{"title":"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。","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":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","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":"{\"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\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"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}","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}
Establishment and evaluation cuproptosis-related gene signature for predicting the prognosis and immunotherapy response of hepatocellular carcinoma.
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.
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.
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