iRNA
Rh3
0-Scr
-siR
NA
Rh3
0-P3F
-siR
NA
Rh4
-Scr
-siR
NA
Rh4
-P3F
-siR
NA
0
20
40
6048 h
72 h
*** ***
*** ***%
of
gate
d c
ells
Figure 5.32 Induction of apoptosis by P3F-siRNA in ARMS and ERMS cell lines. There is no
significant apoptosis seen in the negative control RD. (M ± SEM, n=3) Compare with Scr-control,
treated Rh30 and Rh4 showed ***P<0.001 after both 48 and 72 hours.
RD -
Scr
-siR
NA
RD-P
7F-s
iRNA
CW
9019
-Scr
-siR
NA
CW
9019
-P7F
-siR
NA
RM
Z-RC2-
Scr-s
iRNA
RM
Z-RC2-
P7F-s
iRNA
0
20
40
6048 h
72 h
*** ***
** *
%of
gate
d c
ells
Figure 5.33 Induction of apoptosis by P7F-siRNA in ARMS and ERMS cell lines. Negative control
RD showed no significant apoptotic induction. (M ± SEM, n=3) Compared with Scr-control, treated
91
CW9019 and RMZ-RC2 showed ***P<0.001 after both 48 hours. After 72 hours, CW9019 showed **P
and RMZ-RC2 showed *P.
5.19 PAX3-FOXO1 target down regulation by P3F-siRNA-LPR nanoparticles
Due to the specificity and efficacy P3F-siRNA1 was selected for the validation with
targeted lipid protamine nanoparticles (LPR). Due to the optimal activity, 60nM of
siRNA concentration was used for all nanoformulations. The nanoformulations were
prepared with both scrambled as well as P3F-siRNA. Both RGD targeted as well as
RAD targeted particles were prepared for both the siRNAs in order to cross compare.
After 48 hours, 4% target down regulation was observed in Scr-RAD-LPR and Scr-
RGD-LPR treated sets. The P3F-RAD-LPR expressed 10% down regulation that
could be due to non-specific delivery. However, the targeted RGD-P3F-LPR particle
down regulation of the PAX3-FOXO1 target up to 63.6% that was closed to the
HiPerfect transfection of P3F-siRNA i.e., 65.3% at 40nM concentration.
The target down regulation was active even after 72 hours (Figure 5.34). The results
demonstrated the specificity of the targeted formulation RGD-P3F-LPR to ARMS cell
line Rh30 and the delivery of siRNA and significant gene silencing activity of PAX3-
FOXO1. In addition, the non-specific RAD-P3F-LPR particle showed only a minimal
level of down regulation. However, after 72 hours there was no effect seen by the
non-specific RAD-P3F-LPR particles when compared to the control sets at the same
time point. The RGD-P3F-LPR displayed 45.7% target down regulation after 72
hours. Similar results were obtained for other PAX3-FOXO1 harboring ARMS cell
lines Rh28, Rh4 and Rh41 (Figure 5.35-5.37). There was no variability observed in
target down regulation in different PAX3-FOXO1 ARMS cell lines.
92
Con
trol
Scr
-RAD
Scr
-RGD
P3F
-RAD
P3F
-RGD
Hi-P
erfe
ct
0
20
40
60
80
100
12048 h
72 h***
***
Rh30
Rela
tive e
xpre
ssio
n (
%)
Figure 5.34 Relative expression of PAX3-FOXO1 after transfection with LPR particles in Rh30
cells. (M ± SEM, n=3) P3F-RGD showed ***P<0.001 at both time points compared to Scr-RGD.
Con
trol
Scr
-RAD
Scr
-RGD
P3F
-RAD
P3F
-RGD
Hi-P
erfe
ct
0
20
40
60
80
100
12048 h
72 h***
***
Rh28
Rela
tive e
xpre
ssio
n (
%)
Figure 5.35 Relative expression of PAX3-FOXO1 after transfection with LPR particles in Rh28
cells. (M ± SEM, n=3)
93
Con
trol
Scr
-RAD
Scr
-RGD
P3F
-RAD
P3F
-RGD
Hi-P
erfe
ct
0
20
40
60
80
100
12048 h
72 h***
***
Rh4
Rela
tive e
xpre
ssio
n (
%)
Figure 5.36 Relative expression of PAX3-FOXO1 after transfection with LPR particles in Rh4
cells. (M ± SEM, n=3)
Con
trol
Scr
-RAD
Scr
-RGD
P3F
-RAD
P3F
-RGD
Hi-P
erfe
ct
0
20
40
60
80
100
12048 h
72 h***
***
Rh41
Rela
tive e
xpre
ssio
n (
%)
Figure 5.37 Relative expression of PAX3-FOXO1 after transfection with LPR particles in Rh41
cells. (M ± SEM, n=3)
94
5.20 P3F target down regulation on proliferation inhibition by LPR
nanoparticles
Due to the significant down regulation of the PAX3-FOXO1 target by the RGD-P3F-
LPR particles, it was decided to evaluate the impact on proliferation inhibition. RGD-
P3F-LPR particle inhibited the proliferation at all three time points effectively in the
same kinetics (Figure 5.38). However, there was a significant effect seen in Scr-
RGD-LPR particle due to the effect of RGD on Rh30 cells. The ERMS cell line RD
was also treated with targeted and non-targeted LPRS to acess the effect on a
negative control cell. In all LPR formulations, there was no proliferation inhibition
observed. The readouts were similar for all LPR formulations. Since ERMS has no
PAX3-FOXO1, the targeted particles had no effect on inhibiting the proliferation of
the RD cell line (Figure 5.39).
Con
trol
P3F
-RGD
P3F
-RAD
Scr
-RGD
Scr
-RAD
Blank
0.0
0.2
0.4
0.6
0.8
1.024 h
48 h
72 h
**
**
ns
%A
b a
t 450 n
m
Figure 5.38 Proliferation inhibition by LPR in Rh30 cells. (M ± SEM, n=6) After 48 hours and 72
hours, the **P was observed for P3F-RGD compared to Scr-RGD.
95
Con
trol
P3F
-RGD
P3F
-RAD
Scr
-RGD
Scr
-RAD
Blank
0.0
0.2
0.4
0.6
0.8
1.024 h
48 h
72 h
%A
b a
t 450 n
m
Figure 5.39 Proliferation inhibition by LPR in RD cells. There was no effect noted at any of the
time point. (M ± SD, n=6)
5.21 P3F target down regulation on apoptosis induction by LPR nanoparticles
Although the targeted P3F-RGD-LPR particles displayed higher and longer down
regulation of the PAX3-FOXO1 target, the apoptosis induction was not significant as
there was also an effect noted with the RGD-Scr-LPR. Compared to the scrambled
control targeted with RGD, the targeted RGD-P3F-LPR showed only 10% of
apoptotic difference. In addition in both cases the apoptotic induction was not seen
after 72 hours. Unlike the proliferation inhibition mediated by the targeted LPR where
the inhibition effect was seen after 72 hours, the apoptotic induction got reduced after
72 hours. Scr-RAD has not induced any apoptotic effect (Figure 5.40). To reconfirm
this effect, the LPR particles were transfected with Rh4 cell line. A slight increase to
4.6% of apoptotic induction was observed with Rh4 cells. Compared to Scr-RGD-
LPR particles, the RGD-P3F-LPR particles showed 14.6% apoptotic induction in Rh4
cell line (Figure 5.41). Similarly, the apoptotic induction was reduced after 72 hours.
Over all, the LPR particles have not induced significant apoptosis for an enhanced
cell death after the treatment.
96
RGD-P
3F
RAD
-P3F
RGD-S
cr
RAD
-Scr
Con
trol
0
10
20
30
4048 h
72 h
*****
***%
of
gate
d c
ells
Figure 5.40 Apoptosis induction by LPR in Rh30 cells. The RGD targeted P3F-LPR particles did
not show significant effect on apoptosis. (M ± SD, n=3)
RGD-P
3F
RAD
-P3F
RGD-S
cr
RAD
-Scr
Con
trol
0
10
20
30
40
5048 h
72 h***
******
%of
gate
d c
ells
Figure 5.41 Apoptosis induction by LPR in Rh4 cells. The RGD targeted P3F-LPR particles did not
show significant effect on apoptosis. (M ± SD, n=3) P3F-RGD displayed ***P<0.001 when compared
to P3F-RAD and Scr-RGD after 48 hours.
