Cargando…

Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP

Motivation: TRAIL has been widely studied for the ability to kill cancer cells selectively, but its clinical usefulness has been hindered by the development of resistance. Multiple compounds have been identified that sensitize cancer cells to TRAIL-induced apoptosis. The drug LY303511 (LY30), combin...

Descripción completa

Detalles Bibliográficos
Autores principales: Shi, Yuan, Mellier, Gregory, Huang, Sinong, White, Jacob, Pervaiz, Shazib, Tucker-Kellogg, Lisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3562069/
https://www.ncbi.nlm.nih.gov/pubmed/23239672
http://dx.doi.org/10.1093/bioinformatics/bts702
_version_ 1782258034106433536
author Shi, Yuan
Mellier, Gregory
Huang, Sinong
White, Jacob
Pervaiz, Shazib
Tucker-Kellogg, Lisa
author_facet Shi, Yuan
Mellier, Gregory
Huang, Sinong
White, Jacob
Pervaiz, Shazib
Tucker-Kellogg, Lisa
author_sort Shi, Yuan
collection PubMed
description Motivation: TRAIL has been widely studied for the ability to kill cancer cells selectively, but its clinical usefulness has been hindered by the development of resistance. Multiple compounds have been identified that sensitize cancer cells to TRAIL-induced apoptosis. The drug LY303511 (LY30), combined with TRAIL, caused synergistic (greater than additive) killing of multiple cancer cell lines. We used mathematical modelling and ordinary differential equations to represent how LY30 and TRAIL individually affect HeLa cells, and to predict how the combined treatment achieves synergy. Results: Model-based predictions were compared with in vitro experiments. The combination treatment model was successful at mimicking the synergistic levels of cell death caused by LY30 and TRAIL combined. However, there were significant failures of the model to mimic upstream activation at early time points, particularly the slope of caspase-8 activation. This flaw in the model led us to perform additional measurements of early caspase-8 activation. Surprisingly, caspase-8 exhibited a transient decrease in activity after LY30 treatment, prior to strong activation. cFLIP, an inhibitor of caspase-8 activation, was up-regulated briefly after 30 min of LY30 treatment, followed by a significant down-regulation over prolonged exposure. A further model suggested that LY30-induced fluctuation of cFLIP might result from tilting the ratio of two key species of reactive oxygen species (ROS), superoxide and hydrogen peroxide. Computational modelling extracted novel biological implications from measured dynamics, identified time intervals with unexplained effects, and clarified the non-monotonic effects of the drug LY30 on cFLIP during cancer cell apoptosis. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: LisaTK@nus.edu.sg or Shazib_Pervaiz@nuhs.edu.sg
format Online
Article
Text
id pubmed-3562069
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-35620692013-02-01 Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP Shi, Yuan Mellier, Gregory Huang, Sinong White, Jacob Pervaiz, Shazib Tucker-Kellogg, Lisa Bioinformatics Original Papers Motivation: TRAIL has been widely studied for the ability to kill cancer cells selectively, but its clinical usefulness has been hindered by the development of resistance. Multiple compounds have been identified that sensitize cancer cells to TRAIL-induced apoptosis. The drug LY303511 (LY30), combined with TRAIL, caused synergistic (greater than additive) killing of multiple cancer cell lines. We used mathematical modelling and ordinary differential equations to represent how LY30 and TRAIL individually affect HeLa cells, and to predict how the combined treatment achieves synergy. Results: Model-based predictions were compared with in vitro experiments. The combination treatment model was successful at mimicking the synergistic levels of cell death caused by LY30 and TRAIL combined. However, there were significant failures of the model to mimic upstream activation at early time points, particularly the slope of caspase-8 activation. This flaw in the model led us to perform additional measurements of early caspase-8 activation. Surprisingly, caspase-8 exhibited a transient decrease in activity after LY30 treatment, prior to strong activation. cFLIP, an inhibitor of caspase-8 activation, was up-regulated briefly after 30 min of LY30 treatment, followed by a significant down-regulation over prolonged exposure. A further model suggested that LY30-induced fluctuation of cFLIP might result from tilting the ratio of two key species of reactive oxygen species (ROS), superoxide and hydrogen peroxide. Computational modelling extracted novel biological implications from measured dynamics, identified time intervals with unexplained effects, and clarified the non-monotonic effects of the drug LY30 on cFLIP during cancer cell apoptosis. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: LisaTK@nus.edu.sg or Shazib_Pervaiz@nuhs.edu.sg Oxford University Press 2013-02-01 2012-12-13 /pmc/articles/PMC3562069/ /pubmed/23239672 http://dx.doi.org/10.1093/bioinformatics/bts702 Text en © The Author 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Shi, Yuan
Mellier, Gregory
Huang, Sinong
White, Jacob
Pervaiz, Shazib
Tucker-Kellogg, Lisa
Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP
title Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP
title_full Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP
title_fullStr Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP
title_full_unstemmed Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP
title_short Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP
title_sort computational modelling of ly303511 and trail-induced apoptosis suggests dynamic regulation of cflip
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3562069/
https://www.ncbi.nlm.nih.gov/pubmed/23239672
http://dx.doi.org/10.1093/bioinformatics/bts702
work_keys_str_mv AT shiyuan computationalmodellingofly303511andtrailinducedapoptosissuggestsdynamicregulationofcflip
AT melliergregory computationalmodellingofly303511andtrailinducedapoptosissuggestsdynamicregulationofcflip
AT huangsinong computationalmodellingofly303511andtrailinducedapoptosissuggestsdynamicregulationofcflip
AT whitejacob computationalmodellingofly303511andtrailinducedapoptosissuggestsdynamicregulationofcflip
AT pervaizshazib computationalmodellingofly303511andtrailinducedapoptosissuggestsdynamicregulationofcflip
AT tuckerkellogglisa computationalmodellingofly303511andtrailinducedapoptosissuggestsdynamicregulationofcflip