Identification of Lymph Node Metastasis-Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis

通过共表达分析鉴定膀胱癌淋巴结转移相关关键基因及预后风险模型

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Abstract

Background: Lymph node metastasis (LNM) is an important pathological characteristic of bladder cancer (BCa). However, the molecular mechanism underlying LNM was not thoroughly elaborated. Identification for LNM-related biomarkers may contribute to making suitable therapies. So, the current study was aimed to identify key genes and construct a prognostic signature. Methods: Based on the Cancer Genome Atlas (TCGA) database, gene expression and clinical information were obtained. Then, the weighted gene co-expression network analysis (WGCNA) was performed to identify the key modules and hub genes. A function analysis and a gene set enrichment analysis were applied to explore biological functions and pathways of interested genes. Furthermore, a prognostic model based on LNM-related genes was constructed by using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Results: Finally, nine co-expression modules were constructed, and two modules (turquoise and green) were significantly associated with LNM. Three hub genes were identified as DACT3, TNS1, and MSRB3, which were annotated in actin binding, actin cytoskeleton, adaptive immune response, and cell adhesion molecular binding by the GSEA method. Further analysis demonstrated that three hub genes were associated with the overall survival of BCa patients. In addition, we built a prognostic signature based on the genes from LNM-related modules and evaluated the prognostic value of this signature. Conclusion: In general, this study revealed the key genes related to LNM and prognostic signature, which might provide new insights into therapeutic target of BCa.

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