A novel signature constructed by ferroptosis-associated genes (FAGs) for the prediction of prognosis in bladder urothelial carcinoma (BLCA) and associated with immune infiltration

BACKGROUND: Ferroptosis, a novel form of regulated cell death, has been implicated in the pathogenesis of cancers. Nevertheless, the potential function and prognostic values of ferroptosis in bladder urothelial carcinoma (BLCA) are complex and remain to be clarified. Therefore, we proposed to systematically examine the roles of ferroptosis-associated genes (FAGs) in BLCA. METHODS: According to The Cancer Genome Atlas (TCGA) database, differently expressed FAGs (DEFAGs) and differently expressed transcription factors (DETFs) were identified in BLCA. Next, the network between DEFAGs and DETFs, GO annotations and KEGG pathway analyses were performed. Then, through univariate, LASSO and multivariate regression analyses, a novel signature based on FAGs was constructed. Moreover, survival analysis, PCA analysis, t-SNE analysis, ROC analysis, independent prognostic analysis, clinicopathological and immune correlation analysis, and experimental validation were utilized to evaluate the signature. RESULTS: Twenty-eight DEFAGs were identified, and four FAGs (CRYAB, TFRC, SQLE and G6PD) were finally utilized to establish the FAGs based signature in the TCGA cohort, which was subsequently validated in the GEO database. Moreover, we found that immune cell infiltration, immunotherapy-related biomarkers and immune-related pathways were significantly different between two risk groups. Besides, nine molecule drugs with the potential to treat bladder cancer were identified by the connectivity map database analysis. Finally, the expression levels of crucial FAGs were verified by the experiment, which were consistent with our bioinformatics analysis, and knockdown of TFRC could inhibit cell proliferation and colony formation in BLCA cell lines in vitro. CONCLUSIONS: Our study identified prognostic ferroptosis-associated genes and established a novel FAGs signature, which could accurately predict prognosis in BLCA patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02096-3.