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Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells

Triple negative breast cancer (TNBC) is an aggressive form of breast cancer which accounts for 15–20% of this disease and is currently treated with genotoxic chemotherapy. The BCL2 (B-cell lymphoma 2) family of proteins controls the process of mitochondrial outer membrane permeabilization (MOMP), wh...

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Autores principales: Lucantoni, Federico, Lindner, Andreas U., O’Donovan, Norma, Düssmann, Heiko, Prehn, Jochen H. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5833806/
https://www.ncbi.nlm.nih.gov/pubmed/29352235
http://dx.doi.org/10.1038/s41419-017-0039-y
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author Lucantoni, Federico
Lindner, Andreas U.
O’Donovan, Norma
Düssmann, Heiko
Prehn, Jochen H. M.
author_facet Lucantoni, Federico
Lindner, Andreas U.
O’Donovan, Norma
Düssmann, Heiko
Prehn, Jochen H. M.
author_sort Lucantoni, Federico
collection PubMed
description Triple negative breast cancer (TNBC) is an aggressive form of breast cancer which accounts for 15–20% of this disease and is currently treated with genotoxic chemotherapy. The BCL2 (B-cell lymphoma 2) family of proteins controls the process of mitochondrial outer membrane permeabilization (MOMP), which is required for the activation of the mitochondrial apoptosis pathway in response to genotoxic agents. We previously developed a deterministic systems model of BCL2 protein interactions, DR_MOMP that calculates the sensitivity of cells to undergo mitochondrial apoptosis. Here we determined whether DR_MOMP predicts responses of TNBC cells to genotoxic agents and the re-sensitization of resistant cells by BCL2 inhibitors. Using absolute protein levels of BAX, BAK, BCL2, BCL(X)L and MCL1 as input for DR_MOMP, we found a strong correlation between model predictions and responses of a panel of TNBC cells to 24 and 48 h cisplatin (R(2) = 0.96 and 0.95, respectively) and paclitaxel treatments (R(2) = 0.94 and 0.95, respectively). This outperformed single protein correlations (best performer BCL(X)L with R(2) of 0.69 and 0.50 for cisplatin and paclitaxel treatments, respectively) and BCL2 proteins ratio (R(2) of 0.50 for cisplatin and 0.49 for paclitaxel). Next we performed synergy studies using the BCL2 selective antagonist Venetoclax /ABT199, the BCL(X)L selective antagonist WEHI-539, or the MCL1 selective antagonist A-1210477 in combination with cisplatin. In silico predictions by DR_MOMP revealed substantial differences in treatment responses of BCL(X)L, BCL2 or MCL1 inhibitors combinations with cisplatin that were successfully validated in cell lines. Our findings provide evidence that DR_MOMP predicts responses of TNBC cells to genotoxic therapy, and can aid in the choice of the optimal BCL2 protein antagonist for combination treatments of resistant cells.
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spelling pubmed-58338062018-03-06 Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells Lucantoni, Federico Lindner, Andreas U. O’Donovan, Norma Düssmann, Heiko Prehn, Jochen H. M. Cell Death Dis Article Triple negative breast cancer (TNBC) is an aggressive form of breast cancer which accounts for 15–20% of this disease and is currently treated with genotoxic chemotherapy. The BCL2 (B-cell lymphoma 2) family of proteins controls the process of mitochondrial outer membrane permeabilization (MOMP), which is required for the activation of the mitochondrial apoptosis pathway in response to genotoxic agents. We previously developed a deterministic systems model of BCL2 protein interactions, DR_MOMP that calculates the sensitivity of cells to undergo mitochondrial apoptosis. Here we determined whether DR_MOMP predicts responses of TNBC cells to genotoxic agents and the re-sensitization of resistant cells by BCL2 inhibitors. Using absolute protein levels of BAX, BAK, BCL2, BCL(X)L and MCL1 as input for DR_MOMP, we found a strong correlation between model predictions and responses of a panel of TNBC cells to 24 and 48 h cisplatin (R(2) = 0.96 and 0.95, respectively) and paclitaxel treatments (R(2) = 0.94 and 0.95, respectively). This outperformed single protein correlations (best performer BCL(X)L with R(2) of 0.69 and 0.50 for cisplatin and paclitaxel treatments, respectively) and BCL2 proteins ratio (R(2) of 0.50 for cisplatin and 0.49 for paclitaxel). Next we performed synergy studies using the BCL2 selective antagonist Venetoclax /ABT199, the BCL(X)L selective antagonist WEHI-539, or the MCL1 selective antagonist A-1210477 in combination with cisplatin. In silico predictions by DR_MOMP revealed substantial differences in treatment responses of BCL(X)L, BCL2 or MCL1 inhibitors combinations with cisplatin that were successfully validated in cell lines. Our findings provide evidence that DR_MOMP predicts responses of TNBC cells to genotoxic therapy, and can aid in the choice of the optimal BCL2 protein antagonist for combination treatments of resistant cells. Nature Publishing Group UK 2018-01-19 /pmc/articles/PMC5833806/ /pubmed/29352235 http://dx.doi.org/10.1038/s41419-017-0039-y 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
Lucantoni, Federico
Lindner, Andreas U.
O’Donovan, Norma
Düssmann, Heiko
Prehn, Jochen H. M.
Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells
title Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells
title_full Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells
title_fullStr Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells
title_full_unstemmed Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells
title_short Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells
title_sort systems modeling accurately predicts responses to genotoxic agents and their synergism with bcl-2 inhibitors in triple negative breast cancer cells
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5833806/
https://www.ncbi.nlm.nih.gov/pubmed/29352235
http://dx.doi.org/10.1038/s41419-017-0039-y
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