Integrated bioinformatic evaluation unveils a cellular senescence gene signature as a poor prognostic factor in hepatocellular carcinoma

Cellular senescence (CS) plays a crucial role in various diseases, but its role in hepatocellular carcinoma (HCC) remains unclear. CS-related genes were clustered to identify subtypes. A risk score was constructed and validated in three independent cohorts. Associations with clinical characteristics, tumor immune microenvironment, mutation status, heterogeneity, and treatment efficacy were analyzed. Single-cell analysis was used to examine risk score distribution, and machine learning algorithms along with a nomogram were applied to assess prognostic value. Three CS subtypes were identified, with subtype 1 showing the worst prognosis. High risk score was associated with advanced clinical stage and grade, poor prognosis, and an immunosuppressive microenvironment driven by regulatory T cells. It also correlated with higher tumor mutations (notably TP53) and increased heterogeneity. High-risk patients showed poor response to sorafenib and transcatheter arterial chemoembolization (TACE) but may benefit more from immunotherapy. At single-cell level, the risk score was predominantly expressed in malignant hepatocytes and linked to cell stemness. The CS-related risk score is a potential prognostic indicator for poor outcomes in HCC, playing a significant role in tumor progression and offering potential value for clinical diagnosis and prediction of treatment response.

Authors

Institutions

Publication Details

Journal
Clinical and Experimental Medicine
Published
2026-07-23
DOI
https://doi.org/10.1007/s10238-026-02258-5
Primary Topic
Telomeres, Telomerase, and Senescence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrated bioinformatic evaluation unveils a cellular senescence gene signature as a poor prognostic factor in hepatocellular carcinoma

Jing Lu, L Zhang, X Wang, Junjie Hu et al.
Clinical and Experimental Medicine
Telomeres, Telomerase, and Senescence
article

Integrated bioinformatic evaluation unveils a cellular senescence gene signature as a poor prognostic factor in hepatocellular carcinoma

Jing Lu, L Zhang, X Wang, Junjie Hu, Shaoyang Lu, Junjie Ma
article en

Abstract

Cellular senescence (CS) plays a crucial role in various diseases, but its role in hepatocellular carcinoma (HCC) remains unclear. CS-related genes were clustered to identify subtypes. A risk score was constructed and validated in three independent cohorts. Associations with clinical characteristics, tumor immune microenvironment, mutation status, heterogeneity, and treatment efficacy were analyzed. Single-cell analysis was used to examine risk score distribution, and machine learning algorithms along with a nomogram were applied to assess prognostic value. Three CS subtypes were identified, with subtype 1 showing the worst prognosis. High risk score was associated with advanced clinical stage and grade, poor prognosis, and an immunosuppressive microenvironment driven by regulatory T cells. It also correlated with higher tumor mutations (notably TP53) and increased heterogeneity. High-risk patients showed poor response to sorafenib and transcatheter arterial chemoembolization (TACE) but may benefit more from immunotherapy. At single-cell level, the risk score was predominantly expressed in malignant hepatocytes and linked to cell stemness. The CS-related risk score is a potential prognostic indicator for poor outcomes in HCC, playing a significant role in tumor progression and offering potential value for clinical diagnosis and prediction of treatment response.

Clinical and Experimental Medicine
Central South University (CN), Bengbu Medical College (CN), The Second Affiliated Hospital of Bengbu Medical College (CN), First Affiliated Hospital of Bengbu Medical College (CN), Third Xiangya Hospital (CN)
No poverty
Openalex Percentile: Top 10%
Telomeres, Telomerase, and Senescence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Integrated bioinformatic evaluation unveils a cellular senescence gene signature as a poor prognostic factor in hepatocellular carcinoma — Jing Lu, L Zhang, et al. · Clinical and Experimental Medicine (2026) | TGRS Research Map | TGRS