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Modeling the effects of EMT-immune dynamics on carcinoma disease progression

During progression from carcinoma in situ to an invasive tumor, the immune system is engaged in complex sets of interactions with various tumor cells. Tumor cell plasticity alters disease trajectories via epithelial-to-mesenchymal transition (EMT). Several of the same pathways that regulate EMT are...

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Autores principales: Bergman, Daniel R., Karikomi, Matthew K., Yu, Min, Nie, Qing, MacLean, Adam L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373868/
https://www.ncbi.nlm.nih.gov/pubmed/34408236
http://dx.doi.org/10.1038/s42003-021-02499-y
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author Bergman, Daniel R.
Karikomi, Matthew K.
Yu, Min
Nie, Qing
MacLean, Adam L.
author_facet Bergman, Daniel R.
Karikomi, Matthew K.
Yu, Min
Nie, Qing
MacLean, Adam L.
author_sort Bergman, Daniel R.
collection PubMed
description During progression from carcinoma in situ to an invasive tumor, the immune system is engaged in complex sets of interactions with various tumor cells. Tumor cell plasticity alters disease trajectories via epithelial-to-mesenchymal transition (EMT). Several of the same pathways that regulate EMT are involved in tumor-immune interactions, yet little is known about the mechanisms and consequences of crosstalk between these regulatory processes. Here we introduce a multiscale evolutionary model to describe tumor-immune-EMT interactions and their impact on epithelial cancer progression from in situ to invasive disease. Through simulation of patient cohorts in silico, the model predicts that a controllable region maximizes invasion-free survival. This controllable region depends on properties of the mesenchymal tumor cell phenotype: its growth rate and its immune-evasiveness. In light of the model predictions, we analyze EMT-inflammation-associated data from The Cancer Genome Atlas, and find that association with EMT worsens invasion-free survival probabilities. This result supports the predictions of the model, and leads to the identification of genes that influence outcomes in bladder and uterine cancer, including FGF pathway members. These results suggest new means to delay disease progression, and demonstrate the importance of studying cancer-immune interactions in light of EMT.
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spelling pubmed-83738682021-09-02 Modeling the effects of EMT-immune dynamics on carcinoma disease progression Bergman, Daniel R. Karikomi, Matthew K. Yu, Min Nie, Qing MacLean, Adam L. Commun Biol Article During progression from carcinoma in situ to an invasive tumor, the immune system is engaged in complex sets of interactions with various tumor cells. Tumor cell plasticity alters disease trajectories via epithelial-to-mesenchymal transition (EMT). Several of the same pathways that regulate EMT are involved in tumor-immune interactions, yet little is known about the mechanisms and consequences of crosstalk between these regulatory processes. Here we introduce a multiscale evolutionary model to describe tumor-immune-EMT interactions and their impact on epithelial cancer progression from in situ to invasive disease. Through simulation of patient cohorts in silico, the model predicts that a controllable region maximizes invasion-free survival. This controllable region depends on properties of the mesenchymal tumor cell phenotype: its growth rate and its immune-evasiveness. In light of the model predictions, we analyze EMT-inflammation-associated data from The Cancer Genome Atlas, and find that association with EMT worsens invasion-free survival probabilities. This result supports the predictions of the model, and leads to the identification of genes that influence outcomes in bladder and uterine cancer, including FGF pathway members. These results suggest new means to delay disease progression, and demonstrate the importance of studying cancer-immune interactions in light of EMT. Nature Publishing Group UK 2021-08-18 /pmc/articles/PMC8373868/ /pubmed/34408236 http://dx.doi.org/10.1038/s42003-021-02499-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Bergman, Daniel R.
Karikomi, Matthew K.
Yu, Min
Nie, Qing
MacLean, Adam L.
Modeling the effects of EMT-immune dynamics on carcinoma disease progression
title Modeling the effects of EMT-immune dynamics on carcinoma disease progression
title_full Modeling the effects of EMT-immune dynamics on carcinoma disease progression
title_fullStr Modeling the effects of EMT-immune dynamics on carcinoma disease progression
title_full_unstemmed Modeling the effects of EMT-immune dynamics on carcinoma disease progression
title_short Modeling the effects of EMT-immune dynamics on carcinoma disease progression
title_sort modeling the effects of emt-immune dynamics on carcinoma disease progression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373868/
https://www.ncbi.nlm.nih.gov/pubmed/34408236
http://dx.doi.org/10.1038/s42003-021-02499-y
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