author manuscripts have been peer reviewed and...

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Systematic screening identifies dual PI3K and mTOR inhibition as a conserved 2

therapeutic vulnerability in osteosarcoma 3

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Ankita Gupte1,12, Emma K Baker1,12, Soo-San Wan2, Elizabeth Stewart3, Amos Loh3, Anang 5

A. Shelat4, Cathryn M. Gould5, Alistair M Chalk1, Scott Taylor1, Kurt Lackovic2, Åsa 6

Karlström3, Anthony J Mutsaers1,6, Jayesh Desai7, Piyush B Madhamshettiwar3, Andrew CW 7

Zannettino8, Chris Burns2, David CS Huang2,13, Michael A Dyer3,9,13,14, Kaylene J 8

Simpson5,10,13 & Carl R Walkley1,11,13,14 9

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1St. Vincent’s Institute of Medical Research and Department of Medicine, St Vincent’s 11

Hospital, University of Melbourne, Fitzroy, VIC 3065, Australia; 12

2The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, 13

University of Melbourne, Parkville, VIC 3052, Australia; 14

3Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, 15

Memphis, TN 38105, USA; 16

4Department of Chemical Biology and Therapeutics, St. Jude Children’s Research Hospital, 17

Memphis, TN 38105, USA; 18

5Victorian Centre for Functional Genomics, Peter MacCallum Cancer Centre, East Melbourne, 19

VIC 3002, Australia; 20

6Ontario Veterinary College, University of Guelph, Guelph, Ontario N1G 2W1 Canada. 21

7Department of Medical Oncology, Royal Melbourne Hospital and Peter MacCallum Cancer 22

Centre, Melbourne, VIC 3002, Australia 23

8Myeloma Research Laboratory, School of Medical Sciences, Faculty of Health Sciences, 24

University of Adelaide, Adelaide, SA 5005, Australia and Cancer Theme, South Australian 25

Health and Medical Research Institute, Adelaide, SA 5000, Australia; 26

9Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA; 27

10Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 28

3052, Australia 29

Research. on June 21, 2018. © 2015 American Association for Cancerclincancerres.aacrjournals.org Downloaded from

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http://clincancerres.aacrjournals.org/

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11ACRF Rational Drug Discovery Centre, St. Vincent’s Institute of Medical Research, Fitzroy, 30

VIC 3065, Australia. 31

12Co-first authors 32

13Co-senior authors 33

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14Correspondence address: 35

Carl Walkley 36

St Vincent’s Institute, 37

Fitzroy, Victoria 3065, 38

Australia 39

Telephone number: +61 (3) 9231 2480 40

E-mail address: [email protected] 41

42

Michael Dyer 43

Department of Developmental Neurobiology, 44

St. Jude Children’s Research Hospital, 45

Memphis, TN 38105, USA 46

Telephone number: +1 (901) 595-2257 47

E-mail address: [email protected] 48

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Keywords: Osteosarcoma, PI3K, mTOR, siRNA screen, chemical screen 50

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Running Title: PI3K/mTOR inhibitors in osteosarcoma 52

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Conflict of Interest Statement: Dr Jayesh Desai is a consultant for Novartis, Pfizer, GSK, 54

Bayer, Sanofi, Circadian, and Bionomics and receives research support from Novartis, GSK, 55

and Roche. 56

The remaining author discloses no conflicts of interest. 57

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Financial Information: This work was supported by grants from the AACR-Aflac Inc, Career 59

Development Award for Pediatric Cancer Research (C.W.; 12-20-10-WALK); Colin North 60

(CW); Zig Inge Foundation (C.W.); 5point foundation (to E.B); Cancer Council of Victoria (to 61

C.W. and E.B.; Grant-in-Aid APP1047593); NHMRC Career Development Award (C.W.; 62

APP559016); NHMRC Research Fellowship (D.H.; APP1043149); Cure Cancer Australia 63

Foundation Fellowship (E.B); NHMRC Program grant (D.H.; APP1016701); LLS Specialized 64

Center of Research (C.B., D.H.; 7001-13); NHMRC IRIIS grant (to SVI and WEHI); in part by 65

the Victorian State Government Operational Infrastructure Support Program (to SVI and 66

WEHI); The Victorian Centre for Functional Genomics is funded by the Australian Cancer 67

Research Foundation (ACRF), the Victorian Department of Industry, Innovation and Regional 68

Development (DIIRD), the Australian Phenomics Network (APN) and supported by funding 69

from the Australian Government’s Education Investment Fund through the Super Science 70

Initiative, the Australasian Genomics Technologies Association (AMATA), the Brockhoff 71

Foundation and the Peter MacCallum Cancer Centre Foundation; M.A.D is an Investigator of 72

the Howard Hughes Medical Institute; C.W. is the Philip Desbrow Senior Research Fellow of 73

the Leukaemia Foundation. 74

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Statement of Translational Relevance 78

Current therapy for osteosarcoma relies on surgery and conventional chemotherapy. In 79

recent decades, survival rates have plateaued. Improvements in patient outcome have largely 80

been derived from improved delivery of existing agents, rather than the introduction of novel 81

agents. To probe for new susceptibilities, we have undertaken independent genome wide 82

siRNA and chemical screens in murine models of human OS, identifying PI3K and mTOR 83

pathways as therapeutic vulnerabilities. Our studies demonstrate that dual inhibition of PI3K 84

and mTOR pathways, but not either pathway independently, led to apoptosis of OS cells. 85

These findings were recapitulated in genetically diverse primary human OS samples in 86

separate facilities. These data demonstrate that dual PI3K/mTOR inhibitors warrant 87

prioritization for development as a strategy to treat osteosarcoma. 88

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Abstract 90

Purpose: Osteosarcoma (OS) is the most common cancer of bone occurring mostly in 91

teenagers. Despite rapid advances in our knowledge of the genetics and cell biology of OS, 92

significant improvements in patient survival have not been observed. The identification of 93

effective therapeutics has been largely empirically based. The identification of new therapies 94

and therapeutic targets are urgently needed to enable improved outcomes for OS patients. 95

Experimental Design: We have used genetically engineered murine models of human OS in 96

a systematic, genome wide screen to identify new candidate therapeutic targets. We 97

performed a genome wide siRNA screen, with or without doxorubicin. In parallel a screen of 98

therapeutically relevant small molecules was conducted on primary murine and primary 99

human OS derived cell cultures. All results were validated across independent cell cultures 100

and across human and mouse OS. 101

Results: The results from the genetic and chemical screens significantly overlapped, with a 102

profound enrichment of pathways regulated by PI3K and mTOR pathways. Drugs that 103

concurrently target both PI3K and mTOR were effective at inducing apoptosis in primary OS 104

cell cultures in vitro in both human and mouse OS, while specific PI3K or mTOR inhibitors 105

were not effective. The results were confirmed with siRNA and small molecule approaches. 106

Rationale combinations of specific PI3K and mTOR inhibitors could recapitulate the effect on 107

OS cell cultures. 108

Conclusions: The approaches described here have identified dual inhibition of the 109

PI3K/mTOR pathway as a sensitive, druggable target in OS and provide rationale for 110

translational studies with these agents. 111

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Introduction 114

Osteosarcoma (OS) is the most common primary tumor of bone. It occurs mostly in the 115

second decade of life and is the fifth most prevalent cancer in children. Patients with localized 116

disease have 5 year survival rates of ~70%. However, at presentation ~20% of patients have 117

metastases and almost all patients with recurrent OS have metastatic disease (1, 2). The 5-118

year survival for patients with metastatic disease is 20% (3, 4). Treatment relies on the use of 119

chemotherapy and surgery, which cause considerable morbidity (5). While substantial 120

advances in our understanding of OS biology and genetics have occurred, there have been 121

no significant advances in therapy for the past 30 years (6, 7). The first whole genome 122

sequence of mutations in human OS was recently generated, revealing TP53 pathway 123

mutations in all samples assessed and recurrent somatic changes in RB1, ATRX and DLG2 124

in 29-53% of the tumors (8). This analysis highlighted the complexity of the OS genome and 125

provides invaluable information for improving preclinical modeling of OS, however it does not 126

immediately reveal actionable strategies for improving therapy for patients. 127

To date, research has led to only a limited number of clinically relevant biologic insights 128

