4.6 Article

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

Journal

FRONTIERS IN ONCOLOGY
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2022.857619

Keywords

clear cell renal cell carcinoma (ccRCC); bioinformatics analysis; differentially expressed genes (DEGs); key gene; survival analysis

Categories

Funding

  1. Hunan Natural Science Foundation [S2021JJQNJJ0018]

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The study identified 1,855 DEGs associated with ccRCC, including 1,207 upregulated genes and 648 downregulated genes. Functional and pathway enrichment analyses revealed key genes and pathways related to ccRCC. Oncomine confirmed the top six hub genes from the PPI network, with high expression of CXCL10 linked to poor prognosis in ccRCC patients.Survival analysis showed that CXCL10 expression level was significantly correlated with the prognosis of ccRCC patients.
BackgroundOne 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. MethodsTranscriptome 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 via 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. ResultsThere 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 (p < 0.05). ConclusionsFrom the analysis, the following results were drawn: CXCL10 might be a potential prognostic biomarker and novel therapeutic target for ccRCC.

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