Network-Based Identification of Novel Connections Among Apoptotic Signaling Pathways in Cancer

MicroRNAs (miRNAs), highly conserved, non-coding endogenous RNA and nearly ~22 nucleotides (nt) in length, are well-known to regulate several apoptotic pathways in cancer. In this study, we computationally constructed the initial human apoptotic PPI network by several online databases, and further integrated these high-throughput datasets into a Na?ve Bayesian model to predict protein functional connections. Based on the modified apoptotic network, we identified several apoptotic hub proteins such as TP53, SRC, M3K3/5/8, cyclin-dependent kinase2/6, TNFR16/19, and TGF-?? receptor 1/2. Subsequently, we identified some microRNAs that could target the aforementioned apoptotic hub proteins by using TargetScan, PicTar, and Diana-MicroH. In conclusion, these results demonstrate the PPI network-based identification of new connections amongst apoptotic pathways in cancer, which may shed new light on the intricate relationships between core apoptotic pathways and some targeted miRNAs in human cancers.