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ProKinO: A Unified Resource for Mining the Cancer Kinome

Protein kinases represent a large and diverse family of evolutionarily related proteins that are abnormally regulated in human cancers. Although genome sequencing studies have revealed thousands of variants in protein kinases, translating “big” genomic data into biological knowledge remains a challe...

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Autores principales: McSkimming, Daniel Ian, Dastgheib, Shima, Talevich, Eric, Narayanan, Anish, Katiyar, Samiksha, Taylor, Susan S, Kochut, Krys, Kannan, Natarajan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4342772/
https://www.ncbi.nlm.nih.gov/pubmed/25382819
http://dx.doi.org/10.1002/humu.22726
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author McSkimming, Daniel Ian
Dastgheib, Shima
Talevich, Eric
Narayanan, Anish
Katiyar, Samiksha
Taylor, Susan S
Kochut, Krys
Kannan, Natarajan
author_facet McSkimming, Daniel Ian
Dastgheib, Shima
Talevich, Eric
Narayanan, Anish
Katiyar, Samiksha
Taylor, Susan S
Kochut, Krys
Kannan, Natarajan
author_sort McSkimming, Daniel Ian
collection PubMed
description Protein kinases represent a large and diverse family of evolutionarily related proteins that are abnormally regulated in human cancers. Although genome sequencing studies have revealed thousands of variants in protein kinases, translating “big” genomic data into biological knowledge remains a challenge. Here, we describe an ontological framework for integrating and conceptualizing diverse forms of information related to kinase activation and regulatory mechanisms in a machine readable, human understandable form. We demonstrate the utility of this framework in analyzing the cancer kinome, and in generating testable hypotheses for experimental studies. Through the iterative process of aggregate ontology querying, hypothesis generation and experimental validation, we identify a novel mutational hotspot in the αC-β4 loop of the kinase domain and demonstrate the functional impact of the identified variants in epidermal growth factor receptor (EGFR) constitutive activity and inhibitor sensitivity. We provide a unified resource for the kinase and cancer community, ProKinO, housed at http://vulcan.cs.uga.edu/prokino.
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spelling pubmed-43427722015-03-04 ProKinO: A Unified Resource for Mining the Cancer Kinome McSkimming, Daniel Ian Dastgheib, Shima Talevich, Eric Narayanan, Anish Katiyar, Samiksha Taylor, Susan S Kochut, Krys Kannan, Natarajan Hum Mutat Informatics Protein kinases represent a large and diverse family of evolutionarily related proteins that are abnormally regulated in human cancers. Although genome sequencing studies have revealed thousands of variants in protein kinases, translating “big” genomic data into biological knowledge remains a challenge. Here, we describe an ontological framework for integrating and conceptualizing diverse forms of information related to kinase activation and regulatory mechanisms in a machine readable, human understandable form. We demonstrate the utility of this framework in analyzing the cancer kinome, and in generating testable hypotheses for experimental studies. Through the iterative process of aggregate ontology querying, hypothesis generation and experimental validation, we identify a novel mutational hotspot in the αC-β4 loop of the kinase domain and demonstrate the functional impact of the identified variants in epidermal growth factor receptor (EGFR) constitutive activity and inhibitor sensitivity. We provide a unified resource for the kinase and cancer community, ProKinO, housed at http://vulcan.cs.uga.edu/prokino. Blackwell Publishing Ltd 2015-02 2014-11-10 /pmc/articles/PMC4342772/ /pubmed/25382819 http://dx.doi.org/10.1002/humu.22726 Text en © 2014 The Authors. **Human Mutation published by Wiley Periodicals, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Informatics
McSkimming, Daniel Ian
Dastgheib, Shima
Talevich, Eric
Narayanan, Anish
Katiyar, Samiksha
Taylor, Susan S
Kochut, Krys
Kannan, Natarajan
ProKinO: A Unified Resource for Mining the Cancer Kinome
title ProKinO: A Unified Resource for Mining the Cancer Kinome
title_full ProKinO: A Unified Resource for Mining the Cancer Kinome
title_fullStr ProKinO: A Unified Resource for Mining the Cancer Kinome
title_full_unstemmed ProKinO: A Unified Resource for Mining the Cancer Kinome
title_short ProKinO: A Unified Resource for Mining the Cancer Kinome
title_sort prokino: a unified resource for mining the cancer kinome
topic Informatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4342772/
https://www.ncbi.nlm.nih.gov/pubmed/25382819
http://dx.doi.org/10.1002/humu.22726
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