ArticleCell systems2017
Systems Pharmacology Dissection of Cholesterol Regulation Reveals Determinants of Large Pharmacodynamic Variability between Cell Lines.
Article in Cell systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Functional interrogation of candidate cis-regulatory elements at the LDLR locus.PLoS genetics · 2026Article
- Functional interrogation of cellular Lp(a) uptake by genome-scale CRISPR screening.Atherosclerosis · 2025Article
- Understanding the molecular diversity of synapses.Nature reviews. Neuroscience · 2025Review
- Leveraging gene correlations in single cell transcriptomic data.BMC bioinformatics · 2024Article
- Multi-omics and pharmacological characterization of patient-derived glioma cell lines.Nature communications · 2024Article
- Leveraging gene correlations in single cell transcriptomic data.bioRxiv : the preprint server for biology · 2023Article
- Machine Learning and Hybrid Methods for Metabolic Pathway Modeling.Methods in molecular biology (Clifton, N.J.) · 2023Review
- The Non Catalytic Protein ERG28 has a Functional Role in Cholesterol Synthesis and is Coregulated Transcriptionally.Journal of lipid research · 2022Article
- Genome-scale CRISPR screening for modifiers of cellular LDL uptake.PLoS genetics · 2021Article
- Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes.Nature communications · 2020Article
- Clinical biomarker discovery by SWATH-MS based label-free quantitative proteomics: impact of criteria for identification of differentiators and data normalization method.Journal of translational medicine · 2019Article
- A framework for large-scale metabolome drug profiling links coenzyme A metabolism to the toxicity of anti-cancer drug dichloroacetate.Communications biology · 2018Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.