MicroRNA and Transcription Factor Gene Regulatory Network Analysis Reveals Key Regulatory Elements Associated with Prostate Cancer Progression

Abstract

Technological and methodological advances in multi-omics data generation and integration approaches help elucidate genetic features of complex biological traits and diseases such as prostate cancer. Due to its heterogeneity, the identification of key functional components involved in the regulation and progression of prostate cancer is a methodological challenge. In this study, we identified key regulatory interactions responsible for primary to metastasis transitions in prostate cancer using network inference approaches by integrating patient derived transcriptomic and miRomics data into gene/miRNA/transcription factor regulatory networks. One such network was derived for each of the clinical states of prostate cancer based on differentially expressed and significantly correlated gene, miRNA and TF pairs from the patient data. We identified key elements of each network using a network analysis approach and validated our results using patient survival analysis. We observed that HOXD10, BCL2 and PGR are the most important factors affected in primary prostate samples, whereas, in the metastatic state, STAT3, JUN and JUNB are playing a central role. Benefiting integrative networks our analysis suggests that some of these molecules were targeted by several overexpressed miRNAs which may have a major effect on the dysregulation of these molecules. For example, in the metastatic tumors five miRNAs (miR-671-5p, miR-665, miR-663, miR-512-3p and miR-371-5p) are mainly responsible for the dysregulation of STAT3 and hence can provide an opportunity for early detection of metastasis and development of alternative therapeutic approaches. Our findings deliver new details on key functional components in prostate cancer progression and provide opportunities for the development of alternative therapeutic approaches.

Salivary extracellular vesicle-associated miRNAs as potential biomarkers in oral squamous cell carcinoma

“…No evidence has been reported confirming the involvement of miR-412-3p, miR-512-3p, miR-302b-3p, and miR-517b-3p in OSCC, thus our work provides new insights about the dysregulation of miRNAs in the tumor environment. It is worth mentioning that miR-512-3p has been reported to be up-regulated in metastatic prostate cancer [ 55 ], and conversely shown anti-tumor activity in non-small cell lung cancer [ 56 ] and hepatocellular carcinoma [ 57 ].…”

Integrative Analysis of Breast Cancer Cells Reveals an Epithelial-Mesenchymal Transition Role in Adaptation to Acidic Microenvironment

“…Centrality analysis ranks the nodes (genes in gene regulatory networks) based on their significance. In centrality analysis, adding topological parameters to biological data leads to sufficiently informative results that have been shown to be effective in exploring key signature molecules in biological processes (42). Such biological network analysis has been used in cancer biomarker discovery (43).…”

HAHmiR.DB: A Server Platform For High Altitude Human miRNA-Gene Coregulatory Networks And Associated Regulatory-Circuits

“…These recurring patterns are very common in Gene Regulatory Networks (GRNs) and are known as network motifs. Important regulatory molecules such as miRNA and TFs often follows these recurring pattern in co-regulatory networks to control the complex molecular and cellular responses of living cells (48). FFLs are most overrepresented motifs that are found in the coregulatory networks (49).…”