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Clinical Trial
. 2025 May;31(5):1519-1530.
doi: 10.1038/s41591-025-03575-0. Epub 2025 Mar 7.

Nivolumab plus chemotherapy or ipilimumab in gastroesophageal cancer: exploratory biomarker analyses of a randomized phase 3 trial

Kohei Shitara #  1   2 , Yelena Y Janjigian #  3   4 , Jaffer Ajani  5 , Markus Moehler  6 , Jin Yao  7 , Xuya Wang  7   8 , Aparna Chhibber  7 , Dimple Pandya  7   9 , Lin Shen  10 , Marcelo Garrido  11 , Carlos Gallardo  12 , Lucjan Wyrwicz  13 , Kensei Yamaguchi  14 , Tomasz Skoczylas  15 , Arinilda Bragagnoli  16 , Tianshu Liu  17 , Michael Schenker  18 , Patricio Yañez  19 , Ruben Kowalyszyn  20 , Michalis Karamouzis  21 , Thomas Zander  22 , Kynan Feeney  23 , Elena Elimova  24 , Parul Doshi  7   25 , Mingshun Li  7 , Ming Lei  26
Affiliations
Clinical Trial

Nivolumab plus chemotherapy or ipilimumab in gastroesophageal cancer: exploratory biomarker analyses of a randomized phase 3 trial

Kohei Shitara et al. Nat Med. 2025 May.

Abstract

First-line nivolumab-plus-chemotherapy demonstrated superior overall survival (OS) and progression-free survival versus chemotherapy for advanced gastroesophageal adenocarcinoma with programmed death ligand 1 combined positive score ≥ 5, meeting both primary end points of the randomized phase 3 CheckMate 649 trial. Nivolumab-plus-ipilimumab provided durable responses and higher survival rates versus chemotherapy; however, the prespecified OS significance boundary was not met. To identify biomarkers predictive of differential efficacy outcomes, post hoc exploratory analyses were performed using whole-exome sequencing and RNA sequencing. Nivolumab-based therapies demonstrated improved efficacy versus chemotherapy in hypermutated and, to a lesser degree, Epstein-Barr virus-positive tumors compared with chromosomally unstable and genomically stable tumors. Within the KRAS-altered subgroup, only patients treated with nivolumab-plus-chemotherapy demonstrated improved OS benefit versus chemotherapy. Low stroma gene expression signature scores were associated with OS benefit with nivolumab-based regimens; high regulatory T cell signatures were associated with OS benefit only with nivolumab-plus-ipilimumab. Our analyses suggest that distinct and overlapping pathways contribute to the efficacy of nivolumab-based regimens in gastroesophageal adenocarcinoma.

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Conflict of interest statement

Competing interests: K.S. reports receiving personal fees for consulting and advisory roles from Bristol Myers Squibb, Takeda, Ono Pharmaceutical, Novartis, Daiichi Sankyo, Amgen, Boehringer Ingelheim, Merck Pharmaceutical, Astellas, Guardant Health Japan, Janssen, AstraZeneca, Zymeworks Biopharmaceuticals, ALX Oncology, Bayer, GlaxoSmithKline K.K., HEALIOS K.K., Moderna and Arcus Biosciences; receiving honoraria from Bristol Myers Squibb, Ono Pharmaceutical, Janssen, Eli Lilly, Astellas, and AstraZeneca; and receiving research funding (all to institution) from Astellas, Ono Pharmaceutical, Daiichi Sankyo, Taiho Pharmaceutical, Chugai, Merck Pharmaceutical, Amgen, Eisai, PRA Health Sciences Syneos Health, AstraZeneca, PPD-SNBL K.K. and TORAY. Y.Y.J. reports receiving research funding from the National Cancer Institute of the National Institutes of Health (to Memorial Sloan Kettering Cancer Center), Bayer, Bristol Myers Squibb, Cycle for Survival, Department of Defense, Fred’s Team, Genentech/Roche Lilly, Merck, National Cancer