Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis

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 data...

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Main Authors: Hongwei Wu, Lijing Fan, Haiping Liu, Baozhang Guan, Bo Hu, Fanna Liu, Berthold Hocher, Lianghong Yin
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:BioMed Research International
Online Access:http://dx.doi.org/10.1155/2020/4030915
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spelling doaj-6bcea2a900bd45d1837d883babe88be32020-11-25T00:11:19ZengHindawi LimitedBioMed Research International2314-61332314-61412020-01-01202010.1155/2020/40309154030915Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic AnalysisHongwei Wu0Lijing Fan1Haiping Liu2Baozhang Guan3Bo Hu4Fanna Liu5Berthold Hocher6Lianghong Yin7Department of Nephrology, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou 510632, ChinaDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou 510632, ChinaDepartment of Nephrology, The Second People’s Hospital of Lianping County, Heyuan, ChinaDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou 510632, ChinaDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou 510632, ChinaDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou 510632, ChinaDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou 510632, ChinaDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou 510632, ChinaThe 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.http://dx.doi.org/10.1155/2020/4030915
collection DOAJ
language English
format Article
sources DOAJ
author Hongwei Wu
Lijing Fan
Haiping Liu
Baozhang Guan
Bo Hu
Fanna Liu
Berthold Hocher
Lianghong Yin
spellingShingle Hongwei Wu
Lijing Fan
Haiping Liu
Baozhang Guan
Bo Hu
Fanna Liu
Berthold Hocher
Lianghong Yin
Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis
BioMed Research International
author_facet Hongwei Wu
Lijing Fan
Haiping Liu
Baozhang Guan
Bo Hu
Fanna Liu
Berthold Hocher
Lianghong Yin
author_sort Hongwei Wu
title Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis
title_short Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis
title_full Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis
title_fullStr Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis
title_full_unstemmed Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis
title_sort identification of key genes and prognostic analysis between chromophobe renal cell carcinoma and renal oncocytoma by bioinformatic analysis
publisher Hindawi Limited
series BioMed Research International
issn 2314-6133
2314-6141
publishDate 2020-01-01
description 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.
url http://dx.doi.org/10.1155/2020/4030915
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