Identification and experimental validation of prognostic genes associated with dietary restriction-related signatures in bladder cancer

Abstract

Background Bladder cancer (BLCA) is a common urinary tract malignancy with significant global burden, yet the prognostic relevance of dietary restriction-related genes (DRRGs) in BLCA remains unclear. Methods Prognostic DRRGs in BLCA were identified based on publicly available databases by differential expression analysis, univariate Cox regression analysis, Mendelian randomization (MR) analysis and LASSO regression analysis. A risk model was built and evaluated, after which a nomogram was established and assessed by using the risk score and clinical characteristics. Following this, analysis of functional enrichment, immune infiltration, genetic mutation and drug sensitivity were performed based on the risk model. Importantly, cell annotation and identification of potential key cells were conducted by single-cell RNA sequencing (scRNA-seq) analysis. The expression levels of target DRRGs were examined by qRT-PCR and western blot methods. Cell transfection, in vivo and in vitro assays were performed to analyze the impacts of target DRRGs on BLCA cells’ biological behaviors. Results Three candidate prognostic DRRGs (RBP7, SREBF1 and ZFP64) were screened. The risk model classified BLCA patients two risk groups, and high-risk patients showed worse survival. The AUC values of this model in the training and validation cohorts were generally within the range of 0.60–0.66, suggesting some but limited discriminatory ability. The risk score, age, T stage, and N stage were identified as independent prognostic factors, and the nomogram constructed from these factors showed moderate predictive performance. The two risk groups differed in signaling pathways, immune cell infiltration, immune checkpoints, mutated genes, immunotherapy-related predictive indicators, and drug sensitivity. scRNA-seq analysis annotated eight cell types, among which T cells showed differential expression of the candidate DRRGs and were identified as a potential key cell type associated with prognostic DRRG expression. Experiments showed that SREBF1 and ZFP64 were over-expressed at mRNA and protein levels in BLCA tissues. Knockdown of SREBF1 or ZFP64 inhibited multiple malignant phenotypes of BLCA cells. Conclusions This study screened RBP7, SREBF1, and ZFP64 from a previously computationally inferred DR-related gene category as candidate prognostic genes in BLCA and established a risk model with moderate predictive performance, providing clues for further investigation of this malignancy.