Tumor Genomic Profiling Guides Patients with Metastatic Gastric Cancer to Targeted Treatment: the VIKTORY Umbrella Trial

Published OnlineFirst July 17, 2019; DOI: 10.1158/2159-8290.CD-19-0442

RESEARCH ARTICLE

Tumor Genomic Profiling Guides Patients with Metastatic Gastric Cancer to Targeted Treatment: The VIKTORY Umbrella Trial

Jeeyun Lee1, Seung Tae Kim1, Kyung Kim1, Hyuk Lee2, Iwanka Kozarewa3, Peter G.S. Mortimer4, Justin I. Odegaard5, Elizabeth A. Harrington3, Juyoung Lee1, Taehyang Lee1, Sung Yong Oh6, Jung-Hun Kang7, Jung Hoon Kim8, Youjin Kim9, Jun Ho Ji9, Young Saing Kim10, Kyoung Eun Lee11, Jinchul Kim1, Tae Sung Sohn12, Ji Yeong An12, Min-Gew Choi12, Jun Ho Lee12, Jae Moon Bae12, Sung Kim12, Jae J. Kim2, Yang Won Min2, Byung-Hoon Min2, Nayoung K.D. Kim13,4, Sally Luke3, Young Hwa Kim4, Jung Yong Hong1, Se Hoon Park1, Joon Oh Park1, Young Suk Park1, Ho Yeong Lim1, AmirAli Talasaz5, Simon J. Hollingsworth14, Kyoung-Mee Kim15, and Won Ki Kang1

ABSTRACT The VIKTORY (targeted agent eValuation In gastric cancer basket KORea) trial was designed to classify patients with metastatic gastric cancer based on clinical sequencing and focused on eight different biomarker groups (RAS aberration, TP53 mutation, PIK3CA mutation/amplification, MET amplification, MET overexpression, all negative,TSC2 deficient, or RIC- TOR amplification) to assign patients to one of the 10 associated clinical trials in second-line (2L) treatment. Capivasertib (AKT inhibitor), savolitinib (MET inhibitor), selumetinib (MEK inhibitor), adavosertib (WEE1 inhibitor), and vistusertib (TORC inhibitor) were tested with or without chemotherapy. Seven hundred seventy-two patients with gastric cancer were enrolled, and sequencing was successfully achieved in 715 patients (92.6%). When molecular screening was linked to seamless immediate access to parallel matched trials, 14.7% of patients received biomarker-assigned drug treatment. The biomarker-assigned treatment cohort had encouraging response rates and survival when compared with conventional 2L chemotherapy. Circulating tumor (ctDNA) analysis demonstrated good correlation between high MET copy number by ctDNA and response to savolitinib.

SIGNIFICANCE: Prospective clinical sequencing revealed that baseline heterogeneity between tumor samples from different patients affected response to biomarker-selected therapies. VIKTORY is the first and largest platform study in gastric cancer and supports both the feasibility of tumor profiling and its clinical utility.

INTRODUCTION It has been suggested by previous studies that this interpa- tient tumor molecular heterogeneity may affect the outcomes Recent advances in molecular analysis have revealed that of clinical trials, especially with molecularly targeted agents there are patient subsets with differing genomic alterations (4, 5). To deliver a more tailored approach for each patient, despite the same histologic diagnosis in gastric cancer (1–3). umbrella or platform clinical trials have been developed (6, 7), which assign treatment arms based on the molecular characteristics of the tumor. 1Division of Hematology-Oncology, Department of Medicine, Samsung Gastric cancer was the third leading cause of cancer- Medical Center, Sungkyunkwan University School of Medicine, Seoul, related mortality in 2018, causing 783,000 deaths world- 2 Korea. Division of Gastroenterology, Department of Medicine, Samsung wide (8). The prognosis of patients with metastatic gastric Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. 3Oncology Translational Sciences, IMED Biotech Unit, AstraZeneca, cancer remains extremely poor, with a median overall sur- Cambridge, United Kingdom. 4Clinical, Research and Early Development, vival (OS) of less than 12 months with cytotoxic chemo- Oncology R&D, AstraZeneca, Cambridge, United Kingdom. 5Guardant therapy (9, 10). In addition, gastric cancer is a disease with Health, Redwood, California. 6Dong-A University School of Medicine, significant molecular and histologic heterogeneity (1, 3, 7 Busan, Korea. Department of Internal Medicine, College of Medicine, 11), in which advancements based on “one-size-fits-all” Gyeongsang National University, Jinju, Korea. 8Department of Internal Medicine, Gyeongsang National University School of Medicine, Jinju, clinical trials have yielded only modest survival benefits. Korea. 9Division of Hematology-Oncology, Samsung Changwon Hospital, To identify optimal molecular targets and optimal bio- Sungkyunkwan University School of Medicine, Changwon, Korea. 10Depart- markers, we designed an umbrella trial for second-line ment of Internal Medicine, Gachon University Gil Medical Center, Incheon, (2L) treatment in metastatic gastric cancer based on tumor Republic of Korea. 11Division of Hematology-Oncology, Department of Internal Medicine, Ewha Womans University, Seoul, Korea. 12Department molecular profiling. We took advantage of an umbrella trial of Surgery, Samsung Medical Center, Sungkyunkwan University School design where patients of a single tumor type are directed of Medicine, Seoul, Korea. 13Samsung Genome Institute, Seoul, Korea. toward different arms of the study based on the tumor 14Oncology Business Unit, AstraZeneca, Cambridge, United Kingdom. molecular biomarkers relevant to one or more of the can- 15 Department of Pathology & Translational Genomics, Samsung Medical didate drugs (12). VIKTORY (targeted agent eValuation Center, Sungkyunkwan University School of Medicine, Seoul, Korea. In gastric cancer basket KORea, trial NCT#02299648) was Note: Supplementary data for this article are available at Cancer Discovery Online (http://cancerdiscovery.aacrjournals.org/). designed to classify patients with metastatic gastric cancer based on clinical sequencing and comprised eight different S.T. Kim, K. Kim, H. Lee, and I. Kozarewa contributed equally to this article. biomarker groups (RAS aberration, TP53 mutation, PIK3CA Corresponding Authors: Jeeyun Lee, Samsung Medical Center, Sungky unkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul mutation/amplification, MET amplification, MET protein 06351, Korea. Phone: 822-3410-1779; Fax: 822-3410-1754; E-mail: overexpression, all negative, TSC2 deficient, orRICTOR [email protected]; Kyoung-Mee Kim, [email protected]; and Won Ki amplification) to assign patients to one of the 10 associ- Kang, [email protected] ated phase II clinical trials in 2L treatment. The study drugs Cancer Discov 2019;9:1–18 used were capivasertib (AKT inhibitor), savolitinib (MET doi: 10.1158/2159-8290.CD-19-0442 inhibitor), selumetinib (MEK inhibitor), adavosertib (WEE1 ©2019 American Association for Cancer Research. inhibitor), and vistusertib (TORC inhibitor). The umbrella

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RESEARCH ARTICLE Lee et al. design was based on the preclinical evidence of known The primary tumor was located in the body (53.2%) or molecular alterations, the prevalence of molecular altera- antrum (37.7%) of the stomach in the majority of patients. tions, and the availability of the targeted agents for clinical All patients underwent 1L cytotoxic chemotherapy (>85% trials from AstraZeneca at the time of the study design. The with fluoropyrimidine/platinum regimen). In all, 460 of candidate molecular alterations for the umbrella trial at 715 patients (64.3%) were eligible for 2L therapies: 143 of the time of clinical trial design were molecular alterations 715 (20.6%) were assigned to one of the umbrella-associated in the p53, PIK3CA, MET, EGFR, FGFR2, RAS, and DDR parallel clinical trials in 2L (105 with Biomarker A–E or G; 38 pathways (3). Adavosertib is one of the most potent inhibi- with Biomarker F, unselected), whereas 317 patients received tors targeting WEE1 (13), which is a tyrosine kinase that conventional treatment or treatment via other clinical trials phosphorylates cyclin-dependent kinase 1 (CDK1, CDC2) (Figs. 1B and 2A). to inactivate the CDC2/cyclin B complex (14). Inhibition of WEE1 activity prevents the phosphorylation of CDC2 Tumor Genome Profiling and impairs the G2 DNA-damage checkpoint, leading to The tumor profiles of the 715 patients are shown in Sup- cancer-cell death. Preclinical studies have demonstrated plementary Fig. S1, and the detailed sequencing method is a very promising antitumor efficacyin vivo, especially in provided in the Supplementary Material. The prevalence combination with other cytotoxic chemotherapeutic agents of the predefined biomarkers was as follows (Fig. 2B): Bio- (15) including paclitaxel (16). Capivasertib is a selective marker A1: RAS mutation/amplification (81/715, 12.2%; pan-AKT inhibitor that inhibits the kinase activity of all KRAS 62/715, 8.7%; HRAS 6/715, 0.8%; NRAS 19/715, 2.7%); three AKT isoforms (AKT1–3; ref. 17). Preclinically, sensi- Biomarker A2: high or low MEK signature (49/107, 45.8%); tivity to capivasertib has been strongly correlated with the Biomarker B: TP53 mutation (321/715, 44.9%); Biomarker presence of PIK3CA mutations in gastric cancer models (18, C: PIK3CA mutation/amplification (54/715, 7.6%); Bio- 19). Savolitinib is a potent small-molecule reversible MET marker D: MET amplification (25/715, 3.5%); Biomarker E: kinase inhibitor that inhibits MET kinase at an IC50 of 4 MET overexpression by IHC 3+ (42/479, 8.8%); Biomarker F: nmol/L in MET-amplified cancer cells and has been shown none of the above (Biomarker A–E); Biomarker G: RICTOR to demonstrate promising antitumor activity in patients amplification (5/715, 0.7%)/TSC2 deficient (7/715, 0.9%). In with gastric cancer (20, 21). Selumetinib (AZD6244, ARRY- addition to the predefined biomarkers, we identified other 142886) is a potent, orally active inhibitor of MEK1/2 that known molecular targets in gastric cancer (Supplementary suppresses the pleiotropic output of the RAF/MEK/ERK Fig. S1): FGFR2 amplification (30/715, 4.2%),EGFR ampli- pathway (22, 23). The tolerability and antitumor efficacy of fication (17/715, 2.4%),MDM2 amplification (8/715, 1.1%), the combination of selumetinib and docetaxel were dem- AKT1 amplification (2/715, 0.3%),FGFR1 amplification onstrated in KRAS-mutant non–small cell lung cancer (24). (10/715, 1.4%), and CCNE1 amplification (14/715, 2.0%). Herein we conducted a prospective clinical sequencing In all, 3.5% were MMR-deficient gastric cancer (18/523) master program that was aligned with 8 prespecified genomic and 4% (20/501) were EBV-positive. Concurrent MMR and biomarkers and 10 independent biomarker-associated clin- EBV status are provided in 105 patients treated according ical trials in patients with metastatic gastric cancer. We to biomarker status (Fig. 2B, left). In addition, concurrent explored whether the biomarker-selected platform trial ben- molecular profiling of each patient according to biomarker efits patients with metastatic gastric cancer in terms of sur- (e.g., KRAS mutation and TP53 mutation) and the assigned vival. In addition, we investigated PD-L1 score and circulating umbrella arm is summarized in Fig. 2B (right) according tumor (ctDNA) change between baseline and post-treatment to the biomarker priority. The incidence of MET over- samples following targeted agents. expression by IHC (defined by +3 ) was 8.8% (42/479) in this cohort: 17 (40.5%) of 42 MET-overexpressed tumors RESULTS had MET-amplified tumors by next-generation sequencing (NGS) or FISH, and 25 (59.5%) patients had no MET ampli- Patient Characteristics fication, which concurred with our previous finding on Between March 2014 and July 2018, 772 patients with coactivation of MET protein without amplification (25, 26). metastatic gastric cancer were enrolled onto the VIKTORY trial. Targeted sequencing was successfully achieved with Treatment Efficacy of the Umbrella Trial tissues from 715 patients (92.6%; Fig. 1A and B). Of the 715 The cutoff date for treatment outcome analysis was tissues, 150 (21.1%) were from fresh tumors, 564 (78.9%) October 1, 2018. At the time of analysis, enrollment had from formalin-fixed paraffin-embedded (FFPE) specimens, been completed in all arms or stopped due to early termina- and 1 from ctDNA sequencing using Guardant360 (Fig. 2A). tion of drug development (arms 6, 9, 10) or lack of efficacy Nearly all samples (96.2%) were from the primary gastric at first stage of phase II (arm 7; Supplementary Table S1). tumor specimen; 56.4% of the patients had their tumor Currently, enrollment is completed in phase I of arm 8, sequenced at the time of diagnosis of metastatic gastric and phase II is being considered. Further patient enroll- cancer and 43.6% of patients were sequenced during first- ment was halted in arm 5 (savolitinib/docetaxel combina- line (1L) or at the time of progression following 1L chemo- tion) due to the high efficacy observed with the savolitinib therapy. The tissue type, site of biopsy for sequencing, and monotherapy arm. The primary endpoint was overall response Epstein–Barr virus (EBV) and mismatch-repair (MMR) status rate (ORR); assuming ORR of 20% for 2L paclitaxel, experi- of the 715 patients are summarized in Fig. 2A. A total of mental arms were considered effective if the combination 75.9% of patients had poorly differentiated adenocarcinoma. yielded ≥50% ORR for arms 1–10 except for arm 4 (savolitinib

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The VIKTORY Umbrella Trial in Gastric Cancer RESEARCH ARTICLE

A Patients with metastatic GC

Enrolled for VIKTORY screening 56.4% at the time of 1st-line chemotherapy 43.6% during or at the time of failure to 1st-line chemotherapy

Tumor pathologic–genomic profiling: 1) Targeted tumor sequencing 2) NanoString (MEK signature) 3) IHC panel: MMR, EBV status, PD-L1, c-MET 4) Serial ctDNA sequencing

Biomarker A1: Biomarker A2: Biomarker B: Biomarker C: Biomarker E: Biomarker G: Biomarker D: Biomarker F: RAS mt MEK sig TP53 PIK3CA MET 3+ TSC2 null/ MET amp All negative or amp high or low mutation mt or amp by IHC RICTOR amp

Arm 9*: Vistusertib + paclitaxel Arm 2: PII Arm 3: PII Arm 5: PI/II Arm 6: PII Arm 1: PII Selumetinib + Arm 4: PII Adavosertib + Capivasertib + docetaxel Savolitinib Savolitinib + Vistusertib + Arm 10**: paclitaxel paclitaxel docetaxel paclitaxel Vistusertib + paclitaxel Arm 4-1: PII Arm 7: PII Savolitinib + Capivasertib + docetaxel paclitaxel

Arm 8: PI AZD6738 + paclitaxel

B n = 772, Patients with GC were consented to VIKTORY umbrella screening program n = 57, Excluded n = 48, QC failed for targeted sequencing n = 9, Other reasons (e.g., consent withdrawal)

n = 715, tumor specimens passed QC/sequenced

n = 255, Not eligible for 2nd-line treatment n = 157, Poor PS or followup loss n = 48, Not progressed on 1st-line Tx

n = 460, Patients eligible for 2nd-line treatment

n = 143, Assigned to umbrella associated arms n = 317, Non–umbrella treatment n = 99, Taxol/ramucirumab n = 105, Taxane-based chemotherapy n = 62, Irinotecan-based chemotherapy n = 27, Biomarker-specific sponsored trials (non-VIKTORY) n = 24, Immunotherapy trials

Planned biomarker-negative trial (n = 38) 1) Planned biomarker-negative PII (biomarker exploratory) (n = 27) (vistusertib + paclitaxel (n = 16), capivasertib + paclitaxel (n = 11) 2) Biomarker-negative PI trials (dose finding) (AZD6738 + paclitaxel (n = 9; PI), savolitinib + docetaxel (n = 2; PI) n = 105, Assigned to biomarker-specific trials

Arm 1: Arm 2: Arm 3: Arm 4-1: Arm 5: Arm 9: Arm 10: Selumetinib + Arm 4: Adavosertib Capivasertib Savolitinib + Savolitinib + Vistusertib + Vistusertib + docetaxel + + Savolitinib paclitaxel paclitaxel docetaxel docetaxel paclitaxel paclitaxel KRAS mt or amp/MEK MET amp TP53 mutation PIK3CA mt or MET amp MET 3+ by IHC TSC2 null RICTOR amp high or low (n = 20) (n = 25) amp (n = 24) (n = 4) (n = 4) (n = 2) (n = 1) (n = 25)

Figure 1. An overview of the VIKTORY trial design. A, The study design of the VIKTORY trial. B, The patient allocation schema of the trial. PII, phase II; PI, phase I; GC, gastric cancer; QC, quality control; PS, performance status; mt, mutation; amp, amplification.

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A Targeted seq FF vs. FFPE Site of biopsy EBV status MMR status Disease status Pathology category Treatment assigned

VIKTORY umbrella trial (n = 715)

Targeted sequencing Disease status Yes (715, 100%) Metastatic at diagnosis (577, 80.7%) Tissue type Recurrent after surgery (138, 19.3%) FF (150, 21.0%) Pathology category FFPE (564, 78.9%) w/d adeno (12, 1.7%) Site of biopsy for sequencing m/d adeno (150, 21%) Metastatic lesion (15, 2.1%) p/d adeno ~ signet ring (543, 75.9%) Primary lesion (688, 96.2%) Others (10, 1.4%) N/A (n = 12) Assigned umbrella arm EBV status Arm 1, RAS: Selumetinib/docetaxel (25, 3.5%) Positive (20/501, 4%) Arm 2, TP53 mutation: Adavosertib/paclitaxel (25, 3.5%) Negative (481/501, 96%) Arm 3, PIK3CA mt/amp: Capivasertib/paclitaxel (24, 3.4%) N/A (n = 214) Arm 4, MET amp: Savolitinib (20, 2.8%) MMR status Arm 4-1, MET amp: Savolitinib/docetaxel (4, 0.6%) d-MMR (18/523, 3.5%) Arm 5, MET overexp: Savolitinib/docetaxel (4, 0.6%) p-MMR (505/523, 96.5%) Arm 6/7, Biomarker-negative: Vistusertib or capivasertib (27, 3.8%) Arm 8, AZD6738 phase I (9, 1.3%) N/A (n = 192) Arm 10, RICTOR amp: Vistusertib/paclitaxel (1, 0.1%) Savolitinib/docetaxel phase I (2, 0.3%) Arm 9, TSC1/2 null: Vistusertib/paclitaxel (2, 0.3%) Conventional (317, 44.3%)

B Assigned umbrella arm PIK3CA mutation (n = 25) RAS mt/amplification (n = 22) MET amplification (n = 23) TP53 mutation (n = 48) MET overexpression (n = 21) Assigned umbrella arm MEK high or low (n = 17) Arm 1 (25) Arm 2 (25) Arm 3 (24) Arm 4 (20) Arm 4-1(4) Arm 5 (4) Arm 9 (2) n = 105 Arm 10 (1) n = 102

EBV status Positive (6) Negative (70) N/A (29) MMR status d-MMR (2) p-MMR (74) N/A (29) PD-L1 2 ≥1 (25) <1 (22) N/A (58)

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The VIKTORY Umbrella Trial in Gastric Cancer RESEARCH ARTICLE monotherapy arm). The ORR for each umbrella arm was as most tumor reduction upon adavosertib/paclitaxel therapy. follows: arm 1 (selumetinib/docetaxel): 28% (7/25, 95% CI: Finally, patients with KRAS G13E and KRAS G12D muta- 10.4–45.6), arm 2 (adavosertib/paclitaxel): 24% (6/25, 95% CI: tions, KRAS amplification, or MEK-H withoutKRAS muta- 7.3–40.7), arm 3 (capivasertib/paclitaxel): 33.3% (8/24; 95% tion demonstrated the highest tumor burden reduction by CI: 14.4–52.2), and arm 4 (savolitinib): 50% (10/20, 95% CI: selumetinib/docetaxel. Further focused genomic analysis of 28.0–71.9; Supplementary Table S1 for detailed primary end- the Biomarker D (MET amplification) group and treatment points for each arm). The waterfall plots and swimmer plots response to savolitinib demonstrated that patients with gas- are provided in Fig. 3. Seven of 25 patients who had a partial tric cancer with high MET copy number (>10 MET gene response (PR) in the selumetinib/docetaxel arm (arm 1) had copies by tissue NGS) had high response rates to savolitinib KRAS amplification/high MEK (MEK-H),KRAS wild-type (Fig. 4B). Patient arm4-010 who initially had gastric cancer (WT)/low MEK (MEK-L), KRAS G12R/MEK-H, KRAS G12D/ with peritoneal seeding had a MET tissue NGS copy num- MEK-L, KRAS G12D/MEK-H, KRAS G13D/MEK-I, KRAS WT ber of 25.9 and achieved PR following savolitinib, which MEK-H, and KRAS Q61R/MEK-I, respectively. The longest eventually led to curative surgery, as mentioned previously. responder carried a KRAS amp (KRAS WT) with high MEK Although limited by the small number of patients, 5 respond- signature (arm1-005; Fig. 3A, top right). In terms of KRAS ers to savolitinib had PD-L1–positive tumors [range, 3 to 80 mutational status, there was no significant difference in ORR for combined positive score (CPS)], including patient arm4- between KRAS-mutant (4 of 11, 36.4%) and KRAS WT (3/14, 010 (Fig. 4B). Another focused genomic analysis of the Bio- 21.4%; P = 0.538, χ2 test). For the Biomarker B–arm 2 (ada- marker C (PIK3CA mutation) group and treatment response vosertib/paclitaxel) umbrella, there were six PRs (6/25) and 3 to capivasertib/paclitaxel showed that 57.1% (4 of 7 PRs) had of these patients responded longer than 6 months (Fig. 3B). E542K mutations. Moreover, patients with PIK3CA E542K For Biomarker C–arm 3 (capivasertib/paclitaxel), there were 8 mutations demonstrated an ORR of 50% (4/8), which was responders (8/24) with 4 patients responding for more than higher than the non-E542K cohort (3/16, 18.8%; P = 0.063 by 6 months (Fig. 3C). For Biomarker D–arm 4 (savolitinib mono- χ2; Fig. 4C). Toxicity profiles for the four arms are shown in therapy), there were 10 PRs (10 of 20) one of whom (arm4-010) Supplementary Table S2. had the tumor resected after achieving complete response (CR; Fig. 3D). This patient was a 65-year-old female who was Survival Analysis laparoscopically diagnosed with peritoneal seeding at diag- We conducted an OS analysis on the biomarker-driven nosis. After failing the 1L capecitabine/oxaliplatin treatment treatment group using the Kaplan–Meier plot in all patients. and developing rapidly deteriorating malignant ascites, the In all, patients with gastric cancer who had biomarkers iden- patient was assigned to savolitinib due to high copy-number tified and were treated accordingly N( = 105) demonstrated MET amplification. After significant tumor reduction fol- better OS (median OS, 9.8 months) when compared with lowing savolitinib, the patient underwent curative resection patients who received conventional 2L therapy (N = 266; taxol/ and achieved pathologic downstaging from M1 disease to ramucirumab, N = 99; taxane-based, N = 105; irinotecan-based, T3N2M0 disease. The patient remains in CR, now more than N = 62) treatment (median OS, 6.9 months) with statistical sig- 1 year at the time of manuscript preparation. nificance P( < 0.001; Fig. 5A). The results from the biomarker- driven treatment cohort retained statistical significance in a Prediction of Best Clinical Response Based on multivariate analysis, and this treatment continued to predict Genomic Variations for Individual Patients with better survival (P < 0.0001, HR = 0.58; 95% CI: 0.45–0.76) after Gastric Cancer correcting for potential prognostic factors such as age, gender, Genomic variations are increasingly being utilized as reli- number of involved organs, EBV status, MMR status, and able biomarkers for predicting clinical response to therapy performance status (Fig. 5B). Concordantly, the VIKTORY for gastric cancer (27–29). To identify genomic variants that biomarker-assigned cohort (N = 105) had significantly pro- significantly correlate with clinical response, we compared longed progression-free survival (PFS) when compared with the maximal tumor burden change per RECIST 1.1 against the conventional 2L cohort (N = 266; median PFS, 5.7 months single genomic alterations (Fig. 4A). Patients with MET vs. 3.8 months, respectively, P < 0.0001; Fig. 5C). The mul- amplifications demonstrated the largest absolute decrease in tivariate Cox regression analysis for PFS revealed that being tumor burden per RECIST 1.1. In addition, PIK3CA helical biomarker positive was an independent prognostic factor after domain E542K patients had a more profound (≥50%) reduc- adjustment for the several clinically important factors (Sup- tion in tumor burden when compared with patients with plementary Fig. S2). Hence, when the biomarker was identified other point mutations in PIK3CA—E545G, E545K, E545K, and the patient received a matched treatment with targeted H1047R, C420R, or E453K. Among patients with TP53 muta- agents at an appropriate time, patients had prolonged PFS and tions, R273C, R175H, R342X, and Y220C demonstrated the OS compared with conventional chemotherapy.

Figure 2. Pathologic–genomic landscape of the VIKTORY trial patients. A, A total of 715 patients with gastric cancer were enrolled in the screening program of the VIKTORY trial. Tumor characteristics for each patient are summarized. B, 105 patients were assigned to one of the ongoing biomarker- driven arms. Tumor characteristics for the 105 patients are shown in right panel (MMR status, EBV status, PD-L1 status); concurrently occurring molecular alterations relevant for the clinical trial allocation of each the 105 enrolled patients are shown in right panel. adeno, adenocarcinoma; FF, fresh-frozen tissue; FFPE, formalin-fixed paraffin-embedded; d-MMR, mismatch repair–deficient; p-MMR, mismatch repair–proficient; N/A, not available; w/d, well differentiated; m/d, moderately differentiated; p/d, poorly differentiated; mt, mutation.

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A 75 PR Arm1-005 KRAS amp/MEK-H SD Arm1-008 KRAS Q61H/MEK-I PD Arm1-006 KRAS WT//MEK-L 50 Arm1-019 KRAS WT/MEK-L Arm1-007 KRAS WT/MEK-L Arm1-016 KRAS WT/MEK-L 25 Arm1-003 KRAS G12R/MEK-H * * Arm1-009 KRAS G12R, G12D/MEK-I Arm1-004 KRAS G12D/MEK-I Arm1-012 KRAS G12D/MEK-L 0 Arm1-002 KRAS G13D/MEK-L Arm1-021 KRAS G13D/MEK-I Arm1-024 KRAS WT/MEK-H Arm1-027 KRAS Q61R/MEK-I −25 Arm1-026 KRAS WT/MEK-H Arm1-022 KRAS WT/MEK-H * * Arm1-015 KRAS WT/MEK-H −50 Arm1-025 KRAS WT/MEK-H Arm1-001 KRAS Q61H/MEK-I Arm1-017 KRAS amp/MEK-I Arm1-010 KRAS WT/MEK-L −75 Arm1-011 KRAS G12C/MEK-I Arm1-018 KRAS WT/MEK-L Not evaluable Arm1-014 KRAS WT/MEK-H −100 Arm1-020 KRAS K117N/MEK-I Arm1-017Arm1-024Arm1-002Arm1-001Arm1-004Arm1-026Arm1-006Arm1-015Arm1-011Arm1-019Arm1-016Arm1-010Arm1-009Arm1-008Arm1-022Arm1-003Arm1-027Arm1-012Arm1-005Arm1-021Arm1-007Arm1-025 0816 24 32 40 48 56 Time on study treatment (weeks)

125 B PR SD PD Arm2-004 100 Arm2-014 Arm2-015 Arm2-019 75 Arm2-011 Arm2-005 Arm2-017 50 Arm2-003 Arm2-016 25 Arm2-007 *** ** Arm2-K0001 Arm2-D0001 0 Arm2-012 Arm2-023 Arm2-021 −25 Arm2-010 Arm2-002 Arm2-009 −50 Arm2-018 Arm2-006 Arm2-020 −75 Arm2-001 Arm2-022 Arm2-008 −100 Arm2-020Arm2-022Arm2-018Arm2-001Arm2-008Arm2-003Arm2-023Arm2-006Arm2-007Arm2-002Arm2-012Arm2-009Arm2-021Arm2-D0001Arm2-010Arm2-017Arm2-016Arm2-019Arm2-011Arm2-015Arm2-004Arm2-005Arm2-014Arm2-K0001 0510 15 20 25 30 35 40 45 50 Time on study treatment (weeks)

75 C PR Arm3-KE0001 SD Arm3-017 PD Arm3-010 50 Arm3-013 Arm3-003 Arm3-012 25 Arm3-005 * * Arm3-004 Arm3-DE0001 0 Arm3-019 Arm3-011 Arm3-009 Arm3-008 −25 Arm3-001 Arm3-015 ** Arm3-002 −50 Arm3-020 Arm3-014 EBV-positive Arm3-007 Stopped due to adverse event −75 Arm3-016 Arm3-021 Ongoing Arm3-006 100 Arm3-018 − Arm3-018Arm3-015Arm3-011Arm3-006Arm3-007Arm3-013Arm3-020Arm3-DE0001Arm3-014Arm3-008Arm3-005Arm3-KE0001Arm3-002Arm3-009Arm3-001Arm3-021Arm3-019Arm3-004Arm3-010Arm3-003Arm3-017Arm3-016Arm3-012 Arm3-S001 0816 24 32 40 48 56 64 Time on study treatment (weeks)

100 PR Arm4-010 D SD PD Arm4-005 75 Arm4-012 Arm4-003 50 Arm4-011 Arm4-001 Arm4-004 25 * * Arm4-007 Arm4-009 0 Arm4-013 Arm4-006 Arm4-D0003 −25 Arm4-002 Arm4-014 −50 Arm4-D0002 ≥10 copy MET Arm4-015 5≤ copy <10 MET Arm4-S0001 Ongoing 75 − Arm4-D0004 Not evaluable Arm4-008

−100 Arm4-D0002Arm4-008Arm4-D000Arm4-D0003Arm4-014Arm4-007Arm4-006Arm4-004Arm4-005Arm4-015Arm4-003Arm4-013Arm4-011Arm4-012Arm4-002Arm4-009Arm4-001Arm4-010 0816 24 32 40 48 56 Time on study treatment (weeks) 4

Figure 3. The drug efficacy data. The left panel shows the waterfall plot and the right panel demonstrates the swimmer plot. They -axis represents % of maximum tumor reduction assessed according to RECIST 1.1 criteria. A, Arm 1: selumetinib (MEK inhibitor)/docetaxel arm for patients with RAS- aberrant gastric cancer. B, Arm 2: adovasertib (WEE1 inhibitor)/paclitaxel arm for patients with TP53-mutant gastric cancer. C, Arm 3: capivasertib (AKT inhibitor)/paclitaxel arm for patients with PIK3CA-mutant gastric cancer. D, Arm 4: savolitinib (MET inhibitor) monotherapy arm for patients with MET-amplified gastric cancer. * indicates newly developed lesion per RECIST 1.1. SD, stable disease.

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The VIKTORY Umbrella Trial in Gastric Cancer RESEARCH ARTICLE

