Identification and experimental validation of biomarkers associated with amino acid metabolism and ferroptosis in bladder cancer

Amino acid metabolism-related genes (AAMRGs) and ferroptosis-related genes (FRGs) play pivotal roles in tumor progression, but their specific functions in bladder cancer (BLCA) remain unclear. This study aimed to identify and validate BLCA biomarkers linked to both gene sets, offering potential therapeutic targets. Using The Cancer Genome Atlas-BLCA (TCGA-BLCA) and GSE32894 datasets, candidate genes were identified through the intersection of differentially expressed genes (DEGs). Biomarkers were selected, and a prognostic risk model was developed through regression analysis and machine learning, accompanied by the creation of a nomogram. An integrated analysis of functional networks and other relevant factors was conducted. Five biomarkers (UGT2B4, HIST1H1C, etc.) were found to be significantly overexpressed in BLCA. The prognostic model effectively stratified patients, with a high-risk score associated with reduced survival; the risk score emerged as an independent prognostic factor. Notable differences were observed in the "apical junctions" pathway and 20 immune cell types, with UGT2B4 showing a positive correlation with hepatocytes. TTN mutation rates were 35% for high-risk patients and 50% for low-risk patients. Relevant transcription factors were predicted, and regulatory networks were constructed. Five biomarkers (UGT2B4, HIST1H1C, CGB, DSC1, SLC13A5) were clinically validated as potential BLCA biomarkers, supporting the development of targeted therapies.