Abstract
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, PPARc has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPARγ has been validated through two supporting biological assays.
| Original language | English (US) |
|---|---|
| Article number | e1000684 |
| Journal | PLoS Computational Biology |
| Volume | 6 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 2010 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Cellular and Molecular Neuroscience
- Ecology
- Molecular Biology
- Genetics
- Ecology, Evolution, Behavior and Systematics
- Modeling and Simulation
- Computational Theory and Mathematics
Cite this
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; Bissell, Mina J.; Kenny, Paraic A.; Parvin, Bahram.
In: PLoS Computational Biology, Vol. 6, No. 2, e1000684, 02.2010.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Molecular predictors of 3D morphogenesis by breast cancer cell lines in 3D culture
AU - Han, Ju
AU - Chang, Hang
AU - Giricz, Orsi
AU - Lee, Genee Y.
AU - Baehner, Frederick L.
AU - Gray, Joe
AU - Bissell, Mina J.
AU - Kenny, Paraic A.
AU - Parvin, Bahram
PY - 2010/2
Y1 - 2010/2
N2 - 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, PPARc has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPARγ has been validated through two supporting biological assays.
AB - 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, PPARc 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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U2 - 10.1371/journal.pcbi.1000684
DO - 10.1371/journal.pcbi.1000684
M3 - Article
C2 - 20195492
AN - SCOPUS:77649220426
VL - 6
JO - PLoS Computational Biology
JF - PLoS Computational Biology
SN - 1553-734X
IS - 2
M1 - e1000684
ER -