Cell population dynamics during apoptotic treatment. Imig, D., Pollak, N., & Allgöwer, F. SBHD, Heidelberg, July, 2017. abstract bibtex TNF-related apoptosis-inducing ligand (TRAIL) provokes apoptosis selectively in cancer cells. Although extensively investigated with experimental and theoretical approaches, underlying mechanisms explaining the apoptotic response of a cell population remain unclear. Here, experimental results concerning populations of lung cancer cell line stimulated with a superior second generation TRAIL variant are analyzed with help of appropriate mathematical models. An individual-based framework describing the dynamics of a cell population in response to the ligand is developed. Published models of the signaling pathway are integrated and population parameters are adapted to experimental data. Model simulations show that initial molecular changes after TRAIL stimulation are expected in the XIAP protein distribution. A shift in the caspase-8 distribution is predicted to be of capital importance for a transient insensitivity against TRAIL. Furthermore, it becomes clear that consideration of inheritance is crucial for the understanding of longterm responses to stimulations with TRAIL. Interestingly, the comparison of data and simulations of the population model revealed differences in the cell cycle dependence of death patterns. Hence, a phenomenological minimal model is developed in order to verify possible connections between cell cycle and apoptosis. Longterm time-lapse microscopy data are used for parameter estimation and model selection. The analysis gives insights into mechanisms of cell death progression during different phases of the cell cycle. The presented results are important steps for the improvement of a predictive model with the objective of optimizing TRAIL-based cancer therapies.
@MISC{ist:imig17a,
author = {Imig, D. and Pollak, N. and Allg{\"o}wer, F.},
title = {Cell population dynamics during apoptotic treatment},
howpublished = {SBHD, Heidelberg},
month = {July},
year = {2017},
abstract = {TNF-related apoptosis-inducing ligand (TRAIL) provokes apoptosis selectively
in cancer cells. Although extensively investigated with experimental
and theoretical approaches, underlying mechanisms explaining the
apoptotic response of a cell population remain unclear. Here, experimental
results concerning populations of lung cancer cell line stimulated
with a superior second generation TRAIL variant are analyzed with
help of appropriate mathematical models. An individual-based framework
describing the dynamics of a cell population in response to the ligand
is developed. Published models of the signaling pathway are integrated
and population parameters are adapted to experimental data. Model
simulations show that initial molecular changes after TRAIL stimulation
are expected in the XIAP protein distribution. A shift in the caspase-8
distribution is predicted to be of capital importance for a transient
insensitivity against TRAIL. Furthermore, it becomes clear that consideration
of inheritance is crucial for the understanding of longterm responses
to stimulations with TRAIL. Interestingly, the comparison of data
and simulations of the population model revealed differences in the
cell cycle dependence of death patterns. Hence, a phenomenological
minimal model is developed in order to verify possible connections
between cell cycle and apoptosis. Longterm time-lapse microscopy
data are used for parameter estimation and model selection. The analysis
gives insights into mechanisms of cell death progression during different
phases of the cell cycle. The presented results are important steps
for the improvement of a predictive model with the objective of optimizing
TRAIL-based cancer therapies.},
pubtype = {poster}
}