Institute and Rgenix; serving as a consultant or in an advisory role for Basilea Pharmaceutical, Bayer, Bristol Myers Squibb, Daiichi Sankyo, Imugene, AstraZeneca, Lilly, Merck, Merck Serono, Michael J Hennessy Associates, Paradigm Medical Communications, Seattle Genetics, Pfizer, Rgenix, AmerisourceBergen, Arcus Biosciences, Geneos, GlaxoSmithKline, Imedex, Lynx Health, Peerview, Silverback Therapeutics and Zymeworks; receiving stock options from Rgenix; and nonfinancial relationships with Clinical Care Options, Axis Medical Education and Research to Practice. J.A. reports receiving research grants from Amgen, Astellas Pharma, Bristol Myers Squibb, Daiichi Sankyo, Delta-Fly Pharma, Gilead Sciences, Lilly/ImClone, Merck, Novartis, ProLynx, Roche/Genentech, Taiho Pharmaceutical, Takeda and Zymeworks; serving as a consultant or in an advisory role for American Cancer Society, BeiGene, Bristol Myers Squibb, Insys Therapeutics, Merck, Novartis, Astellas Pharma, Gilead Sciences, Amgen, Servier, Geneos, Arcus Biosciences and Vaccinogen; receiving royalties from or holding patents and other intellectual property with Amgen, Bristol Myers Squibb, Genentech, Lilly, MedImmune, Merck, Roche and Taiho Pharmaceutical; and receiving honoraria from Acrotech BioPharma, Aduro Biotech, Amgen, Oncotherics, Astellas Pharma, BeiGene, Boehringer Ingelheim, Bristol Myers Squibb, Daiichi Sankyo, DAVA Pharmaceuticals, AstraZeneca, Fresenius Kabi, Gilead Sciences, Grail, Lilly, Merck, Novartis, Servier and Zymeworks. M.M. reports receiving research grants from Amgen, Leap Therapeutics, Merck Serono, AstraZeneca and Merck Sharp & Dohme; serving as a consultant or in an advisory role for Amgen, Bayer, BeiGene, Bristol Myers Squibb, Lilly, Merck Serono, Merck Sharp & Dohme, Pfizer, Roche, Servier, AstraZeneca and Taiho Pharmaceutical; receiving travel and accommodation expenses from American Society of Clinical Oncology, Amgen, Bayer, European Society for Medical Oncology, BeiGene, German Cancer Society, Merck Serono, Merck Sharp & Dohme and Roche; and receiving honoraria from Amgen, AstraZeneca/MedImmune, Bristol Myers Squibb, Merck Serono, Merck Sharp & Dohme Oncology, Roche/Genentech, Pierre Fabre, Sanofi and Servier. J.Y. reports being an employee of and holding stock in Bristol Myers Squibb. X.W. has no competing interests to disclose. A.C. reports being employee of Bristol Myers Squibb; and holding stocks from Merck and Bristol Myers Squibb. D.P. reports being a former employee of Bristol Myers Squibb. L.S. reports receiving support for the present paper from Astellas and Oxford PharmaGenesis; receiving grants from Beijing Xiantong Biomedical Technology, Qilu Pharmaceutical, ZaiLab Pharmaceutical (Shanghai), Beihai Kangcheng (Beijing) Medical Technology, Yaojie Ankang (Nanjing) Technology Co., Ltd, Baiji Shenzhou (Beijing) Biotechnology Co., Ltd and Jacobio Pharmaceuticals; receiving consulting fees from Mingji Biopharmaceutical, Haichuang Pharmaceutical and Herbour Biomed; receiving honoraria from Hutchison Whampoa, Hengrui, ZaiLab and CSTONE Pharmaceutical; and participation on advisory board for Merck Sharp & Dohme, Merck, Bristol Myers Squibb, Boehringer Ingelheim, Sanofi, Roche, Servier and AstraZeneca. M.G. reports receiving research grants from Bristol Myers Squibb and Novartis; receiving speakers’ bureau fees from Bayer, Bristol Myers Squibb and Merck; receiving travel and accommodation expenses from Roche; and serving as a consultant or in an advisory role for Merck Sharp & Dohme, AstraZeneca and Roche. C.G. reports receiving research grants from Bristol Myers Squibb, AstraZeneca and Merck; receiving speakers’ bureau fees from AstraZeneca, Merck and Bristol Myers Squibb; serving as a consultant or in an advisory role for Merck, Tecnofarma and AstraZeneca; and honoraria from AstraZeneca, Merck and Roche. L.W. reports receiving speakers’ bureau fees from Bristol Myers Squibb; receiving travel and accommodation expenses from Servier; receiving honoraria from BeiGene, Bristol Myers Squibb and Merck Sharp & Dohme; and serving in a consulting or advisory role for GlaxoSmithKline and Servier. K.Y. reports receiving research grants from Boehringer Ingelheim, Bristol Myers Squibb, Chugai Pharma, Daiichi Sankyo, Eisai, Gilead Sciences, Lilly, Merck Sharp & Dohme Oncology, Ono Pharmaceutical, Sanofi, Taiho Pharmaceutical and Yakult Honsha; receiving speakers’ bureau fees from Bristol Myers Squibb Japan, Chugai Pharma, Daiichi Sankyo, Lilly, Merck, Ono Pharmaceutical, Taiho Pharmaceutical and Takeda; and serving as a consultant or in an advisory role for Bristol Myers Squibb Japan and Daiichi Sankyo. T.S. reports receiving support for the present paper from Bristol Myers Squibb. A.B. reports receiving speakers’ bureau fees from AstraZeneca, Bristol Myers Squibb/Medarex and Merck. T.L. has no competing interests to disclose. M.S. reports receiving research funding from AbbVie, Amgen, Astellas Pharma, AstraZeneca, BeiGene, Bioven, Clovis Oncology, Five Prime Therapeutics, Bristol Myers Squibb, Eli Lilly, Gilead Sciences, Merck Sharp & Dohme, Mylan, GlaxoSmithKline, Novartis, Pfizer/EMD Serono, Tesaro, Sanofi/Regeneron and Roche; and receiving travel accommodations and expenses from Bristol Myers Squibb. P.Y. has no competing interests to disclose. R.K. reports receiving research grants from Amgen, AstraZeneca, Bristol Myers Squibb, Eli Lilly, PPD, GlaxoSmithKline, Labcorp Drug Development, Gaico, Janssen Cliag Farmaceútica, Gilead Sciences, Parexel, Syneos Health, Novartis, Pfizer, Roche SAQ, Merck Sharp & Dohme and Sanofi; receiving support for the present paper from Bristol Myers Squibb, Merck Sharp & Dohme and Astellas Pharma; receiving consulting fees from Astellas Pharma, Bristol Myers Squibb, Merck Sharp & Dohme and Roche; honoraria or speakers bureaus from Astellas Pharma, Bristol Myers Squibb, Merck Sharp & Dohme, Raffo and Roche; receiving travel and accommodation expenses from Bristol Myers Squibb, Merck Sharp & Dohme, Raffo, Gador, Pfizer and Roche; and reports leadership or fiduciary role in other board, society, committee or advocacy group as Academic Director Argentine Association of Clinical Oncology. M.K. has no competing interests to disclose. T.Z. reports consulting or advisory roles for Bristol Myers Squibb, Merck Sharp & Dohme Oncology, Novartis, Pfizer and Roche. K.F. has no competing interests to disclose. E.E. reports being a consultant for Bristol Myers Squibb, Zymeworks, Adaptimmune, BeiGene, Jazz, Astellas, Virecta Tx, Signatera, AbbVie and Daiichi Sankyo; grant/research support from Bristol Myers Squibb, Bold Therapeutics, Zymeworks, AstraZeneca Canada, Amgen and Jazz; and having a family member work for Merck. P.D. reports being an employee of Bristol Myers Squibb at the time of study conduct. M. Li reports receiving support for the present paper, honoraria, holding stocks in, and being an employee of Bristol Myers Squibb. M. Lei reports pending patents with, holding stocks in, and being an employee of Bristol Myers Squibb.

