Identification of a senescence-related transcriptional signature to uncover molecular subtypes and key genes in hepatocellular carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) is a cancer caused by abnormal cell growth due to faulty signal transduction. Cells secrete tumor suppressor factors in response to potential carcinogenic signals, inducing cellular senescence (CS) as a countermeasure. However, accurately measuring CS levels in different types of tumors is challenging due to tumor heterogeneity and the lack of universal and specific CS markers. Machine learning has revealed unique molecular traits in HCC patients, leading to clinical advantages. More research is needed to understand senescence-related molecular features in these patients. In this study, the gene expression profile features of patients with HCC were analyzed by integrating single-cell RNA sequencing and bulk RNA-seq datasets from HCC samples. The analysis iden

SUBMITTER: He X 

PROVIDER: S-EPMC11463828 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature