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

Marta R. Hidalgo, Cankut Cubuk, View ORCID ProfileAlicia Amadoz, Francisco Salavert, View ORCID ProfileJosé Carbonell-Caballero, View ORCID ProfileJoaquin Dopazo
doi: https://doi.org/10.1101/076083
Marta R. Hidalgo
1Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
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Cankut Cubuk
1Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
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Alicia Amadoz
1Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
2Functional Genomics Node (INB), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
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  • ORCID record for Alicia Amadoz
Francisco Salavert
1Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
3Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
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José Carbonell-Caballero
1Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
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  • ORCID record for José Carbonell-Caballero
Joaquin Dopazo
1Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
2Functional Genomics Node (INB), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
3Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), C/ Eduardo Primo Yufera 3, Valencia, 46012, Spain
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  • ORCID record for Joaquin Dopazo
  • For correspondence: jdopazo@cipf.es
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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.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted September 19, 2016.
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High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes
Marta R. Hidalgo, Cankut Cubuk, Alicia Amadoz, Francisco Salavert, José Carbonell-Caballero, Joaquin Dopazo
bioRxiv 076083; doi: https://doi.org/10.1101/076083
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High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes
Marta R. Hidalgo, Cankut Cubuk, Alicia Amadoz, Francisco Salavert, José Carbonell-Caballero, Joaquin Dopazo
bioRxiv 076083; doi: https://doi.org/10.1101/076083

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