fgfr genetic alterations predict for sensitivity to …...the novel anticancer drug nvp-bgj398 and...

FGFR Genetic Alterations Predict for Sensitivity to NVP-BGJ398, a Selective Pan-FGFR Inhibitor Vito Guagnano 1 , Audrey Kauffmann 2 , Simon Wöhrle 2 , Christelle Stamm 2 , Moriko Ito 2 , Louise Barys 2 , Astrid Pornon 2 , Yao Yao 7 , Fang Li 5 , Yun Zhang 6 , Zhi Chen 6 , Christopher J. Wilson 4 , Vincent Bordas 1 , Mickaël Le Douget 1 , L. Alex Gaither 4 , Jason Borawski 4 , John E. Monahan 5 , Kavitha Venkatesan 3 , Thomas Brümmendorf 2 , David M. Thomas 8 , Carlos Garcia-Echeverria 2 , Francesco Hofmann 2 , William R. Sellers 3 , and Diana Graus-Porta 2

RESEARCH ARTICLE

on April 10, 2020. © 2012 American Association for Cancer Research. cancerdiscovery.aacrjournals.org Downloaded from

Published OnlineFirst September 20, 2012; DOI: 10.1158/2159-8290.CD-12-0210

http://cancerdiscovery.aacrjournals.org/

DECEMBER 2012�CANCER DISCOVERY | 1119

ABSTRACT Patient stratifi cation biomarkers that enable the translation of cancer genetic knowledge into clinical use are essential for the successful and rapid development

of emerging targeted anticancer therapeutics. Here, we describe the identifi cation of patient stratifi ca-tion biomarkers for NVP-BGJ398, a novel and selective fi broblast growth factor receptor (FGFR) inhibi-tor. By intersecting genome-wide gene expression and genomic alteration data with cell line–sensitivity data across an annotated collection of cancer cell lines called the Cancer Cell Line Encyclopedia, we show that genetic alterations for FGFR family members predict for sensitivity to NVP-BGJ398. For the fi rst time, we report oncogenic FGFR1 amplifi cation in osteosarcoma as a potential patient selection biomarker. Furthermore, we show that cancer cell lines harboring FGF19 copy number gain at the 11q13 amplicon are sensitive to NVP-BGJ398 only when concomitant expression of β-klotho occurs. Thus, our fi ndings provide the rationale for the clinical development of FGFR inhibitors in selected patients with cancer harboring tumors with the identifi ed predictors of sensitivity.

SIGNIFICANCE: The success of a personalized medicine approach using targeted therapies ultimately depends on being able to identify the patients who will benefi t the most from any given drug. To this end, we have integrated the molecular profi les for more than 500 cancer cell lines with sensitivity data for the novel anticancer drug NVP-BGJ398 and showed that FGFR genetic alterations are the most signifi -cant predictors for sensitivity. This work has ultimately endorsed the incorporation of specifi c patient selection biomakers in the clinical trials for NVP-BGJ398. Cancer Discov; 2(12); 1118–33. ©2012 AACR.

Authors’ Affi liations: 1 Global Discovery Chemistry, 2 Disease Area Oncol-ogy, Novartis Institutes for BioMedical Research, Basel, Switzerland; 3 Disease Area Oncology, 4 Developmental and Molecular Pathways, and 5 Oncology Translational Research, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts; 6 Developmental and Molecular Pathways, 7 Oncology Translational Medicine, China Novartis Institutes for BioMedical Research, Shanghai, China; 8 Sir Peter MacCallum Department of Oncology, University of Melbourne and Peter MacCallum Cancer Centre, St. Andrew’s Place, East Melbourne, Australia Note: Supplementary data for this article are available at Cancer Discovery Online (http://cancerdiscovery.aacrjournals.org/). A. Kauffmann, S. Wöhrle, and C. Stamm contributed equally to this work. Current address for C. Garcia-Echeverria: Oncology Drug Discovery and Preclinical Research, Sanofi , 94403 Vitry-sur-Seine, France. Corresponding Author: Diana Graus-Porta, Novartis Institutes for Bio-Medical Research, Novartis Pharma AG, CH-4002 Basel, Switzerland. Phone: 41-61-6965093; Fax: 41-61-6963835; E-mail: [email protected] doi: 10.1158/2159-8290.CD-12-0210 ©2012 American Association for Cancer Research.

INTRODUCTION

The fi broblast growth factor (FGF) receptor tyrosine kinase (RTK) family, which consists of fi broblast growth factor receptor 1 (FGFR1), FGFR2, FGFR3, and FGFR4, encom-passes the high-affi nity receptors for 18 different FGF lig-ands. These ligand–receptor combinations regulate a broad spectrum of signaling and endocrinologic activities during development and in adult tissue homeostasis ( 1 ). In keep-ing with the importance of FGFR in normal growth control, deregulated FGF signaling has been linked to diseases, most prominently in the pathogenesis of multiple cancers. Epi-demiologic and molecular studies have revealed a variety of

genetic alterations in components of the FGF/FGFR signal-ing system, resulting in aberrant receptor activation and thus enhanced downstream signaling.

The underlying genetic alterations are largely tissue spe-cifi c and include gene amplifi cations, translocations, and point mutations. Evidence for gene copy number changes has been reported in several studies. In particular, Beroukhim and colleagues ( 2 ) analyzed somatic copy number alterations in 3,131 cancer specimens and found that FGFR1 was sig-nifi cantly focally amplifi ed across the entire dataset with a GISTIC (genomic identifi cation of signifi cant targets in cancer) q-value of 9.05E-47 and was located within a region of focal amplifi cation containing only FGFR1 , LETM2 , and WHSC1L1 . In breast cancer, FGFR1 is preferentially amplifi ed in estrogen receptor–positive tumors as shown by chromo-some in situ hybridization, and survival analysis indicates that it may also be an independent prognostic factor for poor outcome ( 3 ). Furthermore, high-resolution gene copy number analysis in lung cancer revealed FGFR1 amplifi cation preferentially in the squamous subtype ( 4, 5 ). FGFR2 copy number gains, albeit with a low incidence, were reported in breast tumors ( 6, 7 ) and in gastric cancer in particular in poorly differentiated adenocarcinomas ( 8–11 ). Among the ligands, FGF19 , located in the common 11q13 amplicon, was recently identifi ed to be a driver gene in liver cancer in coop-eration with its neighboring gene, cyclin D1 ( 12 ).

Germline mutations in FGFR1, FGFR2, and FGFR3 were fi rst discovered as causative lesions in skeletal dysplasias ( 13 ). Kinome exon sequencing in search of human cancer somatic mutations identifi ed FGF signaling components as the most frequently mutated coding regions among protein kinases ( 14 ). Somatic mutations of FGFR1 have been found in gliomas and lung tumors ( 15, 16 ), of FGFR2 in gastric




1120 | CANCER DISCOVERY�DECEMBER 2012 www.aacrjournals.org

Guagnano et al.RESEARCH ARTICLE

and endometrial carcinomas ( 17–19 ), of FGFR3 in bladder carcinomas and multiple myeloma ( 20, 21 ), and of FGFR4 in primary rhabdomyosarcomas ( 22 ).

