Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better

Area of Science:

• Oncology
• Immunotherapy
• Genomics

Background:

• The US Food and Drug Administration (FDA) approved immune checkpoint blockade (ICB) for cancers with high tumor mutation burden (TMB >10 mutations/megabase).
• The current TMB cut-off of >10 mutations/megabase (mut/Mb) is not consistently predictive of ICB response across all cancer types, raising concerns about its universal applicability.
• There is a critical need to establish a more optimal and generalizable TMB cut-off for predicting ICB efficacy.

Purpose of the Study:

• To exhaustively evaluate all potential TMB cut-offs for predicting ICB treatment outcomes across diverse cancer types.
• To determine a universally applicable and reproducible TMB cut-off for identifying patients likely to respond to ICB therapy.
• To investigate the robustness of TMB as a predictive biomarker for ICB in different cancer types based on their intrinsic TMB levels.

Main Methods:

• Analysis of two independent cohorts (n=1662 and n=102) to test all possible TMB cut-offs.
• Application of bootstrap resampling (10,000 iterations) to assess the reproducibility of identified TMB cut-offs.
• Evaluation of ICB treatment outcomes using overall survival, progression-free survival, and objective response rate.

Main Results:

• No single TMB cut-off was effective for all cancer types.
• In high TMB (category I) cancers (e.g., melanoma, colorectal, bladder, non-small cell lung), TMB-H was a more robust predictor of ICB response, with an optimal cut-off of 13 mut/Mb identified.
• Low TMB (category II) cancers showed sensitivity to TMB cut-off selection, with limited ranges of favorable cut-offs.

Conclusions:

• High TMB is more reliably associated with favorable ICB outcomes in cancers with intrinsically higher TMB levels.
• A universal TMB cut-off of 13 mut/Mb may indicate a threshold for initiating an effective anti-tumor immune response.
• This study provides a framework for predicting TMB's utility as a biomarker in new cancer types and suggests a potential general requirement for ICB efficacy.