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Insights regarding novel biomarkers and the pathogenesis of primary colorectal carcinoma based on bioinformatic analysis

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BACKGROUND Biomarkers are important in the study of tumor processes for early detection and precise treatment. The biomarkers that have been previously detected are not useful for clinical application for… Click to show full abstract

BACKGROUND Biomarkers are important in the study of tumor processes for early detection and precise treatment. The biomarkers that have been previously detected are not useful for clinical application for primary colorectal carcinoma (PCRC). The aim of this study was to explore clinically valuable biomarkers of PCRC based on integrated bioinformatic analysis. MATERIAL AND METHODS Gene expression data were acquired from the GSE41258 dataset, and the differentially expressed genes were determined between PCRC and normal colorectal samples. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were implemented via Gene Set Enrichment Analysis. A protein-protein interaction (PPI) network was constructed. The significant modules and hub genes were screened and identified in the PPI network. RESULTS A total of 202 DEGs were identified, including 58 upregulated and 144 downregulated genes in PCRC samples compared to those in normal colorectal samples. Enrichment analysis demonstrated that the gene sets enriched in PCRC were significantly related to bicarbonate transport, regulation of sodium ion transport, potassium ion homeostasis, regulation of telomere maintenance, and other processes. A total of 10 hub genes was identified by cytoHubba: PYY, CXCL3, CXCL11, CXCL8, CXCL12, CCL20, MMP3, P2RY14, NPY1R, and CXCL1. CONCLUSION The hub genes, such as NPY1R, P2RY14, and CXCL12, and the electrolyte disequilibrium resulting from the differential expression of genes, especially bicarbonate imbalance, may provide novel insights and evidence for the future diagnosis and targeted therapy of PCRC.

Keywords: analysis; colorectal carcinoma; primary colorectal; gene; bioinformatic analysis

Journal Title: Computational biology and chemistry
Year Published: 2020

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