Prognostic features of bladder cancer based on five neddylation-related genes.

IF 1.5 Q3 UROLOGY & NEPHROLOGY American journal of clinical and experimental urology Pub Date : 2024-10-15 eCollection Date: 2024-01-01 DOI:10.62347/RWCH7802
Jiang Guo, Yuanning Zhang, Lei He, Xiaojun Wang, Zhangyan Chen, Can Yao
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Abstract

Background: Nedylation and tumours are closely linked. The role of nedylation in bladder cancer (BCa) has rarely been reported and this study aims to explore its potential impact on the pathogenesis and progression of BCa.

Methods: Leveraging gene expression data from the TCGA database, this research employs the limma software package and WGCNA for gene module identification and analysis. Subsequent steps include the construction of a PPI network, the conduct of LASSO and univariate Cox regression analyses, and utilizing GSEA and single-cell sequencing to examine the influence of hub genes in bladder cancer-related biological pathways.

Results: The investigation revealed 11,361 genes with significant differential expression between normal and tumour tissues, and identified 1,500 hub genes through analysis. LASSO regression identified eight critical genes. Univariate Cox regression analysis revealed that COMMD9, GPS1, PSMB5, VHL, and WDR5 are independent prognostic factors for BCa. GSEA and single-cell sequencing highlight the potential of these genes to modulate immune responses and interactions between tumour and immune cells. Meanwhile, GSEA demonstrated that GPS1 can activate the NF-κB signalling pathway, leading to an increase in influenza virus polymerase activity.

Conclusion: This study identifies COMMD9, GPS1, PSMB5, VHL, and WDR5 as significant prognostic markers in BCa, thereby underscoring their roles in immune regulation and tumour-immune cell dynamics.

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基于五个内切酶相关基因的膀胱癌预后特征。
背景:Nedylation与肿瘤密切相关。本研究旨在探讨其对膀胱癌(BCa)发病机制和进展的潜在影响:本研究利用 TCGA 数据库中的基因表达数据,使用 limma 软件包和 WGCNA 进行基因模块的识别和分析。随后的步骤包括构建PPI网络、进行LASSO和单变量Cox回归分析,以及利用GSEA和单细胞测序来研究枢纽基因在膀胱癌相关生物学通路中的影响:结果:研究发现了 11,361 个基因在正常组织和肿瘤组织之间存在显著表达差异,并通过分析确定了 1,500 个枢纽基因。LASSO回归确定了8个关键基因。单变量 Cox 回归分析显示,COMMD9、GPS1、PSMB5、VHL 和 WDR5 是 BCa 的独立预后因素。GSEA和单细胞测序突显了这些基因调节免疫反应以及肿瘤和免疫细胞之间相互作用的潜力。同时,GSEA表明,GPS1可激活NF-κB信号通路,导致流感病毒聚合酶活性增加:结论:本研究发现 COMMD9、GPS1、PSMB5、VHL 和 WDR5 是 BCa 的重要预后标志物,从而强调了它们在免疫调节和肿瘤-免疫细胞动态中的作用。
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