Cellular senescence-related gene signature as a valuable predictor of prognosis in hepatocellular carcinoma.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC) is a lethal tumor. Its prognosis prediction remains a challenge. Meanwhile, cellular senescence, one of the hallmarks of cancer, and its related prognostic genes signature can provide critical information for clinical decision-making.

Method

Using bulk RNA sequencing and microarray data of HCC samples, we established a senescence score model via multi-machine learning algorithms to predict the prognosis of HCC. Single-cell and pseudo-time trajectory analyses were used to explore the hub genes of the senescence score model in HCC sample differentiation.

Result

A machine learning model based on cellular senescence gene expression profiles was identified in predicting HCC prognosis. The feasibility and accuracy of the senescence

SUBMITTER: Zhang S 

PROVIDER: S-EPMC10188344 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature