The differential expression and direct targeting of mRNA by miRNA are two main logics of the traditional approach to constructing the miRNA-mRNA network. This approach, could be led to the loss of considerable information and some challenges of direct targeting. To avoid these problems, we analyzed the rewiring network and constructed two miRNA-mRNA expression bipartite networks for both normal and primary prostate cancer tissue obtained from PRAD-TCGA. We then calculated beta-coefficient of the regression-model when miR was dependent and mRNA independent for each miR and mRNA and separately in both networks. We defined the rewired edges as a significant change in the regression coefficient between normal and cancer states. The rewired nodes through multinomial distribution were defined and network from rewired edges and nodes was analyzed and enriched. Of the 306 rewired edges, 112(37%) were new, 123(40%) were lost, 44(14%) were strengthened, and 27(9%) weakened connections were discovered. The highest centrality of 106 rewired mRNAs belonged to PGM5, BOD1L1, C1S, SEPG, TMEFF2, and CSNK2A1. The highest centrality of 68 rewired miRs belonged to miR-181d, miR-4677, miR-4662a, miR-9.3, and miR-1301. SMAD and beta-catenin binding were enriched as molecular functions. The regulation was a frequently repeated concept in the biological process. Our rewiring analysis highlighted the impact of β-catenin and SMAD signaling as also some transcript factors like TGFB1I1 in prostate cancer progression. Altogether, we developed a miRNA-mRNA co-expression bipartite network to identify the hidden aspects of the prostate cancer mechanism, which traditional analysis -like differential expression- was not detect it.
Keywords: Prostate cancer; Wilks’ theorem; co-expression; extracellular matrix; multinomial distribution; regression; systems biology.