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Novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer
Distant metastasis is the major cause of death in colorectal cancer (CRC). Patients at high risk of developing distant metastasis could benefit from appropriate adjuvant and follow-up treatments if stratified accurately at an early stage of the disease. Studies have increasingly recognized the role...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6135776/ https://www.ncbi.nlm.nih.gov/pubmed/30209315 http://dx.doi.org/10.1038/s41598-018-31799-3 |
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author | Sirinukunwattana, Korsuk Snead, David Epstein, David Aftab, Zia Mujeeb, Imaad Tsang, Yee Wah Cree, Ian Rajpoot, Nasir |
author_facet | Sirinukunwattana, Korsuk Snead, David Epstein, David Aftab, Zia Mujeeb, Imaad Tsang, Yee Wah Cree, Ian Rajpoot, Nasir |
author_sort | Sirinukunwattana, Korsuk |
collection | PubMed |
description | Distant metastasis is the major cause of death in colorectal cancer (CRC). Patients at high risk of developing distant metastasis could benefit from appropriate adjuvant and follow-up treatments if stratified accurately at an early stage of the disease. Studies have increasingly recognized the role of diverse cellular components within the tumor microenvironment in the development and progression of CRC tumors. In this paper, we show that automated analysis of digitized images from locally advanced colorectal cancer tissue slides can provide estimate of risk of distant metastasis on the basis of novel tissue phenotypic signatures of the tumor microenvironment. Specifically, we determine what cell types are found in the vicinity of other cell types, and in what numbers, rather than concentrating exclusively on the cancerous cells. We then extract novel tissue phenotypic signatures using statistical measurements about tissue composition. Such signatures can underpin clinical decisions about the advisability of various types of adjuvant therapy. |
format | Online Article Text |
id | pubmed-6135776 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61357762018-09-15 Novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer Sirinukunwattana, Korsuk Snead, David Epstein, David Aftab, Zia Mujeeb, Imaad Tsang, Yee Wah Cree, Ian Rajpoot, Nasir Sci Rep Article Distant metastasis is the major cause of death in colorectal cancer (CRC). Patients at high risk of developing distant metastasis could benefit from appropriate adjuvant and follow-up treatments if stratified accurately at an early stage of the disease. Studies have increasingly recognized the role of diverse cellular components within the tumor microenvironment in the development and progression of CRC tumors. In this paper, we show that automated analysis of digitized images from locally advanced colorectal cancer tissue slides can provide estimate of risk of distant metastasis on the basis of novel tissue phenotypic signatures of the tumor microenvironment. Specifically, we determine what cell types are found in the vicinity of other cell types, and in what numbers, rather than concentrating exclusively on the cancerous cells. We then extract novel tissue phenotypic signatures using statistical measurements about tissue composition. Such signatures can underpin clinical decisions about the advisability of various types of adjuvant therapy. Nature Publishing Group UK 2018-09-12 /pmc/articles/PMC6135776/ /pubmed/30209315 http://dx.doi.org/10.1038/s41598-018-31799-3 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Sirinukunwattana, Korsuk Snead, David Epstein, David Aftab, Zia Mujeeb, Imaad Tsang, Yee Wah Cree, Ian Rajpoot, Nasir Novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer |
title | Novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer |
title_full | Novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer |
title_fullStr | Novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer |
title_full_unstemmed | Novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer |
title_short | Novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer |
title_sort | novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6135776/ https://www.ncbi.nlm.nih.gov/pubmed/30209315 http://dx.doi.org/10.1038/s41598-018-31799-3 |
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