title: Computational Reconstruction of NFκB Pathway Interaction Mechanisms during Prostate Cancer.
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.
authors.affiliation: Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.|The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
authors.forename: Daniela
authors.initials: D
authors.lastname: Börnigen
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.
authors.forename: Svitlana
authors.initials: S
authors.lastname: Tyekucheva
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Xiaodong
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.
authors.forename: Jennifer R
authors.initials: JR
authors.lastname: Rider
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Gwo-Shu
authors.initials: GS
authors.lastname: Lee
authors.affiliation: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.
authors.forename: Lorelei A
authors.initials: LA
authors.lastname: Mucci
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Christopher
authors.initials: C
authors.lastname: Sweeney
authors.affiliation: Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.|The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
authors.forename: Curtis
authors.initials: C
authors.lastname: Huttenhower
mesh_terms: D048868:Adaptor Proteins, Signal Transducing / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism; D001499:Bayes Theorem; D045744:Cell Line, Tumor; D049109:Cell Proliferation; D019295:Computational Biology; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D055785:Gene Knockdown Techniques; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D006801:Humans; D047468:Immunoprecipitation; D008297:Male; D008954:Models, Biological; D016328:NF-kappa B / Q000378:metabolism*; D010750:Phosphoproteins / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism; D011471:Prostatic Neoplasms / Q000235:genetics / Q000378:metabolism* / Q000473:pathology; D015398:Signal Transduction; D051816:Tristetraprolin / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism
chemical_list: D048868:Adaptor Proteins, Signal Transducing; C099942:NEDD9 protein, human; D016328:NF-kappa B; D010750:Phosphoproteins; D051816:Tristetraprolin; C497552:ZFP36 protein, human