Journal
HUMAN VACCINES & IMMUNOTHERAPEUTICS
Volume 16, Issue 1, Pages 112-115Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/21645515.2019.1631136
Keywords
Tissue-agnostic; pan-cancer; tumor mutational burden; cutoffs
Categories
Funding
- AACR-AstraZeneca Immunotherapy Fellowship
- Pershing Square Sohn Cancer Research grant
- PaineWebber Chair
- Stand Up To Cancer
- NIH [R01 CA205426, K08 DE024774, R01 DE027738]
- STARR Cancer Consortium
- NCI [R35 CA232097]
- Precision Immunotherapy Kidney Cancer Fund
- Frederick Adler Fund
- Cycle for Survival
- Fundacion Alfonso Martin Escudero
- MSKCC through NIH/NCI Cancer Center Support Grant [P30 CA008748]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available