Tumor mutational burden as a predictive biomarker for checkpoint inhibitor immunotherapy

Mark Lee, Robert M. Samstein, Cristina Valero, Timothy A. Chan, Luc G.T. Morris

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

Immune checkpoint inhibitor (ICI) therapies can achieve meaningful tumor responses in a subset of patients with most types of cancer that have been investigated. However, the majority of patients treated with these drugs do not experience any clinical benefit. Because not all patients benefit from ICIs, and some may experience more meaningful tumor response if treated with chemotherapy or other treatments, there is a compelling need for predictive biomarkers to facilitate more informed selection of therapy. Tumor mutational burden (TMB) is one feature of a tumor that has predictive value for ICI therapy across multiple cancer types. In a pan-cancer analysis of over 1,600 patients, higher TMB was associated with longer survival and higher response rates with ICI therapy. While this effect was seen in the majority of cancer types, indicating that TMB underlies fundamental aspects of immune-mediated tumor rejection, the optimal predictive cut-point varied widely by histology, suggesting that there is unlikely to be one tissue-agnostic definition of high TMB that is useful for predicting ICI response. More comprehensive predictive models integrating TMB with other factors–including genetic, immunologic, and clinicopathologic markers–will be needed to potentially achieve a tissue-agnostic predictor of benefit from ICIs.

Original languageEnglish
Pages (from-to)112-115
Number of pages4
JournalHuman Vaccines and Immunotherapeutics
Volume16
Issue number1
DOIs
StatePublished - 2 Jan 2020
Externally publishedYes

Keywords

  • Tissue-agnostic
  • cutoffs
  • pan-cancer
  • tumor mutational burden

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