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Measurement and models accounting for cell death capture hidden variation in compound response

Song Yi Bae, View ORCID ProfileNing Guan, View ORCID ProfileRui Yan, View ORCID ProfileKatrina Warner, View ORCID ProfileAaron S Meyer
doi: https://doi.org/10.1101/863597
Song Yi Bae
1Department of Pharmacology, University of Minnesota-Twin Cities, Minneapolis, MN
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Ning Guan
2Department of Biological Engineering; Massachusetts Institute of Technology, Cambridge, MA
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Rui Yan
3Institute for Computational and Mathematical Engineering; Stanford University, Stanford, CA
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Katrina Warner
4Biological and Biomedical Sciences Program; Harvard University, Cambridge, MA
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Aaron S Meyer
5Department of Bioengineering; University of California, Los Angeles, CA
6Department of Bioinformatics; University of California, Los Angeles, CA
7Jonsson Comprehensive Cancer Center; University of California, Los Angeles, CA
8Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research; University of California, Los Angeles, CA
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  • For correspondence: ameyer@ucla.edu
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Abstract

Cancer cell sensitivity or resistance is almost universally quantified through a direct or surrogate measure of cell number. However, compound responses can occur through many distinct phenotypic outcomes including changes in cell growth, apoptosis, and non-apoptotic cell death. These outcomes have distinct effects on the tumor microenvironment, immune responses, and resistance mechanisms. Here, we show that quantifying cell viability alone is insufficient to distinguish between these compound responses. Using an alternative assay and drug response analysis amenable to high-throughput measurement, we find that compounds with identical viability outcomes can have very different effects on cell growth and death. Moreover, compound pairs with additive cell growth and death effects can appear synergistic when only assessed by viability. Overall, these results demonstrate an approach to incorporating measurements of cell death when characterizing a pharmacologic response.

Summary Points

  • Measurements of solely live cell numbers mask important differences in compound effects.

  • Additive effects on growth and death rates can appear synergistic when analyzed solely via live cell number.

  • Automated imaging can provide reasonable throughput to analyze cell response in terms of cell growth and death, and endpoint analysis is similarly informative.

Footnotes

  • https://github.com/meyer-lab/ps-growth-model

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 04, 2019.
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Measurement and models accounting for cell death capture hidden variation in compound response
Song Yi Bae, Ning Guan, Rui Yan, Katrina Warner, Aaron S Meyer
bioRxiv 863597; doi: https://doi.org/10.1101/863597
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Measurement and models accounting for cell death capture hidden variation in compound response
Song Yi Bae, Ning Guan, Rui Yan, Katrina Warner, Aaron S Meyer
bioRxiv 863597; doi: https://doi.org/10.1101/863597

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