Literature DB >> 21182456

Validation of a high-content screening assay using whole-well imaging of transformed phenotypes.

Christina N Ramirez1, Tatsuya Ozawa, Toshimitsu Takagi, Christophe Antczak, David Shum, Robert Graves, Eric C Holland, Hakim Djaballah.   

Abstract

Automated microscopy was introduced two decades ago and has become an integral part of the discovery process as a high-content screening platform with noticeable challenges in executing cell-based assays. It would be of interest to use it to screen for reversers of a transformed cell phenotype. In this report, we present data obtained from an optimized assay that identifies compounds that reverse a transformed phenotype induced in NIH-3T3 cells by expressing a novel oncogene, KP, resulting from fusion between platelet derived growth factor receptor alpha (PDGFRα) and kinase insert domain receptor (KDR), that was identified in human glioblastoma. Initial image acquisitions using multiple tiles per well were found to be insufficient as to accurately image and quantify the clusters; whole-well imaging, performed on the IN Cell Analyzer 2000, while still two-dimensional imaging, was found to accurately image and quantify clusters, due largely to the inherent variability of their size and well location. The resulting assay exhibited a Z' value of 0.79 and a signal-to-noise ratio of 15, and it was validated against known effectors and shown to identify only PDGFRα inhibitors, and then tested in a pilot screen against a library of 58 known inhibitors identifying mostly PDGFRα inhibitors as reversers of the KP induced transformed phenotype. In conclusion, our optimized and validated assay using whole-well imaging is robust and sensitive in identifying compounds that reverse the transformed phenotype induced by KP with a broader applicability to other cell-based assays that are challenging in HTS against chemical and RNAi libraries.

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Year:  2010        PMID: 21182456      PMCID: PMC3123874          DOI: 10.1089/adt.2010.0342

Source DB:  PubMed          Journal:  Assay Drug Dev Technol        ISSN: 1540-658X            Impact factor:   1.738


  31 in total

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  8 in total

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