Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks

Spatial information in the tumour microenvironment may be exploited to optimise diagnosis, prognosis and therapy. Here, the authors develop a spatial analytics computational and systems pathology platform (SpAn) based on highly multiplexed antibody imaging on colorectal cancer samples to infer emerg...

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Autores principales:	Shikhar Uttam, Andrew M. Stern, Christopher J. Sevinsky, Samantha Furman, Filippo Pullara, Daniel Spagnolo, Luong Nguyen, Albert Gough, Fiona Ginty, D. Lansing Taylor, S. Chakra Chennubhotla
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/a43bb54843794cb1bbe267661f6d6f4c
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spelling	oai:doaj.org-article:a43bb54843794cb1bbe267661f6d6f4c2021-12-02T18:31:30ZSpatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks10.1038/s41467-020-17083-x2041-1723https://doaj.org/article/a43bb54843794cb1bbe267661f6d6f4c2020-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-17083-xhttps://doaj.org/toc/2041-1723Spatial information in the tumour microenvironment may be exploited to optimise diagnosis, prognosis and therapy. Here, the authors develop a spatial analytics computational and systems pathology platform (SpAn) based on highly multiplexed antibody imaging on colorectal cancer samples to infer emergent network biology and predict 5-year risk of recurrence.Shikhar UttamAndrew M. SternChristopher J. SevinskySamantha FurmanFilippo PullaraDaniel SpagnoloLuong NguyenAlbert GoughFiona GintyD. Lansing TaylorS. Chakra ChennubhotlaNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-14 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Shikhar Uttam Andrew M. Stern Christopher J. Sevinsky Samantha Furman Filippo Pullara Daniel Spagnolo Luong Nguyen Albert Gough Fiona Ginty D. Lansing Taylor S. Chakra Chennubhotla Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks
description	Spatial information in the tumour microenvironment may be exploited to optimise diagnosis, prognosis and therapy. Here, the authors develop a spatial analytics computational and systems pathology platform (SpAn) based on highly multiplexed antibody imaging on colorectal cancer samples to infer emergent network biology and predict 5-year risk of recurrence.
format	article
author	Shikhar Uttam Andrew M. Stern Christopher J. Sevinsky Samantha Furman Filippo Pullara Daniel Spagnolo Luong Nguyen Albert Gough Fiona Ginty D. Lansing Taylor S. Chakra Chennubhotla
author_facet	Shikhar Uttam Andrew M. Stern Christopher J. Sevinsky Samantha Furman Filippo Pullara Daniel Spagnolo Luong Nguyen Albert Gough Fiona Ginty D. Lansing Taylor S. Chakra Chennubhotla
author_sort	Shikhar Uttam
title	Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks
title_short	Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks
title_full	Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks
title_fullStr	Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks
title_full_unstemmed	Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks
title_sort	spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/a43bb54843794cb1bbe267661f6d6f4c
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Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks

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