CANCER DRIVER SUBNETWORK IDENTIFICATION BY NETWORK DISMANTLING METHODS

2021-9
Kasapoğlu, Fatma Ülkem
Tissue-specific protein protein interaction networks(TSPPI) are important for studying tissue-based cellular processes and protein functions. As the functions of tissues are various, the proteins they contain and the functions of these proteins also different than each other. Thus, these networks may help clinical studies both in tissue-specific cancer prediction by identification of the important groups in TSPPI. In this study, we aim to detect driver subnetworks in various TSPPIs and to understand effectiveness of the driver subnetworks. We performed iterative centrality attacks, Generalized Network Dismantling(GND), GND with Reinsertion(GNDR) on breast, liver, lymph node, ovary, and peripheral nerve TSPPIs from TissueNet v2 database. After the comparison by using driver gene information of each TSPPI from the Cancer Genome Interpreter and cBioPortal databases, we applied Personalized PageRank to each resulting TSPPI subnetworks to get more compact and robust subnetworks. Finally, we performed enrichment analysis for the proposed driver subnetworks. We found that genes in final subnetworks were enriched in both common and tissue-based cancer related pathways. As a result, we found that there was not optimal attack strategy for all TSPPIs. However, it is possible to obtain promising results for the cancer research by the comparison of these strategies.

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Citation Formats
F. Ü. Kasapoğlu, “CANCER DRIVER SUBNETWORK IDENTIFICATION BY NETWORK DISMANTLING METHODS,” M.S. - Master of Science, Middle East Technical University, 2021.