Multi-Omics Tumor Immunogenicity Score Predicts Immunotherapy Outcome and Survival.

ABSTRACT:

Background

Tumor immunogenicity is a concept for modeling the susceptibility of tumors to immune checkpoint inhibitors (ICIs) and other immunotherapies. Single biomarkers, such as tumor mutation burden (TMB) or PDL1 expression, have been shown to correlate with ICI outcomes but are poor predictors of overall and progression-free survival (OS, PFS). Complex machine learning models that integrate multiple biomarkers have shown improved predictions but often lack clear a priori interpretability. In this study, we developed a coherent Multi-Omics Tumor Immunogenicity score (MOTIscore) that combines immunogenicity biomarkers derived from genomic and transcriptomic data and demonstrated its generalizability across multiple cancer types.

Methods

Several immunogenicity biomar

SUBMITTER: Gschwind A 

PROVIDER: S-EPMC12730895 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature