Zhang Jian, Fan Xiaosong, Xu Xu, Han Yichao, Yu Weixing, Yang Bicheng, Chen Yanling, Zhang Shaolin
Department of Urology, Shangyu People's Hospital of Shaoxing, Shaoxing University, Shaoxing, Zhejiang, China.
Hangzhou Center for Health Development, Hangzhou, Zhejiang, China.
Front Mol Biosci. 2025 Jun 23;12:1602700. doi: 10.3389/fmolb.2025.1602700. eCollection 2025.
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 -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.
尽管治疗方式有所进步，但膀胱癌仍然是一项重大的全球健康挑战，死亡率很高。代谢改变是癌症进展的关键因素，尤其影响肿瘤的侵袭性和患者预后。因此，本研究旨在识别和表征与膀胱癌疾病进展和肿瘤侵袭性相关的代谢枢纽。
从TCGA数据库中检索膀胱癌患者的DNA甲基化、mRNA表达和蛋白质表达以及临床数据。分别使用方差分析和学生t检验识别肿瘤侵袭性组之间以及早期与晚期肿瘤之间差异表达的代谢枢纽，而使用R代码评估代谢基因的生存相关性。分别使用DAVID、Cytoscape、Java、ChEA3和GSEA工具进行通路富集、网络构建、随机游走、转录因子预测和基因集富集分析。使用NCBI GEO数据集对鉴定出的基因特征进行验证。
通过基于代谢靶向差异表达和生存分析的方法，我们鉴定出105个代谢基因，其表达模式与膀胱癌患者的肿瘤侵袭性和临床结果相关。随后的网络构建和随机游走分析将该列表细化为一个七基因代谢特征（Metab-GS），包括致癌（ALDH1B1、ALDH1L2、CHSY1、CSGALNACT2、GPX8）和肿瘤抑制（FBP1、HPGD）枢纽。上游分析确定了表观遗传修饰，特别是肿瘤抑制代谢枢纽的DNA高甲基化以及USF2-NuRD复合物活性降低驱动致癌代谢枢纽表达增加，导致糖酵解转变和细胞外基质重塑，并建立炎症性肿瘤微环境。最后，在多个独立的GEO数据集中对我们的发现进行验证，证实高Metab-GS评分与膀胱癌患者的肿瘤侵袭性和进展、晚期疾病阶段、转移扩散、疾病复发以及总体和癌症特异性生存率低相关。
总体而言，一个七基因代谢特征可预测膀胱癌患者的肿瘤侵袭性和不良预后，强调靶向表观遗传失调诱导的代谢重编程作为侵袭性膀胱癌治疗策略的潜力。
