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Mass spectrometric detection combined with bioinformatic analysis identified possible protein markers and key pathways associated with bladder cancer.

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We aimed to find possible protein markers and key pathways related to bladder cancer. In total, we extracted three bladder cancer tissues and three paracancerous tissues from Jiangsu Provincial People's… Click to show full abstract

We aimed to find possible protein markers and key pathways related to bladder cancer. In total, we extracted three bladder cancer tissues and three paracancerous tissues from Jiangsu Provincial People's Hospital Urology Department, and performed mass spectrometric detection with Q Exactive. Subsequently, we screened the differentially expressed proteins in the disease group and the normal group using the LIMMA package, and performed functional enrichment analyses using DAVID. Further, we constructed protein-protein interaction (PPI) networks with Cytoscape software, and analyzed modules with ClusterONE. In total, 165 differentially expressed proteins including 19 upregulated and 146 downregulated ones were obtained. ACTA2 (Actin, Alpha 2, Smooth Muscle, Aorta), ACTN1 (Actinin, Alpha 1), and VCL (Vinculin) were significant nodes with higher degrees in the PPI network. These three nodes were also hub nodes in module 2. Besides, functional enrichment analysis suggested that ECM-receptor interaction and focal adhesion were significant pathways, and these two pathways were also enriched in three network modules. In addition, ACTN1 and VCL were enriched in the focal adhesion pathway in module 2. Thus, ACTA2, ACTN1, and VCL may play important roles in bladder cancer progression and may be protein markers for this disease. The ECM-receptor interaction pathway and the focal adhesion pathway may be involved in the progression of bladder cancer. Furthermore, ACTN1 and VCL may play roles in bladder cancer development, partly via the focal adhesion pathway.

Keywords: bladder cancer; protein markers; cancer; markers key; possible protein

Journal Title: Gene
Year Published: 2017

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