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Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins

Compiling a comprehensive list of cancer driver genes is imperative for oncology diagnostics and drug development. While driver genes are typically discovered by analysis of tumor genomes, infrequently mutated driver genes often evade detection due to limited sample sizes. Here, we address sample si...

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Autores principales: Waks, Zeev, Weissbrod, Omer, Carmeli, Boaz, Norel, Raquel, Utro, Filippo, Goldschmidt, Yaara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5180091/
https://www.ncbi.nlm.nih.gov/pubmed/28008934
http://dx.doi.org/10.1038/srep38988
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author Waks, Zeev
Weissbrod, Omer
Carmeli, Boaz
Norel, Raquel
Utro, Filippo
Goldschmidt, Yaara
author_facet Waks, Zeev
Weissbrod, Omer
Carmeli, Boaz
Norel, Raquel
Utro, Filippo
Goldschmidt, Yaara
author_sort Waks, Zeev
collection PubMed
description Compiling a comprehensive list of cancer driver genes is imperative for oncology diagnostics and drug development. While driver genes are typically discovered by analysis of tumor genomes, infrequently mutated driver genes often evade detection due to limited sample sizes. Here, we address sample size limitations by integrating tumor genomics data with a wide spectrum of gene-specific properties to search for rare drivers, functionally classify them, and detect features characteristic of driver genes. We show that our approach, CAnceR geNe similarity-based Annotator and Finder (CARNAF), enables detection of potentially novel drivers that eluded over a dozen pan-cancer/multi-tumor type studies. In particular, feature analysis reveals a highly concentrated pool of known and putative tumor suppressors among the <1% of genes that encode very large, chromatin-regulating proteins. Thus, our study highlights the need for deeper characterization of very large, epigenetic regulators in the context of cancer causality.
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spelling pubmed-51800912016-12-29 Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins Waks, Zeev Weissbrod, Omer Carmeli, Boaz Norel, Raquel Utro, Filippo Goldschmidt, Yaara Sci Rep Article Compiling a comprehensive list of cancer driver genes is imperative for oncology diagnostics and drug development. While driver genes are typically discovered by analysis of tumor genomes, infrequently mutated driver genes often evade detection due to limited sample sizes. Here, we address sample size limitations by integrating tumor genomics data with a wide spectrum of gene-specific properties to search for rare drivers, functionally classify them, and detect features characteristic of driver genes. We show that our approach, CAnceR geNe similarity-based Annotator and Finder (CARNAF), enables detection of potentially novel drivers that eluded over a dozen pan-cancer/multi-tumor type studies. In particular, feature analysis reveals a highly concentrated pool of known and putative tumor suppressors among the <1% of genes that encode very large, chromatin-regulating proteins. Thus, our study highlights the need for deeper characterization of very large, epigenetic regulators in the context of cancer causality. Nature Publishing Group 2016-12-23 /pmc/articles/PMC5180091/ /pubmed/28008934 http://dx.doi.org/10.1038/srep38988 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Waks, Zeev
Weissbrod, Omer
Carmeli, Boaz
Norel, Raquel
Utro, Filippo
Goldschmidt, Yaara
Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins
title Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins
title_full Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins
title_fullStr Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins
title_full_unstemmed Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins
title_short Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins
title_sort driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5180091/
https://www.ncbi.nlm.nih.gov/pubmed/28008934
http://dx.doi.org/10.1038/srep38988
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