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Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery

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, i...

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Autores principales: Gough, Albert H., Chen, Ning, Shun, Tong Ying, Lezon, Timothy R., Boltz, Robert C., Reese, Celeste E., Wagner, Jacob, Vernetti, Lawrence A., Grandis, Jennifer R., Lee, Adrian V., Stern, Andrew M., Schurdak, Mark E., Taylor, D. Lansing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103836/
https://www.ncbi.nlm.nih.gov/pubmed/25036749
http://dx.doi.org/10.1371/journal.pone.0102678
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author Gough, Albert H.
Chen, Ning
Shun, Tong Ying
Lezon, Timothy R.
Boltz, Robert C.
Reese, Celeste E.
Wagner, Jacob
Vernetti, Lawrence A.
Grandis, Jennifer R.
Lee, Adrian V.
Stern, Andrew M.
Schurdak, Mark E.
Taylor, D. Lansing
author_facet Gough, Albert H.
Chen, Ning
Shun, Tong Ying
Lezon, Timothy R.
Boltz, Robert C.
Reese, Celeste E.
Wagner, Jacob
Vernetti, Lawrence A.
Grandis, Jennifer R.
Lee, Adrian V.
Stern, Andrew M.
Schurdak, Mark E.
Taylor, D. Lansing
author_sort Gough, Albert H.
collection PubMed
description 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.
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spelling pubmed-41038362014-07-21 Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery Gough, Albert H. Chen, Ning Shun, Tong Ying Lezon, Timothy R. Boltz, Robert C. Reese, Celeste E. Wagner, Jacob Vernetti, Lawrence A. Grandis, Jennifer R. Lee, Adrian V. Stern, Andrew M. Schurdak, Mark E. Taylor, D. Lansing PLoS One Research Article 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. Public Library of Science 2014-07-18 /pmc/articles/PMC4103836/ /pubmed/25036749 http://dx.doi.org/10.1371/journal.pone.0102678 Text en © 2014 Gough et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Gough, Albert H.
Chen, Ning
Shun, Tong Ying
Lezon, Timothy R.
Boltz, Robert C.
Reese, Celeste E.
Wagner, Jacob
Vernetti, Lawrence A.
Grandis, Jennifer R.
Lee, Adrian V.
Stern, Andrew M.
Schurdak, Mark E.
Taylor, D. Lansing
Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery
title Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery
title_full Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery
title_fullStr Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery
title_full_unstemmed Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery
title_short Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery
title_sort identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103836/
https://www.ncbi.nlm.nih.gov/pubmed/25036749
http://dx.doi.org/10.1371/journal.pone.0102678
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