Integrated analysis of mRNA-single nucleotide polymorphism-microRNA interaction network to identify biomarkers associated with prostate cancer

Abstract

Background: Prostate cancer is one of the most common malignancies among men worldwide currently. However, specific mechanisms of prostate cancer were still not fully understood due to lack of integrated molecular analyses. We performed this study to establish an mRNA-single nucleotide polymorphism (SNP)-microRNA (miRNA) interaction network by comprehensive bioinformatics analysis, and search for novel biomarkers for prostate cancer.Materials and methods: mRNA, miRNA, and SNP data were acquired from Gene Expression Omnibus (GEO) database. Differential expression analysis was performed to identify differentially expressed genes (DEGs) and miRNAs (DEMs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, protein-protein interaction (PPI) analysis and expression quantitative trait loci (eQTL) analysis of DEGs were conducted. SNPs related to DEMs (miRSNPs) were downloaded from the open-source website MirSNP and PolymiRTS 3.0. TargetScan and miRDB databases were used for the target mRNA prediction of miRNA. The mRNA-SNP-miRNA interaction network was then constructed and visualized by Cytoscape 3.9.0. Selected key biomarkers were further validated using the Cancer Genome Atlas (TCGA) database. A nomogram model was constructed to predict the risk of prostate cancer.Results: In our study, 266 DEGs and 11 DEMs were identified. KEGG pathway analysis showed that DEGs were strikingly enriched in focal adhesion and PI3K-Akt signaling pathway. A total of 60 mRNA-SNP-miRNAs trios were identified to establish the mRNA-SNP-miRNA interaction network. Seven mRNAs in mRNA-SNP-miRNA network were consistent with the predicted target mRNAs of miRNA. These results were largely validated by the TCGA database analysis. A nomogram was constructed that contained four variables (ITGB8, hsa-miR-21, hsa-miR-30b and prostate-specific antigen (PSA) value) for predicting the risk of prostate cancer.Conclusion: Our study established the mRNA-SNP-miRNA interaction network in prostate cancer. The interaction network showed that hsa-miR-21, hsa-miR-30b, and ITGB8 may be utilized as new biomarkers for prostate cancer.

Deletion in a regulatory region is associated with underexpression of miR-148b‑3p in patients with prostate cancer

“…miRNAs are small non-coding RNAs and are part of the epigenetic machinery that can regulate the expression of genes; therefore, increasingly altered mechanisms are identified due to the malfunction of these miRNAs, for example, it has been observed that several miRNAs dysregulated in PCa, are related to the regulatory T cell marker FOXP3, suggesting a relationship between immune cells, miRNAs and PCa (16). Therefore, the identification of dysregulated miRNAs could have implications both in understanding the pathology and in identifying possible targets for the detection, prognosis and treatment of various cancers (17,18). The dysregulation of the expression of a miRNA can be due to mutations in its coding genes or in their regulatory regions; for example, SNPs in miR-146a and in miR-100 have been identified that act as a factor of bad and an improved prognosis in PCa.…”

Impact of Mir196a-2 Genotypes on Colorectal Cancer Risk in Taiwan

“…Genetic variations have been identified in both miRNA genes and their target genes, and these variations have been associated with a wide range of human diseases. Meanwhile, there is mounting evidence supporting the idea that dysregulated miRNAs play critical roles in tumorigenesis [18,19]. In CRC, several miRNAs have been identified to modulate cell proliferation, migration, apoptosis, and response to radiation in both CRC cells and patient samples.…”