(9, 10). Empirical evaluation of novel agents in human xenografts has not to date yielded any 129

major translational advances (10). The only agent to show promise from these studies has 130

been mTOR inhibitors such as rapamycin (11). Improvements in the delivery and application 131

of existing treatments, rather than the introduction of new therapies, have seen some 132

improvement in the management of OS. Novel approaches to drug target identification are 133

needed alongside robust pre-clinical testing platforms. The development of genetically 134

engineered mouse models (GEMM), reflective of the human OS, represent a critical 135

component to improving patient outcomes and preclinical target validation (12). We previously 136

developed a GEMM of the fibroblastic OS subtype, through deletion of p53 and pRb from the 137

osteoblast-lineage that has been independently validated (13-15). We recently described the 138

first murine model of osteoblastic OS, the most common subtype of human OS (16). 139

Advances in technology and the capacity for high-throughput phenotypic and chemical 140

screens offer considerable promise for identifying new therapeutic agents. Screening 141

approaches afford an opportunity for an unbiased, saturation coverage of the genome. 142

Genome-wide siRNA screens offer an unmatched probing of the genetics of OS, but the 143




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immediate clinical utility of many identified candidates, such as transcription factors, may be 144

limited as they are not modifiable using current therapeutic approaches. Chemical screens 145

with drugs that are in clinical or pre-clinical use interrogate a limited spectrum of targets but, if 146

validated, offer the prospect of a more rapid clinical application if validated (17). Given the 147

limited advances in translating basic knowledge of OS biology to patient benefit an approach 148

utilizing systematic screening of drugs or focusing on defining genetic susceptibilities of OS 149

could offer a new means to identify new potential candidates for either preclinical testing or 150

further development. 151

Here we report results from parallel screens using primary cell cultures derived from 152

murine OS models which faithfully replicate the human disease (13, 16). Firstly, a whole 153

genome siRNA screen for enhancers of cell death was performed. The screen was conducted 154

with either siRNA alone or as siRNA with doxorubicin, a standard of care chemotherapy for 155

OS (5). Secondly, a curated drug/chemical library predominantly targeting kinases or known 156

targets was screened against three independent primary cell cultures derived from paired 157

primary and metastatic OS. Validation across mouse and human biopsy derived primary OS 158

cell cultures established the robustness of our analyses. These complementary chemical and 159

genetic strategies have converged to provide independent evidence that concurrent targeting 160

of protein translation and growth control pathways, in particular the PI3KCA and mTOR 161

pathways, represent tractable targets in OS. 162

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Materials and Methods 165

OS cell cultures and mouse models 166

Primary mouse OS cell cultures were derived from tumors generated in either Osx-Cre 167

p53fl/flpRbfl/fl mice (fibroblastic OS model) (13) or Osx-Cre TRE-p53.1224 pRbfl/fl model 168

(osteoblastic OS model) (16) (all obtained directly from mouse models of OS). Experiments 169

using mouse OS models were approved by the St Vincent’s Hospital AEC. Primary human 170

OS (OS17) was derived from a primary human OS xenograft generously provided by Dr Peter 171

Houghton (Nationwide Children’s Hospital, Ohio). Excess, de-identified tumor material was 172

collected from patients with osteosarcoma at St Jude Children’s Research Hospital (SJCRH) 173

in agreement with local institutional ethical regulations and IRB approval. Primary human OS 174

(SJOS001112_X1, SJOS010929_X1, SJOS001107_X1, SJOS001107_X2) were derived 175

from primary human xenografts collected from patients with osteosarcoma at SJCRH. Human 176

OS cell lines MG-63, Saos-2, U2OS, G-292, 143B and SJSA-1 were purchased from ATCC 177

(MG63 from ECACC cell line remainder from ATCC; no authentication performed by the 178

authors). Normal human osteoblasts were derived from bone marrow aspirates from the 179

posterior iliac crest of healthy human adult donors (17–35 years of age), with informed 180

consent (IMVS/SA Pathology normal bone-marrow donor program RAH#940911a). The cells 181

were outgrown from the bony spicules that were collected following filtration of the BM 182

through a 70μm filter. Cell cultures were grown in αMEM with 10% FCS (non-heat 183

inactivated), 1% Penicillin/Streptomycin and 1% Glutamax supplement. 184

185

High-throughput siRNA whole genome screen 186

OS cell line 494H (Cre:lox model derived cell line representative of fibroblastic OS passage 8 187

from derivation from primary tumor) were grown and transfected with SMARTpool siRNAs 188

using DharmaFECT lipid 3 transfection reagents (Dharmacon GE). The mouse siRNA library 189

(Dharmacon GE) consists of 16,874 individual protein coding genes consisting of the 190

following gene families all designed to RefSeq52. Cells were reverse transfected (18) at 400 191

cells per well with 40nM of the siGENOME SMARTpool library complexed for 20 minutes with 192

DharmaFECT 3 using the Sciclone ALH3000 (Caliper Life Sciences) and BioTek 406 193

(BioTek) liquid handling robotics. Cell lines were transfected in quadruplicate (day 0) and one 194




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set of duplicates treated as control (siRNA only) and a second set of duplicates treated after 195

48hrs (day 2) with 100nM doxorubicin. At 120hrs post transfection (day 5) the cell viability for 196

each well was quantified on the basis of the direct measurement of intracellular ATP using the 197

CellTiter-Glo luminescent assay (Promega) at a 1:2 dilution. Full analysis methods are 198

provided in the supplemental information. RNAi screen data is available from Pubchem with 199

PubChem accession ID #1053208 (primary screen) and PubChem AID# 1053209 (validation 200

screen) and in Supplemental Dataset 1. RNA-seq data from mouse OS models is deposited 201

in GEO (GSE58916). 202

203

Small molecule screen against primary mouse OS paired samples 204

Three independent sets of paired primary and metastatic OS cell lines (from fibroblastic OS 205

model, less than or equal to passage 8 from derivation (13)) were plated at 400 cell/well in 206

384-well plates. After 24hrs the cells were treated with the 131 different compounds in an 11-207

point dose response ranging from 0.01-10mM. All assays were performed in duplicate. At 208

48hr post treatment the cell viability for each well was quantified on the basis of the direct 209

measurement of intracellular ATP using the CellTiter-Glo luminescent assay (Promega) at a 210

1:2 dilution. All luminescent measurements were taken on the EnSpire plate reader 211

(PerkinElmer, Waltham, MA, USA). Data was plotted and the IC50 calculated using Prism 6 212

software. 213

214

Small molecule screen against primary human xenograft-derived OS 215

Excess, de-identified tumor material was collected from patients with osteosarcoma at 216

SJCRH in agreement with local institutional ethical regulations and institutional review board 217

approval. Small molecule/drug screening was performed as previously described (19, 20). 218

219

Cell death assays 220

Cells were treated with the indicated drug or vehicle control for 48hrs prior to harvesting. Cells 221

were washed with PBS and 100,000 cells were stained in 1xAnnexin Binding buffer (BD 222

Biosciences) diluted 1:20 with Annexin V-APC (1mg/ml) (BD Pharmingen) and 7-223

Aminoactinomycin D (7AAD) (100μg/ml) (Life Technologies) for 15 min protected from light. 224




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Following the addition of 4 volumes of 1xAnnexin Binding buffer, apoptotic cells were 225

quantified using FACS (LSRFortessa, BD Biosciences). Live cells (Annexin V negative, 7AAD 226

low) and cells in early and late stages of apoptosis (Annexin V positive, 7AAD low/high) were 227

analyzed using FlowJo software (v8.8.7) (Ashland, OR, USA). Each cell line was assessed in 228

duplicate in three separate biological experiments. 229

230

Statistical analysis (excluding siRNA screen which is described separately) 231

Each experiment is represented as the mean±SEM calculated from biological replicates 232

unless otherwise stated. Unpaired parametric Student’s t-test was used to compare results 233

unless otherwise stated. Where indicated in legends, unpaired nonparametric Mann Whitney 234

ranks test or 2-way analysis of variance (2-way ANOVA) were used to compare groups. Data 235

was log transformed to normalize variances before 2-way ANOVA. In all analyses, statistical 236

significance of p<0.05, p<0.01, p<0.001, and p<0.0001 are represented as *, **, ***, **** 237

respectively. Prism 6.0e software was used for statistical analyses. 238

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Results 240

Whole OS genome siRNA screen to identify OS susceptibilites 241

We sought to identify, in a genome-wide fashion, inducers of OS cell death and in parallel 242

sensitizers to doxorubicin-induced cell death. Doxorubicin is a standard of care agent in the 243

management of OS (5). The screen was performed in early passage cell cultures established 244

from the murine Osx-Cre p53fl/flpRbfl/fl OS model (fibroblastic OS) (13). A genome wide screen 245

was performed using a library containing >16,000 siRNAs targeting murine protein-coding 246

genes (each siRNA pool has 4 individual siRNA against the same target). Mouse OS cells 247

were treated with either siRNA alone or, on a duplicate plate, siRNA in combination with 248

100nM doxorubicin (siRNA + doxorubicin; Figure 1A). The dose of doxorubicin was titrated to 249

achieve ~45% cell death as a single agent. All plates were screened in duplicate under both 250

conditions. A robust z-score sample based normalization strategy was performed across the 251

screen. To be classified as a hit a candidate had to have a robust z-score ≤-2 and a viability 252

of equal to or less than 70% (fold change of ≤0.7) when compared to the respective non-253

targeting siRNA control for each treatment arm (NT1, Figure 1B-C). A total of ~270 hits were 254

identified from the primary screen that passed statistical analysis and robust z-score 255

stratification. A difference of at least 25% between siRNA alone and siRNA+doxorubicin was 256

categorized as an interaction after filtering based on robust z-scores (Figure 1D). We further 257

triaged candidates based on their expression in RNA-seq/microarray datasets from GEMM 258

OS models. The top 299 candidates that enhanced cell death were then validated by 259

deconvolution of the SMARTpool into its constituent 4 individual siRNAs and re-screening 260

using the same assay. Of the primary screen hits, 113 validated with 3 or more of the 261

individual siRNA recapitulating the primary screen result (37.7%), considered high confidence 262

targets. A further 38 candidates were validated with 2 of the individual siRNA, and were 263

classified as medium confidence hits. In total approximately 50% of the primary screen hits 264

validated (Figure 2A-C). 265

A range of candidates that reduced cell viability independently of whether doxorubicin 266

was present in addition to those that specifically enhanced the toxicity of doxorubicin were 267

identified (Figure 2A-D). While not strongly powered to detect loss of function alleles involved 268

in resistance to doxorubicin, several candidates were identified (Figure 2A) including siRNA 269




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against topoisomerase 2a (Top2a), the cellular target of doxorubicin (21, 22), and a number 270

of pro-apoptotic genes such as Bid (Figure 1B, Supp Figure 1A-B). A significantly higher false 271

positive rate on the candidates that prevented cell death was apparent, with only Top2a and 272

Bid robustly validating of the 60 candidates tested. From the enhancers of doxorubicin 273

induced death we identified 266 siRNA candidate genes (1.576%) that fulfilled the 274

classification criteria (subset visualized in Figure 2B). Analysis of the hits interacting with 275

doxorubicin revealed a marked enrichment of candidates on chromosome 7 (p=4.77x10-11, 276

FDR=3.68x10-8; statistics derived from DAVID analysis), relevant as the loss of one to two 277

copies of chromosome 7 from a tetraploid karyotype was recurrently noted in the murine OS 278

models (16). Using Ingenuity Pathway Analysis software, we tested if the identified hits 279

functioned in overlapping pathways/gene expression signatures (Figure 2A-B). Pathways 280

enriched included those associated with RNA transport (Ran) and RNA splicing, in particular 281

the U2 splicing complex (Figure 2A-B, Supp Figure 1C). Eleven of the 13 identified U2 snRNP 282

complex members in mammals were identified in the screen. In contrast, we did not observe 283

enrichment for any other snRNP complexes, suggesting a specific requirement for the U2 284

snRNP complex in OS pathogenesis (Figure 2B). The most significantly enriched pathways 285

were associated with protein translation and mTOR signaling (Figure 2A-D). 286

Next we tested if small molecules targeting the identified pathways demonstrated 287

toxicity against OS cells. The agents were tested against a primary human OS xenograft-288

derived cell culture (OS17) and murine primary tumor derived cultures from both fibroblastic 289

(494H) and osteoblastic (148I) OS models. We tested a Ran inhibitor, an inhibitor of the U2 290

splicing complex member Sf3b spliceostatin A (SSA, (23)), and the proteosome inhibitor 291

bortezomib (Figure 3A-C). All agents showed activity against the OS cells, although the 292

specificity of the bortezomib response was indeterminate given its reported in vitro activity 293

against a large panel of solid tumors. Given the enrichment of the U2 snRNP specifically in 294

the siRNA screen and the potent activity of SSA, we sought to further understand the effects 295

of impaired U2 snRNP activity in OS. We treated fibroblastic and osteoblastic mouse OS cells 296

with non-targeting or siRNA against S3fb1 and U2af1, both components of the U2 snRNP 297

(Figure 3B). In both cases, cell death as measured by cleaved capsase-3 levels was 298

observed. Treatment of human or mouse OS cells with SSA resulted in impaired splicing of 299




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p27 and detection of an aberrant protein isoform (p27*), a known consequence of Sf3b1 300

inhibition (Figure 3C, Supp Figure 2). Consistent with the siRNA results, SSA treatment 301

resulted in massive induction of apoptosis in fibroblastic and osteoblastic murine OS, 302

consistent with the low nM IC50 in these cells. These studies identify a range of susceptibilities 303

in OS cells that had not been previously observed. Furthermore, these targets were validated 304

by independent means using chemical or drugs that target these processes. 305

306

Kinase Inhibitor screen: dual PI3K/mTOR inhibitors show strong activity against OS 307

The activity of a chemical library of 131 primarily kinase inhibitors, either currently in clinical 308

trial and those that either failed trial or were not developed further, as single agents was also 309

assessed. The screen was conducted in duplicate on 3 sets of paired primary and metastatic 310

early passage OS cell cultures derived from the murine fibroblastic OS model (Figure 4A). OS 311

culture (494H) was also used for the siRNA screen. Cell viability was determined after 48hrs 312

exposure to the agents and a dose response curve established. 313

The chemical screen identified 8 compounds with activity as single agents in the sub-314

1μM range (6.1%, Figure 4A). Of the active agents there were 2 multi-kinase inhibitors 315

(Ponatinib and Dasatinib), a CHK inhibitor (AZD7762), flavopiridol (CDK inhibitor) and a PLK-316

1 inhibitor (BI-2536(R-)). Plk-1 siRNA was used as a positive control for our siRNA screen so 317

it was known that inhibition of PLK was toxic to OS cells. Of particular interest were 3 318

compounds with an overlapping spectrum of targets. PIK-75, GSK2126458 and BEZ-235. All 319

target phosphatidylinositide 3-kinases (PI3K) together with mTOR and/or DNA-PK (Supp 320

Figure 3). The effect was specific to these dual inhibitors as we did not observe low IC50 321

values with an additional 14 agents with PI3K restricted activity. Additionally, the specific 322

mTORC1/2 inhibitor (KU0063794), the DNA-PK inhibitor (NU7441) and several specific Akt 323

inhibitors (Akt-I-1; Akt-I-1/2) did not exhibit potent activity (sub-1μM, Figure 4B). These 324

findings suggested that concurrent inhibition of both the PI3K and another pathway (mTOR or 325

DNA-PK) was most likely responsible for the observed activity. We did not observe any 326

differential sensitivity between the primary and metastatic paired samples. The combined 327

overlap of the results from chemical and genetic screening revealed a profound enrichment 328

for cell growth/protein translation regulation pathways as a vulnerability in OS. We further 329




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tested PIK-75, GSK2126458 and BEZ-235 across a panel of OS cultures encompassing 330

murine osteoblastic OS, murine fibroblastic OS, an established human OS line (MG63) and a 331

primary human OS xenograft-derived cell culture (OS17). The activity was confirmed with 332

independent stocks of drug and facilities and on all OS cell cultures tested (Figure 4C). 333

334

Primary human OS also display sensitivity to dual PI3K/mTOR inhibitors 335

Our data indicated that dual targeting of the PI3K/mTOR pathway represents an effective 336

strategy to induce OS cell death. To extend our analysis and expand the genetic diversity of 337

the primary human OS that were assessed, we tested a targeted range of small molecule 338

inhibitors against a panel of acute short-term cultures of primary OS material derived from 339

orthotopic xenografts (8, 20). The established human OS cell lines Saos-2 and U2OS were 340

also included. Strikingly the most active agents against primary human OS cultures were dual 341

PI3K and mTOR inhibitors (GSK2126458, PKI-587, BEZ-235 and BGT-226; Figure 4D). 342

Therefore the sensitivity to concurrent inhibition of PI3K and mTOR pathways is conserved 343

across species and subtypes. These data provide a strong rationale, obtained from 344

systematic screening, for the testing of dual PI3K/mTOR pathway inhibitors in OS. 345

346

Induction of OS cell apoptosis by dual inhibition PI3K and mTOR pathways 347

Of the small molecule inhibitors identified, PIK-75 cannot be directly clinically applied and 348

BEZ-235 has ceased clinical development. Therefore, we tested compounds that could be 349

clinically translated including GSK2126458 and included a second PI3K/mTOR active agent 350

PKI-587 (24, 25) (Supp Figure 3A-C). GSK2126458 and PKI-587 could be combined with 351

doxorubicin in vitro with no reduced effectiveness of either agent (Supp Figure 3D-G). Both 352

agents inhibited phosphorylation of known targets downstream of PI3K/mTOR in a dose 353

dependent manner in mouse OS subtypes and human primary OS cell cultures (Figure 5A). 354

Next we assessed if GSK2126458 and PKI-587 were inducing changes in cell cycle 355

distribution or cell death. There was a significant increase in cells in the G0/G1 phase of the 356

cell cycle in both mouse and human OS cells treated with GSK2126458 and to a lesser 357

magnitude with PKI-587 (Figure 5B). In all cells tested there was a dose dependent increase 358

in the induction of apoptosis as determined by Annexin-V/7AAD staining or the presence of 359




15

cleaved caspase-3 (Figure 5C-D). In all three OS cell models tested, GSK2126458 was more 360

potent at inducing apoptosis than PKI-587, despite similar effectiveness at inhibiting 361

downstream signaling events (Figure 5C-D). 362

363

Combining PIK3CA and mTOR inhibitors as a therapeutic approach 364

The activity of the dual PI3K/mTOR inhibitors corresponded most closely with activity against 365

PIK3CA (Figure 4B). We determined the expression of the different catalytic subunits of PI3K 366

in murine OS subtypes and in human OS and normal human osteoblasts. The murine OS 367

tumors had the highest expression of Pik3ca and Pik3cb with low to undetectable levels of 368

Pik3cd and Pik3cg (Figure 6A). This pattern of expression was mirrored in normal human 369

osteoblasts and OS samples (Figure 6A). Given the relative isoform specificity of PIK-75, 370

GSK2126458 and BEZ-235, this indicated that the activity was most likely primarily mediated 371

by inhibition of PIK3CA together with mTOR. To directly test the requirement for inhibition of 372

PIK3CA, we used siRNA to knockdown the PIK3CA and PIK3CB. Knockdown of Pik3ca in 373

mouse OS and PIK3CA in human OS cells resulted in significantly reduced viability (Figure 374

6B). When the siRNA was combined with the specific mTOR inhibitor everolimus, an 375

increased cell death compared to that achieved with either agent alone was observed. The 376

increased death from concurrent inhibition was more pronounced with PIK3CA compared to 377

PIK3CB knockdown, although the reduced viability with PIK3CB siRNA would suggest some 378

contribution from this isoform to the overall effect (Figure 6B, Supp Figure 4). We tested if 379

knockdown of mTOR, Raptor or Rictor could cooperate with inhibition of Pik3ca. The 380

knockdown of mTor was the most effective and when combined with the PIK3CA specific 381

inhibitor BYL719 resulted in significantly reduced cell viability compared to the siRNA alone 382

(Figure 6C, Supp Figure 4). These data demonstrate that specific targeting of either the PI3K 383

or mTOR pathways in isolation is not as effective at inducing OS cell death as dual inhibition. 384

Finally, we sought to determine if combinations of specific inhibitors of the PI3K and 385

mTOR pathway could be used to recapitulate the activity of the dual inhibitors. This may be 386

an approach amenable to translation as several pathway specific inhibitors have progressed 387

in clinical trial or, in the case of the everolimus, been approved (26). We tested combinations 388

of either the pan-PI3K inhibitor BKM120 or the PIK3CA specific inhibitor BYL719 (27) with 389




16

everolimus. When tested individually all agents failed to demonstrate significant activity 390

(Figure 6D). When combined, we observed a synergistic interaction between the BLY719 and 391

everolimus based on BLISS synergy scores (Figure 6D, Supp Figure 5). Both agents were 392

tolerated alone or in combination by normal osteoblasts in vitro, consistent with in vivo reports 393

with these and similar agents (Supp Figure 6; (28, 29)). Therefore agents currently in clinical 394

trial with activity against PIK3CA and mTOR could be combined and demonstrate efficacy 395

against OS in vitro. These data demonstrate the feasibility of dual targeting of the 396

PI3K/mTOR pathway in OS and propose a new therapeutic approach in this cancer. 397

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Discussion 399

To identify new therapeutic targets for OS we have made use of murine OS models 400

combined with primary human OS xenograft derived cell cultures (13, 16). These independent 401

approaches converged to identify dual inhibition of the PI3K/mTOR pathways as a species 402

conserved sensitivity in OS. The use of the primary tumor derived material from multiple 403

species strengthens the confidence in our data and provides a new approach to integrating 404

mouse models into preclinical target identification and validation. We observed in vivo activity 405

against OS of the dual PI3K/mTOR inhibitor GSK2126458 (Supp Figure 7). Supporting our 406

results are previous data testing a range of compounds that target single arms of these 407

pathways with evidence for some, albeit limited, in vivo activity against human OS xenografts 408

(11, 30-33). Dual PI3K/mTOR inhibitors were far more potent that PI3K selective agents on 409

established OS cell lines, further validating our observations with primary OS derived cells 410

(34). Most recently, exome capture of human OS and shRNA screening independently 411

confirmed that the PI3K/mTOR pathway is an attractive candidate in OS, supported by the 412

data from the screening and validation described here (35). 413

Of the pathways identified in our siRNA screen, the regulation of RNA processing and 414

splicing in OS is an intriguing finding. We recovered 11 of 13 members of the U2 snRNP 415

complex without significant enrichment for other complexes of the RNA splicing machinery in 416

cells treated with siRNA and doxorubicin (36). The OS cells were highly sensitive to inhibition 417

of Sf3b1 with SSA (23). Changes in RNA splicing are recognized as major contributors to 418

cancer, particularly hematological malignancy (37). Recently, other genetics screens have 419

identified RNA splicing machinery as preferentially required in cancer cells, with PRPF6 420

important in colon cancer (38) and PHF5a in brain cancer (39). These data suggest that 421

aberrant RNA splicing in OS are important in maintaining the tumor state and warrant further 422

investigation. The identity of the aberrantly spliced RNAs causing OS cell death OS cells is 423

currently unknown, however one candidate group of transcripts encode pro-death proteins 424

