Multiomic profiling of checkpoint inhibitor-treated melanoma: Identifying predictors of response and resistance, and markers of biological discordance
- PMID: 34951955
- DOI: 10.1016/j.ccell.2021.11.012
Multiomic profiling of checkpoint inhibitor-treated melanoma: Identifying predictors of response and resistance, and markers of biological discordance
Erratum in
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Multiomic profiling of checkpoint inhibitor-treated melanoma: Identifying predictors of response and resistance, and markers of biological discordance.Cancer Cell. 2025 Mar 10;43(3):563. doi: 10.1016/j.ccell.2025.01.011. Epub 2025 Feb 6. Cancer Cell. 2025. PMID: 39919735 No abstract available.
Abstract
We concurrently examine the whole genome, transcriptome, methylome, and immune cell infiltrates in baseline tumors from 77 patients with advanced cutaneous melanoma treated with anti-PD-1 with or without anti-CTLA-4. We show that high tumor mutation burden (TMB), neoantigen load, expression of IFNγ-related genes, programmed death ligand expression, low PSMB8 methylation (therefore high expression), and T cells in the tumor microenvironment are associated with response to immunotherapy. No specific mutation correlates with therapy response. A multivariable model combining the TMB and IFNγ-related gene expression robustly predicts response (89% sensitivity, 53% specificity, area under the curve [AUC], 0.84); tumors with high TMB and a high IFNγ signature show the best response to immunotherapy. This model validates in an independent cohort (80% sensitivity, 59% specificity, AUC, 0.79). Except for a JAK3 loss-of-function mutation, for patients who did not respond as predicted there is no obvious biological mechanism that clearly explained their outlier status, consistent with intratumor and intertumor heterogeneity in response to immunotherapy.
Keywords: RNAseq; anti-CTLA-4; anti-PD-1; immunotherapy; interferon-γ; melanoma; methylation; mutation burden; resistance; targeted therapy; treatment; whole genome sequencing.
Copyright © 2021 Elsevier Inc. All rights reserved.
Conflict of interest statement
Declaration of interests I.P.S. has received travel support by BMS and MSD, and speaker fee by Roche, BMS, MSD, and Novartis. J.F.T. has received honoraria for advisory board participation from Merck Sharpe Dohme Australia and Bristol Myers Squibb Australia and received honoraria and travel expenses from GSK and Provectus Inc. R.A.S. has received fees for professional services from Evaxion, Provectus Biopharmaceuticals Australia, Qbiotics Group Limited, Novartis Pharma AG, MSD Sharp & Dohme (Australia), NeraCare, AMGEN Inc., Bristol-Myers Squibb, Novartis Pharmaceuticals Australia Pty Limited, Myriad Genetics GmbH, and GlaxoSmithKline Australia. G.V.L. is consultant advisor for Aduro Biotech Inc, Agenus Inc, Amgen Inc, Array Biopharma inc, Boehringer Ingelheim International GmbH, Bristol-Myers Squibb, Evaxion Biotech A/S, Hexel AG, Highlight Therapeutics S.L., Merck Sharpe & Dohme, Novartis Pharma AG, OncoSec, Pierre Fabre, QBiotics Group Limited, Regeneron Pharmaceuticals Inc, SkylineDX B.V., Specialised Therapeutics Australia Pty Ltd. R.P.M.S has participated in advisory boards for MSD, Novartis, and Qbiotics and received speaking honoraria from BMS. J.V.P. and N.W. are founders and shareholders of genomiQa Pty Ltd, and members of its Board. M.S.C. is a consultant advisor to MSD, BMS, Novartis, Roche, Pierre Fabre, Sanofi, Merck Serono, Nektar, Eisia, and Ideaya and received honoraria from MSD, BMS, and Novartis. A.M.M. has participated in advisory boards for BMS, MSD, Novartis, Roche, and Pierre-Fabre. C.U.B. has served on advisory boards for BMS, MSD, Roche, Novartis, GSK, AZ, Pfizer, Lilly, GenMab, Pierre Fabre, and Third Rock Ventures; received research funding from BMS, MSD, 4SC, Novartis, and NanoString; has stock ownership in Uniti Cars; and is a cofounder of Immagene BV. The remaining authors declare no competing interests.
Comment in
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Multi-omics prediction in melanoma immunotherapy: A new brick in the wall.Cancer Cell. 2022 Jan 10;40(1):14-16. doi: 10.1016/j.ccell.2021.12.008. Cancer Cell. 2022. PMID: 35016026
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