in vitro and in vivo validation of gene silencing

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


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


HiPerfect transfection reagent Qiagen GmbH, Hilden

Attractene transfection reagent Qiagen GmbH, Hilden

RNase free water Sigma-Aldrich Chemie GmbH

3.5 RNA isolation


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


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


Anti-CD4-PE antibody BD Biosciences, Heidelberg

Anti-CD8-FITC BD Biosciences, Heidelberg

Isotype control BD Biosciences, Heidelberg

3.8 qPCR


Quantitect Reverse transcription kit Qiagen GmbH, Hilden

Quantifast SYBR Green kit Qiagen GmbH, Hilden

3.9 Western blot


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


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


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


SureSilencing Qiagen GmbH, Hilden

iLenti siRNA expression system Applied Biological Materials Inc, Canda

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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


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


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

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100 48 h

72 h

***

*

******

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Rh30

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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-

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72 h

***

*

******

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Rh41

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(%

)

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

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(%

)

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

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80

100

120 48 h

72 h************

************

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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

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%)

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

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120P7F-siRNA

P3F-siRNA

Rela

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%)

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

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40

60

8048 h

72 h

Rela

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%)

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

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60

80

10048 h

72 h

Rela

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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-

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100 48 h

72 h

****

******

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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

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6048 h

72 h

*** ***

** *

%of

gate

d c

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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

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60

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100

12048 h

72 h***

***

Rh30

Rela

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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

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0

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93

Con

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Con

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P3F

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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

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d c

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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

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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]


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]


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.

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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