(40). We identified pro-apoptotic effectors as suppressors of doxorubicin-induced cell death in 425

our siRNA screen, providing a plausible link to the sensitivity of OS cells to U2 snRNP 426

inhibition. Another intriguing candidate was Mesogenin (Msgn), a bHLH transcription factor 427

that was the most potent inducer of OS cell death irrespective of the presence of doxorubicin. 428




18

While there is limited information relating to Msgn, the Msgn-/- mouse has defects in skeletal 429

development and Msgn act downstream of the Wnt and β-catenin pathways, both implicated 430

in OS (41, 42). It would be interesting to determine if Msgn is required for normal osteoblast 431

survival once the lineage is established, or analogous to the requirement for another bHLH 432

transcription factor SCL/tal-1 in hematopoiesis, it is only required developmentally for lineage 433

specification (43). If this were the case then developing strategies to target Msgn may be of 434

value. 435

Given the overlap between the siRNA and chemical/drug screen results we focused 436

our attention on understanding the contribution of the PI3K/mTOR pathway in OS. Recently 437

several groups have reported that agents working within this pathway have some activity in 438

OS (28, 29). Our pre-clinical screening has indicated the requirement for concurrent inhibition 439

of PI3K, in particular PIK3CA, and mTOR pathways. The screens reported herein provide a 440

rationale for combining PI3KCA and mTOR inhibitors, rather than the use of either inhibitor 441

alone, in OS. Recent OS studies from other groups have drawn attention to this pathway (28, 442

29, 44-46), yet our study is distinct from these as we have identified this pathway as a result 443

of independent chemical and genetic screens and can demonstrate that dual pathway 444

inhibition is the most potent. We further define that PI3KCA activity is the driver of this PI3K 445

activity in both human OS and mouse models of OS. The sensitivity to PI3K/mTOR inhibitors 446

is conserved across OS subtypes and across species, greatly strengthening the case that this 447

pathway should be tested clinically. 448

Our results using GSK2126458 and PKI-587 contrast with those described by Gobin 449

et al, who reported the effects of BEZ-235 (28). We identified BEZ-235 as active in our 450

chemical screen. We observe robust induction of apoptosis with both GSK2126458 and PKI-451

587 in murine and in primary human OS derived cells at significantly lower doses than that 452

reported on established murine or human OS cell lines (28, 29). Gobin et al reported a cell 453

cycle arrest in the absence of apoptosis when treating with up to 25μM BEZ-235 or the 454

PI3KCA specific agent BYL719. The discrepancy in effects is most likely a reflection of the 455

cells used for the respective studies. Our study has utilized early passage primary OS cell 456

cultures derived from either GEMM (at least 3 independent cultures of each subtype) or 457

multiple independent primary human OS cultures derived from xenografts. In contrast, Gobin 458




19

et al utilized a range of long established OS derived cell lines. Therefore, the age and nature 459

of the cells used may led to divergent effects on cell survival. The anti-OS activity of the 460

PI3K/mTOR inhibitors on primary OS cells is mediated via induction of apoptosis and cell 461

cycle arrest. 462

A large Phase II trial with single agent mTOR inhibitor ridaforolimus in sarcomas 463

noted some, albeit limited, activity in OS. Two partial responses in OS patients were seen, 464

which is interesting, but modest when a total of 54 patients with bone sarcomas were treated 465

(47). BEZ-235 has in vivo activity in preclinical OS models, supporting our preliminary data 466

(28). However BEZ-235 has been discontinued from further development, emphasizing our 467

focus on clinically utilizable agents. We demonstrate in vitro activity of the dual inhibitors 468

GSK2126458 and PKI-587 and the combination of the PIK3CA specific inhibitor BLY719 and 469

the mTORC1 inhibitor everolimus. BYL719 and everolimus are currently being tested together 470

clinically a Phase I/II trial in patients with in breast cancers, based on the observation that 471

dual inhibition of PIK3CA and mTORC reversed resistance of PIK3CA mutant breast cancer 472

to BYL719 monotherapy (48). This will act as a good indicator of how readily combinable 473

these two agents are in terms of clinical potency, manageable off-target effects, and possible 474

pharmacological interactions. 475

Through combining siRNA screening with targeted chemical library screens we have 476

identified a number of candidate targets in OS. The most directly translatable pathway is 477

PI3K/mTOR dual inhibition, with a number of agents already in clinical trial or approved. The 478

screens described herein provide a rational basis for detailed in vivo orthotopic 479

pharmacokinetic and pharmacodynamic studies and the assessment of these agents in 480

preclinical Phase I, II and III studies that will be required. Furthermore, using independent 481

approaches and validation across species, OS subtypes and facilities, we provide evidence 482

that PI3K/mTOR dual inhibition is an attractive therapeutic candidate for OS. 483

484




20

Acknowledgments 485

We thank the SVH BioResources Centre; L Purton, J Martin and J Heierhorst for comments 486

and discussion; D Thomas and Y Handoko (Victorian Centre for Functional Genomics, Peter 487

MacCallum Cancer Centre) for technical assistance and screening support; P Houghton 488

(Nationwide Children’s Hospital, Ohio) for providing human xenograft material; M Yoshida 489

(RIKEN) for generously providing Spliceostatin A; G Philip and C Sloggett at the Victorian Life 490

Sciences Computation Initiative for help with RNA-seq analysis and pipelines. 491

492

Requests for human OS material should be directed to Dr Michael Dyer at the Developmental 493

Biology and Solid Tumor Program, St. Jude’s Children’s Research Hospital. 494

495

Author contribution statement: 496

C.W., A.M., K.S. and D.H. conceived study; A.G., E.B., C.G., A.C., S.T., S.W, K.L, J.D., P.M., 497

A.Z. C.B., D.H., K.S. and C.W. performed experiments, analyzed and interpreted data; drug 498

screening against primary human OS xenograft derived cells was performed at St. Jude’s 499

Children’s Hospital by A.L., E.S., A.S., A.K. and M.D.; J.D., C.B., M.D., D.H., K.S. and C.W. 500

provided intellectual input and conceptual advice; C.W. wrote the manuscript; All authors 501

reviewed the manuscript. 502

503

504




21

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641

642




26

Figure Legends 643

Figure 1. Whole genome siRNA screen against murine OS. 644

(A) Schematic outline of the siRNA screen. (B) Primary screen results from either siRNA 645

alone (top panel, grey line) or siRNA + 100nM doxorubicin (lower panel, blue line). Each 646

assay was performed in duplicate and is plotted as robust z-score normalized to non-targeting 647

(NT1) control treated cells. Total numbers and selected candidates that increased viability 648

(robust z-score of ≥+2) or decreased viability (robust z-score of ≤-2). (C) Primary screen 649

results based on robust z-score for the indicated groups; (D) stratification of siRNA 650

candidates based on normalized z-score and a difference of at least 30% between control 651

and doxorubicin treated plates. 652

653

Figure 2. Protein translation and RNA splicing enhance OS cell death. 654

(A) Analysis of pathways enriched in the primary screen from both arms (+/- doxorubicin; 655

upper panel), those enriched within hits that enhanced doxorubicin induced cell death (middle 656

panel) and those that increased cell survival in the presence of doxorubicin (lower panel). 657

Data plotted as log fold enrichment (p-value) based on Ingenuity Pathway Analysis. (B) 658

Visualization of the individual candidate hits based on subcellular localization (from Ingenuity 659

Pathway Analysis software) with specific pathways that are enriched indicated within each 660

colored box based on n the validated primary screen results described in part A. (C) 661

Secondary screen deconvolution analysis of the candidates identified in the primary screen. 662

Primary screen candidates were secondarily screened as individual siRNAs and those with 3 663

or 4 of 4 validating the primary screen were considered high confidence candidates; 2 of 4 664

medium confidence and 1 or less not considered further. (D) Examples of individual target 665

effects in the primary and secondary screen. Upper panel: mean viability of duplicate samples 666

for each treatment arm from the primary siRNA screen; lower panel: viability following 667

transfection of the individual siRNA validation for each target in the secondary screen. In the 668

lower panel each point represents an individual siRNA from within the pooled complex used 669

for the primary screen with mean ± SEM for each gene. 670

671

Figure 3. Small molecule validation of siRNA candidates. 672




27

(A) Dose response viability curves of human (OS17) and mouse fibroblastic (494H) or 673

osteoblastic (148I) OS cell cultures treated with the Ran inhibitor Importazole either alone 674

(red line) or in combination with doxorubicin (blue line). Data is presented as IC50 values (n=2-675

4 independent replicates); sensitivity of human (+/- doxorubicin), murine fibroblastic and 676

osteoblastic OS to the proteosome inhibitor bortezomib; sensitivity of human (+/- doxorubicin), 677

murine fibroblastic and osteoblastic OS to the Sf3b1 inhibitor spliceostatin A (SAA). (B) 678

Treatment of murine fibroblastic and osteoblastic OS for 72 hours with mock, non-targeting 679

(NT), Sf3b1 or U2af1 siRNA. Western blots were probed for the presence of cleaved 680

caspase-3 and actin as a control. (C). Murine fibroblastic and osteoblastic OS were treated 681

for 48 hours with SSA. Western blot analysis demonstrates the presence of an abnormally 682

spliced p27 isoform (indicated as p27*) accompanied by cleaved caspase-3 in SSA treated 683

cells. 684

685

Figure 4. Specific sensitivity to PI3K/mTOR inhibition in both mouse and human 686

primary OS cells. 687

(A) Three independent murine fibroblastic primary and metastatic paired OS cell cultures 688

were screened in an 11-point dose response against 131 compounds (full list of compounds 689

and screen results in Supplemental Dataset 2). Data are presented as a heat map of 690

sensitivity for replicate assays or pooled by primary or metastatic location. The greatest 691

sensitivity is in black (0.001-1μM), graded to least/no sensitivity in white (>10μM). Individual 692

agents with sub-1μM activity are listed on the left hand side of the data. (B) All agents that 693

have activity against PI3K are listed and the IC50 (mean± StDev) and target specificity against 694

PI3K subunits and other targets listed. (C). Testing of GSK2126458 against murine 695

fibroblastic (494H, red), murine osteoblastic (148I, blue), primary human (OS17, green) and 696

the established human OS cell line (MG63, grey) with separate drug stocks to those used in 697

the initial screen. Data is presented as mean IC50 values ± SEM (n=3 independent assays for 698

494H, 148I and OS17; n=2 for MG63). (D) Four primary human biopsy derived cultures and 699

the established human OS cell lines Saos-2 and U2OS were treated with the indicated 700

agents. Data are presented as a heat map of sensitivity with replicates as indicated by 701

multiple listings of the same agent. The greatest sensitivity is in black (0.001-1μM), graded to 702




28

least/no sensitivity in white (>10μM) with grey not tested. Target specificity against PI3K 703

subunits and other targets is listed. 704

705

Figure 5. Dual PI3K/mTOR inhibitors induce apoptosis in OS cells. 706

(A) Analysis of target inhibition downstream of PI3K/mTOR activity was assessed by western 707

blot of the indicated proteins against murine fibroblastic, murine osteoblastic and primary 708

human OS. Each cell type was treated with the calculated IC50 and Emax respectively for 709

each drug. (B) Cell cycle distribution of murine fibroblastic OS or primary human OS cells 710

treated with the indicated concentrations of GSK2126458 and PKI587 for 24hrs, statistical 711

comparison performed comparing the proportions of G0/G1 phase cells between vehicle and 712

each treatment. (C) GSK2126458 and PKI587 induce apoptosis as assessed by annexin 713

V/7AAD staining (D) or cleaved caspase-3 western blot in a dose dependent manner. Where 714

indicated data presented as mean ± SEM, *P<0.05, **P<0.01, ***P<0.001 (n=3 technical 715

replicates per cell line, 3 independent cell lines tested as indicated). 716

717

Figure 6. PIK3CA and mTOR inhibition mediate the sensitivity of OS cells to agents 718

targeting these pathways. 719

(A) Transcript levels of Pik3c isoforms were quantified from RNA-seq of murine fibroblastic 720

and osteoblastic OS or by real-time PCR in human OS cells compared to normal human 721

osteoblast cells. Data is presented as TMM (trimmed mean of M values) normalized read 722

counts (n=3 per subtype) for RNA-seq or mean relative expression to PGK1 ± SEM (n=4-7) 723

for QPCR. (B) Human and mouse OS cells were transfected with 25nm SMARTpool siRNAs 724

targeting Pik3ca/b or PIK3CA/B respectively or a pool of non-targeting siRNAs (NT2) for 24 725

hours then treated with the indicated concentrations of the mTOR inhibitor everolimus for 48 726

hours. Cell viability was assessed relative to Non-T DMSO treated cells. Data is presented as 727

mean ± SEM (n=3). (C) Mouse fibroblastic OS cells (494H) were transfected with siRNAs 728

targeting mTor, Raptor or Rictor or a pool of non-targeting siRNAs (Non-T) for 24 hours then 729

treated with the indicated concentrations of the PIK3CA inhibitor BYL719 for 48 hours. Cell 730

viability was assessed relative to Non-T DMSO treated cells. Data is presented as mean ± 731

SEM (n=3). ). *P<0.05, #P<0.05 calculated using students t-tests. (D) Treatment of murine OS 732




29

cells (494H) with the pan-PI3K inhibitor BKM120, PI3KCA specific inhibitor BYL719 or the 733

mTOR inhibitor Everolimus as single agents. Data is presented as mean IC50 values ± SEM 734

(n=3 per treatment); Needle graphs show synergy effects in mouse fibroblastic OS cells 735

treated with combinations of Everolimus and BYL719 for 72 hours. Synergy is represented as 736

percent deviation from a predicted additive response (Bliss additivity). Deviations greater than 737

15% were considered synergistic (red baseline). Data is presented as mean deviation (n=3). 738




A

C

murine OS primary culture(passage 8 from derivation;

fibroblastic OS model)

mouse genome wide siRNA(>16,800 individual pools)

~48 hours

~72 hours

mouse genome wide siRNA(>16,800 individual pools)

siRNA + 100nm doxorubicin(~45% cell death)

B

siRNA alone

Viability assessment(Cell TitreGlo)

Con

trol (

siR

NA

alon

e) a

vera

ge C

TGno

rmal

ised

to N

T1 ro

bust

z s

core

Dox

orub

icin

(siR

NA

+ D

oxo)

ave

rage

CTG

norm

alis

ed to

NT1

robu

st z

sco

re

Pooled Library siRNA reagent

Pooled Library siRNA reagent

Decreased Viabilityn=300; 1.78%

Increased Viability n=563; 3.3%

0 2000 4000 6000 8000 10000 12000 14000 16000 18000-14-12-10-8-6-4-202468

10

Decreased Viabilityn=790; 4.68%

Increased Viability n=371; 2.2%

0 2000 4000 6000 8000 10000 12000 14000 16000 18000-14

-12

-10

-8

-6

-4

-2

0

2

4

6

8

Mesogenin

Mesogenin

BidBag1E2f5

Top2a

Ran

RanSf3b1

Sf3b1

Cse1l

Cse1l

Sf3b4

Sf3b4

Top2a

Topbp1

Topbp1

Bag1Bid

All Primary screen results (robust z-score ≥ ±2)Condition n (of 16874) Percent of total

Increased Viability - Common

- siRNA + Doxo

- siRNA alone

- siRNA+ Doxo

Decreased viability - Common

- siRNA alone

790

300

234

371

563

151

4.68%

1.78%

1.34%

2.2%

3.3%

0.89%

Filtered Primary screen results Condition n Percent of total

Common to both data sets

- robust z-score ≥ -2; ≤ 0.7 compared to NT1 doxo

- robust z-score ≥ +2; ≥ 1.15 compared to NT1 doxo

43

21

14

114

0.25%

0.21%

0.08%

0.67%

169

266

1.0%

1.57%

siRNA + Doxorubicin specific results



siRNA alone specific results



D

Figure 1 Gupte et al




Ribosome

U2 Splicing Complex

Ran/Nuclear pore Complex

Proteosome

EIF2 Signaling

Regulation of eIF4 and p70S6K Signaling

mTOR Signaling

Protein Ubiquitination Pathway

Nucleotide Excision Repair Pathway

Assembly of RNA Polymerase II Complex

Spliceosomal Cycle

Hereditary Breast Cancer Signaling

Control of Chromosomal Replication

Estrogen Receptor Signaling

RAN Signaling

-log(p-value)0 10 20 30 40 50 60

A BAll hits (both arms of screen)

EIF2 SignalingRegulation of eIF4 and p70S6K Signaling

mTOR SignalingProtein Ubiquitination Pathway

Spliceosomal CycleRAN Signaling

-log(p-value)0 10 20 30 40 50 60

Molecular Mechanisms of Cancer

Chronic Myeloid Leukemia Signaling

Glioblastoma Multiforme Signaling

Breast Cancer Regulation by Stathmin1

Apoptosis Signaling

-log(p-value)0 5 10 15

Enhancers of Doxorubicin Induced Death

Suppressors of Doxorubicin Induced Death

C

D

Secondary Screen: Validation Rate (individual siRNA from pools)

n (of 299) Percent of totalDecreased Viability

3 of 4 50 16.07%

4 of 4 63 21.07%

1 of 4 70 23.41%

2 of 4 38 12.71%

0 of 4 78 26.09%

High Confidence(n=113; 37.7%)

Low Confidence(no follow up)

Sf3b1

Psma3

Snrpd1

Copg1

U2af1

Rps3

Snrpb

Rrm2

Eif3f

SonSf3a

2Eif4

a30.00.10.20.30.40.50.60.70.80.91.0

0.00.10.20.30.40.50.60.70.80.91.0

Sf3b1

Psma3

Snrpd1

Copg1

U2af1

Rps3

Snrpb

Rrm2

Eif3f

SonSf3a

2Eif4

a3

Viab

ility

(nor

mal

ised

to N

T1)

Viab

ility

(nor

mal

ised

to N

T1)

Gene Name

PRIM

ARY SC

REEN

SECO

ND

ARY SC

REEN

siRNA alone siRNA + Doxorubicin

Medium Confidence





Ran inhibitor(Importazole)

0

25

50

75

100

125

100101

IC50 = 20.81mM

Concentration (mM)

% C

ell V

iabi

lity

IC50 = 10.42mM

Concentration (mM)

0

25

50

75

100

125

100101

% C

ell V

iabi

lity

IC50 = 11.08mM

Concentration (mM)

0

25

50

75

100

125

100101

% C

ell V

iabi

lity

Proteosome inhibitor(Bortezomib)

IC50 = 0.007236mM

Concentration (mM)

0

25

50

75

100

125

0.00

001

0.00

01

0.00

1

0.01 0.

1 1 10

% C

ell V

iabi

lity

IC50 = 0.007463mM

Concentration (mM)

0

25

50

75

100

125

0.00

001

0.00

01

0.00

1

0.01 0.

1 1 10

% C

ell V

iabi

lity

IC50 = 0.004829mM

Concentration (mM)

0

25

50

75

100

125

0.00

001

0.00

01

0.00

1

0.01 0.

1 1 10

% C

ell V

iabi

lity

Sf3b inhibitor(Spliceostatin A)

IC50 = 0.001310mM

0

25

50

75

100

125

0.00

001

0.00

01

0.00

1

0.01 0.

1 1

Concentration (mM)

% C

ell V

iabi

lity

IC50 = 0.0007016mM

0

25

50

75

100

125

0.00

001

0.00

01

0.00

1

0.01 0.

1 1

Concentration (mM)

% C

ell V

iabi

lity

IC50 = 0.0009499mM

Concentration (mM)

0

25

50

75

100

125

0.00

001

0.00

01

0.00

1

0.01 0.

1 1

% C

ell V

iabi

lity

Prim

ary

hum

an O

S(O

S17)

Fibr

obla

stic

mou

se O

S(4

94H

)O

steo

blas

tic m

ouse

OS

(148

I)

Cleaved caspase-3

Actin

MouseFibroblastic OS

MouseOsteoblastic OS

Mock

NT Sf3b1

U2af1

Mock

NT Sf3b1

U2af1

siRNA

MouseFibro OS

Spliceostatin A0 10

nM0 10

nM

Cleaved caspase-3

Actin

p27p27*

MouseOsteo OS

A

B

C

p27p27*

(overexposed p27 blot)

0

25

50

75

100

125

0

25

50

75

100

125

0

25

50

75

100

125

100101

Concentration (mM)

% C

ell V

iabi

lity

IC50 = 0.0072mM

Concentration (mM)

0.00

001

0.00

01

0.00

1

0.01 0.

1 1 10

% C

ell V

iabi

lity

0.00

001

0.00

01

0.00

1

0.01 0.

1 1

Concentration (mM)

% C

ell V

iabi

lityIC50 = 0.0047mM

IC50 = 20.8mMIC50 = 20.9mM

IC50 = 0.0013mMIC50 = 0.0017mM

Drug alone

Drug + IC20 Doxorubicin





A B

1 1010-110-210-310-410-5

Concentration (mM)

0

25

50

75

100

125

Cel

l Via

bilit

y (%

)

Primary human OS (OS#17)IC50 = 0.051mM

1 1010-110-210-310-410-5

Concentration (mM)

0

25

50

75

100

125

Cel

l Via

bilit

y (%

)

MG63 (human OS)IC50 = 0.016mM

1 1010-110-210-310-410-5

Concentration (mM)

0

25

50

75

100

125

Cel

l Via

bilit

y (%

)

Fibroblastic mouse OS (494H)IC50 = 0.89mM

1 1010-110-210-310-410-5

Concentration (mM)

0

25

50

75

100

125

Cel

l Via

bilit

y (%

)

Osteoblastic mouse OS (148I)IC50 = 0.023mM

C

Prim

OS

Met

OS

PI3K selectivity Othertargetsa

++

+

+

+

+

++++++

b

++

+

+

+

+

+++

d

++

+

+++

+++++

+++

g

++

++

+

++++

+++

mTORC1/2DNA-PK, CDK7/9

mTOR, ATR

CK2mTOR, DNA-PK

PI4IIIb

GNE-493GNE-490

GSK2126458PIK-75

BEZ-235ZSTK474

TG100115XL147

PIK-294TGX221

PIK-90IC87114

LY294002AS-252424

PI103PIK-93

GDC-0941

IC50 (mM)Mean (StDev)

1.86 (0.98)6.07 (3.47)0.21 (0.15)0.15 (0.06)0.22 (0.13)2.66 (1.32)

>10.0>10.0>10.0>10.0

8.57 (3.33)>10.0>10.0>10.0

1.35 (1.18)8.06 (3.04)4.40 (3.15)

DNA-Pk

Merck-22-6A-674563

Akt-I-1Akt-I-1/2

GSK690693KU57788 (Nu7441)

KU0063794

2.34 (0.85)1.56 (0.57)

>10.0>10.0

9.51 (1.15)8.06 (2.37)5.32 (1.87)

Akt1, Akt2Akt1, PKA

Akt1Akt1, Akt2

Akt1, Akt2, Akt3

mTORC1, mTORC2

0.001

OS#493paired samples

Rep

licat

e 1

Rep

licat

e 2

Rep

licat

e 1

Rep

licat

e 2

Prim

ary

OS

Met

asta

tic O

S


Rep

licat

e 1

Rep

licat

e 2

Rep

licat

e 1

Rep

licat

e 2

Prim

ary

OS

Met

asta

tic O

S


Rep

licat

e 1

Rep

licat

e 2

Rep

licat

e 1

Rep

licat

e 2

Prim

ary

OS

Met

asta

tic O

S

Prim

ary

OS

(Ave

rage

of a

ll)

Met

asta

tic O

S (A

vera

ge o

f all)

5 10IC50 (mM)

131

1

Com

poun

d N

umbe

r

Com

poun

d C

lass

mTOR

PI3KDasatinib

Ponatinib

FlavopiridolAZD7762

CD

K

1 0.001 5 10

EC50 (mM) >10Not Determined

PI3K selectivity Othertargetsa

+

+

+

+

+b

+

+

+

+d

+

+

+g

+

+

+BKM-120BKM-120

GDC-0980LY-294002LY-294002

XL147GDC-0941GDC-0941

BYL-719A66

CH-5132799AZD6482

GSK-2636771TGX-221ZSTK474

PIK 293BAY 80-6946

BAY 80-6946 + RDEA-119BYL719+ ARRY162

BKM120 + ARRY162BKM120 + GSK1120212

BGT226+ ARRY162GDC-0941 + GDC-0973

CAL-101

GSK-2126458GSK-2126458

GSK-2126458 + GSK-1120212PKI-587PKI-587

PKI-587 + PD-0325901NVP-BEZ235PF-4691502

NVP-BGT226

NVP-BGT226PIK 103

CUDC-907CUDC-907

NVP-BGT226

TemsirolimusTemsirolimusTemsirolimus

SirolimusEverolimus

SirolimusSirolimus

EverolimusXL-765 + AS-703026

XL-765XL-765

DoxorubicinDoxorubicin

+ + + ++ + + ++ + ++ + ++ + ++ ++ +++

+++

+++

+ + MEK+ MEK

MEK+ + + + MEK+ + + MEK+ + MEK

mTORC1/2+ + + + mTORC1/2+ + + + mTORC1/2, MEK+ + mTORC1/2+ + mTORC1/2+ + + + mTORC1/2, MEK+ + + + mTORC1/2+ + + + mTORC1/2+ + + mTORC1/2+ + + mTORC1/2+ + + mTORC1/2+ + + + mTORC1/2, DNA-PK+ + + HDAC+ + + HDAC

mTORmTORmTORmTORmTORmTORmTORmTOR

+ mTOR, MEK+ mTOR+ mTOR

SJOS00

1112_

X1

SJOS01

0929

_X1

SJOS00

1107

_X2

SJOS00

1107

_X1

Saos-2

U2OS

Primary human OSEstablished human OS

cell line

1

D





C

A

D

B

G2/MSG0/G1

0

20

40

60

80

100

% o

f pop

ulat

ion

Vehicle 100nM

GSK-458 PKI-587

1μM150nM 1μM

Hum

an Primary O

S

0

20

40

60

80

100

Vehicle 1mM 250nM

GSK-458 PKI-587

1mM

% o

f pop

ulat

ion

Murine Fibroblastic O

S



HumanPrimary OS

mTOR

Phospho-mTOR (Ser2448)

Actin

Actin

Phospho-p70 S6 Kinase (Ser371)

Phospho-p70 S6 Kinase (Thr389)

Phospho-4E-BP1 (Thr37/46)

Vehicle 1μ

M5μ

M25

0nM

1μM

GSK-458 PKI-587

Vehicle

25nM 1μ

M10

0nM

1μM

GSK-458 PKI-587

Vehicle

150n

M1μ

M10

0nM

1μM

GSK-458 PKI-587

Fibr

obla

stic

mO

S(4

94H

)O

steo

blas

tic m

OS

(148

I)H

uman

OS

(OS1

7)

DMSO GSK-458 PKI5871μM 5μM 1μM250nM

1μM 1μM

1μM 1μM150nM

Annexin V

7AAD

100nM

100nM

DMSO 1μM 1μM150nM 100nM

1μM 1μM25nM 100nM

1μM 5μM 1μM250nM

GSK-458 PKI587

% A

nnex

in V

pos

itive

60

40

20

0

% A

nnex

in V

pos

itive

% A

nnex

in V

pos

itive

** ***

25nM

Cleaved caspase 3

Actin


Vehicle 1μ

M5μ

M25

0nM

1μM

GSK-458 PKI-587


Vehicle

25nM 1μ

M10

0nM

1μM

GSK-458 PKI-587

Cleaved caspase 3

Actin

HumanPrimary OS

Vehicle

150n

M1μ

M10

0nM

1μM

GSK-458 PKI-587

Cleaved caspase 3

Actin

100

80

60

40

20

0

100

80* **** *

60

40

20

0

100

80 * *** **

DMSO

DMSO

*** *

** ***





BKM120 - pan-PI3K inhibitor (a, b, d)

Cel

l Via

bilit

y (%

)

0

25

50

75

100

125

IC50 2.04µM

Concentration (mM)10-5 10-4 10-3 10-2 10-1 100 101

Cel

l Via

bilit

y (%

)Everolimus - mTOR inhibitor

0

25

50

75

100

125

Concentration (mM)10-2 10-1 100 101

Cel

l Via

bilit

y (%

)

BYL719 - PI3Ka specific inhibitor

0

25

50

75

100

125

Concentration (mM)10-5 10-4 10-3 10-2 10-1 100 101

D

200

150

100

50

0.20.4

0.81.6

0.2 0.4 0.8 1.6

BYL719 (mM)

Everolimus (mM)

Percentage deviation fromBliss additivity

20

40

60

80

100

% C

ell V

iabi

lity

(rela

tive

to N

on-T

DM

SO)

PI3KCA PI3KCB

0.1% v/v DMSO

500nMEverolimus

1mMEverolimus

Primary human OS (OS17)

Non-TsiRNA:

**

**

*

**

20

40

60

80

100

120

% C

ell V

iabi

lity

(rela

tive

to N

on-T

DM

SO)

0.1% v/v DMSO

500nMEverolimus

1mMEverolimus

*

* *

Osteoblastic mouse OS (148I)

Pi3kca Pi3kcbNon-TsiRNA:

B

C

A

0102030405060708090

100110

0.00

0.05

0.10

0.15

0.20TM

M n

orm

alis

ed re

ad c

ount

s

Rel

ativ

e Ex

pres

ion

(nor

mal

ised

to P

GK1

)PIK3C A B D GPik3c a b d g

Pik3c isoform expression PIK3C isoform expression

Fibroblastic OS (mouse)Osteoblastic OS (mouse)

Osteoblasts (human)Osteosarcoma (human)

40

60

80

100

Fibroblastic mouse OS (494H)

% C

ell V

iabi

lity

(rela

tive

to N

on-T

DM

SO)

Non-T mTOR RaptorsiRNA: Rictor

0.1% v/v DMSO

400nMBYL719

800nMBYL719

* * * * * * *Within Tx group:Each siRNA cf DMSO: # # # # #





Published OnlineFirst April 10, 2015.Clin Cancer Res Ankita Gupte, Emma Baker, Soo-San Wan, et al. as a conserved therapeutic vulnerability in osteosarcomaSystematic screening identifies dual PI3K and mTOR inhibition

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