High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes.

TitleHigh throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes.
Publication TypeJournal Article
Year of Publication2017
AuthorsHidalgo, MR, Cubuk, C, Amadoz, A, Salavert, F, Carbonell-Caballero, J, Dopazo, J
JournalOncotarget
Volume8
Issue3
Pagination5160-5178
Date Published2017 Jan 17
ISSN1949-2553
KeywordsComputational Biology; gene expression; Gene Regulatory Networks; Humans; mutation; Neoplasms; Precision Medicine; Sequence Analysis, RNA; Signal Transduction
Abstract

Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is a main challenge for precision medicine. Here we propose a new method that models cell signaling using biological knowledge on signal transduction. The method recodes individual gene expression values (and/or gene mutations) into accurate measurements of changes in the activity of signaling circuits, which ultimately constitute high-throughput estimations of cell functionalities caused by gene activity within the pathway. Moreover, such estimations can be obtained either at cohort-level, in case/control comparisons, or personalized for individual patients. The accuracy of the method is demonstrated in an extensive analysis involving 5640 patients from 12 different cancer types. Circuit activity measurements not only have a high diagnostic value but also can be related to relevant disease outcomes such as survival, and can be used to assess therapeutic interventions.

DOI10.18632/oncotarget.14107
Alternate JournalOncotarget
PubMed ID28042959
PubMed Central IDPMC5354899