biostudies-literatureZhang YGuangzhou Medical UniversityGuangdong Basic and Applied Basic Research FoundationChina Postdoctoral Science FoundationFirst Affiliated Hospital of Guangzhou Medical UniversityDistinguished Young Talents in Higher Education Foundation of Guangdong ProvinceScience and Technology Plan Project of Guangzhoue12843https://www.ebi.ac.uk/biostudies/studies/S-EPMC8796709biostudies-literatureUnknown10<h4>Background</h4>Bladder cancer (BC) is a common urinary tract system tumor with high recurrence rate and different populations show distinct response to immunotherapy. Novel biomarkers that can accurately predict prognosis and therapeutic responses are urgently needed. Here, we aim to identify a novel prognostic and therapeutic responses immune-related gene signature of BC through a comprehensive bioinformatics analysis.<h4>Methods</h4>The robust rank aggregation was conducted to integrate differently expressed genes (DEGs) in datasets of the Cancer Genome Atlas (TCGA) and the gene expression omnibus (GEO). Lasso and Cox regression analyses were performed to formulate a novel mRNA signature that could predict prognosis of BC patients. Subsequently, the prognostic value and predictive vaPeerJIdentification and validation of a novel signature for prediction the prognosis and immunotherapy benefit in bladder cancer.PMC879670901-407-2101ZH201908202102010150 and 2021020800102019A15151100332019KQNCX1152019M662865Li WZhang YLin YLv DWang XJiang DWu XfalseIdentification and validation of a novel signature for prediction the prognosis and immunotherapy benefit in bladder cancer.<h4>Background</h4>Bladder cancer (BC) is a common urinary tract system tumor with high recurrence rate and different populations show distinct response to immunotherapy. Novel biomarkers that can accurately predict prognosis and therapeutic responses are urgently needed. Here, we aim to identify a novel prognostic and therapeutic responses immune-related gene signature of BC through a comprehensive bioinformatics analysis.<h4>Methods</h4>The robust rank aggregation was conducted to integrate differently expressed genes (DEGs) in datasets of the Cancer Genome Atlas (TCGA) and the gene expression omnibus (GEO). Lasso and Cox regression analyses were performed to formulate a novel mRNA signature that could predict prognosis of BC patients. Subsequently, the prognostic value and predictive va2022-01-01T00:00:00Z20222026-05-07T22:20:56.926Z2026-04-07T23:20:44.85ZS-EPMC87967093512729610.7717/peerj.12843