Tumor mutational burden as a predictive biomarker in solid tumors

Dan Sha, Zhaohui Jin, Jan Budczies, Klaus Kluck, Albrecht Stenzinger, Frank A. Sinicrope

Research output: Contribution to journalReview articlepeer-review

12 Scopus citations


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 immuno-therapy outcomes, and has the potential to expand the candidate pool of patients for treatment with immune checkpoint inhibitors.

Original languageEnglish (US)
Pages (from-to)1808-1825
Number of pages18
JournalCancer discovery
Issue number12
StatePublished - Dec 2020

ASJC Scopus subject areas

  • Oncology


Dive into the research topics of 'Tumor mutational burden as a predictive biomarker in solid tumors'. Together they form a unique fingerprint.

Cite this