Cell Systems
Volume 5, Issue 6, 27 December 2017, Pages 604-619.e7
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Article
Systems Pharmacology Dissection of Cholesterol Regulation Reveals Determinants of Large Pharmacodynamic Variability between Cell Lines

https://doi.org/10.1016/j.cels.2017.11.002Get rights and content
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Highlights

  • Mass spectrometry-based quantification of multi-level cellular response to drugs

  • Generation of a large multi-omics dataset from different perturbed cell lines

  • Capturing the cell-type-specific responses to drugs with mathematical models

  • Identification of pharmacodynamic variability as major determinant of drug response

Summary

In individuals, heterogeneous drug-response phenotypes result from a complex interplay of dose, drug specificity, genetic background, and environmental factors, thus challenging our understanding of the underlying processes and optimal use of drugs in the clinical setting. Here, we use mass-spectrometry-based quantification of molecular response phenotypes and logic modeling to explain drug-response differences in a panel of cell lines. We apply this approach to cellular cholesterol regulation, a biological process with high clinical relevance. From the quantified molecular phenotypes elicited by various targeted pharmacologic or genetic treatments, we generated cell-line-specific models that quantified the processes beneath the idiotypic intracellular drug responses. The models revealed that, in addition to drug uptake and metabolism, further cellular processes displayed significant pharmacodynamic response variability between the cell lines, resulting in cell-line-specific drug-response phenotypes. This study demonstrates the importance of integrating different types of quantitative systems-level molecular measurements with modeling to understand the effect of pharmacological perturbations on complex biological processes.

Keywords

proteomics
metabolomics
mass spectrometry
logic modeling
statins
T0901317
GW3965
LXR
SREBP
SWATH

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Present address: Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, CT 06510, USA

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