Figures

Fig. 1
Fig. 1. Genomic characterization of baseline tumors from CheckMate 649.
a, Flowchart depicting method of genomic classification of tumors (left). Scatter-plot of TMB versus genomic instability in EBV-negative tumors (right). b, Tumor subtyping by anatomical location. c,d, Forest plot of OS by genomic subsets in patients treated with nivolumab-plus-chemotherapy (c) or nivolumab-plus-ipilimumab (d) versus chemotherapy. Data are presented as unstratified HRs and 95% CI. HR was not calculated if the number of patients in each arm was <5. Open circles represent MSI-H, filled circles represent MSS, and squares represent not available (NA). IPI, ipilimumab; MSI-H, MSI-high; NIVO, nivolumab.
Fig. 2
Fig. 2. OS by TMB in patients treated with nivolumab-plus-chemotherapy or nivolumab-plus-ipilimumab versus chemotherapy.
a, Forest plot showing OS by baseline TMB status in patients who received nivolumab-plus-chemotherapy versus chemotherapy. Data are presented as unstratified HRs and 95% CI. b, Kaplan–Meier curves of OS by microsatellite stability status in patients treated with nivolumab-plus-chemotherapy versus chemotherapy. c, Forest plot showing OS by baseline TMB status in patients who received nivolumab-plus-ipilimumab versus chemotherapy. d, Kaplan–Meier curves of OS by microsatellite stability status in patients treated with nivolumab-plus-ipilimumab versus chemotherapy. TMB-high denotes ≥199 mutations per exome, whereas TMB-low denotes <199 mutations per exome. Data are presented as unstratified HRs and 95% CI. HR was not calculated if the number of patients in each arm was <5. aTMB not evaluable (NE)/available in 896 patients (NIVO + chemo: n = 431; Chemo: n = 465). bTMB not evaluable/available in 727 patients (NIVO + chemo: n = 355; Chemo: n = 372). cTMB not evaluable/available in 447 patients (NIVO + IPI: n = 226; Chemo: n = 221). dTMB not evaluable/available in 351 patients (NIVO + IPI: n = 181; Chemo: n = 170).
Fig. 3
Fig. 3. Efficacy by KRAS alterations in patients treated with nivolumab-plus-chemotherapy versus chemotherapy.
a, Kaplan–Meier estimates of OS in all WES-evaluable patients with altered (left) or unaltered (right) KRAS mutations + amplifications. b, OS by baseline KRAS pathway alteration status derived from the model, including interaction of KRAS alteration status with treatment, MSI and TMB status. Data are presented as unstratified HRs and 95% CI. c, KRAS mutation map. aMSI status not evaluable/available in two patients. KRAS, Kirsten rat sarcoma viral oncogene.
Fig. 4
Fig. 4. Relationship between key biomarkers in all patients treated with nivolumab-plus-chemotherapy, nivolumab-plus-ipilimumab or chemotherapy.
a, Correlation of gene signatures among all RNA-seq evaluable patients. Numbers indicate the Spearman’s correlation. The strength of association is indicated by the color scale shown on the right. b, Heatmap of baseline tumors clustered by the gene signatures of interest in patients treated with nivolumab-plus-chemotherapy, nivolumab-plus-ipilimumab or chemotherapy. For visualization purposes, each gene signature was first normalized by z-score method where samples with high z-score (red) indicates relative high gene signature score and low z-score (blue) indicates relative low gene signature score. Patients (column) were ordered based on similarity of gene signatures of their tumor samples via hierarchical clustering method. Dendrogram (top) was added to show the hierarchical relationship between samples. Similarly, gene signatures (rows) were ordered and dendrogram (left) was added to show the hierarchical relationship between gene signatures. aMutations per exome.
Fig. 5
Fig. 5. OS by GES scores in patients treated with nivolumab-plus-chemotherapy versus chemotherapy.
a, Forest plot showing the correlation between OS and selected signatures used to stratify patients into tertiles (high, medium or low). Data are presented as unstratified HRs and 95% CI. HR was not calculated if the number of patients in each arm was <5. b, Kaplan–Meier estimates of OS in all RNA-seq-evaluable patients with low, medium or high angiogenesis GES scores (five-gene angiogenesis) at baseline.
Fig. 6
Fig. 6. OS by GES scores in patients treated with nivolumab-plus-ipilimumab versus chemotherapy.
a, Forest plot showing the correlation between OS and selected signatures used to stratify patients into tertiles (high, medium or low). Data are presented as unstratified HRs and 95% CI. HR was not calculated if the number of patients in each arm was <5. b, Kaplan–Meier estimates of OS in all RNA-seq-evaluable patients with high, medium or low Treg cell GES scores (two-gene Treg cell) at baseline.
Extended Data Fig. 1
Extended Data Fig. 1. Genomic characterization of baseline tumors from CheckMate 649.
a and b, Tumor characterization subtyping by genomic subtypes and histology (a), or PD-L1 CPS (b). P values are based on two-sided Chi-squared test. Exact P value for (a) was 6.673e-09. c and d, Forest plot of OS by genomic subsets in all WES-evaluable patients treated with nivolumab-plus-chemotherapy (c) or nivolumab-plus-ipilimumab (d) versus chemotherapy. Data are presented as unstratified HRs and 95% CI. HR was not calculated if the number of patients in each arm was less than 5. CIN, chromosomal instability; CPS, combined positive score; EBV, Epstein–Barr virus; GS, genomically stable; IPI, ipilimumab; MSI-H, microsatellite instability high; MSS, microsatellite stable; N/A, not available; NIVO, nivolumab; PD-L1, programmed death ligand 1; TMB, tumor mutational burden; WES, whole-exome sequencing.
Extended Data Fig. 2
Extended Data Fig. 2. OS by PD-L1 CPS and TMB status in patients treated with nivolumab-plus-chemotherapy or nivolumab-plus-ipilimumab versus chemotherapy.
a, Forest plot showing OS by baseline PD-L1 CPS and TMB status in patients who received nivolumab-plus-chemotherapy versus chemotherapy. b, Forest plot showing OS by baseline PD-L1 CPS and TMB status in patients who received nivolumab-plus-ipilimumab versus chemotherapy. Data are presented as unstratified HRs and 95% CI. aTMB not evaluable/available in 504 patients (NIVO+chemo: n = 238; chemo: n = 266). bTMB not evaluable/available in 376 patients (NIVO+chemo: n = 185; chemo: n = 191). cTMB not evaluable/available in 243 patients (NIVO+IPI: n = 121; chemo: n = 122). dTMB not evaluable/available in 191 patients (NIVO+IPI: n = 98; chemo: n = 93). Chemo, chemotherapy; CI, confidence interval; CPS, combined positive score; HR, hazard ratio; NA, not available; NIVO, nivolumab; OS, overall survival; PD-L1, programmed death ligand 1; TMB, tumor mutational burden; WES, whole-exome sequencing.
Extended Data Fig. 3
Extended Data Fig. 3. OS by gene alterations.
a, Oncoprints of gene alterations among all WES-evaluable patients. Frequency and overlap of select gene alterations. b and c, Forest plots showing the association between OS and selected gene alterations in patients who received nivolumab-plus-chemotherapy versus chemotherapy (b) or nivolumab-plus-ipilimumab versus chemotherapy (c). Data are presented as unstratified HRs and 95% CI. HR was not calculated if the number of patients in each arm was less than 10. HR were derived from model including interaction of gene alteration status with treatment, MSI and TMB status. aMSI status not evaluable/available in 2 patients. Chemo, chemotherapy; CI, confidence interval; CPS, combined positive score; HR, hazard ratio; IPI, ipilimumab; MSI-H, microsatellite instability high; N/A, not available; NIVO, nivolumab; OS, overall survival; WES, whole-exome sequencing.
