Evidence map›Paper›PMID 40296031›Full record

ArticleCancer cell international2025

Establishment and evaluation cuproptosis-related gene signature for predicting the prognosis and immunotherapy response of hepatocellular carcinoma.

Shuo Wang, Xinzi Xue, Hongyan Bai, Junwen Qi, Sujuan Fei, Bei Miao

Abstract read
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Article in Cancer cell international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Shuo Wang *Department of Rheumatology and Immunology, the Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, 223001, China.
Xinzi Xue *Department of Oncology and Radiotherapy, Lianshui County People's Hospital, Lianshui, 223400, China.
Hongyan Bai *Department of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, 99 West Huaihai Road, Xuzhou, 221002, Jiangsu, China.
Junwen QiInstitute of Digestive Disease, Xuzhou Medical University, 84 West Huaihai Road, Xuzhou, 221002, Jiangsu, China.
Sujuan FeiDepartment of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, 99 West Huaihai Road, Xuzhou, 221002, Jiangsu, China. feisj99@163.com.
Bei MiaoDepartment of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, 99 West Huaihai Road, Xuzhou, 221002, Jiangsu, China. miaobei@xzhmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aims to develop a novel cuproptosis-related model through bioinformatics analysis, providing new insights into HCC classification. It also explores the correlation between the cuproptosis-related risk score and factors such as prognosis, tumor mutation burden (TMB), biological function, tumor microenvironment (TME), and immune efficacy.

methodsWe performed unsupervised clustering of cuproptosis-related gene expression profiles from TCGA and GEO to identify molecular subtypes and differentially expressed genes. Prognostic models were constructed using univariate, Lasso, and multivariate Cox regression analyses. HCC patients were classified into high-risk and low-risk subgroups, and the model's prognostic value was assessed through survival analysis, ROC curves, and nomograms. Immune checkpoint, drug sensitivity, and IPS were used to evaluate immunotherapy response. The model's predictive ability was further validated with the ICGC database and IMvigor210 cohort. Finally, key gene expression and biological functions were validated in human tissues and HCC cell lines.

resultsThe cuproptosis-related gene risk score model (CRGRM), based on GMPS, DNAJC6, BAMBI, MPZL2, ASPHD1, IL7R, EPO, BBOX1, and CXCL9, independently predicted HCC prognosis and immune response. Clinical correlation and ROC curve analysis demonstrated its accuracy in predicting 0.5-, 1-, 3-, and 5-year survival. The risk score also strongly correlates with immunotherapy response and serves as a reliable treatment predictor. Drug sensitivity analysis revealed that the low-risk group was more sensitive to dasatinib, imatinib, and gefitinib. In vitro, BAMBI knockdown significantly inhibited HCC cell proliferation and metastasis.

conclusionsThis model demonstrates potential in predicting prognosis and immunotherapy response, providing insights into personalized treatment strategies for HCC. Additionally, our study suggests that BAMBI may serve as a novel biomarker and potential therapeutic target for HCC.

Indexed as

CuproptosisHepatocellular carcinomaImmunotherapy responsePrognosisTumor microenvironment

Identifiers

PMID40296031
PMCPMC12038930

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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.