Analysis of competing endogenous RNA network to identify the key RNAs associated with prostate adenocarcinoma.

Objectives: Prostate adenocarcinoma (PRAD) is the most common cancer in men. The aim of this study was to reveal the critical long non-coding RNA (lncRNAs), microRNA (miRNAs) and mRNAs involved in the pathogenesis of PRAD.

Methods: The level 3 mRNA and miRNA sequencing data of PRAD were downloaded from The Cancer Genome Atlas database. Using the edgeR package of R, the differentially expressed mRNAs (DEGs), lncRNAs (DE-lncRNAs) and miRNAs (DE-miRNAs) between PRAD and normal tissues were screened. The Cox proportional hazards regression method in the survival package was used to select the lncRNAs significantly related to clinical characteristics. After the miRNA-lncRNA and miRNA-mRNA pairs were predicted, a regulatory network was constructed by the Cytoscape software. For the DEGs involved in the network, enrichment analysis was conducted by the Fisher algorithm.

Results: Compared to the normal samples, 25 DE-lncRNAs, 1421 DEGs and 68 DE-miRNAs were identified in the PRAD samples. The down-regulated MESTIT1 had a significantly negative correlation with overall survival. A total of 44 DE-miRNA-DE-lncRNA pairs were predicted, including the PCA3-miR-96 and UCA1-miR-96. Meanwhile, 33 DEGs targeted by miRNAs (for example, miR-96-CYP19A1) were found to correlate with cancers.

Conclusion: Functional enrichment analysis showed that the reproductive development process (which involved TDRD1) was enriched for the DEGs implicated in the lncRNA-miRNA-mRNA regulatory network. The lncRNAs MESTIT1, PCA3, and UCA1; mRNAs CYP19A1 and TDRD1; as well as miR-96 might affect the pathogenesis of PRAD.