Construction of miRNA-mRNA network and a nomogram model of prognostic analysis for prostate cancer

Abstract

Background: Dysregulated genetic factors correlate with carcinoma progression. However, the hub miRNAs-mRNAs related to biochemical recurrence in prostate cancer remain unclear. We aim to identify potential miRNA-mRNA regulatory network and hub genes in prostate cancer.Methods: Datasets of gene expression microarray were downloaded from Gene Expression Omnibus (GEO) database for Robust Rank Aggregation (RRA), targeted gene prediction, gene function and signal pathway enrichment analyses, miRNA-mRNA regulatory network construction, core network screening, as well as validation and survival analysis were carried out by using exogenous data.Results: Prostate cancer-related differentially expressed genes were mostly related to actin filament regulation. Moreover, the cGMP-PKG signaling pathway might play a role in prostate cancer progression.As the core of microRNAs, hsa-miR-106b-5p, hsa-miR-17-5p and hsa-miR-183-5p were matched to hub genes (such as TMEM100, FRMD6, NBL1 and STARD4). The expression levels of hub genes in prostate cancer tissues were significantly lower than normal and closely related to prognosis of patients. The ridge regression model was applied to establish a risk score system. Both risk score and Gleason were used to establish a nomogram. Nomogram predicted the area under the [receiver operating characteristic (ROC)] curve (AUC) of biochemical recurrence at 1-, 3-, and 5-year of 0.713, 0.732 and 0.753, respectively.Conclusions: Hub genes were closely related to prostate cancer development and progression, which might become biomarkers for diagnosis and prognosis. This novel nomogram established could be applied to clinical prediction.

A panel based on three-miRNAs as diagnostic biomarker for prostate cancer

“…In another study, researchers constructed a miRNA-mRNA regulatory network containing miR-106b-5p to identify genes such as TMEM100, FRMD6, NBL1, and STARD4 for the diagnosis and prognosis of prostate cancer patients. They concluded that signaling pathways such as cGMP-PKG, PI3K-Akt, and cAMP are involved in regulating prostate cancer progression ( Su et al, 2022 ). Among the five single miRNAs studied, miR-106b-5p demonstrated the best diagnostic ability, exhibiting excellent sensitivity and specificity (90.48% and 63.10%, respectively).…”