Creation of an innovative diagnostic framework for hepatocellular carcinoma employing bioinformatics techniques focused on senescence-related and pyroptosis-related genes.

ABSTRACT:

Background

Liver hepatocellular carcinoma (LIHC) continues to pose a major global health concern and is characterized by elevated mortality rates and a lack of effective therapies. This study aimed to explore differential gene expression linked to cellular senescence and pyroptosis in LIHC and to develop a prognostic risk model for use in clinical settings.

Methods

We acquired datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). DESeq2 was used to identify differentially expressed genes associated with cell senescence and pyrodeath. The least absolute shrinkage and selection operator (LASSO) regression model was developed using cellular senescence- and pyroptosis-related differentially expressed genes (CSR&PRDEGs), and its predictive performance wa

SUBMITTER: Liu B 

PROVIDER: S-EPMC11864952 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature