Discovery and Validation of a New Biomarker Integrating Ferroptosis and Glycolysis‐Related Genes in Bladder Cancer

Bladder cancer (BCa) is a highly invasive tumor with few successful therapies, and its unfavorable prognosis mainly stems from late diagnosis and resistance to treatment. Ferroptosis is a type of non-apoptotic cell death characterized by iron-dependent regulated necrosis due to extensive lipid peroxidation. Glycolysis is fundamental to cancer cell metabolism, with cancer cells developing various strategies to enhance this process. In this study, we combined ferroptosis and glycolysis gene sets, two biological processes closely related to tumorigenesis and development, and obtained ferroptosis and glycolysis-related gene sets (FGRGs). By leveraging both single-cell and bulk transcriptome data from BCa, we have investigated the presence and role of FGRGs in the onset and progression of BCa through various approaches. Using machine learning algorithms, we identified a feature gene set consisting of 13 genes in the TCGA data set to predict the prognosis of BCa and verified it in the GEO data set. After that, we explored FGRGs in depth using a variety of bioinformatics analyses, such as mutational landscape analysis, functional enrichment analysis, immune infiltration analysis, FGRGs-associated risk and clinical characterization, and drug susceptibility analysis. Finally, we validated the function of the core gene chondroitin polymerizing factor 2 (CHPF2) using CCK-8, clone formation, transwell, and wound healing assays. Our research innovatively combines ferroptosis with glycolytic genes and applies it as an independent prognostic factor in the study of BCa. It reveals new characteristic genes and therapeutic targets that can predict the prognosis of BCa patients and lays a foundation for the study of the occurrence and development mechanism of BCa and targeted data strategies.