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Updated: Nov 3, 2025

A Next-generation Tissue Microarray ngTMA Protocol for Biomarker Studies
Published on: September 23, 2014
TMB or not TMB as a biomarker: That is the question
Alfredo Addeo1, Alex Friedlaender2, Giuseppe L Banna3
1Oncology Department, University Hospital of Geneva, Switzerland.
Abstract:
Immune checkpoint inhibitors (ICIs) have revolutionized the landscape of therapeutic options for many cancers. These treatments have demonstrated improved efficacy and often a more favourable toxicity profile compared to standard cytotoxic chemotherapy. There are considerable differences among responders, with some patients experiencing durable long-term disease control and even remission. Given this variability, determining a proper biomarker to select patients for ICI therapy has become increasingly important. The only biomarker proven to be predictive of overall survival benefit with ICI therapy is PD-L1 expression level measured by immunohistochemistry. Several attempts have been made to identify different predictive biomarkers. One of the most intriguing and divisive is tumor mutational burden (TMB). TMB represents the number of mutations per megabase (Mut/Mb) of DNA that were sequenced in a specific cancer. With a higher number of mutations detected, and consequentially an increase in the number neo-epitopes, then it is more likely that one or more of those neo-antigens could be immunogenic and trigger a T cell response. Initially, TMB was identified as a biomarker for ICIs in melanoma and subsequent studies suggested a possible clinical role for TMB in non-small cell lung cancer. The initial data were not confirmed in a prospective study assessing OS as the primary endpoint. Recently, the FDA has approved pembrolizumab in all cancers with a TMB > 10Mut/Mb[12] based on findings from the phase 2 KEYNOTE-158. Much criticism has emerged about this pan-cancer approval, in particular about the use of TMB as biomarker to select patients. Here we review the data about the importance and role of TMB as possible pan-cancer one-size-fits-all biomarker. We highlight the strengths and intrinsic limitations of such a complex biomarker and its adoption in the daily practice.
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