Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

Tumour expression profiling is currently used for prognostic and predictive purposes without taking into account the intra patient heterogeneity. Here the authors show that cancer cell specific signatures overcome the tumour heterogeneity effect and result in better classification of colorectal canc...

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Autores principales:	Philip D. Dunne, Matthew Alderdice, Paul G. O'Reilly, Aideen C. Roddy, Amy M. B. McCorry, Susan Richman, Tim Maughan, Simon S. McDade, Patrick G. Johnston, Daniel B. Longley, Elaine Kay, Darragh G. McArt, Mark Lawler
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/4cfe33bfecaf449b9233c78e1aecfd67
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spelling	oai:doaj.org-article:4cfe33bfecaf449b9233c78e1aecfd672021-12-02T14:42:28ZCancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification10.1038/ncomms156572041-1723https://doaj.org/article/4cfe33bfecaf449b9233c78e1aecfd672017-05-01T00:00:00Zhttps://doi.org/10.1038/ncomms15657https://doaj.org/toc/2041-1723Tumour expression profiling is currently used for prognostic and predictive purposes without taking into account the intra patient heterogeneity. Here the authors show that cancer cell specific signatures overcome the tumour heterogeneity effect and result in better classification of colorectal cancer patients.Philip D. DunneMatthew AlderdicePaul G. O'ReillyAideen C. RoddyAmy M. B. McCorrySusan RichmanTim MaughanSimon S. McDadePatrick G. JohnstonDaniel B. LongleyElaine KayDarragh G. McArtMark LawlerNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Philip D. Dunne Matthew Alderdice Paul G. O'Reilly Aideen C. Roddy Amy M. B. McCorry Susan Richman Tim Maughan Simon S. McDade Patrick G. Johnston Daniel B. Longley Elaine Kay Darragh G. McArt Mark Lawler Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification
description	Tumour expression profiling is currently used for prognostic and predictive purposes without taking into account the intra patient heterogeneity. Here the authors show that cancer cell specific signatures overcome the tumour heterogeneity effect and result in better classification of colorectal cancer patients.
format	article
author	Philip D. Dunne Matthew Alderdice Paul G. O'Reilly Aideen C. Roddy Amy M. B. McCorry Susan Richman Tim Maughan Simon S. McDade Patrick G. Johnston Daniel B. Longley Elaine Kay Darragh G. McArt Mark Lawler
author_facet	Philip D. Dunne Matthew Alderdice Paul G. O'Reilly Aideen C. Roddy Amy M. B. McCorry Susan Richman Tim Maughan Simon S. McDade Patrick G. Johnston Daniel B. Longley Elaine Kay Darragh G. McArt Mark Lawler
author_sort	Philip D. Dunne
title	Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification
title_short	Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification
title_full	Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification
title_fullStr	Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification
title_full_unstemmed	Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification
title_sort	cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/4cfe33bfecaf449b9233c78e1aecfd67
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Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

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