A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses
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Published:2022-10-07
Issue:1
Volume:5
Page:
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ISSN:2399-3642
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Container-title:Communications Biology
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language:en
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Short-container-title:Commun Biol
Author:
Gross Sean M., Dane Mark A.ORCID, Smith Rebecca L., Devlin Kaylyn L., McLean Ian C.ORCID, Derrick Daniel S., Mills Caitlin E.ORCID, Subramanian Kartik, London Alexandra B., Torre Denis, Evangelista John Erol, Clarke Daniel J. B., Xie Zhuorui, Erdem CemalORCID, Lyons Nicholas, Natoli Ted, Pessa Sarah, Lu Xiaodong, Mullahoo James, Li Jonathan, Adam Miriam, Wassie Brook, Liu Moqing, Kilburn David F., Liby Tiera A., Bucher ElmarORCID, Sanchez-Aguila Crystal, Daily Kenneth, Omberg Larsson, Wang Yunguan, Jacobson Connor, Yapp Clarence, Chung Mirra, Vidovic Dusica, Lu Yiling, Schurer StephanORCID, Lee Albert, Pillai Ajay, Subramanian Aravind, Papanastasiou MalvinaORCID, Fraenkel ErnestORCID, Feiler Heidi S.ORCID, Mills Gordon B., Jaffe Jake D.ORCID, Ma’ayan Avi, Birtwistle Marc R., Sorger Peter K.ORCID, Korkola James E., Gray Joe W., Heiser Laura M.ORCID
Abstract
AbstractThe 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.
Publisher
Springer Science and Business Media LLC
Subject
General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)
Reference117 articles.
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