Multiomic profiling of checkpoint inhibitor-treated melanoma: Identifying predictors of response and resistance, and markers of biological discordance
March 9, 2022
Abstract
This study concurrently examined 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. It showed 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.
Source:
Felicity Newell, Ines Pires da Silva, Peter A. Johansson, Alexander M. Menzies, James S. Wilmott, Venkateswar Addala, Matteo S. Carlino, Helen Rizos, Katia Nones, Jarem J. Edwards, Vanessa Lakis, Stephen H. Kazakoff, Pamela Mukhopadhyay, Peter M. Ferguson, Conrad Leonard, Lambros T. Koufariotis, Scott Wood, Christian U. Blank, John F. Thompson, Andrew J. Spillane, Robyn P.M. Saw, Kerwin F. Shannon, John V. Pearson, Graham J. Mann, Nicholas K. Hayward, Richard A. Scolyer, Nicola Waddell, Georgina V. Long, Multiomic profiling of checkpoint inhibitor-treated melanoma: Identifying predictors of response and resistance, and markers of biological discordance, Cancer Cell, Volume 40, Issue 1, 2022, Pages 88-102.e7, ISSN 1535-6108, https://doi.org/10.1016/j.ccell.2021.11.012.