In addition, studies of hematologic malignancies have led to the characterization of chromosomal translocations involving FGFR genes. In particular, FGFR1 intragenic trans-locations between the N-terminus of a transcription fac-tor and the FGFR1 kinase domain leading to constitutive kinase activation by oligomerization are responsible for 8p11 myeloproliferative disorder ( 23 ). Similar translocations of FGFR3 are associated with peripheral T-cell lymphoma ( 24 ), whereas in multiple myeloma, recurrent chromosomal trans-locations of 14q32 into the immunoglobulin G (IgG) heavy chain switch region result in deregulated ectopic expression of FGFR3 and the adjacent multiple myeloma SET domain-containing (MMSET) gene ( 21 ).

On the basis of the evidence of broad genetic alteration of the FGF/FGFR system in cancer, we hypothesized that the targeted inhibition of FGFRs would be an attractive modal-ity for therapeutic intervention across multiple indications bearing such specifi c underlying genetic alterations. To this end, we have developed NVP-BGJ398, a potent, orally bio-available, small-molecule pan-FGFR kinase inhibitor, which is currently in a clinical phase I trial ( 25 ). To preclinically identify and validate patient stratifi cation biomarkers to enrich for patients likely to respond to NVP-BGJ398, the Cancer Cell Line Encyclopedia (CCLE) was interrogated. The CCLE is a collection of almost 1,000 cancer cell lines representing multiple tumor types that, in a collabora-tive effort between The Novartis Institutes for BioMedi-cal Research and the Broad Institute (Cambridge, MA), has been comprehensively annotated in terms of genome-scale mRNA expression, gene copy number alterations, and gene mutations ( 26 ). In addition, more than half of these cell lines were subjected to high-throughput cell viability assays upon exposure to hundreds of compounds representing a variety of mechanisms of action, including the FGFR inhibitor NVP-BGJ398. Analysis of these cell lines’ sensitivity profiles revealed that NVP-BGJ398 sig-nificantly inhibits proliferation of cancer cell lines bearing FGF/FGFR genetic alterations across various cancer types, thus preclinically validating the hypothesis that a defined patient selection strategy based on tumors harboring FGF/FGFR genetic alterations is likely to enrich for responses to NVP-BGJ398.

RESULTS

NVP-BGJ398 Is a Potent and Selective FGFR Kinase Inhibitor

NVP-BGJ398 is an N -aryl- N ′-pyrimidin-4-yl urea derivative that was designed by applying a new and nonconventional strategy to mimic the pyrido[2,3-d]pyrimidin-7-one core structure of a well-known class of protein kinase inhibitors ( Fig. 1A ; refs. 25 , 27 ). The proposed binding mode of NVP-BGJ398 was elucidated by solving the 3-dimensional structure of the FGFR1 kinase domain in complex with NVP-BGJ398 ( Fig. 1B ). As shown in Fig. 1B , the 4-(4-ethyl-piperazin-1-yl)-phenylamine NH and the adjacent pyrimidine nitrogen are involved in critical H-bonds with the carbonyl and the

amino group of alanine 564 (an amino acid residue located in the hinge region of the ATP-binding pocket), respectively. The urea carbonyl group is engaged in a water-mediated H-bond with the side chain amino group of lysine 514, whereas the aryl ring of the 4-(4-ethyl-piperazin-1-yl)-phe-nylamine is in contact with the hydrophobic side chains of 2 amino acid residues, glycine 567 and leucine 484 (the former not represented for clarity) in a sandwich-like manner. The 2,6-dichloro-3,5 dimethoxy-aniline fi lls optimally the com-plementary cavity in the kinase. Indeed, the perpendicular orientation of the tetrasubstituted benzene ring with respect to the plane of the pesudo-bicyclic system enforced by the 2 chlorine atoms allows productive hydrophobic interactions with several amino acid residues. In addition, this same ring is responsible for an H-bond between the methoxy oxygen and the NH of aspartate 641.

NVP-BGJ398 was tested against the 4 FGFRs and a panel of additional kinases in biochemical and cellular assays. NVP-BGJ398 inhibited FGFR1, FGFR2, and FGFR3 with single digit nmol/L IC 50 in biochemical and cellular auto-phosphorylation assays and FGFR4 with 38- to 60-fold lower potency ( Fig. 1C and D ; Supplementary Table S1). In cellular assays, the most potently inhibited kinase, in addi-tion to the FGFRs, was found to be VEGFR2, displaying 70- to 100-fold reduced potency as compared with FGFR1, FGFR2, and FGFR3. Therefore, NVP-BGJ398 is a selective, pan-FGFR kinase inhibitor, with predominant activity on FGFR1, FGFR2, and FGFR3.

Predicting Responses to NVP-BGJ398 by Means of the CCLE

Activation of the FGFR pathway is a common feature in human cancers with underlying genetic abnormalities in the FGF/FGFR system ( 28 ). To test whether tumors pre-senting these abnormalities depend on FGFR kinase activ-ity, and hence would be sensitive to NVP-BGJ398, and to eventually elucidate predictive patient selection biomarkers for clinical trials with NVP-BGJ398, the antiproliferative activity of NVP-BGJ398 was assayed in a panel of 541 cell lines from the CCLE. From 2 independent high-through-put cell viability screens encompassing 435 and 424 cell lines respectively, with about 80% overlap, cell viability data in triplicate met the quality criteria for NVP-BGJ398 across a total of 517 cell lines (Supplementary Data File S1). Analysis of cell line distribution with respect to the A max and infl ection point values for NVP-BGJ398 across the entire cell viability dataset indicates that a subgroup of cell lines is highly sensitive ( n = 35) to the compound, whereas a large majority of cell lines ( n = 482) are insensitive (Sup-plementary Fig. S1A). Sensitive and nonsensitive groups were defi ned according to specifi c cutoff values for A max and infl ection point. To mitigate the risk of missing sensitive cell lines because of the accuracy limitations of a high-throughput screening mode, the thresholds for sensitivity in a fi rst fi ltering step were set at relatively low stringency with A max −40 and lower and infl ection point 1 μmol/L or higher. To validate the sensitive response calls to NVP-BGJ398, the 35 cell lines fulfi lling the above selection cri-teria (lower left quadrant in Supplementary Fig. S1A) were tested in subsequent viability assays manually.





Predictive Modeling of FGFR Inhibitor Sensitivity RESEARCH ARTICLE

Figure 1. A, structure of NVP-BGJ398. B, the crystal structure of NVP-BGJ398 in complex with the tyrosine kinase domain of FGFR1 at 2.8 Å resolu-tion. C, biochemical FGFR kinase assays; all assays were conducted with purifi ed recombinant enzymes under optimized conditions using peptidic substrates and a microfl uidic mobility shift readout using the KinaseGlo Luminescent Kinase Assay. The concentrations for ATP were adjusted to the respective K m values of the kinase. D, cellular FGFR autophosphorylation assays; HEK293 cells expressing the indicated FGFR were incubated with NVP-BGJ398 for 40 minutes at the indicated concentrations, and inhibition of FGFR Tyr-phosphorylation was measured by ELISA using a capturing FGFR-specifi c antibody and the antiphospho-tyrosine antibody PY20 coupled to HRP. In C and D the percentage of phospho-tyrosine inhibition versus dose curves is shown.

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To defi ne the range of on-target FGFR-dependent inhibi-tion of cell proliferation, the IC 50 values obtained in cell viabil-ity assays for BaF3 cells rendered dependent on the specifi c FGFRs were used as a reference. On this basis, only cancer cell lines in which proliferation was inhibited with an IC 50 less than 500 nmol/L were classifi ed as sensitive. Among the 35 cell lines selected from the high-throughput assays, 28 were con-fi rmed as sensitive to NVP-BGJ398 with IC 50 s ranging from

0.001 to 500 nmol/L (Supplementary Fig. S1B). In addition, 24 selected lines from the CCLE for which high-throughput cell line profi ling data were not available were also tested in manual cell proliferation assays, and 4 of them were found to be sensitive to the FGFR inhibitor (Supplementary Fig. S1B). Collectively, among the 541 (517 + 24) cell lines from the CCLE subjected to viability testing, 5.9% (encompassing 21 different cancer types) were found to be sensitive to






Figure 2. NVP-BGJ398 inhibits proliferation of a subset of cancer cell lines. Scatter plot showing IC 50 values expressed in μmol/L of NVP-BGJ398 in cell viability assays of cell lines according to cancer type. A total of 5.9% of the cell lines were sensitive to NVP-BGJ398 at concentrations up to 500 nmol/L. Cell lines with the composite “FGFR genetic alterations” feature are indicated in red. Points were jittered horizontally to improve readability.

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NVP-BGJ398 when an IC 50 cutoff of 500 nmol/L for on-target inhibition of cell proliferation was applied ( Fig. 2 ).

To derive molecular correlates of drug sensitivity, we used a predictive categorical model approach as described ( 26 ). The feature matrix examined in this approach encompassed all CCLE genomic data as single genomic features (expression, copy number, COSMIC mutation data), 25 lineage features, 1,777 “GeneSet” features (expression signatures each of them consisting of multiple genes), and a composite “FGFR genetic alteration” feature consisting of 9 distinct types of FGFR genetic alterations: FGFR1, FGFR2, FGFR3, and FGFR4 copy number gains, activating mutations in FGFR1, FGFR2, and FGFR3, as well as the chromosomal translocations for either FGFR1 or FGFR3 previously reported in the literature ( 21 , 29 ).

From more than 50,000 input features, this analysis identifi ed the “FGFR genetic alteration” feature as the top

predictor for response to NVP-BGJ398 followed by 2 muta-tion features and 2 “GeneSet” features ( Fig. 3A and B ). As shown in Fig. 2 , within the 541 cell lines used in the analysis, only 37 were found to bear genetic abnormalities for either of the FGFRs (total of 6.8%), in line with the general low incidence of these genetic lesions in tumors. Among those, 17 cell lines were sensitive to NVP-BGJ398, representing 53% of all cell lines testing sensitive to the drug (17/32, Sup-plementary Table S2). In contrast, in the insensitive group, only 3.9% of the cell lines harbored FGFR genetic altera-tions. This indicates that NVP-BGJ398-sensitive tumor cells are strongly enriched among the panel of lines scoring positive for the “FGFR genetic alteration” feature. The other 2 features revealed by the model among the top 3 predictors are “ FGFR2 mutation” and “ FGFR3 mutation,” indicating that genetic alterations in individual FGFRs can






Figure 3. Predictive modeling of NVP-BGJ398 sensitivity using the CCLE features. Top features of drug response identifi ed by categorical-based predictive modeling. Wilcoxon test or Fisher exact test were conducted for continuous or discrete features, respectively. A, fold change or OR as well as P values and Benjamini–Hochberg corrected P values are reported. The number between parentheses for the GeneSets corresponds to the number of genes in the set. B, heatmap for the top 5 features in the model. NVP-BGJ398 response is shown in dark green for the sensitive cell lines and light green for the insensitive cell lines; dark purple is used for discrete features. For GeneSet expression signatures, continuous Z scores are used. P90 and P10 refer to the 90th and 10th percentiles of the GeneSet scores.

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be identifi ed by the predictive categorical model despite their relatively low frequency in the test set. Indeed, all of the FGFR2- and FGFR3-mutated cell lines, except 2 and 1, respectively, were growth inhibited by NVP-BGJ398, in line with its ability to effectively block FGFR downstream signaling in the 6 FGFR- mutated cell lines tested (Supple-mentary Fig. S2). Of note, all FGFR2- and FGFR3 -mutant lines belong to the endometrial and multiple myeloma cancer types, respectively. Additional predictors of sensitiv-ity included the 2 GeneSet expression signatures, “Develop-ment FGF-family signaling” and “Inhibition of Hedgehog signaling in medulloblastoma stem cells,” in which protein product components comprise multiple members of the FGF signaling cascade (Supplementary Table S3). Interest-ingly, the GeneSet expression signature–positive cell lines comprised most of the NVP-BGJ398–sensitive cell lines with FGFR genetic alterations as well as most of the sensi-tive ones for which no FGFR genetic abnormalities were identifi ed (Supplementary Fig. S3A). Conversely, many of the insensitive cell lines harboring FGFR genetic alterations

were GeneSet signature negative or had a low z-score (Sup-plementary Fig. S3B).

FGFR1 Amplifi cation Is Associated with Response to NVP-BGJ398

Because NVP-BGJ398–sensitive FGFR -amplifi ed cell lines were captured by the “FGFR genetic alteration” and “GeneSets” features, we examined further these genomic features across the CCLE. FGFR1 copy number gain defi ned as log 2 ratio ≥1 (equal to ≥4 normalized DNA copies) was observed in cell lines of breast, lung, and osteosarcoma lineages ( Fig. 4A ). Fur-ther analysis of the cell lines within these lineages ( n = 145) showed that 5 of the FGFR1 -amplifi ed lines were sensitive to NVP-BGJ398 in proliferation assays and displayed constitu-tive FGFR pathway activation, as measured by the presence of Tyr-phosphorylated FGFR substrate 2 (FRS2), whereas treat-ment with NVP-BGJ398 led to pathway inhibition ( Fig. 4B and C and Supplementary Fig. S1B). The scatter plot of copy number versus transcript expression revealed that the 5 sensitive cell lines were among the highest expressers of






Figure 4. FGFR1 amplifi cation in breast, lung, and osteosarcoma cancer cells is associated with response to NVP-BGJ398. A, box-plot showing FGFR1 copy number expressed as log 2 ratio for the 541 cell lines clustered according to cancer type. B, scatter plot of breast, lung, and osteosarcoma cancer cell lines showing the correlation between DNA copy number and transcript expression of FGFR1 . Cell lines are colored according to response to NVP-BGJ398. C, effect of NVP-BGJ398 on FGFR downstream signaling as measured by FRS2 Tyr-phosphorylation and Erk1/2 activation. α-Actinin and total Erk1/2 protein levels are shown as a loading control. DMSO, dimethyl sulfoxide. D, stable G292 cell lines expressing short hairpin RNA (shRNA) under the control of a doxycycline (Dox)-inducible promoter were generated via lentiviral infection and puromycin selection. Western blot analysis shows effi cient FGFR1 knockdown, p-FRS2 and p-Erk inhibition with shRNA1237 and shRNA1425, as compared with 2 nontargeting shRNAs (NT sh1 and NT sh2). β-Tubulin Western blot analysis is shown as a loading control. E and F, effect of FGFR1-targeting as compared with nontargeting shRNAs on monolayer cell proliferation (E) and anchorage-independent cell growth assays (F) of G292 cells. For monolayer cell proliferation assay, cell growth was monitored at the indicated days after cell seeding, whereas endpoint measure-ments are given for the soft agar assay (day 15 after cell seeding). G, FGFR1 copy number in a panel of 17 primary human osteosarcoma samples was analyzed by quantitative real-time PCR. Data are shown as average with SEM ( n ≥ 2). Br, breast; Ch, chondrosarcoma; CN, copy number; Co, colorectal; En, endometrial; ERK, extracellular signal-regulated kinase; Es, esophagus; Ew, Ewing sarcoma; Ga, gastric; Gl, glioma; HL, hematopoietic and lymphoid tissue; HN, head and neck; Ki, kidney; Li, liver; Lu, lung; Me, melanoma; Ms, mesothelioma; Nb, neuroblastoma; Os, osteosarcoma; Ov, ovarian; Pa, pancreas; Th, thyroid; UT, urinary tract.

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FGFR1 mRNA within the breast, lung, and osteosarcoma line-ages ( Fig. 4B ). Statistical analysis using the Fisher exact test showed that FGFR1 amplifi cation was signifi cantly associated with response to NVP-BGJ398 when all the cell lines were considered ( P = 4.8 × 10 −4 ) and in particular in the breast, lung, and osteosarcoma subsets ( P = 1.5 × 10 −5 ). A require-ment of FGFR1 activity for proliferation has been previously shown for FGFR1 -amplifi ed breast and lung cancer cell lines ( 5, 6 ). Because FGFR1 amplifi cation in osteosarcoma associ-ated with sensitivity to an FGFR inhibitor has not previously been reported, we sought to further assess the role of FGFR1 as a cancer driver in this indication with an independent approach. To this end, lentivirus expressing doxycycline-inducible short hairpin RNAs (shRNA) targeting FGFR1 was introduced into G292 cells. Although infection with viruses expressing 2 nontargeting shRNAs had no effect on the pro-tein expression levels and cell growth, the viruses directing the expression of 2 shRNAs targeting FGFR1 led to a signifi cant decrease in FGFR1 protein expression, FRS2 tyrosine phos-phorylation, and extracellular signal-regulated kinase (ERK) phosphorylation. In parallel, the FGFR1 shRNA–containing viruses suppressed G292 cell proliferation in both monol-ayer and anchorage-independent conditions ( Fig. 4D–F ). The functional relevance of FGFR1 amplifi cation in the osteosar-coma cell line led us to investigate FGFR1 copy number levels in a panel of primary human osteosarcoma samples. Consist-ent with FGFR1 amplifi cation in 1 of 7 osteosarcoma cell lines within the CCLE, we identifi ed 1 of 17 primary osteosarcoma samples as FGFR1 amplifi ed ( Fig. 4G ). Interestingly, both the G292 cell line and the primary tumor sample showed similar levels of amplifi cation, with about 5 copies of the FGFR1 gene in both cases.

These results reveal for the fi rst time that FGFR1 amplifi ca-tion occurs in osteosarcoma, confi rm its prevalence in breast and lung cancer cells, and show that FGFR1 is required for cancer cell growth in these settings. Hence, FGFR1 amplifi ca-tion is a predictor of sensitivity to an FGFR inhibitor in these 3 lineages.

FGFR2 Amplifi cation Is Associated with Response to NVP-BGJ398 in Cell Lines and Primary Human Tumors

FGFR2 -amplifi ed cell lines were also enriched in the “FGFR genetic alteration” and “GeneSets” positive clusters. Analysis of single-nucleotide polymorphism (SNP) 6.0 array data across the CCLE revealed a high level of FGFR2 amplifi cation (log 2 ratio ≥1) in cell lines of gastric lineage, as previously shown ( 8 ), but also in a colon cancer line ( Fig. 5A ). Gene amplifi cation in these cell lines was correlated with striking FGFR2 transcript overexpression when specifi c Affymetrix probesets (211401_s_at_) that detect FGFR2 C-terminal splice variants in addition to the canonical FGFR2 form were used ( Fig. 5B ). These data are consistent with previously published results showing that breast and gastric cancer cells with FGFR2 amplifi cation over-express the more oncogenic FGFR2-c3 variant ( 30 ). In addi-tion, by means of quantitative real-time PCR (qRT-PCR), we confi rmed that NCI-H716 colon cancer cells also overexpress this specifi c C-terminal–truncated FGFR2 isoform and that only cell lines with FGFR2 amplifi cation showed signifi cant FGFR2-c3 expression (Supplementary Fig. S4A).

In keeping with the high levels of FGFR2 gene expression, FGFR2 -amplifi ed gastric (KATOIII and SNU16) and colon (NCI-H716) cancer cell lines showed strong baseline activity of the FGFR pathway, which was modulated upon NVP-BGJ398 treatment ( Fig. 5C ), and were dependent on FGFR signaling for proliferation, as evident from the low nanomo-lar IC 50 for NVP-BGJ398 (Supplementary Table S2).

In agreement with inhibition of in vitro proliferation, NVP-BGJ398 also effectively inhibited growth of SNU16 tumor xenografts in a dose-dependent manner when administered orally to rats on a daily schedule ( Fig. 5D ). Tumor growth inhibition was correlated with inhibition of FGFR2 tyrosine phosphorylation in tumor tissue ( Fig. 5E ), which was almost completely abolished 3 hours after dosing and recovered at 24 hours after dosing, in line with the pharmacokinetic pro-fi le of the compound ( 25 ).

A statistical analysis by Fisher exact test showed a signifi -cant association between FGFR2 amplifi cation and response to NVP-BGJ398 across the CCLE ( P = 1.9 × 10 −4 ), as well as when restricted to the gastric and colon cancer lineages ( P = 1.6 × 10 −4 ). To further test the predictive value of FGFR2 genomic amplifi cation, we interrogated a collection of 49 human primary gastric tumors for which SNP6.0 copy number and Affymetrix expression data had been gener-ated. Two primary tumors showing FGFR2 copy number 4 or more and FGFR2 transcript overexpression were selected for in vivo antitumor effi cacy testing in mice ( Fig. 6A ). Oral treatment with NVP-BGJ398 on a daily schedule led to sub-stantial tumor growth inhibition leading to tumor stasis and regression at daily doses of 15 mg/kg or more ( Fig. 6B and C ). Pharmacodynamic effects were evaluated in the GAM033 tumor model; at the 15-mg/kg dose, NVP-BGJ398 completely suppressed FGFR2 tyrosine phosphorylation 3 hours after dosing ( Fig. 6D ), in line with the pharmacoki-netic profi le of the compound ( 25 ).

Thus, FGFR2 -amplifi ed cell lines are sensitive to NVP-BGJ398 in vitro as well as when grown in vivo as human tumor xenografts. Hence, we envision that human gastric tumors harboring FGFR2 amplifi cation will be responsive to NVP-BGJ398 in the clinic. Interestingly, in addition to confi rming the incidence of this genetic alteration in gastric cancer, we also found FGFR2 amplifi cation in 1 of 22 esophageal tumors, which offers a novel potential clinical opportunity for an FGFR inhibitor (Supplementary Fig. S4B).

FGF19 Amplifi cation in Liver Cancer Correlates with Response to NVP-BGJ398

Approximately 47% of the cell lines responsive to NVP-BGJ398 did not harbor FGFR genetic alterations. Among those, the gene encoding for the FGF19 ligand was found to be amplifi ed (log 2 ratio ≥1) in the liver cancer cell lines HUH7, HEP3B, and JHH7 ( Fig. 7A ), as previously reported ( 12 ). The analysis of the CCLE SNP6.0 data revealed 49 addi-tional cell lines with FGF19 copy number gain across vari-ous cancer types (Supplementary Fig. S5A, top). However, among the FGF19 -amplifi ed cell lines, only 3 liver cell lines showing concomitant expression of β-Klotho were sensitive to NVP-BGJ398, with the exception of a breast and a lung cancer cell line (MDAMB134 and DMS114) that harbor






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Figure 5. FGFR2 amplifi cation in gastric and colon cancer cell lines is associated with response to NVP-BGJ398. A, box-plot showing FGFR2 copy number expressed as log 2 ratio for the 541 cell lines grouped according to cancer type. B, scatter plot of gastric and large intestine cancer cell lines showing the correlation between FGFR2 DNA copy number and transcript expression. C, effect of NVP-BGJ398 on FGFR downstream signaling as measured by FRS2 Tyr-phosphorylation and Erk1/2 activation. α-Actinin and total Erk1/2 protein levels are shown as a loading control. D, SNU16 tumor xenograft–bearing nude rats received NVP-BGJ398 at the indicated doses or vehicle for 14 consecutive days ( n = 6 per group). The changes over time in tumor volume are shown. Statistical analysis was conducted by 1-way ANOVA–Dunnett versus vehicle control (*, P < 0.001). E, tumor tissues were recovered 3 and 24 hours after dose treatment and analyzed for FGFR2 Tyr-phosphorylation by Western blot analysis. Total FGFR2 Western blot analysis was conducted to monitor equal loading. Pharmacodynamic analysis of tumors treated with 15 mg/kg NVP-BGJ398 was not feasible due to insuffi cient material. Br, breast; Ch, chondrosar-coma; Co, colorectal; En, endometrial; Es, esophagus; Ew, Ewing sarcoma; Ga, gastric; Gl, glioma; HL, hematopoietic and lymphoid tissue; HN, head and neck; Ki, kidney; Li, liver; Lu, lung; Me, melanoma; Ms, mesothelioma; Nb, neuroblastoma; Os, osteosarcoma; Ov, ovarian; Pa, pancreas; Th, thyroid; UT, urinary tract.






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Figure 6. FGFR2 amplifi cation in primary human gastric tumors predicts for response to NVP-BGJ398. A, scatter plot of primary human gastric tumors showing the relationship between FGFR2 copy number and transcript expression ( n = 49). The gastric tumors CHGA10 and GAM033 with FGFR2 gene amplifi cation [(B) and (C), respectively] were grown subcutaneously in mice. Treatment with NVP-BGJ398 at the indicated doses started when average tumor volume was 150 to 180 mm 3 and proceeded for up to 14 or 25 days. Tumor volume changes over the course of treatment are shown. Statistical analysis was conducted by 1-way ANOVA–Dunnett versus vehicle control (*, P < 0.001). D, tumor tissues from primary tumor model GAM033 treated with 15 mg/kg NVP-BGJ398 were recovered 3 hours after the last dose treatment and analyzed for FGFR2 Tyr-phosphorylation and Erk1/2 activation by Western blot analysis. Total FGFR2, Erk1/2, and β-tubulin Western blot analyses were conducted to monitor loading.

FGFR1 amplifi cation ( Fig. 7A and Supplementary Fig. S5A, bottom). Accordingly, the Fisher exact test showed a statis-tically signifi cant association between FGF19 copy number and response to NVP-BGJ398 for the liver cancer lineage ( P = 0.01), but not when the correlation was tested across all lineages ( P = 0.2).

The 3 sensitive liver cancer cell lines showed constitutive FRS2 Tyr-phosphorylation, which was abolished upon treat-ment with NVP-BGJ398 at doses of 50 nmol/L ( Fig. 7B ). In hepatocytes and liver cancer cells, FGF19 has been shown to signal through FGFR4 ( 31 ). In line with these fi ndings, we found that the 3 cell lines expressed signifi cantly high levels of FGFR4 mRNA ( Fig. 7A ), and conditional silencing of

FGFR4 with 3 different shRNAs in the JHH7 cell line, previ-ously shown to require FGF19 for survival, led to signifi cant inhibition of cell proliferation ( Fig. 7C and D ).

Thus, these results suggest that whereas most cancers with 11q13 amplifi cation may not respond to FGF19/FGFR4 inhibitors, the subset of FGF19 -amplifi ed liver cancer with concomitant expression of β-Klotho may provide a suitable niche indication for this therapeutic modality.

DISCUSSION

In this study, we have identifi ed patient selection strategies for NVP-BGJ398, a novel selective pan-FGFR kinase inhibitor






Figure 7. FGF19 amplifi cation in liver cancer cell lines is associated with response to NVP-BGJ398. A, scatter plot showing the correlation between FGF19 copy number and transcript expression of FGF19 , FGFR4 , and β-Klotho ( KLB ) in liver cancer cell lines. B, effect of NVP-BGJ398 on FGFR down-stream signaling as measured by FRS2 Tyr-phosphorylation and Erk1/2 activation by Western blot analysis after 40 minutes of FGFR inhibitor treatment. Expression of α-actinin indicates equal loading. C, effect of 3 different shRNAs targeting FGFR4 in JHH7 cells upon induction with doxycycline (Dox), compared with a nontargeting shRNA. FGFR4 expression and FRS2 Tyr-phosphorylation are shown in doxycycline-induced and noninduced cell lines. Western blot analysis shows α-actin as a loading control. D, effect of FGFR4 downregulation on monolayer cell proliferation assays at day 7 after cell seeding.

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currently in phase I clinical trials in patients with cancer. To guide patient selection and to maximize the likelihood of patient benefi t and successful clinical proof-of-concept for this novel targeted anticancer modality, we have analyzed the sensitivity of more than 500 cell lines from the CCLE to NVP-BGJ398 in cell viability assays and intersected response data with information on gene expression and genomic altera-tions. We show that NVP-BGJ398 inhibits proliferation of about 6% of the cancer cell lines tested at concentrations that are consistent with its mechanism of action and in line with its highly selective nature. Furthermore, the integrative analy-sis of the CCLE has revealed “FGFR genetic alteration” as the top predictor for response to NVP-BGJ398 among more than 50,000 input features containing genomic, lineage, and gene set features.

Indeed, among the 541 cell lines in the CCLE with phar-macologic drug sensitivity data, 37 harbored an FGFR genetic alteration and 17 of them were sensitive to NVP-BGJ398; this represents 53% of the total cell lines respond-ing to the drug (17/32). Gene amplifi cations were most prevalent (10/17) and involved FGFR1 , FGFR2 , and, sur-prisingly, also FGFR3 , followed by sequence variations in FGFR2 and FGFR3 (6/17) and chromosomal translocations affecting FGFR1 and FGFR3 (3/17). High-resolution SNP6.0 array data across the CCLE subjected to analysis with the GISTIC algorithm revealed that the FGFR1 locus lies in a focal peak region of amplifi cation, whereas FGFR2 was found in a GISTIC peak when the analysis was restricted to the gastric cancer cell lines ( 32 ). In this setting, NVP-BGJ398 response was associated in a statistically signifi cant manner with both FGFR1 amplifi cation and FGFR2 amplifi cation. These data confi rmed the fi nding of FGFR1 and FGFR2 copy number alterations in breast, lung, and gastric cancer cell lines as previously reported ( 5, 6 , 9 ), but it also revealed the occurrence of these genetic lesions in additional cancer types, such as osteosarcoma and colon, respectively. In this context, among the 7 osteosarcoma lines in the CCLE, the one harboring FGFR1 amplifi cation (G292) was signifi cantly growth suppressed under both monolayer and soft-agar conditions upon inducible knockdown of FGFR1 by 2 distinct shRNAs, consistent with the notion that amplifi ed FGFR1 confers cancer dependence. In addition, and for the fi rst time, we report FGFR1 amplifi cation in 1 of 17 pri-mary osteosarcomas, suggesting that this may be another potential indication for an FGFR inhibitor. Similarly, NCI-H710, the only colon cancer cell line with high level FGFR2 amplifi cation, was sensitive to NVP-BGJ398. In line with the notion that FGFR2 is a driver oncogene when its locus is aberrantly amplifi ed, we selected human primary gastric tumors for the presence of FGFR2 copy number altera-tions and confi rmed them to be exquisitely responsive to the selective FGFR inhibitor NVP-BGJ398, whereas models with normal FGFR2 DNA copy number were insensitive to the drug (data not shown). In agreement with previous analyses of FGFR2 copy number alterations conducted by FISH ( 8, 9 ) or Southern blot ( 11 ), we have found high level amplifi cations (copy number > 10) of FGFR2 by means of PCR in 5% of gastric tumors among a total of 147 specimens as well as in 1 of 22 esophageal tumors, which has not previously been reported, thus providing additional new opportunities

for the therapeutic application of an FGFR inhibitor. Inter-estingly, we also identifi ed FGFR3 copy number gains in 3 of the bladder cancer cell lines that were inhibited by NVP-BGJ398 (log 2 ratio 1 for RT112 and RT112/84 and log 2 ratio 0.94 for RT4), which may account for the signifi -cantly high FGFR3 transcript expression in these cell lines (Supplementary Fig. S5B). Taken together, these data sup-port the evaluation of NVP-BGJ398 in cancer types selected upon the presence of FGFR gene amplifi cation.

Genomic predictors of drug sensitivity also revealed FGFR2 and FGFR3 mutation among the top 3 most sig-nifi cant features. The viability of 6 of 9 FGFR-mutated cell lines was pharmacologically inhibited by NVP-BGJ398; they belong to the endometrial and multiple myeloma lin-eages and showed constitutive FGFR pathway activation (Supplementary Fig. S2), in line with the notion that these mutations result in receptor kinase activation ( 17 , 19 , 21 ). Notably, most endometrial FGFR2- mutated cell lines also carried mutations affecting either PTEN or PIK3CA (Sup-plementary Table S4), suggesting that the activation of this pathway does not confer resistance to an FGFR-inhibitory therapy in this cancer type. Of note, we observed constitutive AKT phosphorylation in the endometrial cancer cell lines, which was not affected by NVP-BGJ398 treatment (Sup-plementary Fig. S2). Therefore, phosphoinositide 3-kinase inhibitors may provide opportunities for combination ther-apy with NVP-BGJ398 in these specifi c settings.

Interestingly, 54% ( n = 20) of the FGFR genetically altered cell lines were not NVP-BGJ398-sensitive. It is likely that at least in some of these cell lines, additional genetic alterations bypass FGFR dependency. For instance, 1 cell line (A375) had a BRAF V600E mutation, and 10% ( n = 2) of the cell lines showed amplifi cation of other oncogenes (JIMT1 HER2 amplifi ca-tion and NCI-H1703 PDGFRα amplifi cation), whereas 20% ( n = 4) harbored KRAS mutations (Supplementary Table S4), and KRAS mutation was revealed by the predictive model as one of the genomic predictors for NVP-BGJ398 insensitivity (data not shown). Thus, we are currently exploring whether hypothesis-driven concomitant targeting of other genetically altered molecular pathways will synergize with NVP-BGJ398 in these settings. Alternatively, and in the case of the breast and lung FGFR1 -amplifi ed cell lines that did not respond to NVP-BGJ398, it is plausible that one of the other genes found in the GISTIC peak ( LETM2 , WHSC1L1 ) may have become the driver gene. It is also noticeable that none of the FGFR4 -amplifi ed cell lines in our data set responded to the FGFR inhibitor, thus indicating that FGFR4 is not a driver oncogene in those settings.

Conversely, several cell lines that displayed sensitivity to NVP-BGJ398 did not harbor FGFR genetic lesions. Three of them, belonging to the liver cancer type, showed copy number gain for the FGFR4 ligand, FGF19, and FGF19 amplifi cation was statistically signifi cantly associated with response to NVP-BGJ398 when the analysis was restricted to liver cancer cell lines. Furthermore, by conditional knockdown of FGFR4, we showed dependency on this RTK in the JHH7 cells, thus supporting the concept of an FGF19/FGFR4 autocrine loop as the oncogenic driver in liver cancer with FGF19 amplifi cation. In line with the notion that this autocrine loop is only functional in the






presence of the coreceptor β-Klotho, which is essential for high affi nity interactions of FGF19 with FGFR4 ( 33 ), we showed that only 3 liver cancer cells with FGF19 amplifi ca-tion and concomitant β-Klotho expression responded to NVP-BGJ398. This suggests that β-Klotho depicts another critical determinant for patient selection, which has not been analyzed previously. Consequently, FGF19 amplifi ca-tion was not associated with NVP-BGJ398 response in other cancer types most likely due to the lack of or low β-Klotho expression. This is in line with a recent study ( 12 ) showing that FGF19 amplifi cation correlated with increased expres-sion and with sensitivity to FGF19 blockage only in liver cancer cell lines.

Taken together, we have not detected FGF/FGFR genetic abnormalities in 37.5% ( n = 12) of NVP-BGJ398–sensitive cell lines. Most of these cell lines were GeneSet signature– positive or expressed high levels of either of the FGFRs and FGF ligands and generally showed constitutive activation of the FGFR pathway and modulation upon NVP-BGJ398 treatment (Supplementary Fig. S2), suggesting that FGFR dependency could be the result of intrinsic upregulation of components of the FGF signaling system leading to con-stitutive pathway activation. It will be interesting in future studies to address the underlying mechanisms resulting in FGF/FGFR induction in the absence of gene copy number gain or activating mutations of the receptors. It is plausible that epigenetic modulations or genetic alterations on other pathways ultimately leading to FGF/FGFR elevated expres-sion and/or activation may have occurred. For example, it has recently been discovered that FGFR4 overexpression occurs in alveolar rhabdomyosarcomas with PAX3/7–FKHR transloca-tion and that FGFR4 is a downstream target of the oncogenic fusion protein ( 34 ).

In summary, by leveraging the integration of the CCLE annotation and compound sensitivity data, we have identi-fi ed genetic alterations in various members of the FGF/FGFR system that confer cancer dependence and thus represent suitable predictive biomarkers to guide patient selection for treatment with selective FGFRs targeting agents, such as the novel pan-FGFR kinase inhibitor NVP-BGJ398. Based on these data, a phase I clinical trial with NVP-BGJ398 is being conducted in patients with cancer bearing FGFR genetic alterations ( 35 ).

METHODS

Compound and Antibodies NVP-BGJ398 has been identifi ed and synthesized in the Global

Discovery Chemistry Department at NIBR (Novartis) as described ( 25 ). For in vitro studies, 10 mmol/L stock solutions were prepared in 100% dimethyl sulfoxide (DMSO). For in vivo studies in rodents, NVP-BGJ398 was formulated in acetic acid/acetate buffer pH 4.6/PEG300 1:1.

Antibodies used for Western blot analysis were anti-S473P-Akt (#9271), anti-Akt (#9271), anti-T202P/Y204P-Erk1/2 (#9101), anti-Erk1/2 (#9102), anti-Y196P-FRS2 (#3864), anti-Y653/654P-FGFR (55H2; #3476) from Cell Signaling; anti-Flg (M2F12) FGFR1 (#sc-57132), anti-Bek (C-17) FGFR2 (#sc-122), anti-FGFR4 (C-16; #sc-124), anti-FRS2 (H-91; #sc-8318) from Santa Cruz; anti-FGFR2 (α-isoforms; MAB6841) from R&D Systems; anti-FRS2/SNT-1

(#05-502), anti-phospho-Tyrosine, clone 4G10 (05-321), anti-α-actinin (#05-384) from Millipore; and anti-β-tubulin (# T4026) from Sigma.

In Vitro Compound Profi ling Biochemical in vitro kinase assays, cellular FGFR autophosphor-

ylation assays, and BaF3 cell proliferation assays were conducted as described ( 25 ).

High-Throughput Cell Line Profi ling and Manual Cell Proliferation Assays

Cell lines were obtained from American Type Culture Collec-tion, Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ) and Health Science Research Resources Bank (HSRRB) and cultured in RPMI or Dulbecco’s modifi ed Eagle’s medium plus 10% FBS (Invitrogen) at 37°C 5% CO 2 using automated processing. Cell line identities were confi rmed using a 48-variant SNP panel and comparing them with previous cell line tests. A detailed descrip-tion of the high-throughput cell viability assays can be found in the report of Barretina and colleagues ( 26 ). In brief, assays were automated and conducted with an ultra–high-throughput screen-ing system. Cell lines were dispensed into tissue culture–treated 1,536-well plates in a fi nal volume of 5 μL and a concentration of 250 cells per well, were allowed to adhere, and were cultured for 12 to 24 hours. Prediluted compounds were transferred to the cells, resulting in a fi nal concentration range of 8 μmol/L to 2.5 nmol/L in more than 8 steps and a uniform DMSO concentration of 0.4%. The cell–compound mixture was incubated for 72 to 84 hours, and cell growth was analyzed by determination of the cellular ATP content (Cell Titer Glo; Promega) using a luminescence plate reader (ViewLux; PerkinElmer). On all plates, wells containing vehicle only and the positive control MG132, a proteasome inhibitor, at 1 μmol/L were included. Raw values were percentage normalized on a plate-by-plate basis such that 0% was equivalent to the median of vehicle wells and −100% equivalent to the median of the positive control. Quality of cell response to the positive control (MG132) was measured using a standard Z ′ factor ( 36 ). In general, nearly all responses were more than 0.5, indicating a robust assay window. All dose–response data were reduced to a fi tted model using a propriety decision tree method that is based on the NIH Chemical Genom-ics Center assay guidelines ( 26 ). Fitted models were assessed with a standard χ 2 test that was also used to determine which model to use. All data were manually reviewed as well. Parameters derived form the models include IP, the infl ection point of the curve; cross-ing point (CP), the concentration in which the fi tted curve crosses −50%; and A max , the maximal activity value reached within a model.

For manual cell proliferation assays, cells were seeded in 96-well plates at a density of 10 3 to 10 4 cells per well in a volume of 100 μL. Media containing compound dilutions or DMSO was added 24 hours thereafter. After 72 hours or 7 days, Cell Titer Glo was added as done earlier. The concentration of compound providing 50% of prolifera-tion inhibition (IC 50 ) was determined using XLfi t (idbs).

Generation of Stable Cell Lines with Hairpin shRNAs Hairpin shRNAs were cloned in pLKO-Tet-On vector to produce

replication-incompetent lentiviruses as described previously ( 37 ). Upon lentiviral infection, stable cell lines were generated by selec-tion with puromycin (1.5 μg/mL) for 5 days. For monolayer cell proliferation assays, cells were seeded in 96-well plates and shRNAs were induced with doxycycline. Cell proliferation was evaluated by methylene blue staining or Cell Titer Glo as done earlier. For soft-agar assays, cells were dispensed in 96-well plates in growth medium containing 0.6% agar on a layer of solidifi ed media containing 1% agar. shRNAs were induced with doxycycline, and colony formation was evaluated 14 days after plating with Resazurin staining.






shRNA sequences were as follows:

FGFR1-sh1: GCCAAGACAGTGAAGTTCAAA, FGFR1-sh2: GAAT-GAGTACGGCAGCATCAA, NT-sh1: GGATAATGGTGATTGA-GATGG, NT-sh2: AGAAGAAGAAATCCGTGTGAA.

FGFR4-sh13: GCCGACACAAGAACATCATCA, FGFR4-sh14: GCT-GGAGAGCTGCTATGCTAA, FGFR4-sh15: TCCATGATCGTC-CTGCAGAAT, NT-sh3: CAACAAGATGAAGAGCACCAA.

Genomic Analysis of Cell Lines and Primary Tumors A detailed description can be found in the report of Barretina and

colleagues ( 26 ); see also ( 32 ). In brief, DNA copy number was meas-ured using high-density SNP arrays (Affymetrix SNP6.0) and normal-ized to copy number estimates (log 2 ratios; with log 2 ratio 0 being equal to 2N normalized copies) using a Gene-Pattern pipeline ( 38 ) and hg18 Affymetrix probe annotations. Sample-specifi c and recur-rent copy number changes were identifi ed using the GISTIC algo-rithm ( 39 ). mRNA expression levels were obtained using Affymetrix U133 plus 2.0 arrays according to the manufacturer’s instructions. The microarray data accession number in GEO is GSE36139.

FGFR2-c3 Isoform mRNA Expression The primers to specifi cally monitor expression of the FGFR2-c3

isoform were designed for TaqMan assay: FGFR2-F: CTTGGATC-GAATTCTCACTCTCACA, FGFR2-R: CCTGACCAACTTTTC-CCAGTTTCT, probe: CCAATGAGATCTGAAAGTTT. For internal control, β-actin primers and probe (ABI catalog number: 4326315E) were mixed with those of FGFR2. The qRT-PCR thermal cycles were run at 95°C for 15 seconds, 56°C for 25 seconds, and 68°C for 45 sec-onds using TaqMan Universal PCR Master Mix (ABI catalog number 4304437).

FGFR1 PCR from Human Primary Osteosarcoma DNA Samples

Seventeen genomic DNA samples from osteosarcomas were acquired from the Peter MacCallum Cancer Institute, (Melbourne, Australia; ref. 40 ). The primers used for FGFR1 copy number deter-mination by SYBR green PCR assays were: FGFR1-F: GCATCATAAT-GGACTCTGTGGTG, FGFR1-R: GTGGTTGATGCTGCCGTACTC. LINE1 was used as the reference: LINE-F: AAAGCCGCTCAACTA-CATGG, LINE-R: TGCTTTGAATGCGTCCCAGAG. The assay was carried out using ABI SYBR Green PCR Master Mix (catalog number: 4309155) as described previously ( 40 ).

FGFR2 PCR from Human Primary Tumor DNA Samples One hundred and thirteen genomic DNA samples from gastric

or esophageal cancer specimens were acquired from Asterand, Indi-vumed, Cytomyx, and Bio Serve. Fifty-six samples from gastric tumors were from PrognoGen Biotechnology Co., LTD, who conducted the copy number analysis by PCR according to Novartis protocols. The primers to quantify FGFR2 locus copy number were designed for SYBR green assays: FGFR2-F: GTGTGTCTGGCAAGCTGTGT, FGFR2-R: AGACTCTGGCTTTCGCTGAG. Quantifi cation using LINE1 as a reference was conducted as described earlier for FGFR1 .

Xenograft Rodent Models and Antitumor Effi cacy Studies The experimental procedures involving animal studies strictly

adhered to the Association for Assessment and Accreditation of Laboratory Animal Care International guidelines as published in the Guide for the Care and Use of Laboratory Animals, and to Novartis Corporate Animal Welfare policies. The study with the human pri-mary gastric model GAM033 was conducted at CrownBio Inter-national R&D center. The studies with the human primary gastric

model CHGA010 and the cell line–derived xenograft SNU16 were conducted at Novartis facilities. All primary tumor samples were obtained from patients at the time of surgery, with informed writ-ten patient consent, and the study was approved by the local ethical committee. Tumor cells, or tumor fragments in the case of primary tumors, were implanted subcutaneously in rodents. Treatment with NVP-BGJ398 or vehicle control started when average tumor size was at least 100 mm 3 and tumor volumes were monitored at the indicated times over the course of treatment. Data are presented as mean ± SEM. Comparisons between groups and the vehicle control group were done using 1-way ANOVA followed by Dunnett tests. The level of signifi cance is indicated for each experiment. At the end of treatment, tumors were excised and snap-frozen in liquid nitrogen. Frozen tissues were pulverized using a swing mill (RETSCH MM200), and tumor powder was lysed in standard protein lysis buffer for further Western blot analysis.

Disclosure of Potential Confl icts of Interest V. Guagnano , A. Kauffmann, S. Wöhrle, C. Stamm, M. Ito, L. Barys,

A. Pornon, Y. Yao, F. Li, Y. Zhang, Z. Chen, C.J. Wilson, V. Bordas, M. Le Douget, L.A. Gaither, J. Borawski, J.E. Monahan, K. Venkate-san, T. Brümmendorf, F. Hofmann, W.R. Sellers, and D. Graus-Porta are employees of Novartis Institutes for BioMedical Research. W.R. Sellers holds the position of VP/Global Head of Oncology in Novartis Institutes for BioMedical Research and has ownership interest (including patents) in Novartis Pharmaceuticals. C. Garcia-Echeverria was an employee of Novartis Institutes for BioMedical Research and is now an employee of Sanofi and has ownership inter-est (including patents) in Sanofi . No potential confl icts of interest were disclosed by D.M. Thomas.

Authors’ Contributions Conception and design: Y. Yao, Y. Zhang, L.A. Gaither, F. Hofmann, W.R. Sellers, D. Graus-Porta Development of methodology: C. Stamm, M. Ito, Y. Zhang, Z. Chen, C.J. Wilson, L.A. Gaither, J.E. Monahan, T. Brümmendorf Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): S. Wöhrle, C. Stamm, M. Ito, L. Barys, A. Pornon, Y. Yao, Y. Zhang, Z. Chen, C.J. Wilson, L.A. Gaither, J. Borawski, J.E. Monahan, D.M. Thomas, D. Graus-Porta Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): A. Kauffmann, S. Wöhrle, C. Stamm, M. Ito, L. Barys, A. Pornon, Y. Yao, F. Li, Y. Zhang, C.J. Wilson, L.A. Gaither, J. Borawski, K. Venkatesan, T. Brümmendorf, D. Graus-Porta Writing, review, and/or revision of the manuscript: V. Guagnano, A. Kauffmann, M. Ito, Y. Zhang, Z. Chen, L.A. Gaither, T. Brümmen-dorf, C. Garcia-Echeverria, F. Hofmann, W.R. Sellers, D. Graus-Porta Administrative, technical, or material support (i.e., report-ing or organizing data, constructing databases): M. Ito, A. Por-non, Y. Zhang, C.J. Wilson, V. Bordas, M. Le Douget, L.A. Gaither, D.M. Thomas Study supervision: Y. Zhang, Z. Chen, F. Hofmann, D. Graus-Porta Scientifi c and managerial supervision and mentorship: C. Garcia-Echeverria

Acknowledgments The authors thank Joerg Trappe and Juergen Koeppler for con-

ducting the biochemical assays, Sandra Molle for technical help with cellular assays, Markus Wartmann and Timothy Smith for the BaF3 profi ling assays, Sabine Zumstein-Mecker for technical assistance with genomic PCRs, Ramona Rebmann, Flavia Reimann, and Her-bert Schmid for technical assistance with in vivo profi ling, and Jordi Barretina-Ginesta for proofreading the article. The authors also thank






Oncotest (GmbH, Freiburg, Germany) and Crown Bioscience Inc. (Beijing, P.R. China) for their services with primary human xenografts and Richard Versace for coordinating the contract and being the liaison.

Grant Support This study has been supported by VCA Translational Research Pro-

gram in Sarcoma EOI 71 and by a Senior Research Fellowship from the National Health and Medical Research Council (to D.M. Thomas).

Received May 9, 2012; revised August 22, 2012; accepted September 13, 2012; published OnlineFirst September 20, 2012.

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2012;2:1118-1133. Published OnlineFirst September 20, 2012.Cancer Discovery Vito Guagnano, Audrey Kauffmann, Simon Wöhrle, et al. Selective Pan-FGFR InhibitorFGFR Genetic Alterations Predict for Sensitivity to NVP-BGJ398, a

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