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Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture

Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to seg...

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Autores principales: Han, Ju, Chang, Hang, Giricz, Orsi, Lee, Genee Y., Baehner, Frederick L., Gray, Joe W., Bissell, Mina J., Kenny, Paraic A., Parvin, Bahram
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2829039/
https://www.ncbi.nlm.nih.gov/pubmed/20195492
http://dx.doi.org/10.1371/journal.pcbi.1000684
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author Han, Ju
Chang, Hang
Giricz, Orsi
Lee, Genee Y.
Baehner, Frederick L.
Gray, Joe W.
Bissell, Mina J.
Kenny, Paraic A.
Parvin, Bahram
author_facet Han, Ju
Chang, Hang
Giricz, Orsi
Lee, Genee Y.
Baehner, Frederick L.
Gray, Joe W.
Bissell, Mina J.
Kenny, Paraic A.
Parvin, Bahram
author_sort Han, Ju
collection PubMed
description Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to segment and represent each colony at multiple dimensions. Subsequently, subpopulations from these morphological responses were identified through consensus clustering to reveal three clusters of round, grape-like, and stellate phenotypes. In some cases, cell lines with particular pathobiological phenotypes clustered together (e.g., ERBB2 amplified cell lines sharing the same morphometric properties as the grape-like phenotype). Next, associations with molecular features were realized through (i) differential analysis within each morphological cluster, and (ii) regression analysis across the entire panel of cell lines. In both cases, the dominant genes that are predictive of the morphological signatures were identified. Specifically, PPARγ has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPARγ has been validated through two supporting biological assays.
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spelling pubmed-28290392010-03-02 Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture Han, Ju Chang, Hang Giricz, Orsi Lee, Genee Y. Baehner, Frederick L. Gray, Joe W. Bissell, Mina J. Kenny, Paraic A. Parvin, Bahram PLoS Comput Biol Research Article Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to segment and represent each colony at multiple dimensions. Subsequently, subpopulations from these morphological responses were identified through consensus clustering to reveal three clusters of round, grape-like, and stellate phenotypes. In some cases, cell lines with particular pathobiological phenotypes clustered together (e.g., ERBB2 amplified cell lines sharing the same morphometric properties as the grape-like phenotype). Next, associations with molecular features were realized through (i) differential analysis within each morphological cluster, and (ii) regression analysis across the entire panel of cell lines. In both cases, the dominant genes that are predictive of the morphological signatures were identified. Specifically, PPARγ has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPARγ has been validated through two supporting biological assays. Public Library of Science 2010-02-26 /pmc/articles/PMC2829039/ /pubmed/20195492 http://dx.doi.org/10.1371/journal.pcbi.1000684 Text en Han 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
Han, Ju
Chang, Hang
Giricz, Orsi
Lee, Genee Y.
Baehner, Frederick L.
Gray, Joe W.
Bissell, Mina J.
Kenny, Paraic A.
Parvin, Bahram
Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture
title Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture
title_full Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture
title_fullStr Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture
title_full_unstemmed Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture
title_short Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture
title_sort molecular predictors of 3d morphogenesis by breast cancer cell lines in 3d culture
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2829039/
https://www.ncbi.nlm.nih.gov/pubmed/20195492
http://dx.doi.org/10.1371/journal.pcbi.1000684
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