Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma

• Published in: Frontiers in oncology Vol. 12; p. 857619
• Main Authors: Qu, Genyi, Wang, Hao, Yan, Huiqin, Liu, Genlin, Wu, Min
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 28.02.2022
• Subjects: bioinformatics analysis; clear cell renal cell carcinoma (ccRCC); differentially expressed genes (DEGs); key gene; Oncology; survival analysis; differentially expressed genes (DEGs); survival analysis; clear cell renal cell carcinoma (ccRCC); bioinformatics analysis; key gene
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2022.857619

One of the widespread forms of kidney tumor is clear cell renal cell carcinoma (ccRCC), with poor prognosis and insensitivity to radio chemotherapy as there is limited capacity to understand the disease mechanism. This study aims at identifying potential biomarkers and the underlying processes of ccRCC using bioinformatics analysis. Transcriptome data of relevant samples were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to screen differentially expressed genes (DEGs) using the "edgeR" package. Two types of analysis-Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment-were accomplished by applying Database for Annotation, Visualization, and Integrated Discovery (DAVID) and Search Tool for the Retrieval of Interacting Genes database (STRING) online bioinformatics tools. A protein-protein interaction (PPI) network of the identified DEGs was constructed using Cytoscape software, and hub genes were subsequently selected the Cytohubba plug-in. The selected genes were input into Oncomine for verification. Finally, selected hub genes were analyzed by doing survival analysis to notice the relationship between survival (OS) rate and the selected genes' level of expression. There were 1,855 DEGs found connected to ccRCC, with 1,207 upregulated genes and 648 downregulated genes. G-protein-coupled receptor signaling pathway, integral component of membrane, calcium ion binding, and cytokine-cytokine receptor interaction were among the DEGs discovered. Oncomine confirmed the top six hub genes from the PPI network (C3, CXCR3, CXCL10, CCR5, CCL4, and CCL5). A high level of expression of CXCL10, one of these hub genes, was linked to a poor prognosis in individuals with ccRCC. The results of survival analysis showed that the expression level of CXCL10 was significantly correlated with the prognosis of ccRCC patients ( < 0.05). From the analysis, the following results were drawn: CXCL10 might be a potential prognostic biomarker and novel therapeutic target for ccRCC.