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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...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
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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. |
format | Text |
id | pubmed-2829039 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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