Extended Data Fig. 4
Extended Data Fig. 4. Association test of differential OS treatment effect by GES scores in patients treated with nivolumab-plus-chemotherapy or with nivolumab-plus-ipilimumab versus chemotherapy.
a, P value of interaction between GES score and treatment arm among all RNA-seq-evaluable patients and by PD-L1 CPS status who received nivolumab-plus-chemotherapy versus chemotherapy. Selected gene signatures with P values < 0.1 from Likelihood Ratio Test are colored in the table; color scale is shown at the bottom. b, P value of interaction between GES score and treatment arm among all RNA-seq-evaluable patients and by PD-L1 CPS status who received nivolumab-plus-ipilimumab versus chemotherapy. Selected gene signatures with P values < 0.1 from Likelihood Ratio Test are colored in the table; color scale is shown at the bottom. Selected gene signatures with P values < 0.1 from Likelihood Ratio Test are colored in the table; color scale is shown at the bottom.
Extended Data Fig. 5
Extended Data Fig. 5. OS by GES scores and PD-L1 CPS status in patients treated with nivolumab-plus-chemotherapy versus chemotherapy.
a, Forest plot showing the correlation between OS and selected signatures used to stratify patients into tertiles (high, medium, or low). Data are presented as unstratified HRs and 95% CI. HR was not calculated if the number of patients in each arm was less than 5. b and c, Kaplan–Meier estimates of OS in all RNA-seq-evaluable patients with low, medium or high angiogenesis GES scores (5-gene angiogenesis) and PD-L1 CPS ≥ 5 (b) or PD-L1 CPS < 5 (c) at baseline. Chemo, chemotherapy; CI, confidence interval; CPS, combined positive score; GES, gene expression signature; HR, hazard ratio; NIVO, nivolumab; OS, overall survival; PD-L1, programmed death ligand 1.
Extended Data Fig. 6
Extended Data Fig. 6. OS by GES scores and PD-L1 CPS status in patients treated with nivolumab-plus-ipilimumab versus chemotherapy.
Forest plot showing the correlation between OS and selected signatures used to stratify patients into tertiles (high, medium versus low). Data are presented as unstratified HRs and 95% CI. HR was not calculated if the number of patients in each arm was less than 5. CI, confidence interval; CPS, combined positive score; GES, gene expression signature; HR, hazard ratio; PD-L1, programmed death ligand 1.
Extended Data Fig. 7
Extended Data Fig. 7. OS by PD-L1 CPS and Treg status in patients treated with nivolumab-plus-ipilimumab versus chemotherapy.
a and b, Kaplan–Meier estimates of OS in all RNA-seq-evaluable patients with high, medium or low regulatory T cell GES scores (2-gene regulatory T cell) and PD-L1 CPS ≥ 5 (a) or PD-L1 CPS < 5 (b) at baseline. Chemo, chemotherapy; CI, confidence interval; CPS, combined positive score; HR, hazard ratio; IPI, ipilimumab; NIVO, nivolumab; OS, overall survival; PD-L1, programmed death ligand 1.
Extended Data Fig. 8
Extended Data Fig. 8. Correlations between biomarkers in patients treated with nivolumab-plus-chemotherapy, nivolumab-plus-ipilimumab or chemotherapy.
Summary of factors potentially associated with efficacy with nivolumab-plus-chemotherapy or nivolumab-plus-ipilimumab. aIndicates significant association with treatment when treated as a continuous variable (P < 0.1). These exploratory P values are not meant to show statistical significance and are intended to describe the relative performance of the different signatures for association with response. Chemo, chemotherapy; CPS, combined positive score; GES, gene expression signatures; IPI, ipilimumab; NIVO, nivolumab; PD-L1, programmed death ligand 1; TMB, tumor mutational burden.
Extended Data Fig. 9
Extended Data Fig. 9. Gene set enrichment analysis in patients treated with nivolumab-plus-chemotherapy or nivolumab-plus-ipilimumab versus chemotherapy.
Enrichment of genes associated with OS in nivolumab-plus-chemotherapy, nivolumab-plus-ipilimumab, or chemotherapy as well as the genes with differential OS association by treatment arm (interaction) using chemotherapy as the reference. The data are shown as NES (adjusted P value) and the cells are colored if adjusted P value is < 0.01. The strength of association is shown as a color scale at the bottom. Chemo, chemotherapy; IPI, ipilimumab; NES, normalized enrichment score; NIVO, nivolumab; OS, overall survival.
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