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Identification of ATP6V0A4 as a potential biomarker in renal cell carcinoma using integrated bioinformatics analysis.

Oncology letters(2023)

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Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of renal cancer, and is associated with a high mortality rate, which is related to high rates of tumor recurrence and metastasis. The aim of the present study was to identify reliable molecular biomarkers with high specificity and sensitivity for ccRCC. A total of eight ccRCC-related expression profiles were downloaded from Gene Expression Omnibus for integrated bioinformatics analysis to screen for significantly differentially expressed genes (DEGs). Reverse transcription-quantitative (RT-q)PCR, western blotting and immunohistochemistry staining assays were performed to evaluate the expression levels of candidate biomarkers in ccRCC tissues and cell lines. In total, 255 ccRCC specimens and 165 adjacent normal kidney specimens were analyzed, and 344 significant DEGs, consisting of 115 upregulated DEGs and 229 downregulated DEGs, were identified. The results of Gene Ontology analysis suggested a significant enrichment of DEGs in 'organic anion transport' and 'small molecule catabolic process' in biological processes, in 'apical plasma membrane' and 'apical part of the cell' in cell components, and in 'anion transmembrane transporter activity' and 'active transmembrane transporter activity' in molecular functions. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that the DEGs were significantly enriched in the 'phagosome', the 'PPAR signaling pathway', 'complement and coagulation cascades', the 'HIF-1 signaling pathway' and 'carbon metabolism'. Next, 7 hub genes (SUCNR1, CXCR4, VCAN, CASR, ATP6V0A4, VEGFA and SERPINE1) were identified and validated using The Cancer Genome Atlas database. Survival analysis showed that low expression of ATP6V0A4 was associated with a poor prognosis in patients with ccRCC. Additionally, received operating characteristic curves indicated that ATP6V0A4 could distinguish ccRCC samples from normal kidney samples. Furthermore, RT-qPCR, western blotting and immunohistochemistry staining results showed that ATP6V0A4 was significantly downregulated in ccRCC tissues and cell lines. In conclusion, ATP6V0A4 may be involved in tumor progression and regarded as a potential therapeutic target for the recurrence and metastasis of ccRCC.
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Key words
ccRCC, bioinformatics analysis, biomarker, prognosis
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