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Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification
Clinical manifestations and response to therapies in ulcerative colitis (UC) are heterogeneous, yet patient classification criteria for tailored therapies are currently lacking. Here, we present an unsupervised molecular classification of UC patients, concordant with response to therapy in independe...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598981/ https://www.ncbi.nlm.nih.gov/pubmed/31253778 http://dx.doi.org/10.1038/s41467-019-10769-x |
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author | Czarnewski, Paulo Parigi, Sara M. Sorini, Chiara Diaz, Oscar E. Das, Srustidhar Gagliani, Nicola Villablanca, Eduardo J. |
author_facet | Czarnewski, Paulo Parigi, Sara M. Sorini, Chiara Diaz, Oscar E. Das, Srustidhar Gagliani, Nicola Villablanca, Eduardo J. |
author_sort | Czarnewski, Paulo |
collection | PubMed |
description | Clinical manifestations and response to therapies in ulcerative colitis (UC) are heterogeneous, yet patient classification criteria for tailored therapies are currently lacking. Here, we present an unsupervised molecular classification of UC patients, concordant with response to therapy in independent retrospective cohorts. We show that classical clustering of UC patient tissue transcriptomic data sets does not identify clinically relevant profiles, likely due to associated covariates. To overcome this, we compare cross-sectional human data sets with a newly generated longitudinal transcriptome profile of murine DSS-induced colitis. We show that the majority of colitis risk-associated gene expression peaks during the inflammatory rather than the recovery phase. Moreover, we achieve UC patient clustering into two distinct transcriptomic profiles, differing in neutrophil-related gene activation. Notably, 87% of patients in UC1 cluster are unresponsive to two most widely used biological therapies. These results demonstrate that cross-species comparison enables stratification of patients undistinguishable by other molecular approaches. |
format | Online Article Text |
id | pubmed-6598981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65989812019-07-01 Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification Czarnewski, Paulo Parigi, Sara M. Sorini, Chiara Diaz, Oscar E. Das, Srustidhar Gagliani, Nicola Villablanca, Eduardo J. Nat Commun Article Clinical manifestations and response to therapies in ulcerative colitis (UC) are heterogeneous, yet patient classification criteria for tailored therapies are currently lacking. Here, we present an unsupervised molecular classification of UC patients, concordant with response to therapy in independent retrospective cohorts. We show that classical clustering of UC patient tissue transcriptomic data sets does not identify clinically relevant profiles, likely due to associated covariates. To overcome this, we compare cross-sectional human data sets with a newly generated longitudinal transcriptome profile of murine DSS-induced colitis. We show that the majority of colitis risk-associated gene expression peaks during the inflammatory rather than the recovery phase. Moreover, we achieve UC patient clustering into two distinct transcriptomic profiles, differing in neutrophil-related gene activation. Notably, 87% of patients in UC1 cluster are unresponsive to two most widely used biological therapies. These results demonstrate that cross-species comparison enables stratification of patients undistinguishable by other molecular approaches. Nature Publishing Group UK 2019-06-28 /pmc/articles/PMC6598981/ /pubmed/31253778 http://dx.doi.org/10.1038/s41467-019-10769-x Text en © The Author(s) 2019 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 Czarnewski, Paulo Parigi, Sara M. Sorini, Chiara Diaz, Oscar E. Das, Srustidhar Gagliani, Nicola Villablanca, Eduardo J. Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification |
title | Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification |
title_full | Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification |
title_fullStr | Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification |
title_full_unstemmed | Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification |
title_short | Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification |
title_sort | conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598981/ https://www.ncbi.nlm.nih.gov/pubmed/31253778 http://dx.doi.org/10.1038/s41467-019-10769-x |
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