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Identifying and quantifying heterogeneity in high content analysis: Application of heterogeneity indices to drug discovery

Gough, AH and Chen, N and Shun, TY and Lezon, TR and Boltz, RC and Reese, CE and Wagner, J and Vernetti, LA and Grandis, JR and Lee, AV and Stern, AM and Schurdak, ME and Taylor, DL (2014) Identifying and quantifying heterogeneity in high content analysis: Application of heterogeneity indices to drug discovery. PLoS ONE, 9 (7).

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Abstract

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology. © 2014 Gough et al.

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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Gough, AHgough@pitt.eduGOUGH
Chen, Nningchen@pitt.eduNINGCHEN
Shun, TYtos8@pitt.eduTOS8
Lezon, TRlezon@pitt.eduLEZON
Boltz, RCrcb56@pitt.eduRCB56
Reese, CEcer25@pitt.eduCER25
Wagner, J
Vernetti, LAvernetti@pitt.eduVERNETTI
Grandis, JRjgrandis@pitt.eduJGRANDIS
Lee, AVavl10@pitt.eduAVL10
Stern, AMSTERNAM@pitt.eduSTERNAM
Schurdak, MEmes234@pitt.eduMES234
Taylor, DLdltaylor@pitt.eduDLTAYLOR
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorPaulmurugan, RamasamyUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Centers: Other Centers, Institutes, Offices, or Units > Drug Discovery Institute
Other Centers, Institutes, Offices, or Units > Pittsburgh Cancer Institute
Date: 18 July 2014
Date Type: Publication
Journal or Publication Title: PLoS ONE
Volume: 9
Number: 7
DOI or Unique Handle: 10.1371/journal.pone.0102678
Schools and Programs: School of Medicine > Computational and Systems Biology
School of Medicine > Otolaryngology
School of Medicine > Pharmacology and Chemical Biology
Refereed: Yes
Date Deposited: 23 Sep 2014 15:08
Last Modified: 02 Feb 2019 16:58
URI: http://d-scholarship.pitt.edu/id/eprint/22990

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