摘要：

Reactive Oxygen Species (ROS), a hallmark of cancer, is related to prognosis, tumor progression, and treatment response. Nevertheless, the correlation of ROS-based molecular signature with clinical outcome and immune cell infiltration has not been thoroughly studied in bladder cancer (BLCA). Accordingly, we aimed to thoroughly examine the role and prognostic value of ROS-related genes in BLCA. We obtained RNA sequencing and clinical data from The Cancer Genome Atlas (TCGA) for bladder cancer (BLCA) patients and identified ROS-associated genes using the GeneCards and Molecular Signatures Database (MSigDB). We then analyzed differential gene expression between BLCA and normal tissues and explored the functions of these ROS-related genes through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) analysis. Prognostic ROS-related genes were identified using Univariate Cox regression (UCR) and LASSO analyses, which were further refined in a Multivariate Cox Regression (MCR) analysis to develop a Prognostic Signature (PS). This PS was validated in the GSE13507 cohort, assessing its predictive power with Kaplan-Meier survival and time-dependent ROC curves. To forecast BLCA outcomes, we constructed a nomogram integrating the PS with clinical variables. We also investigated the signature's molecular characteristics through Gene Set Enrichment Analysis (GSEA), Immune Cell Infiltration (ICI), and Tumor Mutational Burden (TMB) analyses. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to predict chemotherapy responses based on the PS. Additionally, we screened for Small-Molecule Drugs (SMDs) targeting ROS-related genes using the CMAP database. Finally, we validated our findings by checking protein levels of the signature genes in the Human Protein Atlas (HPA) and confirmed the role of Aldo-keto reductase family 1 member B1 (AKR1B1) through in vitro experiments. The constructed and validated PS that comprised 17 ROS-related genes exhibited good performance in predicting overall survival (OS), constituting an independent prognostic biomarker in BLCA patients. Additionally, we successfully established a nomogram with superior predictive capacity, as indicated by the calibration plots. The bioinformatics analysis findings showcased the implication of PS in several oncogenic pathways besides tumor ICI regulation. The PS was negatively associated with the TMB. The high-risk group patients had greater chemotherapy sensitivity in comparison to low-risk group patients. Further, 11 candidate SMDs were identified for treating BLCA. The majority of gene expression exhibited a correlation with the protein expression. In addition, the expression of most genes was consistent with protein expression. Furthermore, to test the gene reliability we constructed, AKR1B1, one of the seventeen genes identified, was used for in-depth validation. In vitro experiments indicate that siRNA-mediated AKR1B1 silencing impeded BLCA cell viability, migration, and proliferation. We identified a PS based on 17 ROS-related genes that represented independent OS prognostic factors and 11 candidate SMDs for BLCA treatment, which may contribute to the development of effective individualized therapies for BLCA.

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