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Type: Journal article
Title: Computational reconstruction of NFκB pathway interaction mechanisms during prostate cancer
Other Titles: Computational reconstruction of NFkappaB pathway interaction mechanisms during prostate cancer
Author: Börnigen, D.
Tyekucheva, S.
Wang, X.
Rider, J.
Lee, G.
Mucci, L.
Sweeney, C.
Huttenhower, C.
Citation: PLoS Computational Biology, 2016; 12(4):e1004820-1-e1004820-30
Publisher: Public Library of Science
Issue Date: 2016
ISSN: 1553-734X
Statement of
Daniela Börnigen, Svitlana Tyekucheva, Xiaodong Wang, Jennifer R. Rider, Gwo-Shu Lee, Lorelei A. Mucci, Christopher Sweeney, Curtis Huttenhower
Abstract: Molecular research in cancer is one of the largest areas of bioinformatic investigation, but it remains a challenge to understand biomolecular mechanisms in cancer-related pathways from high-throughput genomic data. This includes the Nuclear-factor-kappa-B (NFκB) pathway, which is central to the inflammatory response and cell proliferation in prostate cancer development and progression. Despite close scrutiny and a deep understanding of many of its members' biomolecular activities, the current list of pathway members and a systems-level understanding of their interactions remains incomplete. Here, we provide the first steps toward computational reconstruction of interaction mechanisms of the NFκB pathway in prostate cancer. We identified novel roles for ATF3, CXCL2, DUSP5, JUNB, NEDD9, SELE, TRIB1, and ZFP36 in this pathway, in addition to new mechanistic interactions between these genes and 10 known NFκB pathway members. A newly predicted interaction between NEDD9 and ZFP36 in particular was validated by co-immunoprecipitation, as was NEDD9's potential biological role in prostate cancer cell growth regulation. We combined 651 gene expression datasets with 1.4M gene product interactions to predict the inclusion of 40 additional genes in the pathway. Molecular mechanisms of interaction among pathway members were inferred using recent advances in Bayesian data integration to simultaneously provide information specific to biological contexts and individual biomolecular activities, resulting in a total of 112 interactions in the fully reconstructed NFκB pathway: 13 (11%) previously known, 29 (26%) supported by existing literature, and 70 (63%) novel. This method is generalizable to other tissue types, cancers, and organisms, and this new information about the NFκB pathway will allow us to further understand prostate cancer and to develop more effective prevention and treatment strategies.
Keywords: Cell Line, Tumor; Humans; Prostatic Neoplasms; Adaptor Proteins, Signal Transducing; NF-kappa B; Phosphoproteins; Bayes Theorem; Gene Expression Profiling; Immunoprecipitation; Computational Biology; Signal Transduction; Cell Proliferation; Models, Biological; Databases, Genetic; Male; Tristetraprolin; Gene Regulatory Networks; Gene Knockdown Techniques; Gene Ontology
Description: Research article
Rights: © 2016 Börnigen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
RMID: 0030047842
DOI: 10.1371/journal.pcbi.1004820
Appears in Collections:Medicine publications

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