Abstract
The present techniques of clinical and histopathological diagnosis hardly distinguish chromophobe renal cell carcinoma (ChRCC) from renal oncocytoma (RO). To identify differentially expressed genes (DEGs) as effective biomarkers for diagnosis and prognosis of ChRCC and RO, three mRNA microarray datasets (GSE12090, GSE19982, and GSE8271) were downloaded from the GEO database. Functional enrichment analysis of DEGs was performed by DAVID. STRING and Cytoscape were applied to construct the protein-protein interaction (PPI) network and key modules of DEGs. Visualized plots were conducted by the R language. We downloaded clinical data from the TCGA database and the influence of key genes on the overall survival of ChRCC was performed by Kaplan–Meier and Cox analyses. Gene set enrichment analysis (GSEA) was utilized in exploring the function of key genes. A total of 79 DEGs were identified. Enrichment analyses revealed that the DEGs are closely related to tissue invasion and metastasis of cancer. Subsequently, 14 hub genes including ESRP1, AP1M2, CLDN4, and CLDN7 were detected. Kaplan–Meier analysis indicated that the low expression of CLDN7 and GNAS was related to the worse overall survival in patients with ChRCC. Univariate Cox analysis showed that CLDN7 might be a helpful biomarker for ChRCC prognosis. Subgroup analysis revealed that the expression of CLDN7 showed a downtrend with the development of the clinical stage, topography, and distant metastasis of ChRCC. GSEA analysis identified that cell adhesion molecules cams, B cell receptor signaling pathway, T cell receptor signaling pathway, RIG-I like receptor signaling pathway, Toll-like receptor signaling pathway, and apoptosis pathway were associated with the expression of CLDN7. In conclusion, ESRP1, AP1M2, CLDN4, PRSS8, and CLDN7 were found to distinguish ChRCC from RO. Besides, the low expression of CLDN7 was closely related to ChRCC progression and could serve as an independent risk factor for the overall survival in patients with ChRCC.
Highlights
Chromophobe renal cell carcinoma (ChRCC) was the third most common histologic subtype of renal cell carcinoma, accounting for about 5%–10% of the total cases of renal cell carcinoma [1]
Enrichment analysis was carried out using online DAVID and the results were visualized by R language
gene ontology (GO) analysis showed that changes in the biological process (BP) of 79 differentially expressed genes (DEGs) were significantly enriched in positive regulation of cytokine-mediated signaling pathway, auditory receptor cell development, and transport
Summary
Chromophobe renal cell carcinoma (ChRCC) was the third most common histologic subtype of renal cell carcinoma, accounting for about 5%–10% of the total cases of renal cell carcinoma [1]. Surgical intervention was the standard treatment for RO, while no standard therapy has been identified for advanced ChRCC. These two types of renal tumors shared histologic, immunohistochemical, and ultrastructural features, which added difficulties in accurately distinguishing the two entities [3]. Microarray technology showed an increasingly powerful function on genome-wide scanning and new key genes discovery in special diseases. To identify new DEGs as effective biomarkers for the diagnosis in ChRCC and RO, we merged multichip mRNA microarray datasets which were downloaded from Gene Expression Omnibus (GEO) and used e Cancer Genome Atlas (TCGA) data to analyze the prognostic value of key genes in ChRCC.
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