Evolutionary genetic algorithm identifies <i>IL2RB</i> as a potential predictive biomarker for immune-checkpoint therapy in colorectal cancer.

ABSTRACT: Identifying robust predictive biomarkers to stratify colorectal cancer (CRC) patients based on their response to immune-checkpoint therapy is an area of unmet clinical need. Our evolutionary algorithm Atlas Correlation Explorer (ACE) represents a novel approach for mining The Cancer Genome Atlas (TCGA) data for clinically relevant associations. We deployed ACE to identify candidate predictive biomarkers of response to immune-checkpoint therapy in CRC. We interrogated the colon adenocarcinoma (COAD) gene expression data across nine immune-checkpoints (PDL1, PDCD1, CTLA4, LAG3, TIM3, TIGIT, ICOS, IDO1 and BTLA). IL2RB was identified as the most common gene associated with immune-checkpoint genes in CRC. Using human/murine single-cell RNA-seq data, we demonstrated that

SUBMITTER: Alderdice M 

PROVIDER: S-EPMC8057496 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature