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Identification of Pharmacologically Tractable Protein Complexes in Cancer Using the R-Based Network Clustering and Visualization Program MCODER

Authors
 Sungjin Kwon  ;  Hyosil Kim  ;  Hyun Seok Kim 
Citation
 BIOMED RESEARCH INTERNATIONAL, Vol.2017 : 1016305, 2017 
Journal Title
BIOMED RESEARCH INTERNATIONAL
ISSN
 2314-6133 
Issue Date
2017
MeSH
Antineoplastic Agents/pharmacology* ; Cluster Analysis ; Humans ; Multiprotein Complexes/metabolism* ; Neoplasm Proteins/metabolism* ; Neoplasms/metabolism* ; Software* ; Time Factors
Abstract
Current multiomics assay platforms facilitate systematic identification of functional entities that are mappable in a biological network, and computational methods that are better able to detect densely connected clusters of signals within a biological network are considered increasingly important. One of the most famous algorithms for detecting network subclusters is Molecular Complex Detection (MCODE). MCODE, however, is limited in simultaneous analyses of multiple, large-scale data sets, since it runs on the Cytoscape platform, which requires extensive computational resources and has limited coding flexibility. In the present study, we implemented the MCODE algorithm in R programming language and developed a related package, which we called MCODER. We found the MCODER package to be particularly useful in analyzing multiple omics data sets simultaneously within the R framework. Thus, we applied MCODER to detect pharmacologically tractable protein-protein interactions selectively elevated in molecular subtypes of ovarian and colorectal tumors. In doing so, we found that a single molecular subtype representing epithelial-mesenchymal transition in both cancer types exhibited enhanced production of the collagen-integrin protein complex. These results suggest that tumors of this molecular subtype could be susceptible to pharmacological inhibition of integrin signaling.
Files in This Item:
T201701730.pdf Download
DOI
10.1155/2017/1016305
Appears in Collections:
1. College of Medicine (의과대학) > BioMedical Science Institute (의생명과학부) > 1. Journal Papers
Yonsei Authors
Kim, Hyun Seok(김현석) ORCID logo https://orcid.org/0000-0003-4498-8690
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/160227
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