Bayesian Network Inference Modeling Identifies TRIB1 as a Novel Regulator of Cell-Cycle Progression and Survival in Cancer Cells

• Published in: Cancer research (Chicago, Ill.) Ill.), 2017-04, Vol.77 (7), p.1575-1585
• Main Authors: Gendelman, Rina, Xing, Heming, Mirzoeva, Olga K, Sarde, Preeti, Curtis, Christina, Feiler, Heidi S, McDonagh, Paul, Gray, Joe W, Khalil, Iya, Korn, W Michael
• Format: Article
• Language: English
• Subjects: Apoptosis; Bayes Theorem; Bayesian analysis; Breast cancer; Breast Neoplasms - drug therapy; Breast Neoplasms - genetics; Breast Neoplasms - pathology; Cancer; Cell culture; Cell Cycle; Cell Line, Tumor; Cell Survival; Computer applications; Computer simulation; Copy number; Cyclin D1; Cyclin D1 - genetics; Female; Gene expression; Humans; Inhibition; Interleukin 8; Interrogation; Intracellular Signaling Peptides and Proteins - genetics; Intracellular Signaling Peptides and Proteins - physiology; Mathematical models; Mitogen-Activated Protein Kinase Kinases - antagonists & inhibitors; Multidimensional data; NF-kappa B - physiology; NF-κB protein; Phosphatidylinositol 3-Kinases - physiology; Promoter Regions, Genetic; Protein-Serine-Threonine Kinases - antagonists & inhibitors; Protein-Serine-Threonine Kinases - genetics; Protein-Serine-Threonine Kinases - physiology; Proto-Oncogene Proteins c-akt - physiology; Signal transduction; Signal Transduction - physiology; Transcription factors
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/0008-5472.can-16-0512

Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G -S transition. The model identified known components of the cell-cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G -S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 of 12 predicted genes to have a role in G -S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NFκB and AP-1 sites and sensitized cells to TRAIL-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NFκB and its target genes ( ), and TRIB1 copy number and expression were predictive of clinical outcome. Together, our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFκB signaling. .