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Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling
BACKGROUND: Thrombospondin-1 (TSP1) is a matricellular protein that functions to inhibit angiogenesis. An important pathway that contributes to this inhibitory effect is triggered by TSP1 binding to the CD36 receptor, inducing endothelial cell apoptosis. However, therapies that mimic this function h...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5735807/ https://www.ncbi.nlm.nih.gov/pubmed/29258506 http://dx.doi.org/10.1186/s12964-017-0207-9 |
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author | Wu, Qianhui Finley, Stacey D. |
author_facet | Wu, Qianhui Finley, Stacey D. |
author_sort | Wu, Qianhui |
collection | PubMed |
description | BACKGROUND: Thrombospondin-1 (TSP1) is a matricellular protein that functions to inhibit angiogenesis. An important pathway that contributes to this inhibitory effect is triggered by TSP1 binding to the CD36 receptor, inducing endothelial cell apoptosis. However, therapies that mimic this function have not demonstrated clear clinical efficacy. This study explores strategies to enhance TSP1-induced apoptosis in endothelial cells. In particular, we focus on establishing a computational model to describe the signaling pathway, and using this model to investigate the effects of several approaches to perturb the TSP1-CD36 signaling network. METHODS: We constructed a molecularly-detailed mathematical model of TSP1-mediated intracellular signaling via the CD36 receptor based on literature evidence. We employed systems biology tools to train and validate the model and further expanded the model by accounting for the heterogeneity within the cell population. The initial concentrations of signaling species or kinetic rates were altered to simulate the effects of perturbations to the signaling network. RESULTS: Model simulations predict the population-based response to strategies to enhance TSP1-mediated apoptosis, such as downregulating the apoptosis inhibitor XIAP and inhibiting phosphatase activity. The model also postulates a new mechanism of low dosage doxorubicin treatment in combination with TSP1 stimulation. Using computational analysis, we predict which cells will undergo apoptosis, based on the initial intracellular concentrations of particular signaling species. CONCLUSIONS: This new mathematical model recapitulates the intracellular dynamics of the TSP1-induced apoptosis signaling pathway. Overall, the modeling framework predicts molecular strategies that increase TSP1-mediated apoptosis, which is useful in many disease settings. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi: 10.1186/s12964-017-0207-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5735807 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57358072017-12-21 Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling Wu, Qianhui Finley, Stacey D. Cell Commun Signal Research BACKGROUND: Thrombospondin-1 (TSP1) is a matricellular protein that functions to inhibit angiogenesis. An important pathway that contributes to this inhibitory effect is triggered by TSP1 binding to the CD36 receptor, inducing endothelial cell apoptosis. However, therapies that mimic this function have not demonstrated clear clinical efficacy. This study explores strategies to enhance TSP1-induced apoptosis in endothelial cells. In particular, we focus on establishing a computational model to describe the signaling pathway, and using this model to investigate the effects of several approaches to perturb the TSP1-CD36 signaling network. METHODS: We constructed a molecularly-detailed mathematical model of TSP1-mediated intracellular signaling via the CD36 receptor based on literature evidence. We employed systems biology tools to train and validate the model and further expanded the model by accounting for the heterogeneity within the cell population. The initial concentrations of signaling species or kinetic rates were altered to simulate the effects of perturbations to the signaling network. RESULTS: Model simulations predict the population-based response to strategies to enhance TSP1-mediated apoptosis, such as downregulating the apoptosis inhibitor XIAP and inhibiting phosphatase activity. The model also postulates a new mechanism of low dosage doxorubicin treatment in combination with TSP1 stimulation. Using computational analysis, we predict which cells will undergo apoptosis, based on the initial intracellular concentrations of particular signaling species. CONCLUSIONS: This new mathematical model recapitulates the intracellular dynamics of the TSP1-induced apoptosis signaling pathway. Overall, the modeling framework predicts molecular strategies that increase TSP1-mediated apoptosis, which is useful in many disease settings. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi: 10.1186/s12964-017-0207-9) contains supplementary material, which is available to authorized users. BioMed Central 2017-12-19 /pmc/articles/PMC5735807/ /pubmed/29258506 http://dx.doi.org/10.1186/s12964-017-0207-9 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Wu, Qianhui Finley, Stacey D. Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling |
title | Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling |
title_full | Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling |
title_fullStr | Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling |
title_full_unstemmed | Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling |
title_short | Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling |
title_sort | predictive model identifies strategies to enhance tsp1-mediated apoptosis signaling |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5735807/ https://www.ncbi.nlm.nih.gov/pubmed/29258506 http://dx.doi.org/10.1186/s12964-017-0207-9 |
work_keys_str_mv | AT wuqianhui predictivemodelidentifiesstrategiestoenhancetsp1mediatedapoptosissignaling AT finleystaceyd predictivemodelidentifiesstrategiestoenhancetsp1mediatedapoptosissignaling |