Tumor mutational burden as a predictive biomarker for checkpoint inhibitor immunotherapy Review

   


Authors: Lee, M.; Samstein, R. M.; Valero, C.; Chan, T. A.; Morris, L. G. T.
Review Title: Tumor mutational burden as a predictive biomarker for checkpoint inhibitor immunotherapy
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. © 2019, © 2019 Taylor & Francis Group, LLC.
Keywords: pan-cancer; tumor mutational burden; tissue-agnostic; cutoffs
Journal Title: Human Vaccines & Immunotherapeutics
Volume: 16
Issue: 1
ISSN: 2164-5515
Publisher: Taylor & Francis Group  
Date Published: 2020-01-01
Start Page: 112
End Page: 115
Language: English
DOI: 10.1080/21645515.2019.1631136
PUBMED: 31361563
PROVIDER: scopus
PMCID: PMC7012182
DOI/URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070279205&doi=10.1080%2f21645515.2019.1631136&partnerID=40&md5=1d772ac623954697cb5197bc8b381836
Notes: Article -- Source: Scopus
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MSK Authors
  1. Timothy Chan
    317 Chan
  2. Luc Morris
    278 Morris
  3. Robert M Samstein
    43 Samstein
  4. Cristina Valero Mayor
    58 Valero Mayor
  5. Mark Lee
    15 Lee
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