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{"_id":"AfArWmX7SLbRR6rfy","bibbaseid":"imig-pollak-allgwer-cellpopulationdynamicsduringapoptotictreatment-2017","downloads":0,"creationDate":"2018-11-29T07:13:47.350Z","title":"Cell population dynamics during apoptotic treatment","author_short":["Imig, D.","Pollak, N.","Allgöwer, F."],"year":2017,"bibtype":"misc","biburl":"http://www.ist.uni-stuttgart.de/.content/publication_database/ist.bib","bibdata":{"bibtype":"misc","type":"misc","author":[{"propositions":[],"lastnames":["Imig"],"firstnames":["D."],"suffixes":[]},{"propositions":[],"lastnames":["Pollak"],"firstnames":["N."],"suffixes":[]},{"propositions":[],"lastnames":["Allgöwer"],"firstnames":["F."],"suffixes":[]}],"title":"Cell population dynamics during apoptotic treatment","howpublished":"SBHD, Heidelberg","month":"July","year":"2017","abstract":"TNF-related apoptosis-inducing ligand (TRAIL) provokes apoptosis selectively in cancer cells. Although extensively investigated with experimental and theoretical approaches, underlying mechanisms explaining the apoptotic response of a cell population remain unclear. Here, experimental results concerning populations of lung cancer cell line stimulated with a superior second generation TRAIL variant are analyzed with help of appropriate mathematical models. An individual-based framework describing the dynamics of a cell population in response to the ligand is developed. Published models of the signaling pathway are integrated and population parameters are adapted to experimental data. Model simulations show that initial molecular changes after TRAIL stimulation are expected in the XIAP protein distribution. A shift in the caspase-8 distribution is predicted to be of capital importance for a transient insensitivity against TRAIL. Furthermore, it becomes clear that consideration of inheritance is crucial for the understanding of longterm responses to stimulations with TRAIL. Interestingly, the comparison of data and simulations of the population model revealed differences in the cell cycle dependence of death patterns. Hence, a phenomenological minimal model is developed in order to verify possible connections between cell cycle and apoptosis. Longterm time-lapse microscopy data are used for parameter estimation and model selection. The analysis gives insights into mechanisms of cell death progression during different phases of the cell cycle. The presented results are important steps for the improvement of a predictive model with the objective of optimizing TRAIL-based cancer therapies.","pubtype":"poster","bibtex":"@MISC{ist:imig17a,\n author = {Imig, D. and Pollak, N. and Allg{\\\"o}wer, F.},\n title = {Cell population dynamics during apoptotic treatment},\n howpublished = {SBHD, Heidelberg},\n month = {July},\n year = {2017},\n abstract = {TNF-related apoptosis-inducing ligand (TRAIL) provokes apoptosis selectively\n\tin cancer cells. Although extensively investigated with experimental\n\tand theoretical approaches, underlying mechanisms explaining the\n\tapoptotic response of a cell population remain unclear. Here, experimental\n\tresults concerning populations of lung cancer cell line stimulated\n\twith a superior second generation TRAIL variant are analyzed with\n\thelp of appropriate mathematical models. An individual-based framework\n\tdescribing the dynamics of a cell population in response to the ligand\n\tis developed. Published models of the signaling pathway are integrated\n\tand population parameters are adapted to experimental data. Model\n\tsimulations show that initial molecular changes after TRAIL stimulation\n\tare expected in the XIAP protein distribution. A shift in the caspase-8\n\tdistribution is predicted to be of capital importance for a transient\n\tinsensitivity against TRAIL. Furthermore, it becomes clear that consideration\n\tof inheritance is crucial for the understanding of longterm responses\n\tto stimulations with TRAIL. Interestingly, the comparison of data\n\tand simulations of the population model revealed differences in the\n\tcell cycle dependence of death patterns. Hence, a phenomenological\n\tminimal model is developed in order to verify possible connections\n\tbetween cell cycle and apoptosis. Longterm time-lapse microscopy\n\tdata are used for parameter estimation and model selection. The analysis\n\tgives insights into mechanisms of cell death progression during different\n\tphases of the cell cycle. The presented results are important steps\n\tfor the improvement of a predictive model with the objective of optimizing\n\tTRAIL-based cancer therapies.},\n pubtype = {poster}\n}\n\n","author_short":["Imig, D.","Pollak, N.","Allgöwer, F."],"key":"ist:imig17a","id":"ist:imig17a","bibbaseid":"imig-pollak-allgwer-cellpopulationdynamicsduringapoptotictreatment-2017","role":"author","urls":{},"metadata":{"authorlinks":{}}},"search_terms":["cell","population","dynamics","during","apoptotic","treatment","imig","pollak","allgöwer"],"keywords":[],"authorIDs":[],"dataSources":["EXg9RjjTit3R3tBWv"]}