{"title":"探讨锌指蛋白相关基因在预测肝癌预后、免疫反应和药物疗效中的应用。","authors":"Pengtao Zhai, Mei Li, Yuan Cheng","doi":"10.1177/09603271251340277","DOIUrl":null,"url":null,"abstract":"<p><p>BackgroundHepatocellular carcinoma (LIHC), a prevalent liver cancer with a grim prognosis due to high recurrence rates, is under scrutiny for its association with zinc finger proteins (ZNFs) in tumorigenesis. This study aims to create a prognostic model for LIHC incorporating ZNF-related genes.MethodsBy analyzing TCGA data, we identified differentially expressed genes (DEGs) between normal and LIHC samples, focusing on ZNF-related genes through univariate Cox and LASSO Cox regression. A multivariate Cox regression model was built, categorizing LIHC patients into high- and low-ZNFRS groups based on ZNF-related risk scores. Model performance was evaluated using ROC curves, with a nomogram integrating clinical data and ZNFRS. Immune microenvironment, enrichment analysis, mutations, and drug responses in LIHC were also explored.ResultsA prognostic model utilizing 10 ZNF-related genes accurately predicted LIHC survival. The low-risk group exhibited enhanced immune cell infiltration, contrasting with cell cycle and DNA replication enrichment in the high-risk group, which also displayed increased mutation rates. Promising drug candidates like SNS-314 and Decitabine warrant further investigation in LIHC treatment.ConclusionThis study introduces impactful prognostic markers for LIHC management, emphasizing the significance of ZNFs in predicting patient outcomes and guiding treatment strategies.</p>","PeriodicalId":94029,"journal":{"name":"Human & experimental toxicology","volume":"44 ","pages":"9603271251340277"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring the utility of zinc finger protein-related genes in predicting hepatocellular carcinoma prognosis, immune responses, and drug efficacy.\",\"authors\":\"Pengtao Zhai, Mei Li, Yuan Cheng\",\"doi\":\"10.1177/09603271251340277\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>BackgroundHepatocellular carcinoma (LIHC), a prevalent liver cancer with a grim prognosis due to high recurrence rates, is under scrutiny for its association with zinc finger proteins (ZNFs) in tumorigenesis. This study aims to create a prognostic model for LIHC incorporating ZNF-related genes.MethodsBy analyzing TCGA data, we identified differentially expressed genes (DEGs) between normal and LIHC samples, focusing on ZNF-related genes through univariate Cox and LASSO Cox regression. A multivariate Cox regression model was built, categorizing LIHC patients into high- and low-ZNFRS groups based on ZNF-related risk scores. Model performance was evaluated using ROC curves, with a nomogram integrating clinical data and ZNFRS. Immune microenvironment, enrichment analysis, mutations, and drug responses in LIHC were also explored.ResultsA prognostic model utilizing 10 ZNF-related genes accurately predicted LIHC survival. The low-risk group exhibited enhanced immune cell infiltration, contrasting with cell cycle and DNA replication enrichment in the high-risk group, which also displayed increased mutation rates. Promising drug candidates like SNS-314 and Decitabine warrant further investigation in LIHC treatment.ConclusionThis study introduces impactful prognostic markers for LIHC management, emphasizing the significance of ZNFs in predicting patient outcomes and guiding treatment strategies.</p>\",\"PeriodicalId\":94029,\"journal\":{\"name\":\"Human & experimental toxicology\",\"volume\":\"44 \",\"pages\":\"9603271251340277\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human & experimental toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/09603271251340277\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/9 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human & experimental toxicology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/09603271251340277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/9 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring the utility of zinc finger protein-related genes in predicting hepatocellular carcinoma prognosis, immune responses, and drug efficacy.
BackgroundHepatocellular carcinoma (LIHC), a prevalent liver cancer with a grim prognosis due to high recurrence rates, is under scrutiny for its association with zinc finger proteins (ZNFs) in tumorigenesis. This study aims to create a prognostic model for LIHC incorporating ZNF-related genes.MethodsBy analyzing TCGA data, we identified differentially expressed genes (DEGs) between normal and LIHC samples, focusing on ZNF-related genes through univariate Cox and LASSO Cox regression. A multivariate Cox regression model was built, categorizing LIHC patients into high- and low-ZNFRS groups based on ZNF-related risk scores. Model performance was evaluated using ROC curves, with a nomogram integrating clinical data and ZNFRS. Immune microenvironment, enrichment analysis, mutations, and drug responses in LIHC were also explored.ResultsA prognostic model utilizing 10 ZNF-related genes accurately predicted LIHC survival. The low-risk group exhibited enhanced immune cell infiltration, contrasting with cell cycle and DNA replication enrichment in the high-risk group, which also displayed increased mutation rates. Promising drug candidates like SNS-314 and Decitabine warrant further investigation in LIHC treatment.ConclusionThis study introduces impactful prognostic markers for LIHC management, emphasizing the significance of ZNFs in predicting patient outcomes and guiding treatment strategies.