Evidence map›Paper›PMID 41459880›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2025

m5C-Related Regulators Define Tumor Microenvironment and Predict Prognosis in Hepatocellular Carcinoma.

Xiang-Qian Gu, Bin Li, Cheng-Yu Gu, Ming-Yu Wu, Ning Wang

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Article in Asian Pacific journal of cancer prevention : APJCP, 2025. 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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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiang-Qian GuDepartment of Hepatobiliary Surgery, Wuxi People's Hospital Affiliated Nanjing Medical University, Wuxi, China.
Bin LiDepartment of Hepatobiliary Surgery, Wuxi People's Hospital Affiliated Nanjing Medical University, Wuxi, China.
Cheng-Yu GuDepartment of Hepatobiliary Surgery, Wuxi People's Hospital Affiliated Nanjing Medical University, Wuxi, China.
Ming-Yu WuDepartment of Hepatobiliary Surgery, Wuxi People's Hospital Affiliated Nanjing Medical University, Wuxi, China.
Ning WangNHC Key Lab of Hormones and Development and Tianjin Key Lab of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Institute of Endocrinology, Tianjin, 300134, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is a highly lethal cancer and a leading cause of cancer-related deaths globally. RNA 5-methylcytosine (m5C) modification plays a vital role in epigenetic regulation, yet its impact on prognosis and the tumor immune microenvironment (TIME) in HCC remains unclear. MATERIALS AND

methodsRNA sequencing and clinical data were obtained from the Cancer Genome Atlas (TCGA) database. We applied an unsupervised clustering algorithm for the cluster analysis of m5C RNA methylation regulators, and then performed survival analyses to determine the best prognosis for HCC samples. Univariate and multivariate Cox regression analyses were conducted to construct a prognostic model. HCC patients were classified into high- and low-risk groups based on risk scores. Model performance was evaluated using ROC curves and validated with the ICGC cohort. Immune infiltration, clinicopathological features, and functional enrichment analyses were also performed.

resultWe analyzed the differential expression patterns of the m5C-related regulators between HCC and normal tissue samples. Based on consensus clustering of these regulators, three distinct molecular subgroups were identified, each associated with differences in patient survival and immune cell infiltration. Furthermore, we developed a prognostic signature comprising NSUN3, NSUN5, and YBX1, and stratified HCC patients into low- and high-risk groups. Patients in the low-risk group exhibited significantly better overall survival (OS) than those in the high-risk group. The robustness of this risk model was validated using the ICGC database. When integrated with clinicopathological characteristics, the risk score emerged as an independent prognostic factor. Additionally, we performed functional annotation and enrichment analyses based on differentially expressed genes (DEGs) between the two risk subgroups to explore potential underlying biological mechanisms.

conclusionOur study revealed the potential roles of these m5C-related regulators in TIME and identified their prognosis value and therapeutic potential for HCC patients.

Indexed as

Carcinoma, HepatocellularRNA MethylationTumor MicroenvironmentBiomarkers, TumorCluster AnalysisEpigenesis, GeneticHumansPrognosisRisk AssessmentSurvival AnalysisBiomarkers, TumorHepatocellular carcinomaimmune infiltrationm5C methylationprognostic signatureTumor Microenvironment

Identifiers

PMID41459880
PMCPMC13245535

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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.