Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors.
Journal
Cancer discovery
ISSN: 2159-8290
Titre abrégé: Cancer Discov
Pays: United States
ID NLM: 101561693
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
27
04
2020
revised:
03
07
2020
accepted:
09
09
2020
pubmed:
4
11
2020
medline:
25
11
2021
entrez:
3
11
2020
Statut:
ppublish
Résumé
Tumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, varies across malignancies. Panel sequencing-based estimates of TMB have largely replaced whole-exome sequencing-derived TMB in the clinic. Retrospective evidence suggests that TMB can predict the efficacy of immune checkpoint inhibitors, and data from KEYNOTE-158 led to the recent FDA approval of pembrolizumab for the TMB-high tumor subgroup. Unmet needs include prospective validation of TMB cutoffs in relationship to tumor type and patient outcomes. Furthermore, standardization and harmonization of TMB measurement across test platforms are important to the successful implementation of TMB in clinical practice. SIGNIFICANCE: Evaluation of TMB as a predictive biomarker creates the need to harmonize panel-based TMB estimation and standardize its reporting. TMB can improve the predictive accuracy for immunotherapy outcomes, and has the potential to expand the candidate pool of patients for treatment with immune checkpoint inhibitors.
Identifiants
pubmed: 33139244
pii: 2159-8290.CD-20-0522
doi: 10.1158/2159-8290.CD-20-0522
pmc: PMC7710563
mid: NIHMS1629441
doi:
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1808-1825Subventions
Organisme : NCI NIH HHS
ID : R01 CA210509
Pays : United States
Informations de copyright
©2020 American Association for Cancer Research.
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