5.22 Down regulation of PAX3-FOXO1 fusion protein
The effect of targeted and non-targeted LPR particles on PAX3-FOXO1 gene
silencing at the protein level was analyzed by western blot. After 48 and 72 hours of
97
transfection, cells were lysed and the isolated proteins were evaluated by western
blot. The 97 kDa fusion protein was detected by using anti-FOXO1 antibody along
with anti-PAX3 antibody (1:250 dilutions) (Figure 5.42).
Figure 5.42 Down regulation of fusion protein by LPR. Rh30 and Rh4 cells were transfected with
Scr-RGD-LPR (Control) and P3F-RGD-LPR (Treated) particles for 48 and 72 hours. The blot was
stained with two antibody combinations (anti-PAX3+anti-FOXO1). Treated samples displayed down
regulation of PAX3-FOXO1 protein after 48 and 72 hours (Green box).
The PAX3-FOXO1 fusion was identified at 100kD position in the dual staining blot.
FOXO1 and PAX3 bands were observed at 75 and 53 kD positions respectively. Both
Rh30 and Rh4 showed clear down regulation after 72 hours (T4) however after 48
hours considerable down regulation was noted. Rh30 cells treated with scrambled
control and targeted particles were also analyzed with single antibody staining in
98
order to access the cross reactivity of the P3F-siRNA on PAX3 and FOXO1 at protein
level when compared to the fusion protein region at 97kD. There was no significant
cross reactivity observed for PAX3 but FOXO1 region showed cross reactivity at
75kD region after 48 and 72 hours. In addition, the fusion protein at 97kD region was
clearly down regulated after 72 hours but partially down regulated after 48 hours
(Figure 5.43 and 5.44). The control set did not have any effect on the fusion protein
on Rh30 (Figure 5.35) as well as Rh5 at 48 and 72 hours.
Figure 5.43 Anti-PAX3 staining after LPR treatment. Rh30 cells were transfected with Scr-RGD-
LPR (Control) and P3F-RGD-LPR (Treated) particles for 48 and 72 hours. The blot was stained with
PAX3 antibody. Treated and control samples did not show down regulation of PAX3 at 53kD position.
99
Figure 5.44 Anti-FOXO1 staining after LPR treatment. Rh30 cells were transfected with Scr-RGD-
LPR (Control) and P3F-RGD-LPR (Treated) particles for 48 and 72 hours. The blot was stained with
FOXO1 antibody. The fusion protein was significantly down regulated after 48 and 72 hours (Green
box). However, cross reactivity after 72 hours with FOXO1 alone (Blue box) was observed. In addition,
the fusion protein was significantly down regulated after 72 hours.
100
Figure 5.45 Control LPRs on fusion protein in Rh30. Rh30 cells were transfected with mock, Scr-
RAD-LPR and P3F-RAD-LPR control particles for 48 and 72 hours. The control particles did not show
any effect on the PAX3-FOXO1 fusion that is clearly seen at 97kD region (Green box).
101
Figure 5.46 Control LPRs on fusion protein in Rh4. Rh4 cells were transfected with mock, Scr-
RAD-LPR and P3F-RAD-LPR control particles for 48 and 72 hours. Control particles did not show any
effect on PAX3-FOXO1 fusion (Green box).
5.23 Inhibition of tumor initiation
In order to evaluate the effect of PAX3-FOXO1 down regulation in vivo, the LPR
particles were tested initially to inhibit tumor initiation. 20x106 cells of Rh30 (passage
12) were subcutaneously grafted in 5-6 weeks old female SCID/Beige mice at the
right flank. The Rh30 cells were allowed to settle down at the host system. After 90
minutes, the mice were given tail vain injection. Group 1 (n=9) was injected with
nuclease free water. Group 2 (n=10) was injected with Scrambled-RAD-LPR
particles. Group 3 (n=8) was injected with Scrambled-RGD-LPR. Group 4 (n=8) was
injected with P3F-RAD-LPR. Group 5 (n=10) was injected with P3F-RGD-LPR. 20µg
of siRNA (Lipid-Protamine-siRNA particle) were applied in every single injection for
three times in the interval of every three days. The siRNA concentration was 1mg/kg
body weight. The volume of the dose was adjusted to the body weight of the mice.
