Development and validation of a gemcitabine sensitivity-related long noncoding RNA signature for predicting the prognosis and subtypes of bladder cancer

Background: Bladder cancer (BLCA) is a common urogenital malignancy with significant heterogeneity, and gemcitabine serves as a key chemotherapeutic agent for BLCA. This study examined gemcitabine sensitivity-related long noncoding RNA (GSRlncRNA) in BLCA and constructed a prognostic signature. Methods: Gene expression and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The gemcitabine sensitivity of BLCA samples was quantitatively calculated. Using weighted gene coexpression network analysis (WGCNA), we analyzed the role of GSRlncRNA in BLCA. We developed a prognostic signature using machine learning algorithm integration, with the TCGA-BLCA cohort (n=405) serving as the training set and GSE31684 (n=93) serving as the validation cohort. Patients were stratified into low- and high-risk groups based on risk scores. Comparative analyses included prognosis, immune infiltration, mutational profiles, and pathway enrichment. Single-cell RNA sequencing (scRNA-seq) and in vitro experiments further validated the expression and functional roles of GSRlncRNA in BLCA. Results: suppression impaired BLCA cell proliferation, migration, invasion, apoptosis, cell cycle, and gemcitabine sensitivity. Conclusions: We identified critical prognostic associations between GSRlncRNAs and BLCA. Based on these findings, we constructed a GSRlncRNA-based predictive signature, which demonstrated considerable potential for risk stratification and personalized treatment decisions. Functional experiments further validated the involvement of GSRlncRNAs in BLCA progression.