Skip to main navigation Skip to search Skip to main content

Multiomic profiling of checkpoint inhibitor-treated melanoma: identifying predictors of response and resistance, and markers of biological discordance

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. SpillaneRobyn P. M. Saw, Kerwin F. Shannon, John V. Pearson, Graham J. Mann, Nicholas K. Hayward, Richard A. Scolyer, Nicola Waddell, Georgina V. Long*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)88-102.e7
Number of pages23
JournalCancer Cell
Volume40
Issue number1
DOIs
Publication statusPublished - 10 Jan 2022

Bibliographical note

A correction exists for this article, and can be found in Cancer Cell 43(3) p. 563 at doi: 10.1016/j.ccell.2025.01.011

Keywords

  • anti-CTLA-4
  • anti-PD-1
  • immunotherapy
  • interferon-γ
  • melanoma
  • methylation
  • mutation burden
  • resistance
  • RNAseq
  • targeted therapy
  • treatment
  • whole genome sequencing

Fingerprint

Dive into the research topics of 'Multiomic profiling of checkpoint inhibitor-treated melanoma: identifying predictors of response and resistance, and markers of biological discordance'. Together they form a unique fingerprint.

Cite this