Evidence map›Paper›PMID 42661129›Full record

ArticleClinical and experimental medicine2026

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

Shaoyang Lu, Junjie Ma, Xiaodan Wang, Lei Zhang, Jin Lu, Junjie Hu

Abstract read
In one paragraph

Article in Clinical and experimental medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Shaoyang Lu *First Clinical Medical College, Bengbu Medical University, Bengbu, 233080, Anhui Province, China.
Junjie Ma *Department of Hepatobiliary and Pancreatic Surgery, The Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan Province, China.
Xiaodan WangDepartment of Oncology Surgery, the Second Affiliated Hospital of Bengbu Medical University, Bengbu, 233080, Anhui Province, China.
Lei ZhangDepartment of Oncology Surgery, the Second Affiliated Hospital of Bengbu Medical University, Bengbu, 233080, Anhui Province, China.
Jin LuDepartment of Human Anatomy, Bengbu Medical University, Bengbu, 233030, Anhui Province, China. 0100197@bbmu.edu.cn.
Junjie HuDepartment of Radiotherapy, the Second Affiliated Hospital of Bengbu Medical University, Bengbu, 233080, Anhui, China. 472863866@qq.com.

Funding

Key Natural Science Project of Bengbu Medical University XJ2024014201Key Natural Science Research Project of Anhui Provincial Universities 2023AH051929
6 · The paper itself

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) and may benefit less 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.

Indexed as

Carcinoma, HepatocellularCellular SenescenceComputational BiologyLiver NeoplasmsBiomarkers, TumorFemaleGene Expression ProfilingHumansMaleMiddle AgedPrognosisSingle-Cell AnalysisTumor MicroenvironmentBiomarkers, TumorCellular senescenceHepatocellular carcinomaImmunotherapyTumor immune microenvironment

Identifiers

PMID42661129
PMCPMC13522098

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.