Identification of tumor mutation burden-associated molecular and clinical features in cancer by analyzing multi-omics data.

ABSTRACT:

Background

Tumor mutation burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in cancer. Systematic identification of molecular features correlated with TMB is significant, although such investigation remains insufficient.

Methods

We analyzed associations of somatic mutations, pathways, protein expression, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), competing endogenous RNA (ceRNA) antitumor immune signatures, and clinical features with TMB in various cancers using multi-omics datasets from The Cancer Genome Atlas (TCGA) program and datasets for cancer cohorts receiving the immune checkpoint blockade therapy.

Results

Among the 32 TCGA cancer types, melanoma harbored the highest percentage of high-TMB (≥ 10/Mb) cancers (49.4%),

SUBMITTER: Li M 

PROVIDER: S-EPMC9998480 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature