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PMID: 31578273 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Review

Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence.

The oncologist ·Vol. 25 ·No. 1 ·2020-00-00 ·Pages e147-e159

Klempner SJ, Fabrizio D, Bane S, Reinhart M, Peoples T, Ali SM, Sokol ES, Frampton G, Schrock AB, Anhorn R, Reddy P

Abstract

Treatment with immune checkpoint inhibitors (ICPIs) extends survival in a proportion of patients across multiple cancers. Tumor mutational burden (TMB)-the number of somatic mutations per DNA megabase (Mb)-has emerged as a proxy for neoantigen burden that is an independent biomarker associated with ICPI outcomes. Based on findings from recent studies, TMB can be reliably estimated using validated algorithms from next-generation sequencing assays that interrogate a sufficiently large subset of the exome as an alternative to whole-exome sequencing. Biological processes contributing to elevated TMB can result from exposure to cigarette smoke and ultraviolet radiation, from deleterious mutations in mismatch repair leading to microsatellite instability, or from mutations in the DNA repair machinery. A variety of clinical studies have shown that patients with higher TMB experience longer survival and greater response rates following treatment with ICPIs compared with those who have lower TMB levels; this includes a prospective randomized clinical trial that found a TMB threshold of ≥10 mutations per Mb to be predictive of longer progression-free survival in patients with non-small cell lung cancer. Multiple trials are underway to validate the predictive values of TMB across cancer types and in patients treated with other immunotherapies. Here we review the rationale, algorithm development methodology, and existing clinical data supporting the use of TMB as a predictive biomarker for treatment with ICPIs. We discuss emerging roles for TMB and its potential future value for stratifying patients according to their likelihood of ICPI treatment response. IMPLICATIONS FOR PRACTICE: Tumor mutational burden (TMB) is a newly established independent predictor of immune checkpoint inhibitor (ICPI) treatment outcome across multiple tumor types. Certain next-generation sequencing-based techniques allow TMB to be reliably estimated from a subset of the exome without the use of whole-exome sequencing, thus facilitating the adoption of TMB assessment in community oncology settings. Analyses of multiple clinical trials across several cancer types have demonstrated that TMB stratifies patients who are receiving ICPIs by response rate and survival. TMB, alongside other genomic biomarkers, may provide complementary information in selecting patients for ICPI-based therapies.

Keywords
Antibodies/therapeutic use DNA DNA mutational analysis Genes Neoplasm Programmed cell death 1 receptor Sequence analysis
MeSH Terms
Antibodies, Monoclonal/pharmacology,therapeutic use Biomarkers, Tumor Humans Immunotherapy/methods Mutation Treatment Outcome Tumor Burden
Chemicals
Antibodies, Monoclonal Biomarkers, Tumor
Authors & Affiliations
11 authors, click to expand affiliations / ORCID
Klempner Samuel J ORCID
The Angeles Clinic and Research Institute, Los Angeles, California, USA. | Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Fabrizio David
Foundation Medicine, Inc., Cambridge, Massachusetts, USA.
Bane Shalmali ORCID
Analysis Group, Inc., Menlo Park, California, USA.
Reinhart Marcia
Analysis Group, Inc., Menlo Park, California, USA.
Peoples Tim
Amgen Inc., Thousand Oaks, California, USA.
Ali Siraj M
Foundation Medicine, Inc., Cambridge, Massachusetts, USA.
Sokol Ethan S
Foundation Medicine, Inc., Cambridge, Massachusetts, USA.
Frampton Garrett
Foundation Medicine, Inc., Cambridge, Massachusetts, USA.
Schrock Alexa B
Foundation Medicine, Inc., Cambridge, Massachusetts, USA.
Anhorn Rachel
Foundation Medicine, Inc., Cambridge, Massachusetts, USA.
Reddy Prasanth
Foundation Medicine, Inc., Cambridge, Massachusetts, USA.
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Article Info
Journal
The oncologist
Abbr.
Oncologist
ISSN
1549-490X
Published
2020-00-00
Epub
2019-00-02
Pages
e147-e159
Language
English
Region
United States
NLM ID
9607837
PMCID
PMC6964127
Subset
IM
Analysis Services
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