Identification of CXCL13 as a potential biomarker in clear cell renal cell carcinoma via comprehensive bioinformatics analysis

Tianbo Xu; Hailong Ruan; Zhengshuai Song; Qi Cao; Keshan Wang; Lin Bao; Di Liu; Junwei Tong; Hongmei Yang; Ke Chen; Xiaoping Zhang

doi:10.1016/j.biopha.2019.109264

Identification of CXCL13 as a potential biomarker in clear cell renal cell carcinoma via comprehensive bioinformatics analysis

Biomed Pharmacother. 2019 Oct:118:109264. doi: 10.1016/j.biopha.2019.109264. Epub 2019 Aug 4.

Authors

Tianbo Xu¹, Hailong Ruan², Zhengshuai Song³, Qi Cao⁴, Keshan Wang⁵, Lin Bao⁶, Di Liu⁷, Junwei Tong⁸, Hongmei Yang⁹, Ke Chen¹⁰, Xiaoping Zhang¹¹

Affiliations

¹ Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].
² Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].
³ Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].
⁴ Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].
⁵ Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].
⁶ Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].
⁷ Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].
⁸ Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].
⁹ Department of Pathogenic Biology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan 430030, China. Electronic address: [email protected].
¹⁰ Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].
¹¹ Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China. Electronic address: [email protected].

PMID: 31390578
DOI: 10.1016/j.biopha.2019.109264

Abstract

Background: Clear cell renal cell carcinoma (ccRCC) is one of the most common malignancies in urinary system. However, there are still no reliable biomarkers for the diagnosis and prognosis of ccRCC. In this study, we aimed to screen candidate biomarkers and potential therapeutic targets for ccRCC.

Methods: Differentially expressed genes (DEGs) were screened using NetworkAnalyst. Protein-protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA) were utilized to identify hub genes. Then, we assessed the prognostic and diagnostic values of hub genes to screen candidate biomarkers. Gene Set Enrichment Analysis (GSEA) was applied to reveal potential mechanisms of candidate biomarkers in ccRCC. Oncomine database and The Human Protein Atlas were used to verify the expression of candidate biomarkers online. In addition, qRT-PCR, Enzyme linked immunosorbent assay (ELISA) and Immunohistochemistry (IHC) assays were performed to validate the expression level of candidate biomarkers in ccRCC cells and tissues.

Results: A total of 771 genes were identified as DEGs. GO function analysis showed that DEGs were mostly enriched in excretion, apical part of cell and monovalent inorganic cation transmembrane transporter activity. KEGG pathway analysis demonstrated that DEGs were mostly involved in Neuroactive ligand-receptor interaction. After utilizing PPI network and WGCNA, nine genes (IFNG, CXCR3, PMCH, CD2, FASLG, CXCL13, CD8A, CD3D and GZMA) were identified as the hub genes. Moreover, survival analysis exhibited that high expression of CXCL13 predicted poor survival in both overall survival (OS) and disease free survival (DFS). The ROC curves indicated that CXCL13 could distinguish ccRCC samples from normal kidney samples. High expression of CXCL13 group was mostly associated with RB and MEL18 pathways by GSEA. Furthermore, qRT-PCR, ELISA and IHC results showed that the expression of CXCL13 was elevated in ccRCC.

Conclusions: Our study illustrated that CXCL13 had good diagnostic and prognostic value, which may become a candidate biomarker and therapeutic target for ccRCC.

Keywords: Biomarker; CXCL13; Clear cell renal cell carcinoma; Weighted gene co-expression network analysis.

MeSH terms

Biomarkers, Tumor / metabolism*
Carcinoma, Renal Cell / genetics
Carcinoma, Renal Cell / metabolism*
Cell Line, Tumor
Chemokine CXCL13 / metabolism*
Computational Biology*
Gene Expression Regulation, Neoplastic
Gene Ontology
Gene Regulatory Networks
Humans
Kaplan-Meier Estimate
Kidney Neoplasms / genetics
Kidney Neoplasms / metabolism*
Neoplasm Grading
Neoplasm Staging
Protein Interaction Maps / genetics
RNA, Messenger / genetics
RNA, Messenger / metabolism
ROC Curve
Reproducibility of Results

Substances

Biomarkers, Tumor
CXCL13 protein, human
Chemokine CXCL13
RNA, Messenger