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- W2912666525 abstract "Abstract In pharmaceutical research, high-content screening is an integral part of lead candidate development. Drug response in vitro over 40 parameters including biomarkers, signaling molecules, cell morphological changes, proliferation indexes and toxicity in a single sample could significantly enhance discovery of new therapeutics. As a proof of concept, we present a workflow for multidimensional Imaging Mass Cytometry™ (IMC™) and data processing with open source computational tools. CellProfiler was used to identify single cells through establishing cellular boundaries, followed by histoCAT™ (histology topography cytometry analysis toolbox) for extracting single-cell quantitative information visualized as t-SNE plots and heatmaps. Human breast cancer-derived cell lines SKBR3, HCC1143 and MCF-7 were screened for expression of cellular markers to generate digital images with a resolution comparable to conventional fluorescence microscopy. Predicted pharmacodynamic effects were measured in MCF-7 cells dosed with three target-specific compounds: growth stimulatory EGF, microtubule depolymerization agent nocodazole and genotoxic chemotherapeutic drug etoposide. We show strong pairwise correlation between nuclear markers pHistone3 S28 , Ki-67 and p4E-BP1 T37/T46 in classified mitotic cells and anti-correlation with cell surface markers. Our study demonstrates that IMC data expands the number of measured parameters in single cells and brings higher-dimension analysis to the field of cell-based screening in early lead compound discovery." @default.
- W2912666525 created "2019-02-21" @default.
- W2912666525 creator A5006824850 @default.
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- W2912666525 date "2019-02-18" @default.
- W2912666525 modified "2023-09-23" @default.
- W2912666525 title "Multidimensional Profiling of Drug-Treated Cells by Imaging Mass Cytometry" @default.
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- W2912666525 doi "https://doi.org/10.1101/549592" @default.
- W2912666525 hasPublicationYear "2019" @default.
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