Continuous prediction for tumor mutation burden based on transcriptional data in gastrointestinal cancers.

ABSTRACT:

Background

Tumor mutation burden (TMB) has been considered a biomarker for utilization of immune checkpoint inhibitors(ICIs), but whole exome sequencing(WES) and cancer gene panel(CGP) based on next generation sequencing for TMB detection are costly. Here, we use transcriptome data of TCGA to construct a model for TMB prediction in gastrointestinal tumors.

Methods

Transcriptome data, somatic mutation data and clinical data of four gastrointestinal tumors from TCGA, including esophageal cancer (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ). Using R, we performed visual analysis of somatic mutation data, differentially expressed genes (DEGs) function enrichment analysis, gene set enrichment analysis (GSEA), and estimated TMB

SUBMITTER: Hu B 

PROVIDER: S-EPMC11654420 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature