Literature DB >> 24792166

Unraveling the regulatory connections between two controllers of breast cancer cell fate.

Jinho Lee1, Abhinav Tiwari2, Victor Shum3, Gordon B Mills4, Michael A Mancini5, Oleg A Igoshin6, Gábor Balázsi7.   

Abstract

Estrogen receptor alpha (ERα) expression is critical for breast cancer classification, high ERα expression being associated with better prognosis. ERα levels strongly correlate with that of GATA binding protein 3 (GATA3), a major regulator of ERα expression. However, the mechanistic details of ERα-GATA3 regulation remain incompletely understood. Here we combine mathematical modeling with perturbation experiments to unravel the nature of regulatory connections in the ERα-GATA3 network. Through cell population-average, single-cell and single-nucleus measurements, we show that the cross-regulation between ERα and GATA3 amounts to overall negative feedback. Further, mathematical modeling reveals that GATA3 positively regulates its own expression and that ERα autoregulation is most likely absent. Lastly, we show that the two cross-regulatory connections in the ERα-GATA3 negative feedback network decrease the noise in ERα or GATA3 expression. This may ensure robust cell fate maintenance in the face of intracellular and environmental fluctuations, contributing to tissue homeostasis in normal conditions, but also to the maintenance of pathogenic states during cancer progression.
© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2014        PMID: 24792166      PMCID: PMC4066784          DOI: 10.1093/nar/gku360

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  70 in total

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Review 2.  Chromatin remodeling: why it is important in cancer.

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5.  GATA3 inhibits breast cancer metastasis through the reversal of epithelial-mesenchymal transition.

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Journal:  J Biol Chem       Date:  2010-02-26       Impact factor: 5.157

6.  A cell-type-specific transcriptional network required for estrogen regulation of cyclin D1 and cell cycle progression in breast cancer.

Authors:  Jérôme Eeckhoute; Jason S Carroll; Timothy R Geistlinger; Maria I Torres-Arzayus; Myles Brown
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7.  An engineered epigenetic transgene switch in mammalian cells.

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8.  Functional proteomics can define prognosis and predict pathologic complete response in patients with breast cancer.

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Journal:  Clin Proteomics       Date:  2011-07-08       Impact factor: 3.988

9.  Cellular reprogramming by the conjoint action of ERα, FOXA1, and GATA3 to a ligand-inducible growth state.

Authors:  Say Li Kong; Guoliang Li; Siang Lin Loh; Wing-Kin Sung; Edison T Liu
Journal:  Mol Syst Biol       Date:  2011-08-30       Impact factor: 11.429

10.  Gene expression patterns associated with p53 status in breast cancer.

Authors:  Melissa A Troester; Jason I Herschkowitz; Daniel S Oh; Xiaping He; Katherine A Hoadley; Claire S Barbier; Charles M Perou
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  7 in total

1.  GalNAc-T4 putatively modulates the estrogen regulatory network through FOXA1 glycosylation in human breast cancer cells.

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Journal:  Mol Cell Biochem       Date:  2015-11-05       Impact factor: 3.396

2.  Coupling the modules of EMT and stemness: A tunable 'stemness window' model.

Authors:  Mohit Kumar Jolly; Dongya Jia; Marcelo Boareto; Sendurai A Mani; Kenneth J Pienta; Eshel Ben-Jacob; Herbert Levine
Journal:  Oncotarget       Date:  2015-09-22

3.  Sampling-based Bayesian approaches reveal the importance of quasi-bistable behavior in cellular decision processes on the example of the MAPK signaling pathway in PC-12 cell lines.

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4.  Patterns of cell cycle checkpoint deregulation associated with intrinsic molecular subtypes of human breast cancer cells.

Authors:  Jacquelyn J Bower; Leah D Vance; Matthew Psioda; Stephanie L Smith-Roe; Dennis A Simpson; Joseph G Ibrahim; Katherine A Hoadley; Charles M Perou; William K Kaufmann
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5.  Engineering of a synthetic quadrastable gene network to approach Waddington landscape and cell fate determination.

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6.  A mechanistic model captures the emergence and implications of non-genetic heterogeneity and reversible drug resistance in ER+ breast cancer cells.

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7.  Gain- and Loss-of-Function Mutations in the Breast Cancer Gene GATA3 Result in Differential Drug Sensitivity.

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  7 in total

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