A Arm2-004 TP53 Y220C Arm2-010 TP53 Y220C Arm2-020 TP53 Y163C Arm2-015 TP53 R342X Arm2-011 TP53 R342X Arm2-014 TP53 R273C Arm2-007 TP53 R273C Arm2-008 TP53 R273C Arm2-017 TP53 R248W Arm2-006 TP53 R248W Arm2-021 TP53 R248Q Arm2-018 TP53 R248Q Arm2-D0001 TP53 R213X Arm2-012 TP53 R175H; R248Q; Y163N Arm2-K0001 TP53 R175H Arm2-009 TP53 R175H Arm2-001 TP53 R174X Arm2-002 TP53 P152fs Arm2-003 TP53 L252P Arm2-019 TP53 I63S Arm2-023 TP53 G245S Arm2-005 TP53 G244S Arm2-016 TP53 D281H Arm2-022 TP53 C135Y Arm3-019 PIK3CA P471L Arm3-010 PIK3CA M820V Arm3-DE0001 PIK3CA H1047R Arm3-007 PIK3CA H1047R Arm3-011 PIK3CA H1047R Arm3-015 PIK3CA H1047R Arm3-020 PIK3CA G364R Arm3-004 PIK3CA E545K Arm3-001 PIK3CA E545K Arm3-005 PIK3CA E545K Arm3-018 PIK3CA E545K Arm3-KE0001 PIK3CA E545G Arm3-012 PIK3CA E542K Arm3-016 PIK3CA E542K Arm3-017 PIK3CA E542K Arm3-003 PIK3CA E542K Arm3-002 PIK3CA E542K Arm3-014 PIK3CA E542K Arm3-013 PIK3CA E542K Arm3-006 PIK3CA E542K Arm3-008 PIK3CA E453K Arm3-009 PIK3CA C420R Arm4-010 MET Amp Arm4-001 MET Amp Arm4-009 MET Amp Arm4-002 MET Amp Arm4-012 MET Amp Arm4-011 MET Amp Arm4-013 MET Amp Arm4-003 MET Amp Arm4-004 MET Amp Arm4-006 MET Amp Arm4-007 MET Amp Arm4-014 MET Amp Arm4-005 MET Amp Arm4-D0003 MET Amp Arm4-D0004 MET Amp Arm4-008 MET Amp Arm4-D0002 MET Amp Arm1-007 MEK Low Arm1-016 MEK Low Arm1-019 MEK Low Arm1-006 MEK Low Arm1-002 MEK Low Arm1-003 MEK High; KRAS G12R Arm1-025 MEK High Arm1-027 MEK High Arm1-022 MEK High Arm1-015 MEK High Arm1-024 MEK High Arm1-026 KRAS Q61R Arm1-001 KRAS Q61H Arm1-021 KRAS G13D Arm1-008 KRAS G12V Arm1-009 KRAS G12D, G12R Arm1-012 KRAS G12D Arm1-004 KRAS G12D Arm1-011 KRAS G12C Arm1-005 KRAS Amp Arm1-017 KRAS Amp Arm1-010 KRAS A146P –100 –50 050 100 Maximum change from baseline per RECIST 1.1

Figure 4. Molecular alterations and drug efficacy for each patient. A, Demonstration of each patient’s tumor profile and the maximal tumor size with each drug. (continued on next page)

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B Biomarker D-Arm 4: Savolitinib 10

0 Mutation count RRRRRRRRRNRNRNRNRNRNRNRNR PR EBV SD/PD MMR PD-L1 EBV status MET copy 48.6 26.7 25.9 11.6 11.3 10.2 8.5 6.3 5.4 27.4 10.9 10.9 8.9 8.6 8.0 5.2 2.1 Positive number Negative TP53 N/A FGFR2 MMR status KIT d-MMR PIK3CA p-MMR KRAS N/A PD-L1 GNAS ≥1 PDGFRA 0 EGFR N/A IDH2 PTEN TSHR MDM2 CCND1 Mutation ERBB2 Amplification Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Arm4 Deletion -D00 -D00 -D00 -002 -013 -010 -001 -003 -011 -005 -012 -009 -008 -007 -014 -004 -006 03 02 04

C Biomarker C-Arm 3: Capivasertib + Paclitaxel t 10

0 Mutation coun R RRRRRRNR NR NR NR NR NR NR NR NR NR NR NR NR NR NR EBV MMR PD-L1 E542 E542 E542 E542 P471 E545 M820 E542 E542 E542 E542 E545 E545 E545 H104 H104 H104 H104 E453 G364 C420 E545 PIK3CA K K K K L K V K K K K K K K 7R 7R 7R 7R K R R G MET TP53 KRAS

CTNNB1

EGFR KIT FGFR2 IDH1 IDH2 NRAS PTEN RET STK11 MDM2 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 Arm3 -DE0 -KE0 -016 -003 -017 -012 -019 -004 -010 -002 -006 -014 -013 -001 -005 -018 -015 -007 -011 -008 -020 -009 001 001

Figure 4. (Continued) B, Molecular landscape of the patients enrolled in savolitinib monotherapy (arm 4). C, Molecular landscape of the patients enrolled in capivasertib/paclitaxel (arm 3). Heat map showing the mutational landscape of patients. Bar plot showing mutation counts. R, responder; NR, nonresponder; N/A, not available.

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The VIKTORY Umbrella Trial in Gastric Cancer RESEARCH ARTICLE

Overall survival A 1.00 P < 0.0001

0.75 Conventional chemotherapy (n = 266) Biomarker-driven treatment (n = 105) 0.50

Survival probability 0.25

0.00 0 5 10 15 20 25 Time Conventional chemotherapy 266 185 43 8 0 0 Biomarker-driven treatment 105 85 46 9 6 2 Numbers at risk

1.53 B PS 1,2 vs. 0 1.11 Metastasis ≥ 2 vs. < 2 1.11 Age ≥ 65 vs. < 65 0.93 Male vs. female 0.81 p-MMR/N/D vs. d-MMR 0.77 Recurrent vs. metastatic 0.55 EBV-positive 0.52 Biomarker-positive

0.40.6 0.81 2 C Progression-free survival

1.00 P < 0.0001

0.75 Conventional chemotherapy (n = 266) Biomarker-driven treatment (n = 105) 0.50

Survival probability 0.25

0.00

0 5 10 15 20 25 Time Conventional chemotherapy 266 78 8 0 0 0 Biomarker-driven treatment 105 57 19 3 1 1 Number at risk

Figure 5. Survival outcome. Survival analysis of the patients with gastric cancer who were treated according to biomarker as 2L treatment (N = 105) versus conventional 2L treatment (N = 266; taxol/ramucirumab, N = 99; taxane-based, N = 105; irinotecan-based, N = 62). A, OS subgroup analysis for 371 patients with gastric cancer who underwent any 2L treatment; B, HRs for OS. C, PFS subgroup analysis for 371 patients with gastric cancer who underwent any 2L treatment.

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Changes in ctDNA and PD-L1 Expression 5 to 8 months of selumetinib/docetaxel treatment (Fig. 7A). after Treatment Arm1-019 patient developed multiple somatic mutations at On the basis of the tumor heterogeneity and genomic the time of progression on selumetinib/docetaxel treatment changes we observed in our previous studies (11, 27, 30), we by ctDNA analysis (Fig. 7B). collected plasma for ctDNA analysis at baseline and every CT evaluation until progression to address tumor evolution. The concordance rate between tumor and ctDNA (tested by DISCUSSION Guardant360; Supplementary Table S3) for MET amplifica- To our knowledge, this is the first and largest study to use tion was 89.5%, with 100% specificity and 83.3% sensitivity an umbrella platform trial design with preplanned genomic relative to tissue testing, which increased to 100% if patients biomarker analyses to assign patients with advanced gastric without detectable ctDNA were excluded (Fig. 6A). The maxi- cancer to molecularly matched therapies. Using a centrally mal tumor burden decrease was observed in patients with standardized molecular screening protocol, we enrolled 772 high adjusted MET copy number by ctDNA, although statisti- patients with gastric cancer and successfully performed tis- cal significance was not reached (Fig. 6B). More importantly, sue analysis for more than 90% (92.6%) of the patients as however, increased adjusted plasma copy number for MET reported in our previous studies (28, 31). In this study, we amplification was significantly associated with prolonged PFS demonstrated that when comprehensive molecular screening on savolitinib (Fig. 6C; P = 0.0216) to a significantly greater is linked to seamless immediate access to parallel matched tri- degree than tissue NGS MET copy number, which may reflect als, nearly 1 in 7 (14.7%) patients with advanced gastric cancer plasma’s ability to synthesize the entire tumor cell population. can receive biomarker-assigned drug treatment. The propor- Savolitinib therapy markedly decreased total ctDNA levels in tion of biomarker-driven treatment (14.7%) can be increased all patients for which baseline and 4-week plasma results were if the availability of seamless parallel trials is increased (i.e., available (Fig. 6D), demonstrating clear biological activity FGFR2 amplification,EGFR amplification). Importantly, we before most radiographic evidence of response. Congruently, showed that the biomarker-assigned cohort had encouraging adjusted plasma MET copy number was markedly suppressed response rates, underscoring the importance of genomically at 4 weeks in all patients for whom results were available, characterizing every patient’s tumor for precision therapy. although 2 of the 6 patients tested retained detectable MET Of the multiple arms, the highest response rate was amplification on progression, suggesting additional off-target observed in arm 4 (MET amplification–savolitinib mono- mechanisms of acquired resistance (Fig. 6E). therapy). Savolitinib is a potent small-molecule reversible

We additionally sequenced 55 (from 29 patients) ctDNA MET kinase inhibitor that inhibits MET kinase with an IC50 samples from arm 1 (13 patients) and arm 2 (16 patients) of 4 nmol/L in MET-amplified cancer cell lines. A phase II using a 300-gene AstraZeneca (AZ) panel (Supplementary trial of savolitinib monotherapy in 44 patients with MET- Table S4 and S5; Fig. 6F and G). Concordance between tumor altered papillary renal cell carcinoma showed very promising DNA and ctDNA was observed in 10 of 13 (76.9%) patients for results, including 8 PRs (32). Our savolitinib monotherapy KRAS aberration status (arm 1) and 75% (12 of 16) for TP53 arm met the prespecified 6-week PFS rate, indicating that mutation status (arm 2; Fig. 6F and G). Of the 8 baseline/ this treatment is worthy of phase III exploration in the MET- progressive disease (PD) paired ctDNA samples in arm 1, only amplified subset of patients with gastric cancer (3%–5%; refs. 2 (25%) had retained baseline genomic alterations at disease 33, 34). Responders were enriched for higher MET copy num- progression. Of the 11 baseline/PD paired ctDNA samples in ber (7/10 with MET >10 copies), a biological phenomenon arm 2, 5 (45.5%) patients showed no major alterations at dis- seen in HER2- and EGFR-amplified gastric cancer (35, 36), ease progression in the 300-gene panel following adavosertib/ and adjusted plasma MET copy number was strongly cor- paclitaxel treatment. Dynamic changes from baseline to dis- related with duration of PFS. Highlighting the importance ease progression in ctDNA mutational count using the AZ of genomic biomarker context, concurrent receptor tyrosine 300-gene panel are shown in Supplementary Fig. S3. kinase (RTK) amplifications in addition toMET amplifica- Finally, we analyzed PD-L1 score in 230 patients, which tion resulted in short duration of response or no response revealed that 30.4% (70 of 230) had PD-L1 CPS ≥1. In this to savolitinib. The importance of understanding the concur- subset, we had 25 paired biopsy specimens (baseline and at PD rent alteration landscape is highlighted by mixed results to one of the VIKTORY regimens) available for PD-L1 analysis with prior MET-directed therapies in gastric cancer, likely (Supplementary Table S6). All baseline and post-treatment owing to incomplete biomarker selection (37–39). Although biopsies were obtained from the same primary stomach lesion. this analysis is lacking functional validation, we speculate Of the 25 paired samples analyzed, there were 2 patients tumors with higher MET copy number without other RTK (both treated with selumetinib/docetaxel) who showed a coamplifications are more dependent on MET signaling significant increase in PD-L1 (CPS≥ 10) at progression after and may represent the optimal candidates for MET-directed

Figure 6. ctDNA genomic analysis. A, The concordance rate between tumor and ctDNA (tested by Guardant360) for MET amplification. PPA, positive percent agreement; NPA, negative percent agreement; PPV, positive predictive value; TND, target not detected. B, The maximal tumor burden decrease was observed in patients with high adjusted MET copy number by ctDNA, although statistical significance was not reached. C, Correlation between plasma copy number for MET amplification and PFS on savolitinib. D, Baseline and 4-week plasma ctDNA MET amplification change during savolitinib treatment. E, Adjusted plasma MET copy number at baseline (before savolitinib treatment), at 4 weeks and at progression. F, ctDNA landscape for arm 1 (RAS–selumetinib/docetaxel). G, Arm 2 (TP53 mutation–adavosertib/paclitaxel). cfDNA, cell-free DNA.

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A B C 200 200 Tissue + − 150 150 + 10 0 PPA 83.3% Plasma − 0 5 100% NPA 100 100 TND 2 2 PPV 100% Concordance 89.5% 50 50 MET copy number MET copy number

0 20 0 −20 −40 −60 −80 010203040 Greatest change in lesion size (%) PFS (weeks) 2 R P R2 P 0.9294 Observed plasma 0.0012 Observed plasma 0.01464 0.7392 Adjusted plasma 0.1165 0.3687 Adjusted plasma 0.5031 0.0216 0.03203 Tissue 0.701 Tissue 0.1088 0.425 D E 1.5 SD SD 10 PR B5-005 PR 1.0

1 B5-013 MET amplification 0.5 (proportion initial)

ctDNA ctDNA B5-006, B5-007 B5-009, B5-014 ctDNA amplification change ctDNA 0.0 (proportion adjusted copy number) ≤0.1 Baseline C3D1 Progression

F G

Selumetinib arm: paired baseline/PD cfDNA Adavosertib arm: paired baseline/PD cfDNA TP53

KRAS amp Tumor TP53 0 5 10 15 20 2 4 8 6 10 KRAS 0 84% TP53 KRAS WT 28% NF1 20% ARID1A KRAS mt 50% KRAS 24% APC 24% REUN TP53 12% EGFR 35% 16% NOTCH1 PIK3CA 16% PIK3C2G 20% 16% ER882 Tumor 16% ESR1 10% ERBB2 16% RP56KB2 16% EPHA3 KIT 8% MAP3K1 10% 12% PIK3CA 12% PTEN 10% NF1 12% AR 12% BRCA2 10% SMAD2 12% ABL1 8% MAP2K1 SMC3 8% SOX17 10% 8% TOP2A AR 8% BCL9 5% 8% EPPK_1 8% MDM4 5% ARID1A 8% RPL22 8% GAS6 BRAF 8% ACVR2A 5% 8% AMER1 8% ARID2 5% BRD3 8% CTCF CDH1 8% CTNNB1 5% ctDNA 8% EPPK1 8% FGF7

ctDNA CDKN2A 8% FGF8 5% 8% FGFR4 CTNNB1 8% JAK1 5% 8% KRAS 8% PALB2 5% MET 8% PIK3CG 8% POLE PBRM1 8% RASA1 5% 8% RET PIK3C3 8% RP56 5% 8% RPTOR 8% SMARCA4 5% PIK3CG 8% TERT 8% ZNF217 RBM10 8% LRRK2 5% 8% RHOA RELN 8% TSC1 5% 8% VEZF1 8% ATR 5% ROS1 8% KMT2C 8% DCUN1D1 RUNX1 8% MAP3K13 5% 8% MET SMAD4 4% ER884 5% 4% KEAP1 4% RB1 5% TBL1XR1 4% ATM 4% PIK3R1 USP9X 4% FBXW7 5% 4% MSH3 4% STK11 Key to alterations Amplification Frameshift mutation Missense mutation B1-011_B B1-002_B B1-003_B B1-004_B B1-006_B B1-008_B B1-009_B B1-010_B B1-017_B B1-019_B Deletion B1-011_PD B1-001_PD B1-002_PD B1-003_PD B1-004_PD B1-005_PD B1-006_PD B1-008_PD B1-009_PD B1-019_PD Truncating mutation B2-004-B B2-007-B B2-008-B B2-009-B B2-010-B B2-012-B B2-015-B B2-016-B B2-017-B B2-019-B B2-020-B B2-021-B B2-022-B B2-023-B Splice site mutation B2-004-PD B2-007-PD B2-008-PD B2-012-PD B2-015-PD B2-016-PD B2-017-PD B2-020-PD B2-021-PD B2-022-PD B2-023-PD

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A Arm1-019 baseline (stomach) Progression (stomach) Arm1-012 baseline (stomach) Progression (stomach)

PD-L1 CPS 0 PD-L1 CPS 80 PD-L1 CPS 0 PD-L1 CPS 41

CD3 CD3 CD3 CD3

CD8 CD8 CD8 CD8

B Arm1-019 SMC3_c.343A>G_M115V 150 SMAD4_c.1497C>A_C499*

ROS1_c.3391T>A_F1131I 100 PIK3CG_c.2936A>G_N979S

PBRM1_c.829A>T_K277*

50 DNMT3A_c.1600C>T_Q534* CTNNB1_c.100G>C_G34R Cumulative allelic frequency (%) ARID1A_c.3296_3297delGT_C1099fs 0 Baseline On-treatment Progression Average VAF 3.67 follow-up Average VAF 20.57 Average VAF 5.43

Figure 7. Changes in PD-L1 after docetaxel/selumetinib treatment. A, Changes in PD-L1 score between baseline and at disease progression following 8 months of selumetinib/docetaxel treatment from patient arm1-019. IHC for T-cell markers (CD3 and CD8) showed a dramatic increase in T cells after treatment (left two columns). Likewise, patient arm1-012 demonstrated a dramatic increase in PD-L1 CPS that was accompanied by increase in CD3+ and CD8+ lymphocyte infiltration following 5 months of selumtinib/docetaxel treatment. All biopsies were obtained from primary stomach cancer tissue. B, For patient arm1-019, the genomic landscape of ctDNA changed during selumetinib/docetaxel treatment with newly emerged mutations at disease progression. VAF, variant allele frequency.

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The VIKTORY Umbrella Trial in Gastric Cancer RESEARCH ARTICLE therapies. Of note, patients with gastric cancer with a high especially in patients with metastatic gastric cancer with level of ctDNA MET amplification (by Guardant360 assay in EBV-positive or high mutational load or MSI-H or PD-L1 our study) may benefit more substantially from MET-targeted combined CPS ≥ 1 by IHC (27, 44). We observed substan- therapy. tial induction (increase of ≥10) of PD-L1 in 8% (2/25) of In arm 3 (PIK3CA mutation–capivasertib), we observed paired biopsies from primary tumors in the selumetinib/ moderate antitumor activity with an ORR of 33.3% (95% docetaxel arm (Supplementary Table S6). MAPK inhibition CI: 14.4–52.2) in 2L gastric cancer, especially when com- by cobimetinib in preclinical tumor models has been shown pared with the low response rate (<15%) observed in arm 7 to promote tumor-infiltrating CD8+ T-cell activity (45). In (PIK3CA WT–capivasertib). Capivasertib is a selective pan- addition, atezolizumab and cobimetinib combination treat- AKT inhibitor that inhibits the kinase activity of all three ment has been shown to increase intratumoral CD8+ T-cell AKT isoforms (AKT1–3; ref. 17). We and others have previ- infiltration and MHC I expression in patients with MSS ously observed differential distribution of PIK3CA hotspot colorectal cancer (46). Concordantly, we also observed PD-L1 mutations (E542K, E545K, H1047R) according to molecu- change with recruitment of intratumoral CD8+ lympho- lar subtypes—PIK3CA kinase domain H1047R mutations cytes following selumetinib/docetaxel treatment. Although were enriched in microsatellite instability–high (MSI-H) a recent cobimetinib/atezolizumab trial has failed to show gastric cancer (>80%), whereas helical domain E542K and survival benefit in patients with MSS colorectal cancer (47), E545K mutations were enriched in microsatellite-stable selumetinib and anti–PD-1 treatment may be explored in (MSS) tumors (1, 40). Given that each molecular subtype patients with MSS gastric cancer. Congruently, this high- (MSI-H, MSS, genomically stable, or mesenchymal sub- lights the nonstatic nature of PD-L1 as a selection biomarker type) has substantially different survival outcomes (1), we and suggests combination and/or sequential strategies are have hypothesized that specific point mutations may show worth exploration. different drug sensitivity to capivasertib. Among arm 3 Although we are a long way from claiming “VIKTORY” patients, we observed strikingly different efficacy based on in gastric cancer, we have successfully shown that tumor PIK3CA genotype (Fig. 4C). In fact, none of the 4 patients genomic profiling with matched therapies improves out- with H1047R PIK3CA mutations responded to capivasertib. comes in 2L treatment, and that platform clinical trials can In contrast, 4 of the 8 with E542K mutations had durable efficiently identify the optimal biomarker treatment match responses to the capivasertib/paclitaxel combination, and (e.g., savolitinib to patients with MET-amplified gastric 3 of the 4 patients were EBV-positive (Fig. 3C, green cir- cancer). Nevertheless, this signal needs to be confirmed cles). Taken together, capivasertib/paclitaxel demonstrated in an expansion or randomized trial. Exploratory analyses the highest antitumor activity in MSS gastric cancer with demonstrated that biomarkers such as genomic alterations PIK3CA E542K mutations. While this represents the first and/or PD-L1 may not be static, especially during or after trial of a pan-AKT inhibitor in PIK3CA-mutated gastric can- treatment. The proportion (14.7%) of patients receiving cer, randomized data will be important to validate our puta- biomarker-driven treatment in the VIKTORY trial may be tive composite biomarker (PIK3CA helical domain +/MSS) improved with more available targeted agents based on population. genomic alterations (e.g., FGFR2 or EGFR2 amplification) MAPK pathway alterations are frequent in advanced gas- and inclusion of PD-L1 positivity (especially PD-L1 CPS tric cancer. We attempted to explore two biomarker selec- ≥10) may enable interrogation of the potential benefit of tion strategies using selumetinib (AZD6244, ARRY-142886), anti–PD-L1 treatment with or without targeted agents which is a potent, orally active inhibitor of MEK1/2 that in future umbrella trials. Finally, although limited by a suppresses the pleiotropic output of the RAF/MEK/ERK very small number of patients, we have demonstrated that pathway (22, 23). First, we confirmed thatKRAS mutational PD-L1 status changes over time in gastric cancer following status did not predict response to selumetinib in patients selumetinib/docetaxel treatment. with gastric cancer, supporting the preclinical data with MEK inhibitors (23). On the basis of a study showing that the RAS pathway can be activated in the absence of KRAS METHODS mutation and that the RAS-pathway signature was superior Patient Selection to KRAS mutation status for the prediction of response Patients with histologically confirmed metastatic and/or recur- to RAS-pathway inhibitors (41), a 6-gene MEK signature rent gastric adenocarcinoma, an Eastern Cooperative Oncology (DUSP4, DUSP6, ETV4, ETV5, PHLDA1, and SPRY2) was devel- Group (ECOG) performance status of 0 or 1, and at least one meas- oped and validated in the gastric cancer cohort (42). Given urable lesion according to the RECIST 1.1 were eligible for enroll- that the prevalence of high MEK signature was only 6.9%, the ment in the VIKTORY trial, the molecular screening program, and predictive power of high MEK signature should be tested in one of the associated umbrella trial protocols in gastric cancer. Ade- a subsequent enriched clinical trial with high MEK signature quate hematologic function, hepatic function, and renal function as a selection biomarker in gastric cancer. Interestingly, we were required. Patients with other concurrent uncontrolled medical diseases and/or other tumors were also excluded. The trial was observed the most durable response in a KRAS amplification/ conducted in accordance with the Declaration of Helsinki and the MEK-H patient without concurrent KRAS mutation, consist- Guidelines for Good Clinical Practice (ClinicalTrials.gov Identifier: ent with recent reports of MEK inhibition in this genomically NCT#02299648). The trial protocol was approved by the institu- defined subset (43). tional review board of Samsung Medical Center (Seoul, Korea) and Recent trials have underscored the importance of anti– all participating centers, and all patients provided written informed PD-1 or anti–PD-L1 therapy in gastric cancer treatment consent before enrollment.

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Study Design MMR Determination and EBV In Situ Hybridization The main goal of the VIKTORY trial as a molecular screening pro- Antibodies used in this study were specific for MLH-1 (M1, gram was to identify novel molecular subsets for assigning patients Ventana, ready to use) using Ventana BenchMark XT autostainer into one of the associated biomarker-directed arms (Fig. 1A). There (Ventana); MSH2 (G219-1129, 1:500, Cell Marque), PMS2 (MRQ-28, were 10 associated independently operated phase II arms (arms 4 1:20, Cell Marque), and MSH6 (44/MSH6, 1:500, BD Biosciences) and 8 included a dose-finding phase I trial) with eight biomark- using BOND-MAX autoimmunostainer (Leica Biosystems). In inter- ers. Each experimental drug protocol was designed independently pretation, loss of nuclear staining in the tumor cells with positively from the screening protocol. The eight biomarkers were: Biomarker stained internal control was counted as an abnormal result. In cases A1: RAS mutation or RAS amplification; Biomarker A2: high MEK with loss or suspected as loss of MMR protein, IHC was initially (MEK-H) or low MEK (MEK-L) signature; Biomarker B: TP53 muta- selected and further IHC with the entire block was performed to tion; Biomarker C: PIK3CA mutation or amplification; Biomarker D: screen for MMR deficiency. Cases with negative or equivocal nuclear MET amplification; Biomarker E: MET overexpression (3+) without staining were subsequently tested for microsatellite instability using MET amplification; Biomarker F: all negative (TP53 WT/PIK3CA PCR. EBV status was determined by EBER in situ hybridization using WT/RAS WT); and Biomarker G: TSC2 null or RICTOR amplifica- standard protocols (27). tion. There were 10 phase II trials that were associated with the VIK- TORY screening protocol: arm 1: selumetinib + docetaxel (Biomarker ctDNA Purification A1/A2, NCT#02448290); arm 2: adavosertib + paclitaxel (Biomarker ctDNA testing using Guardant360 (Guardant Health) was per- B, NCT#02448329); arm 3: capivasertib + paclitaxel (Biomarker C, formed as described previously (49). Briefly, up to 30 ng of cell-free NCT#02451956); arm 4-1: savolitinib monotherapy (Biomarker DNA extracted from banked plasma was used for library prepara- D, #02449551); arm 4-2: savolitinib + docetaxel (Biomarker D, tion and enrichment by hybridization capture. Enriched libraries NCT#02447406), arm 5: savolitinib + docetaxel (Biomarker E, were then sequenced on a NextSeq 550 (Illumina), and the resulting NCT#02447380); arm 6/7/8: vistusertib + paclitaxel or capivasertib sequence data was analyzed using a locked, previously validated cus- + paclitaxel (Biomarker F, NCT#02449655) or AZD6738 + paclitaxel tom bioinformatics pipeline. Plasma copy number was reported as (NCT#02630199); and arm 9–10: vistusertib + paclitaxel (Biomarker directly observed and adjusted as described previously (50). Change G, NCT#03082833, NCT#02449655), vistusertib + paclitaxel (Bio- in total ctDNA levels was calculated as described previously (51) and marker G, NCT#03061708). If patients initially enrolled in the reported as proportional fold change truncated at 10% for graphical VIKTORY trial were not eligible or refused to participate in one of purposes. the associated trials, they were allowed to be treated with conventional chemotherapy, or in non-VIKTORY clinical trials. Treatment Allocation Procedure The molecular tumor board (MTB) was composed of medical Sample Collection and IHC oncologists, pathologists, bioinformaticians, and the small-molecule FFPE or fresh samples of gastric cancer containing >40% tumor experts from AstraZeneca. The MTB had the responsibilities of sci- cellularity were used for targeted sequencing. Genomic DNA was entific validation, prioritization of identified molecular aberrations, extracted using the Qiagen DNA kit for FFPE tissue or the QIAamp and providing guidance on the suitable biomarker-driven experimen- DNA Mini Kit for fresh tumor tissues (Qiagen) according to the tal arm under the umbrella trial. The process time between biopsy manufacturer’s instructions. The IHC protocol for MET and HER2 and molecular results was set as 21 to 30 days from our previous used for this trial has been reported previously (48). The remaining study (28, 31). If multiple targets were simultaneously detected in tissue samples were reused in case of insufficient DNA amount/ a single patient, the following prioritization was used for patient quality for molecular analysis, or otherwise stored for further assignment based on known drivers: (i) PIK3CA mutation/amplifica- study. tion; (ii) RAS mutation/amplification or MEK signature; (iii)MET amplification; (iv)TP53 mutation; (v) RICTOR amplification; (vi) Tissue DNA Targeted Sequencing TSC2 null; (vii) MET overexpression by IHC 3+; and (viii) if none The targeted sequencing method for tissue specimens is provided of the above biomarkers were present, patients were allocated to in the Supplementary Material. the biomarker-negative arms AZD6738/paclitaxel, capivasertib/ paclitaxel, phase I portion of docetaxel/savolitinib, other clinical tri- PD-L1, CD3, and CD8 IHC als, or conventional treatment. The status of enrollment for 10 associated clinical trials (10 phase II studies) is shown in Supplementary Tissue sections were freshly cut to 4 μm–thick sections and Table S1. Currently, patient enrollment has been completed in arms mounted on Fisherbrand Superfrost Plus Microscope Slides (Thermo 1, 2, 3, 4, 6, and 7. Further patient enrollment was stopped in arms Fisher Scientific) and then dried at 60°C for 1 hour. IHC stain- 4-1 and 5, and arms 9/10 have been closed early due to early termina- ing was carried out on Dako Autostainer Link 48 system (Agilent tion of the drug for further clinical development. Technologies) using Dako PD-L1 IHC 22C3 pharmDx kit (Agilent Technologies) with EnVision FLEX visualization system and coun- terstained with hematoxylin according to the manufacturer’s instruc- Statistical Analysis tions. PD-L1 protein expression was determined using CPS, which This trial was designed as two parts: (i) VIKTORY screening pro- was the number of PD-L1–staining cells (tumor cells, lymphocytes, tocol for molecular profiling; (ii) parallel phase I/II study with inde- macrophages) divided by the total number of viable tumor cells, pendent statistical assumptions for each arm. For each arm, the multiplied by 100. The specimen was considered to have PD-L1 primary endpoint was ORR. We adopted Simon’s optimal design expression if CPS was ≥1. For CD3 and CD8, IHC staining was assuming ORR of 20% for 2L weekly paclitaxel regimen based on performed on tissue sections from FFPE-embedded specimens with robust data from previous studies; the experimental arm (paclitaxel VENTANA BenchMark automated staining instrument (Ventana + targeted agents) was considered effective for further development if Medical Systems, Inc.). Specimens were incubated with CONFIRM the combination rendered an ORR of ≥50%. Each arm was designed as anti-CD3 (2GV6) and CONFIRM anti-CD8 (SP57) rabbit mAbs for a two-stage design, allowing ineffective drugs to be terminated early at 20 minutes and CD3+ and CD8+ immune cells were visualized using stage I. Secondary endpoints were PFS, OS, and correlative biomarker the OptiView DAB IHC Detection Kit. analysis using ctDNA, PD-L1 score, and genomic aberration.

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The VIKTORY Umbrella Trial in Gastric Cancer RESEARCH ARTICLE

Statistical analyses were performed using the software environ- work was supported by funding from the Korean Health Technology ment R v3.4.0. The clinical information distribution plots were R&D Project, Ministry of Health & Welfare, Republic of Korea created using Circos (52). Survival analyses were performed to (HI14C3418). Support was also provided by a grant from the 20 by 20 explore the influences of age, gender, pathology, disease status, Project of Samsung Medical Center (GF01140111). This investigator- the number of metastatic organs, EBV status, MMR status, PD-L1 initiated trial was also funded by a study-drug donation and partial status, and VIKTORY biomarker status. Survival function curves fund from AstraZeneca. were visualized using the library and the differences between the levels of each factor were assessed using a log-rank test. Likewise, to Received April 14, 2019; revised July 2, 2019; accepted July 12, model hazard functions and determine the effects of these factors on 2019; published first July 17, 2019. a patient’s survival, Cox proportional hazard models were used. The proportional hazard assumption of Cox models was tested using the R library survival (53). The significance of multiple predictors of survival was assessed by the Cox regression analysis. P < 0.01 was REFERENCES considered to indicate a statistically significant difference. The forest . 1 Cristescu R, Lee J, Nebozhyn M, Kim KM, Ting JC, Wong SS, et al. plot of the HRs according to the OS was generated using in-house Molecular analysis of gastric cancer identifies subtypes associated code. We used the lollipop chart to visualize the maximum change in with distinct clinical outcomes. Nat Med 2015;21:449–56. tumor size per RECIST 1.1. 2. Overman MJ, Morris V, Kee B, Fogelman D, Xiao L, Eng C, et al. 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RESEARCH ARTICLE Lee et al.

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Tumor Genomic Profiling Guides Patients with Metastatic Gastric Cancer to Targeted Treatment: The VIKTORY Umbrella Trial

Jeeyun Lee, Seung Tae Kim, Kyung Kim, et al.

Cancer Discov Published OnlineFirst July 17, 2019.

Updated version Access the most recent version of this article at: doi:10.1158/2159-8290.CD-19-0442

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