102
Figure 5.47 Inhibition of tumor initiation. LPR particles were injected 90 minutes after cell grafting.
Tumor progression in the treated group was delayed for nearly three weeks (M ± SD, n=8-10).
The tumors in the control group started emerging from day 13 onwards like a lump.
However, the tumors were measurable from day 21 onwards. In the treated group the
lump stated initiating after day 35 and grew to measurable size from day 37 onwards.
All the control group tumors grew in the same phase and reached a size of 1250-
1500 mm3 within 40 days. However, to reach the size of around 1000 mm3 there was
a delay of three weeks. Since the treatment started immediately after the grafting of
cells, the nanoformulations of the P3F-RGD-LPR handled these tumor cells
effectively and delayed the process of tumorigenesis. With this proof of concept, next
experiments to test the effect on tumor inhibition were planned with limited group.
Since all the controls shown nearly the same growth kinetics, the water control was
not selected for further experiments (Figure 5.47).
5.24 Tumor growth inhibition with 20µg concentration
The female SCID/Beige mice were grafted with 20x106 cells of Rh30 (passage 12)
subcutaneously at the right flank region. The tumor growth started as a lump on day
14 and became measurable from day 17 onwards. Four groups were treated with
Scr-RAD-LPR, Scr-RGD-LPR, P3F-RAD-LPR and P3F-RGD-LPR (n=8 for all
0.0
500.0
1000.0
1500.0
2000.0
20 25 30 35 40 45 50 55
Tum
or
volu
me
[m
m3 ]
Days after treatment
Water control n=9
Scr-RAD n=10
Scr-RGD n=8
P3F-RAD n=8
P3F-RGD n=10
103
groups). Tumors were allowed to grow up to a size of 250mm3. The doses of 20µg of
siRNA (Lipid-Protamine-siRNA particle) (siRNA concentration was 1 mg/kg) were
given in the interval of three days from day 18 onwards. The tumor size was
measured every four days.
Figure 5.48 Tumor growth inhibition in xenografted mice with Rh30 cells by 20µg siRNA in LPR.
All the animals treated with control particles have reached the optimal tumor volumes within 36 days.
In the treated group, tumor growth was delayed for a week (M ± SD, n=8).
The mice were scarified at a tumor volume of about 1500mm3. The Scr-RGD-LPR
particle showed slight inhibition in the tumor growth that might be due to the effect of
RGD. However, there was a distinct delay of around seven days in the tumor growth
in order to reach the size of 1500mm3 in the P3F-RGD-LPR treated group. Due to
this significant tumor growth inhibition, it was decided to increase the dose up to
40µg for only two groups in the next experiment (Figure 5.48).
5.25 Tumor growth inhibition with 40µg concentration
SCID/Beige mice were grafted with 20x106 cells of Rh30 (passage 12)
subcutaneously at the right flank region in order to develop the tumor up to a volume
0
500
1000
1500
2000
15 20 25 30 35 40
Tum
or
volu
me
[m
m3]
Days after treatment
Scr-RAD n=8
Scr-RGD n=8
P3F-RAD n=8
P3F-RGD n=8
104
of 250mm3. Lumps started emerging on day 13 and became measurable from day 17
onwards. Only two groups were treated with Scr-RAD-LP and P3F-RGD-LPR (n=8
for both groups). The doses of 40µg of siRNA (Lipid-Protamine-siRNA particle)
(siRNA concentration was 2 mg/kg) were given in the interval of three days from day
19 onwards. The tumor size was measured every four days.
Figure 5.49 Tumor growth inhibition in xenografted mice with Rh30 cells by 20µg siRNA in LPR.
