Estimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments
Abstract In-vitro chemo-sensitivity experiments are an essential step in the early stages of cancer therapy development, but existing data analysis methods suffer from problems with fitting, do not permit assessment of uncertainty, and can give misleading estimates of cell growth inhibition. We pres...
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Nature Portfolio
2018
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oai:doaj.org-article:49deb11bf7ae455090e308a5693ea20e2021-12-02T15:08:53ZEstimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments10.1038/s41598-018-21017-52045-2322https://doaj.org/article/49deb11bf7ae455090e308a5693ea20e2018-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-21017-5https://doaj.org/toc/2045-2322Abstract In-vitro chemo-sensitivity experiments are an essential step in the early stages of cancer therapy development, but existing data analysis methods suffer from problems with fitting, do not permit assessment of uncertainty, and can give misleading estimates of cell growth inhibition. We present an approach (bdChemo) based on a mechanistic model of cell division and death that permits rigorous statistical analyses of chemo-sensitivity experiment data by simultaneous estimation of cell division and apoptosis rates as functions of dose, without making strong assumptions about the shape of the dose-response curve. We demonstrate the utility of this method using a large-scale NCI-DREAM challenge dataset. We developed an R package “bdChemo” implementing this method, available at https://github.com/YiyiLiu1/bdChemo.Yiyi LiuForrest W. CrawfordNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-8 (2018) |
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Medicine R Science Q Yiyi Liu Forrest W. Crawford Estimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments |
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Abstract In-vitro chemo-sensitivity experiments are an essential step in the early stages of cancer therapy development, but existing data analysis methods suffer from problems with fitting, do not permit assessment of uncertainty, and can give misleading estimates of cell growth inhibition. We present an approach (bdChemo) based on a mechanistic model of cell division and death that permits rigorous statistical analyses of chemo-sensitivity experiment data by simultaneous estimation of cell division and apoptosis rates as functions of dose, without making strong assumptions about the shape of the dose-response curve. We demonstrate the utility of this method using a large-scale NCI-DREAM challenge dataset. We developed an R package “bdChemo” implementing this method, available at https://github.com/YiyiLiu1/bdChemo. |
format |
article |
author |
Yiyi Liu Forrest W. Crawford |
author_facet |
Yiyi Liu Forrest W. Crawford |
author_sort |
Yiyi Liu |
title |
Estimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments |
title_short |
Estimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments |
title_full |
Estimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments |
title_fullStr |
Estimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments |
title_full_unstemmed |
Estimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments |
title_sort |
estimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments |
publisher |
Nature Portfolio |
publishDate |
2018 |
url |
https://doaj.org/article/49deb11bf7ae455090e308a5693ea20e |
work_keys_str_mv |
AT yiyiliu estimatingdosespecificcelldivisionandapoptosisratesfromchemosensitivityexperiments AT forrestwcrawford estimatingdosespecificcelldivisionandapoptosisratesfromchemosensitivityexperiments |
_version_ |
1718387995586854912 |