Feng Xiong, Bowen Wang, Haoxun Zhang, Guoling Zhang, Boju Tao, Yiwen Liu, Chunyang Wang
{"title":"预后相关特征预测免疫治疗肾透明细胞癌的益处。","authors":"Feng Xiong, Bowen Wang, Haoxun Zhang, Guoling Zhang, Boju Tao, Yiwen Liu, Chunyang Wang","doi":"10.1007/s12672-025-02991-5","DOIUrl":null,"url":null,"abstract":"<p><p>Clear cell renal cell carcinoma (ccRCC) stands as the pivotal pathological subtype of renal cell carcinoma. However, there exists a dearth of pertinent biological targets crucial for advancing the clinical application of ccRCC. In our investigation, we employed the weighted gene co-expression network analysis (WGCNA) to discern 13 distinct gene co-expression modules, with the yellow module exhibiting a pronounced association with tumorigenesis. Concurrently, we scrutinized 6147 differentially expressed genes through rigorous differential expression analysis. Through an intersecting approach with the genes within the yellow module, we pinpointed 265 cancer-related genes displaying notable differential expression. Subsequent Cox-regression analysis unveiled that among the 265 genes, four were notably linked to ccRCC prognosis. Furthermore, we executed single-sample gene set enrichment analysis (ssGSEA) on the signature comprising these four genes, subsequently deriving normalized enrichment scores (NESs). This investigation substantiated that the said signature bears significant implications for prognosis, holding the potential to forecast the efficacy of immunotherapy.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1153"},"PeriodicalIF":2.8000,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12179015/pdf/","citationCount":"0","resultStr":"{\"title\":\"Prognostic related signature predicts the benefits of immunotherapy for kidney renal clear cell carcinoma.\",\"authors\":\"Feng Xiong, Bowen Wang, Haoxun Zhang, Guoling Zhang, Boju Tao, Yiwen Liu, Chunyang Wang\",\"doi\":\"10.1007/s12672-025-02991-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Clear cell renal cell carcinoma (ccRCC) stands as the pivotal pathological subtype of renal cell carcinoma. However, there exists a dearth of pertinent biological targets crucial for advancing the clinical application of ccRCC. In our investigation, we employed the weighted gene co-expression network analysis (WGCNA) to discern 13 distinct gene co-expression modules, with the yellow module exhibiting a pronounced association with tumorigenesis. Concurrently, we scrutinized 6147 differentially expressed genes through rigorous differential expression analysis. Through an intersecting approach with the genes within the yellow module, we pinpointed 265 cancer-related genes displaying notable differential expression. Subsequent Cox-regression analysis unveiled that among the 265 genes, four were notably linked to ccRCC prognosis. Furthermore, we executed single-sample gene set enrichment analysis (ssGSEA) on the signature comprising these four genes, subsequently deriving normalized enrichment scores (NESs). This investigation substantiated that the said signature bears significant implications for prognosis, holding the potential to forecast the efficacy of immunotherapy.</p>\",\"PeriodicalId\":11148,\"journal\":{\"name\":\"Discover. Oncology\",\"volume\":\"16 1\",\"pages\":\"1153\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12179015/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Discover. Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s12672-025-02991-5\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discover. Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12672-025-02991-5","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Prognostic related signature predicts the benefits of immunotherapy for kidney renal clear cell carcinoma.
Clear cell renal cell carcinoma (ccRCC) stands as the pivotal pathological subtype of renal cell carcinoma. However, there exists a dearth of pertinent biological targets crucial for advancing the clinical application of ccRCC. In our investigation, we employed the weighted gene co-expression network analysis (WGCNA) to discern 13 distinct gene co-expression modules, with the yellow module exhibiting a pronounced association with tumorigenesis. Concurrently, we scrutinized 6147 differentially expressed genes through rigorous differential expression analysis. Through an intersecting approach with the genes within the yellow module, we pinpointed 265 cancer-related genes displaying notable differential expression. Subsequent Cox-regression analysis unveiled that among the 265 genes, four were notably linked to ccRCC prognosis. Furthermore, we executed single-sample gene set enrichment analysis (ssGSEA) on the signature comprising these four genes, subsequently deriving normalized enrichment scores (NESs). This investigation substantiated that the said signature bears significant implications for prognosis, holding the potential to forecast the efficacy of immunotherapy.