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

IF 5.3 2区医学 Q1 ONCOLOGY

Cancer Cell International Pub Date : 2025-04-28 DOI:10.1186/s12935-025-03688-z

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

{"title":"Establishment and evaluation cuproptosis-related gene signature for predicting the prognosis and immunotherapy response of hepatocellular carcinoma.","authors":"Shuo Wang, Xinzi Xue, Hongyan Bai, Junwen Qi, Sujuan Fei, Bei Miao","doi":"10.1186/s12935-025-03688-z","DOIUrl":null,"url":null,"abstract":"Background: This 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.Methods: We 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.Results: The 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.Conclusions: This 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.","PeriodicalId":9385,"journal":{"name":"Cancer Cell International","volume":"25 1","pages":"166"},"PeriodicalIF":5.3000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12038930/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Cell International","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12935-025-03688-z","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Background: This 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.

Methods: We 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.

Results: The 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.

Conclusions: This 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.

查看原文本刊更多论文

预测肝细胞癌预后及免疫治疗应答的铜绿相关基因标记的建立与评价。

背景：本研究旨在通过生物信息学分析，建立一种新的铜臭相关模型，为HCC的分类提供新的见解。探讨铜肾相关风险评分与预后、肿瘤突变负荷（tumor mutation burden， TMB）、生物学功能、肿瘤微环境（tumor microenvironment， TME）、免疫效果等因素的相关性。方法：我们对来自TCGA和GEO的铜裂相关基因表达谱进行无监督聚类，以确定分子亚型和差异表达基因。使用单变量、Lasso和多变量Cox回归分析构建预后模型。将HCC患者分为高危亚组和低危亚组，通过生存分析、ROC曲线和nomogram评估模型的预后价值。采用免疫检查点、药物敏感性和IPS评价免疫治疗反应。通过ICGC数据库和IMvigor210队列进一步验证了该模型的预测能力。最后，在人体组织和HCC细胞系中验证了关键基因的表达和生物学功能。结果：基于GMPS、DNAJC6、BAMBI、MPZL2、ASPHD1、IL7R、EPO、BBOX1、CXCL9的铜质增生相关基因风险评分模型（CRGRM）能够独立预测HCC预后和免疫应答。临床相关分析和ROC曲线分析显示其预测0.5年、1年、3年和5年生存率的准确性。风险评分也与免疫治疗反应密切相关，并可作为可靠的治疗预测指标。药物敏感性分析显示，低危组对达沙替尼、伊马替尼和吉非替尼更敏感。在体外，BAMBI敲低可显著抑制HCC细胞的增殖和转移。结论：该模型显示了预测预后和免疫治疗反应的潜力，为HCC的个性化治疗策略提供了见解。此外，我们的研究表明BAMBI可能作为HCC的一种新的生物标志物和潜在的治疗靶点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Cancer Cell International ONCOLOGY-

CiteScore

10.90

自引率

1.70%

发文量

360

审稿时长

1 months

期刊介绍： Cancer Cell International publishes articles on all aspects of cancer cell biology, originating largely from, but not limited to, work using cell culture techniques. The journal focuses on novel cancer studies reporting data from biological experiments performed on cells grown in vitro, in two- or three-dimensional systems, and/or in vivo (animal experiments). These types of experiments have provided crucial data in many fields, from cell proliferation and transformation, to epithelial-mesenchymal interaction, to apoptosis, and host immune response to tumors. Cancer Cell International also considers articles that focus on novel technologies or novel pathways in molecular analysis and on epidemiological studies that may affect patient care, as well as articles reporting translational cancer research studies where in vitro discoveries are bridged to the clinic. As such, the journal is interested in laboratory and animal studies reporting on novel biomarkers of tumor progression and response to therapy and on their applicability to human cancers.