Epigenetic dysregulation-induced metabolic reprogramming fuels tumor progression in bladder cancer

Bladder cancer remains a significant global health challenge with a high mortality rate despite advancements in treatment modalities. Metabolic alterations serve as crucial contributors to cancer progression, particularly influencing tumor aggressiveness and patient outcomes. Therefore, this study aimed to identify and characterize metabolic hubs associated with disease progression and tumor aggressiveness in bladder cancer.

DNA methylation, mRNA expression and protein expression, along with clinical data for bladder cancer patients were retrieved from TCGA database. Differentially expressed metabolic hubs among tumor aggressiveness groups and between early vs advanced stage tumors were identified using ANOVA and Student's t-test respectively, whereas survival association of metabolic genes was assessed using an R code. Pathway enrichment, network construction, random walk, transcription factor prediction and gene set enrichment analyses were conducted using DAVID, Cytoscape, Java, ChEA3 and GSEA tools respectively. Validation of the identified gene signature was performed using NCBI GEO datasets.

Through a metabolism-targeted differential expression and survival analysis-based approach, we identified 105 metabolic genes, whose expression patterns correlated with tumor aggressiveness and clinical outcomes in bladder cancer patients. Subsequent network construction and random walk analysis refined this list to a seven-gene metabolic signature (Metab-GS), comprising both oncogenic (ALDH1B1, ALDH1L2, CHSY1, CSGALNACT2, GPX8) and tumor suppressors (FBP1, HPGD) hubs. Upstream analysis identified epigenetic modifications, particularly DNA hypermethylation of tumor suppressor metabolic hubs and reduced USF2-NuRD complex activity-driven increased expression of oncogenic metabolic hubs, contributing to glycolytic shift and extracellular matrix remodeling, and establishing an inflammatory tumor microenvironment. Lastly, validation of our findings in multiple independent GEO datasets confirmed that high Metab-GS scores are associated with tumor aggressiveness and progression, advanced disease stage, metastatic spread, disease recurrence, and poor overall and cancer-specific survival in bladder cancer patients.

Overall, a seven-gene metabolic signature predicts tumor aggressiveness and poor prognosis in bladder cancer patients, underscoring the potential of targeting the epigenetic dysregulation-induced metabolic reprogramming as a therapeutic strategy for aggressive bladder cancer.