Identification of aberrantly methylated‑differentially expressed genes and gene ontology in prostate cancer
- Linbang Wang
- Bing Wang
- Zhengxue Quan
Affiliations: Department of Orthopedic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P.R. China, Laboratory of Environmental Monitoring, Shaanxi Province Health Inspection Institution, Xi'an, Shaanxi 710077, P.R. China
- Published online on: December 11, 2019 https://doi.org/10.3892/mmr.2019.10876
Copyright: © Wang
et al. This is an open access article distributed under the
terms of Creative
Commons Attribution License.
Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )
This article is mentioned in:
Prostate cancer (PCa) is the most frequent urological malignancy in men worldwide. DNA methylation has an essential role in the etiology and pathogenesis of PCa. The purpose of the present study was to identify the aberrantly methylated‑differentially expressed genes and to determine their potential roles in PCa. The important node genes identified were screened by integrated analysis. Gene expression microarrays and gene methylation microarrays were downloaded and aberrantly methylated‑differentially expressed genes were obtained. Enrichment analysis and protein‑protein interactions (PPI) were obtained, their interactive and visual networks were created, and the node genes in the PPI network were validated. A total of 105 hypomethylation‑high expression genes and 561 hypermethylation‑low expression genes along with their biological processes were identified. The top 10 node genes obtained from the PPI network were identified for each of the two gene groups. The methylation and gene expression status of node genes in TCGA database, GEPIA tool, and the HPA database were generally consistent with those of our results. In conclusion, the present study identified 20 aberrantly methylated‑differentially expressed genes in PCa by combining bioinformatics analyses of gene expression and gene methylation microarrays, and concurrently, the survival of these genes was analyzed. Notably, methylation is a reversible biological process, which makes it of great biological significance for the diagnosis and treatment of prostate cancer using bioinformatics technology to determine abnormal methylation gene markers. The present study provided novel therapeutic targets for the treatment of PCa.