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Deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence

Predicting colorectal cancer recurrence after tumor resection is crucial because it promotes the administration of proper subsequent treatment or management to improve the clinical outcomes of patients. Several clinical or molecular factors, including tumor stage, metastasis, and microsatellite inst...

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Autores principales: Kim, Donghyo, Kim, Jinho, Lee, Juhun, Han, Seong Kyu, Lee, Kwanghwan, Kong, JungHo, Kim, Yeon Jeong, Lee, Woo Yong, Yun, Seong Hyeon, Kim, Hee Cheol, Hong, Hye Kyung, Cho, Yong Beom, Park, Donghyun, Kim, Sanguk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9636036/
https://www.ncbi.nlm.nih.gov/pubmed/36345336
http://dx.doi.org/10.1016/j.isci.2022.105392
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author Kim, Donghyo
Kim, Jinho
Lee, Juhun
Han, Seong Kyu
Lee, Kwanghwan
Kong, JungHo
Kim, Yeon Jeong
Lee, Woo Yong
Yun, Seong Hyeon
Kim, Hee Cheol
Hong, Hye Kyung
Cho, Yong Beom
Park, Donghyun
Kim, Sanguk
author_facet Kim, Donghyo
Kim, Jinho
Lee, Juhun
Han, Seong Kyu
Lee, Kwanghwan
Kong, JungHo
Kim, Yeon Jeong
Lee, Woo Yong
Yun, Seong Hyeon
Kim, Hee Cheol
Hong, Hye Kyung
Cho, Yong Beom
Park, Donghyun
Kim, Sanguk
author_sort Kim, Donghyo
collection PubMed
description Predicting colorectal cancer recurrence after tumor resection is crucial because it promotes the administration of proper subsequent treatment or management to improve the clinical outcomes of patients. Several clinical or molecular factors, including tumor stage, metastasis, and microsatellite instability status, have been used to assess the risk of recurrence, although their predictive ability is limited. Here, we predicted colorectal cancer recurrence based on cellular deconvolution of bulk tumors into two distinct immune cell states: cancer-associated (tumor-infiltrating immune cell-like) and noncancer-associated (peripheral blood mononuclear cell-like). Prediction model performed significantly better when immune cells were deconvoluted into two states rather than a single state, suggesting that the difference in cancer recurrence was better explained by distinct states of immune cells. It indicates the importance of distinguishing immune cell states using cellular deconvolution to improve the prediction of colorectal cancer recurrence.
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spelling pubmed-96360362022-11-06 Deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence Kim, Donghyo Kim, Jinho Lee, Juhun Han, Seong Kyu Lee, Kwanghwan Kong, JungHo Kim, Yeon Jeong Lee, Woo Yong Yun, Seong Hyeon Kim, Hee Cheol Hong, Hye Kyung Cho, Yong Beom Park, Donghyun Kim, Sanguk iScience Article Predicting colorectal cancer recurrence after tumor resection is crucial because it promotes the administration of proper subsequent treatment or management to improve the clinical outcomes of patients. Several clinical or molecular factors, including tumor stage, metastasis, and microsatellite instability status, have been used to assess the risk of recurrence, although their predictive ability is limited. Here, we predicted colorectal cancer recurrence based on cellular deconvolution of bulk tumors into two distinct immune cell states: cancer-associated (tumor-infiltrating immune cell-like) and noncancer-associated (peripheral blood mononuclear cell-like). Prediction model performed significantly better when immune cells were deconvoluted into two states rather than a single state, suggesting that the difference in cancer recurrence was better explained by distinct states of immune cells. It indicates the importance of distinguishing immune cell states using cellular deconvolution to improve the prediction of colorectal cancer recurrence. Elsevier 2022-10-17 /pmc/articles/PMC9636036/ /pubmed/36345336 http://dx.doi.org/10.1016/j.isci.2022.105392 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Donghyo
Kim, Jinho
Lee, Juhun
Han, Seong Kyu
Lee, Kwanghwan
Kong, JungHo
Kim, Yeon Jeong
Lee, Woo Yong
Yun, Seong Hyeon
Kim, Hee Cheol
Hong, Hye Kyung
Cho, Yong Beom
Park, Donghyun
Kim, Sanguk
Deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence
title Deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence
title_full Deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence
title_fullStr Deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence
title_full_unstemmed Deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence
title_short Deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence
title_sort deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9636036/
https://www.ncbi.nlm.nih.gov/pubmed/36345336
http://dx.doi.org/10.1016/j.isci.2022.105392
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