Activation of executioner caspases is a predictor of progression-free survival in glioblastoma patients: a systems medicine approach

Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults. GBM cells are highly resistant to apoptosis induced by antitumor drugs and radiotherapy resulting in cancer progression. We assessed whether a systems medicine approach, analysing the ability of tumor cells to execut...

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Main Authors: Murphy, Á C, Weyhenmeyer, B, Schmid, J, Kilbride, S M, Rehm, M, Huber, H J, Senft, C, Weissenberger, J, Seifert, V, Dunst, M, Mittelbronn, M, Kögel, D, Prehn, J H M, Murphy, B M
Format: Online
Language:English
Published: Nature Publishing Group 2013
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3674364/
id pubmed-3674364
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spelling pubmed-36743642013-06-06 Activation of executioner caspases is a predictor of progression-free survival in glioblastoma patients: a systems medicine approach Murphy, Á C Weyhenmeyer, B Schmid, J Kilbride, S M Rehm, M Huber, H J Senft, C Weissenberger, J Seifert, V Dunst, M Mittelbronn, M Kögel, D Prehn, J H M Murphy, B M Original Article Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults. GBM cells are highly resistant to apoptosis induced by antitumor drugs and radiotherapy resulting in cancer progression. We assessed whether a systems medicine approach, analysing the ability of tumor cells to execute apoptosis could be utilized to predict the response of GBM patients to treatment. Concentrations of the key proapoptotic proteins procaspase-3, procaspase-9, Smac and Apaf-1 and the antiapopotic protein XIAP were determined in a panel of GBM cell lines and GBM patient tumor resections. These values were used as input for APOPTO-CELL, a systems biological based mathematical model built to predict cellular susceptibility to undergo caspase activation. The modeling was capable of accurately distinguishing between GBM cells that die or survive in response to treatment with temozolomide in 10 of the 11 lines analysed. Importantly the results obtained using GBM patient samples show that APOPTO-CELL was capable of stratifying patients according to their progression-free survival times and predicted the ability of tumor cells to support caspase activation in 16 of the 21 GBM patients analysed. Calculating the susceptibility to apoptosis execution may be a potent tool in predicting GBM patient therapy responsiveness and may allow for the use of APOPTO-CELL in a clinical setting. Nature Publishing Group 2013-05 2013-05-16 /pmc/articles/PMC3674364/ /pubmed/23681224 http://dx.doi.org/10.1038/cddis.2013.157 Text en Copyright © 2013 Macmillan Publishers Limited http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Murphy, Á C
Weyhenmeyer, B
Schmid, J
Kilbride, S M
Rehm, M
Huber, H J
Senft, C
Weissenberger, J
Seifert, V
Dunst, M
Mittelbronn, M
Kögel, D
Prehn, J H M
Murphy, B M
spellingShingle Murphy, Á C
Weyhenmeyer, B
Schmid, J
Kilbride, S M
Rehm, M
Huber, H J
Senft, C
Weissenberger, J
Seifert, V
Dunst, M
Mittelbronn, M
Kögel, D
Prehn, J H M
Murphy, B M
Activation of executioner caspases is a predictor of progression-free survival in glioblastoma patients: a systems medicine approach
author_facet Murphy, Á C
Weyhenmeyer, B
Schmid, J
Kilbride, S M
Rehm, M
Huber, H J
Senft, C
Weissenberger, J
Seifert, V
Dunst, M
Mittelbronn, M
Kögel, D
Prehn, J H M
Murphy, B M
author_sort Murphy, Á C
title Activation of executioner caspases is a predictor of progression-free survival in glioblastoma patients: a systems medicine approach
title_short Activation of executioner caspases is a predictor of progression-free survival in glioblastoma patients: a systems medicine approach
title_full Activation of executioner caspases is a predictor of progression-free survival in glioblastoma patients: a systems medicine approach
title_fullStr Activation of executioner caspases is a predictor of progression-free survival in glioblastoma patients: a systems medicine approach
title_full_unstemmed Activation of executioner caspases is a predictor of progression-free survival in glioblastoma patients: a systems medicine approach
title_sort activation of executioner caspases is a predictor of progression-free survival in glioblastoma patients: a systems medicine approach
description Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults. GBM cells are highly resistant to apoptosis induced by antitumor drugs and radiotherapy resulting in cancer progression. We assessed whether a systems medicine approach, analysing the ability of tumor cells to execute apoptosis could be utilized to predict the response of GBM patients to treatment. Concentrations of the key proapoptotic proteins procaspase-3, procaspase-9, Smac and Apaf-1 and the antiapopotic protein XIAP were determined in a panel of GBM cell lines and GBM patient tumor resections. These values were used as input for APOPTO-CELL, a systems biological based mathematical model built to predict cellular susceptibility to undergo caspase activation. The modeling was capable of accurately distinguishing between GBM cells that die or survive in response to treatment with temozolomide in 10 of the 11 lines analysed. Importantly the results obtained using GBM patient samples show that APOPTO-CELL was capable of stratifying patients according to their progression-free survival times and predicted the ability of tumor cells to support caspase activation in 16 of the 21 GBM patients analysed. Calculating the susceptibility to apoptosis execution may be a potent tool in predicting GBM patient therapy responsiveness and may allow for the use of APOPTO-CELL in a clinical setting.
publisher Nature Publishing Group
publishDate 2013
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3674364/
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