A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses

Sean M. Gross; Mark A. Dane; Rebecca L. Smith; Kaylyn L. Devlin; Ian C. McLean; Daniel S. Derrick; Caitlin E. Mills; Kartik Subramanian; Alexandra B. London; Denis Torre; John Erol Evangelista; Daniel J.B. Clarke; Zhuorui Xie; Cemal Erdem; Nicholas Lyons; Ted Natoli; Sarah Pessa; Xiaodong Lu; James Mullahoo; Jonathan Li; Miriam Adam; Brook Wassie; Moqing Liu; David F. Kilburn; Tiera A. Liby; Elmar Bucher; Crystal Sanchez-Aguila; Kenneth Daily; Larsson Omberg; Yunguan Wang; Connor Jacobson; Clarence Yapp; Mirra Chung; Dusica Vidovic; Yiling Lu; Stephan Schurer; Albert Lee; Ajay Pillai; Aravind Subramanian; Malvina Papanastasiou; Ernest Fraenkel; Heidi S. Feiler; Gordon B. Mills; Jake D. Jaffe; Avi Ma’ayan; Marc R. Birtwistle; Peter K. Sorger; James E. Korkola; Joe W. Gray; Laura M. Heiser

doi:10.1038/s42003-022-03975-9

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses

Sean M. Gross, Mark A. Dane, Rebecca L. Smith, Kaylyn L. Devlin, Ian C. McLean, Daniel S. Derrick, Caitlin E. Mills, Kartik Subramanian, Alexandra B. London, Denis Torre, John Erol Evangelista, Daniel J.B. Clarke, Zhuorui Xie, Cemal Erdem, Nicholas Lyons, Ted Natoli, Sarah Pessa, Xiaodong Lu, James Mullahoo, Jonathan LiMiriam Adam, Brook Wassie, Moqing Liu, David F. Kilburn, Tiera A. Liby, Elmar Bucher, Crystal Sanchez-Aguila, Kenneth Daily, Larsson Omberg, Yunguan Wang, Connor Jacobson, Clarence Yapp, Mirra Chung, Dusica Vidovic, Yiling Lu, Stephan Schurer, Albert Lee, Ajay Pillai, Aravind Subramanian, Malvina Papanastasiou, Ernest Fraenkel, Heidi S. Feiler, Gordon B. Mills, Jake D. Jaffe, Avi Ma’ayan, Marc R. Birtwistle, Peter K. Sorger, James E. Korkola, Joe W. Gray, Laura M. Heiser

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

Original language	English (US)
Article number	1066
Journal	Communications Biology
Volume	5
Issue number	1
DOIs	https://doi.org/10.1038/s42003-022-03975-9
State	Published - Dec 2022

ASJC Scopus subject areas

Medicine (miscellaneous)
General Biochemistry, Genetics and Molecular Biology
General Agricultural and Biological Sciences

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Gross, S. M., Dane, M. A., Smith, R. L., Devlin, K. L., McLean, I. C., Derrick, D. S., Mills, C. E., Subramanian, K., London, A. B., Torre, D., Evangelista, J. E., Clarke, D. J. B., Xie, Z., Erdem, C., Lyons, N., Natoli, T., Pessa, S., Lu, X., Mullahoo, J., ... Heiser, L. M. (2022). A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses. Communications Biology, 5(1), Article 1066. https://doi.org/10.1038/s42003-022-03975-9

Gross, SM, Dane, MA, Smith, RL, Devlin, KL, McLean, IC, Derrick, DS, Mills, CE, Subramanian, K, London, AB, Torre, D, Evangelista, JE, Clarke, DJB, Xie, Z, Erdem, C, Lyons, N, Natoli, T, Pessa, S, Lu, X, Mullahoo, J, Li, J, Adam, M, Wassie, B, Liu, M, Kilburn, DF, Liby, TA, Bucher, E, Sanchez-Aguila, C, Daily, K, Omberg, L, Wang, Y, Jacobson, C, Yapp, C, Chung, M, Vidovic, D, Lu, Y, Schurer, S, Lee, A, Pillai, A, Subramanian, A, Papanastasiou, M, Fraenkel, E, Feiler, HS , Mills, GB, Jaffe, JD, Ma’ayan, A, Birtwistle, MR, Sorger, PK, Korkola, JE, Gray, JW & Heiser, LM 2022, 'A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses', Communications Biology, vol. 5, no. 1, 1066. https://doi.org/10.1038/s42003-022-03975-9

