Transcriptome Data Reveal Geographic Heterogeneity in Gene Expression in Patients with Prostate Cancer
BackgroundThe incidence of prostate cancer (PC) exhibits geographical heterogeneity. However, the metabolic mechanisms underlying this geographic heterogeneity remain unclear. This study aimed to reveal the metabolic mechanism of the geographic heterogeneity in the incidence of PC.This study aimed t...
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Veröffentlicht in: | Reports of biochemistry and molecular biology 2023-04, Vol.12 (1), p.92-101 |
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Sprache: | eng |
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Zusammenfassung: | BackgroundThe incidence of prostate cancer (PC) exhibits geographical heterogeneity. However, the metabolic mechanisms underlying this geographic heterogeneity remain unclear. This study aimed to reveal the metabolic mechanism of the geographic heterogeneity in the incidence of PC.This study aimed to investigate the anti-cancer effects of different gum extracts on metabolic changes and their impact on gene expression in HT-29 cell. MethodsTranscriptomic data from public databases were obtained and analyzed to screen geographic-differentially expressed genes and metabolic pathways. Associations between these differentially expressed genes and the incidence of PC were determined to identify genes that were highly associated with PC incidence. A co-expression network analysis was performed to identify geographic-specific regulatory pathways. ResultsA total of 175 differentially expressed genes were identified in four countries and were associated with the regulation of DNA replication and the metabolism of pyrimidine, nucleotides, purines, and galactose.Additionally, the expression of the genes CLVS2, SCGB1A1, KCNK3, HHIPL2, MMP26, KCNJ15, and PNMT was highly correlated with the incidence of PC. Geographic-specific differentially expressed genes in low-incidence areas were highly correlated with KCNJ15, MMP26, KCNK3, and SCCB1A1, which play a major role in ion channel-related functions. ConclusionsThis study suggests that geographic heterogeneity in PC incidence is associated with the expression levels of genes associated with amino acid metabolism, lipid metabolism, and ion channels. |
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ISSN: | 2322-3480 2322-3480 |
DOI: | 10.52547/rbmb.12.1.92 |