title: Robust clinical outcome prediction based on Bayesian analysis of transcriptional profiles and prior causal networks.
abstract: BACKGROUND
  Understanding and predicting an individual's response in a clinical trial is the key to better treatments and cost-: effective medicine. Over the coming years, more and more large-scale omics datasets will become available to characterize patients with complex and heterogeneous diseases at a molecular level. Unfortunately, genetic, phenotypical and environmental variation is much higher in a human trial population than currently modeled or measured in most animal studies. In our experience, this high variability can lead to failure of trained predictors in independent studies and undermines the credibility and utility of promising high-dimensional datasets.
  
  
  METHODS
  We propose a method that utilizes patient-level genome-wide expression data in conjunction with causal networks based on prior knowledge. Our approach determines a differential expression profile for each patient and uses a Bayesian approach to infer corresponding upstream regulators. These regulators and their corresponding posterior probabilities of activity are used in a regularized regression framework to predict response.
  
  
  RESULTS
  We validated our approach using two clinically relevant phenotypes, namely acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. To demonstrate pitfalls in translating trained predictors across independent trials, we analyze performance characteristics of our approach as well as alternative feature sets in the regression on two independent datasets for each phenotype. We show that the proposed approach is able to successfully incorporate causal prior knowledge to give robust performance estimates.
authors.affiliation: Computational Sciences Center of Emphasis, Pfizer Worldwide R&D, Cambridge, Department of Mathematics, University of Massachusetts Boston, Boston, MA, Drug Safety Research & Development, Pfizer Worldwide R&D, Groton, CT, USA and Computational Sciences Center of Emphasis, Pfizer Worldwide R&D, Berlin, GermanyComputational Sciences Center of Emphasis, Pfizer Worldwide R&D, Cambridge, Department of Mathematics, University of Massachusetts Boston, Boston, MA, Drug Safety Research & Development, Pfizer Worldwide R&D, Groton, CT, USA and Computational Sciences Center of Emphasis, Pfizer Worldwide R&D, Berlin, Germany.
authors.forename: Kourosh
authors.initials: K
authors.lastname: Zarringhalam
authors.affiliation: Computational Sciences Center of Emphasis, Pfizer Worldwide R&D, Cambridge, Department of Mathematics, University of Massachusetts Boston, Boston, MA, Drug Safety Research & Development, Pfizer Worldwide R&D, Groton, CT, USA and Computational Sciences Center of Emphasis, Pfizer Worldwide R&D, Berlin, Germany.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Enayetallah
authors.affiliation: Computational Sciences Center of Emphasis, Pfizer Worldwide R&D, Cambridge, Department of Mathematics, University of Massachusetts Boston, Boston, MA, Drug Safety Research & Development, Pfizer Worldwide R&D, Groton, CT, USA and Computational Sciences Center of Emphasis, Pfizer Worldwide R&D, Berlin, Germany.
authors.forename: Padmalatha
authors.initials: P
authors.lastname: Reddy
authors.affiliation: Computational Sciences Center of Emphasis, Pfizer Worldwide R&D, Cambridge, Department of Mathematics, University of Massachusetts Boston, Boston, MA, Drug Safety Research & Development, Pfizer Worldwide R&D, Groton, CT, USA and Computational Sciences Center of Emphasis, Pfizer Worldwide R&D, Berlin, Germany.
authors.forename: Daniel
authors.initials: D
authors.lastname: Ziemek
mesh_terms: D000465:Algorithms; D000911:Antibodies, Monoclonal / Q000627:therapeutic use; D001499:Bayes Theorem; D003093:Colitis, Ulcerative / Q000188:drug therapy / Q000235:genetics; D020869:Gene Expression Profiling / Q000379:methods*; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D006084:Graft Rejection / Q000235:genetics; D006801:Humans; D000069285:Infliximab; D016030:Kidney Transplantation; D010641:Phenotype; D012044:Regression Analysis; D016896:Treatment Outcome
chemical_list: D000911:Antibodies, Monoclonal; D000069285:Infliximab