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title = "A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses",

abstract = "The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.",

author = "Gross, {Sean M.} and Dane, {Mark A.} and Smith, {Rebecca L.} and Devlin, {Kaylyn L.} and McLean, {Ian C.} and Derrick, {Daniel S.} and Mills, {Caitlin E.} and Kartik Subramanian and London, {Alexandra B.} and Denis Torre and Evangelista, {John Erol} and Clarke, {Daniel J.B.} and Zhuorui Xie and Cemal Erdem and Nicholas Lyons and Ted Natoli and Sarah Pessa and Xiaodong Lu and James Mullahoo and Jonathan Li and Miriam Adam and Brook Wassie and Moqing Liu and Kilburn, {David F.} and Liby, {Tiera A.} and Elmar Bucher and Crystal Sanchez-Aguila and Kenneth Daily and Larsson Omberg and Yunguan Wang and Connor Jacobson and Clarence Yapp and Mirra Chung and Dusica Vidovic and Yiling Lu and Stephan Schurer and Albert Lee and Ajay Pillai and Aravind Subramanian and Malvina Papanastasiou and Ernest Fraenkel and Feiler, {Heidi S.} and Mills, {Gordon B.} and Jaffe, {Jake D.} and Avi Ma{\textquoteright}ayan and Birtwistle, {Marc R.} and Sorger, {Peter K.} and Korkola, {James E.} and Gray, {Joe W.} and Heiser, {Laura M.}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1038/s42003-022-03975-9",

language = "English (US)",

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T1 - A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses

AU - Gross, Sean M.

AU - Dane, Mark A.

AU - Smith, Rebecca L.

AU - Devlin, Kaylyn L.

AU - McLean, Ian C.

AU - Derrick, Daniel S.

AU - Mills, Caitlin E.

AU - Subramanian, Kartik

AU - London, Alexandra B.

AU - Torre, Denis

AU - Evangelista, John Erol

AU - Clarke, Daniel J.B.

AU - Xie, Zhuorui

AU - Erdem, Cemal

AU - Lyons, Nicholas

AU - Natoli, Ted

AU - Pessa, Sarah

AU - Lu, Xiaodong

AU - Mullahoo, James

AU - Li, Jonathan

AU - Adam, Miriam

AU - Wassie, Brook

AU - Liu, Moqing

AU - Kilburn, David F.

AU - Liby, Tiera A.

AU - Bucher, Elmar

AU - Sanchez-Aguila, Crystal

AU - Daily, Kenneth

AU - Omberg, Larsson

AU - Wang, Yunguan

AU - Jacobson, Connor

AU - Yapp, Clarence

AU - Chung, Mirra

AU - Vidovic, Dusica

AU - Lu, Yiling

AU - Schurer, Stephan

AU - Lee, Albert

AU - Pillai, Ajay

AU - Subramanian, Aravind

AU - Papanastasiou, Malvina

AU - Fraenkel, Ernest

AU - Feiler, Heidi S.

AU - Mills, Gordon B.

AU - Jaffe, Jake D.

AU - Ma’ayan, Avi

AU - Birtwistle, Marc R.

AU - Sorger, Peter K.

AU - Korkola, James E.

AU - Gray, Joe W.

AU - Heiser, Laura M.

PY - 2022/12

Y1 - 2022/12

N2 - The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

AB - The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

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JO - Communications Biology

JF - Communications Biology

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A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses

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