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ProKinO: A Unified Resource for Mining the Cancer Kinome

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 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Human Mutation Wiley

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References (81)

Publisher
Wiley
Copyright
Copyright © 2015 Wiley Periodicals, Inc.
ISSN
1059-7794
eISSN
1098-1004
DOI
10.1002/humu.22726
pmid
25382819
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Human MutationWiley

Published: Feb 1, 2015

Keywords: personalized medicine; cancer therapy; database; drug discovery; big data; disease; mutation; resistance; kinase; conformation; regulation

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