The treated group displayed around 10 days delay. Water control group showed to cross the optimal
cut-off size during day 35 (M ± SD, n=8).
The mice were scarified at a tumor volume of about 1500mm3. The tumor delay when
compared to the control group was nearly ten days. Also the tumor size has gone
down after the first two doses. However, the tumor started growing during the third
dose. Although the raise in the dose did not delay the tumor inhibition by a factor of
two as compared to the 20µg dose, further delay of three days was observed to
reach the same volume. Also the growth kinetics of the tumor at different time points
showed the effect of the 40µg dose. Even with such a strong dose, the tumor growth
was not fully inhibited (Figure 5.37). After the third dose the tumor remission started
again. This indicates targeting PAX3-FOXO1 alone may not be sufficient to inhibit the
tumor totally. However, effective targeting is successful to deliver a combination of
P3F-siRNA along with one or more siRNAs against other downstream aberrant
signals like CXCR4, FGFR4, IGF1R, MET, MYCN etc.
0
500
1000
1500
2000
15 20 25 30 35 40 45
Tum
or
volu
me
[m
m3]
Days after treatment
Scr-RAD n=8
P3F-RGD n=8
105
5.26 In vivo tolerance of LPR
The mice treated with LPR were monitored for different parameters (Table 1). All the
mice gained significant weight. There was no significant change observed in the liver
function and kindney function parameters before and after the treatment. There was
no difference observed in fecal consistency during and after the LPR injections. The
components of this LPR nanohybrid system appeared to be safe.
106
107
6. Conclusion
Due to the therapeutic complexities associated with the aggressive tumor tissues
such as drug resistance, ineffective therapy in advanced stages and relapse, there is
a demand to explore new drug targets and discovery approaches. Recent
advancements in the molecular analysis of PAX3/7-FOXO1 fusion positive alveolar
rhabdomyosarcoma have identified several therapeutic targets. Identification of the
associated aberrant genetic alterations that contribute to the development and
progression of the cancerous tissue is relevant for developing novel anticancer
therapeutics. Targeting the oncogene involved in the cycle of aberrant signaling
pathways or mutated genes that suppress the induction of cell death will be one
among the ideal targets for cancer gene therapy. Although targeting specific
oncogenic chimeras is a viable therapeutic approach, the rare tumor context in which
these fusion genes are expressed presents considerable challenges [Olanich M and
Barr F 2013].
Tumor specific targeted therapy aims to exploit such biological features that suppress
the genes involved in proliferation and induction of cell death. In contrary to
conventional chemotherapy that is non-specific and targets both healthy and
malignant cells, targeted therapy through functionalized ligands, aim to be tumor
specific. Gene therapy that targets the unique cancer causing fusion-transcripts and
their induced signals, would only kills the cancer cells, sparing the healthy ones. This
approach would provide effective cancer treatment with fewer short term and long
term side effects.
Despite more than 800 new anticancer drugs estimated to be in clinical development
for adult tumors, the biopharmaceutical industry does not conduct preclinical
research on development for rare cancers [Norris RE and Adamson PC 2012].
Rhabdomyosarcomas are rare heterogeneous pediatric tumors that are treated by
surgery, chemotherapy and irradiation. Alveolar rhabdomyosarcoma accounts for 20-
30% of rhabdomyosarcoma and out of that 60-70% are caused by PAX3-FOXO1 and
20% by PAX7-FOXO1 fusion transcript. Regulating the expression of the fusion
protein through gene silencing or small molecule inhibition along with conventional
therapy may open up better treatment outcome.
108
This study is aimed to evaluate the effect of gene silencing of the fusion transcript
PAX3/7-FOXO1 and its therapeutic significance in vitro and in vivo. By implementing
the combination of siRNA design rules along with different filters, site specific siRNAs
were developed for the PAX3/7-FOXO1 fusion transcript. These siRNAs will be
validated for their safety and toxicity in vitro and be ensured for non-inflammatory
therapeutic applications. Dicer substrate siRNAs (DssiRNA) and chemically modified
siRNAs have proven to have enhanced target down regulation and stability. They
were tested in vitro in this study. Down regulation of PAX3-FOXO1 and PAX7-
FOXO1 targets exhibited direct impact on other over expressed pro-oncogenic
signals.
Down regulation of the fusion transcript has shown enhanced inhibition of cell
proliferation without significant apoptotic induction. This could be due to other factors
involved in ARMS. Such factors regulate the pro-survival growth of the cell by
overpowering the apoptotic machinery. Targeting other over expressed downstream
candidates like MET and MYCN along with PAX3-FOXO1 exhibited enhanced
apoptosis and proliferation after 48 hours. RGD targeted lipid protamine siRNA
particles showed efficient delivery and down regulation of the PAX3-FOXO1. ARMS
cell lines treated with these LPR particles showed significant proliferation inhibition
even after 72 hours. By using RGD peptide as a targeting ligand, these LPR particles
enhanced cellular delivery and longtime proliferation inhibition, however, induction of
apoptosis was not very apparent.
Xenograft tumor generation was done through Rh30 cell lines. With three doses of
20µg of siRNA, the LPR particles inhibited tumor initiation significantly for three
weeks. Tumor growth inhibition was delayed for a week at 20µg concentration.
However, even with 40µg siRNA concentration tumors were not totally inhibited. They
were not effective in reducing the tumor growth. However, it is difficult to conclude
this with only three doses. More frequent doses and non-invasive measurement of
the tumor volume and progression may reveal the effect of PAX3-FOXO1 target
down regulation and the impact on migration/metastasis and tumor inhibition. Several
studies have shown that PAX3-FOXO1 alone is not sufficient for complete oncogenic
transformation in ARMS [Linardic CM, 2008; De Giovanni C, Landuzzi L, 2009;
Hettmer S and Wagers AJ 2010]. In association with several other genetic lesions,
109
PAX3-FOXO1 expression is capable of transforming human and murine cells to
recapitulate ARMS tumors [Linardic CM, 2008; De Giovanni C, Landuzzi L, 2009].
Thus, this could explain why targeting PAX3-FOXO1 alone was not sufficient for total
tumor inhibition.
Several RMS cell lines were used for all in vitro experiments. However, these cell
lines and induced xenograft tumor do not succeed to mimic the real pathophysiology
of PAX3/7-FOXO1 fusion positive ARMS cases in patients. Using primary culture
derived from the patients for in vitro experiments followed by patient derived
xenograft (PDX) mice model for further validation would have been a better approach
for such studies to access the reality of drug response. In addition, several biological
challenges like heterogeneity of the cell lines used for in vitro validations, tumor
heterogeneity, physiology of tumor microenvironment and pattern of gene expression
at initial and relapse cases need to be considered for future therapeutic development.
In this study, fusion transcript sequence specific siRNAs were developed and
validated. Highly effective dicer substrate siRNAs and chemically modified siRNAs
were evaluated for longer RNAi activity. In addition, enhanced proliferation inhibition
was achieved by the down regulation of fusion transcript. However, targeting the
fusion transcript alone is not therapeutically significant. Delivering a combination of
P3FsiRNA along with one or more siRNAs against other downstream aberrant
signals could eventually enhance the therapeutic significance. However, effective
inhibition of tumor initiation could be exploited in the clinical setting. Introducing
maintenance treatment after “conventional” systemic and local therapy in ARMS with
regular administration of fusion gene specific siRNA-LPR could help to prevent tumor
relapse and secure complete remission. Targeting the integrin receptor of ARMS
through RGD tagged lipid-protamine based nanoparticle delivery system has shown
to exhibit a promising approach in the treatment of residual disease of alveolar
rhabdomyosarcoma.
110
7. Significant outcome of the work
Design of fusion specific siRNAs and DssiRNAs
Validation of chemical modification for higher RNAi activity
Development of shRNA clones for long time silencing
Development of iLenti DssiRNA clones for conditional expression
Validation of downstream targets of fusion transcript
siRNA design for the downstream targets
In vivo and in vitro Therapeutic validation of PAX3-FOXO1
Combination siRNA therapy along with miRNAs
111
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“…… the only tired I was, was tired of giving in.” – Rosa Parks. December 1, 1955.