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A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks

Functional interpretation of genomic variation is critical to understanding human disease but it remains difficult to predict the effects of specific mutations on protein interaction networks and the phenotypes they regulate. We describe an analytical framework based on multiscale statistical mechan...

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Autores principales: AlQuraishi, Mohammed, Koytiger, Grigoriy, Jenney, Anne, MacBeath, Gavin, Sorger, Peter K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4244270/
https://www.ncbi.nlm.nih.gov/pubmed/25362484
http://dx.doi.org/10.1038/ng.3138
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author AlQuraishi, Mohammed
Koytiger, Grigoriy
Jenney, Anne
MacBeath, Gavin
Sorger, Peter K.
author_facet AlQuraishi, Mohammed
Koytiger, Grigoriy
Jenney, Anne
MacBeath, Gavin
Sorger, Peter K.
author_sort AlQuraishi, Mohammed
collection PubMed
description Functional interpretation of genomic variation is critical to understanding human disease but it remains difficult to predict the effects of specific mutations on protein interaction networks and the phenotypes they regulate. We describe an analytical framework based on multiscale statistical mechanics that integrates genomic and biophysical data to model the human SH2-phosphoprotein network in normal and cancer cells. We apply our approach to data in The Cancer Genome Atlas (TCGA) and test model predictions experimentally. We find that mutations in phosphoproteins often create new interactions but that mutations in SH2 domains result almost exclusively in loss of interactions. Some of these mutations eliminate all interactions but many cause more selective loss, thereby rewiring specific edges in highly connected subnetworks. Moreover, idiosyncratic mutations appear to be as functionally consequential as recurrent mutations. By synthesizing genomic, structural, and biochemical data our framework represents a new approach to the interpretation of genetic variation.
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spelling pubmed-42442702015-06-01 A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks AlQuraishi, Mohammed Koytiger, Grigoriy Jenney, Anne MacBeath, Gavin Sorger, Peter K. Nat Genet Article Functional interpretation of genomic variation is critical to understanding human disease but it remains difficult to predict the effects of specific mutations on protein interaction networks and the phenotypes they regulate. We describe an analytical framework based on multiscale statistical mechanics that integrates genomic and biophysical data to model the human SH2-phosphoprotein network in normal and cancer cells. We apply our approach to data in The Cancer Genome Atlas (TCGA) and test model predictions experimentally. We find that mutations in phosphoproteins often create new interactions but that mutations in SH2 domains result almost exclusively in loss of interactions. Some of these mutations eliminate all interactions but many cause more selective loss, thereby rewiring specific edges in highly connected subnetworks. Moreover, idiosyncratic mutations appear to be as functionally consequential as recurrent mutations. By synthesizing genomic, structural, and biochemical data our framework represents a new approach to the interpretation of genetic variation. 2014-11-02 2014-12 /pmc/articles/PMC4244270/ /pubmed/25362484 http://dx.doi.org/10.1038/ng.3138 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
AlQuraishi, Mohammed
Koytiger, Grigoriy
Jenney, Anne
MacBeath, Gavin
Sorger, Peter K.
A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks
title A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks
title_full A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks
title_fullStr A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks
title_full_unstemmed A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks
title_short A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks
title_sort multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4244270/
https://www.ncbi.nlm.nih.gov/pubmed/25362484
http://dx.doi.org/10.1038/ng.3138
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