THOR: a TMB heterogeneity-adaptive optimization model predicts immunotherapy response using clonal genomic features in group-structured data.

ABSTRACT: With the increasing number of indications for immune checkpoint inhibitors in early and advanced cancers, the prospect of a tumor-agnostic biomarker to prioritize patients is compelling. Tumor mutation burden (TMB) is a widely endorsed biomarker that quantifies nonsynonymous mutations within tumor DNA, essential for neoantigen production, which, in turn, correlates with the immune response and guides decision-making. However, the general clinical application of TMB-relying on simple mutational counts targeted at a single endpoint-does not adequately capture the complex clonal structure of tumors nor the multifaceted nature of prognostic indicators. This recognition has spurred the exploration of sophisticated high-dimensional regression techniques. Unfortunately, the limited cohort sizes i

SUBMITTER: Wang Y 

PROVIDER: S-EPMC11647273 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature