Cellular imaging in drug discovery

Lang, Paul; Yeow, Karen; Nichols, Anthony; Scheer, Alexander

doi:10.1038/nrd2008

Cited by 316 publications

(220 citation statements)

References 117 publications

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“…1 The search for chemical entities modulating important cellular phenotypes, such as proliferation, differentiation, and survival, can now be conducted in biologically relevant cellular systems. In contrast to single-readout assays, high-content screening (HCS) permits the parallel measurement of an array of parameters (high content), extensively characterizing the cellular phenotype.…”

Section: High-content Phenotypic Screensmentioning

confidence: 99%

Robust Hit Identification by Quality Assurance and Multivariate Data Analysis of a High-Content, Cell-Based Assay

Dürr¹,

Duval²,

Nichols³

et al. 2007

SLAS Discovery

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Recent technological advances in high-content screening instrumentation have increased its ease of use and throughput, expanding the application of high-content screening to the early stages of drug discovery. However, high-content screens produce complex data sets, presenting a challenge for both extraction and interpretation of meaningful information. This shifts the high-content screening process bottleneck from the experimental to the analytical stage. In this article, the authors discuss different approaches of data analysis, using a phenotypic neurite outgrowth screen as an example. Distance measurements and hierarchical clustering methods lead to a profound understanding of different high-content screening readouts. In addition, the authors introduce a hit selection procedure based on machine learning methods and demonstrate that this method increases the hit verification rate significantly (up to a factor of 5), compared to conventional hit selection based on single readouts only. (Journal of Biomolecular

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Section: High-content Phenotypic Screensmentioning

confidence: 99%

Robust Hit Identification by Quality Assurance and Multivariate Data Analysis of a High-Content, Cell-Based Assay

Dürr¹,

Duval²,

Nichols³

et al. 2007

SLAS Discovery

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“…The combination of validated immunofluorescent assays, availability of automated microscopy, and advances in image analysis software led to increased exploitation of this technology in a variety of settings ranging from cellular signaling pathways to drug discovery (6,7). Recently, others have shown the advantages of HCI by revealing complex interactions between experimental molecules and cellular populations using several variables (8 -10).…”

Section: Introductionmentioning

confidence: 99%

“…First, most experiments continue to focus treatment effects on an entire population of cells and how one or two variables are affected in individual cells (6,7,9). In these experiments, the population of cells is viewed as giving a singular response rather than a combination of several subpopulations, all potentially responding differently to treatment.…”

Section: Introductionmentioning

confidence: 99%

High-content imaging characterization of cell cycle therapeutics through in vitro and in vivo subpopulation analysis

Low

Huang²,

Blosser³

et al. 2008

Molecular Cancer Therapeutics

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Although the cycling of eukaryotic cells has long been a primary focus for cancer therapeutics, recent advances in imaging and data analysis allow even further definition of cellular events as they occur in individual cells and cellular subpopulations in response to treatment. High-content imaging (HCI) has been an effective tool to elucidate cellular responses to a variety of agents; however, these data were most frequently observed as averages of the entire captured population, unnecessarily decreasing the resolution of each assay. Here, we dissect the eukaryotic cell cycle into individual cellular subpopulations using HCI in conjunction with unsupervised K-means clustering. We generate distinct phenotypic fingerprints for each major cell cycle and mitotic compartment and use those fingerprints to screen a library of 310 commercially available chemotherapeutic agents. We determine that the cell cycle arrest phenotypes caused by these agents are similar to, although distinct from, those found in untreated cells and that these distinctions frequently suggest the mechanism of action. We then show via subpopulation analysis that these arrest phenotypes are similar in both mouse models and in culture. HCI analysis of cell cycle using data obtained from individual cells under a broad range of research conditions and grouped into cellular subpopulations represents a powerful method to discern both cellular events and treatment effects. In particular, this technique allows for a more accurate means of assessing compound selectivity and leads to more meaningful comparisons between so-called targeted therapeutics.

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“…1 The complex intracellular responses involved in drug-induced efficacy or cytotoxicity can be observed in organ-specific cells by HCS. 2,3 This capability of HCS allows the acquisition of cellular information in more detail and provides a useful basis for making better decisions on progressing compounds.…”

Section: Introductionmentioning

confidence: 99%

Visible-to-Near IR Quantum Dot–Based Hypermulticolor High-Content Screening of Herbal Medicines for the Efficacy Monitoring of Hair Growth Promotion and Hair Loss Inhibition

Kim

Lim

Lee³

et al. 2013

SLAS Discovery

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There is a growing interest in alopecia prevention strategies, as the number of alopecia patients is increasing. We examine the efficacy of herbal medicine for hair growth promotion/hair loss inhibition in two cell lines via Western blot and highcontent screening (HCS). Nine herbal extracts were obtained from three different herbal medicine mixtures using 3 different extraction methods. Five target proteins-IGF-1 (insulin-like growth factor-1), TGF-β2 (transforming growth factor-β2), VEGF (vascular endothelial growth factor), DKK-1 (Dickkopf-1), and Wnt5α-were observed for the assessment of hair growth promotion/hair loss inhibition efficacy. The efficacies of nine extracts were compared with minoxidil as control. Efficacy was defined as a rise in the expression levels of IGF-1, VEGF, and Wnt5α but a decrease in DKK-1 and TGF-β2. Intracellular concurrent imaging of these proteins was successfully achieved using HCS, employing visible-to-near infrared probing based on quantum-antibody conjugates and hypermulticolor imaging.

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Cellular imaging in drug discovery

Cited by 316 publications

References 117 publications

Robust Hit Identification by Quality Assurance and Multivariate Data Analysis of a High-Content, Cell-Based Assay

Robust Hit Identification by Quality Assurance and Multivariate Data Analysis of a High-Content, Cell-Based Assay

High-content imaging characterization of cell cycle therapeutics through in vitro and in vivo subpopulation analysis

Visible-to-Near IR Quantum Dot–Based Hypermulticolor High-Content Screening of Herbal Medicines for the Efficacy Monitoring of Hair Growth Promotion and Hair Loss Inhibition

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