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A Mathematical Model of Bimodal Epigenetic Control of miR-193a in Ovarian Cancer Stem Cells

Accumulating data indicate that cancer stem cells contribute to tumor chemoresistance and their persistence alters clinical outcome. Our previous study has shown that ovarian cancer may be initiated by ovarian cancer initiating cells (OCIC) characterized by surface antigen CD44 and c-KIT (CD117). It...

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Autores principales: Cheng, Frank H. C., Aguda, Baltazar D., Tsai, Je-Chiang, Kochańczyk, Marek, Lin, Jora M. J., Chen, Gary C. W., Lai, Hung-Cheng, Nephew, Kenneth P., Hwang, Tzy-Wei, Chan, Michael W. Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4278842/
https://www.ncbi.nlm.nih.gov/pubmed/25545504
http://dx.doi.org/10.1371/journal.pone.0116050
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author Cheng, Frank H. C.
Aguda, Baltazar D.
Tsai, Je-Chiang
Kochańczyk, Marek
Lin, Jora M. J.
Chen, Gary C. W.
Lai, Hung-Cheng
Nephew, Kenneth P.
Hwang, Tzy-Wei
Chan, Michael W. Y.
author_facet Cheng, Frank H. C.
Aguda, Baltazar D.
Tsai, Je-Chiang
Kochańczyk, Marek
Lin, Jora M. J.
Chen, Gary C. W.
Lai, Hung-Cheng
Nephew, Kenneth P.
Hwang, Tzy-Wei
Chan, Michael W. Y.
author_sort Cheng, Frank H. C.
collection PubMed
description Accumulating data indicate that cancer stem cells contribute to tumor chemoresistance and their persistence alters clinical outcome. Our previous study has shown that ovarian cancer may be initiated by ovarian cancer initiating cells (OCIC) characterized by surface antigen CD44 and c-KIT (CD117). It has been experimentally demonstrated that a microRNA, namely miR-193a, targets c-KIT mRNA for degradation and could play a crucial role in ovarian cancer development. How miR-193a is regulated is poorly understood and the emerging picture is complex. To unravel this complexity, we propose a mathematical model to explore how estrogen-mediated up-regulation of another target of miR-193a, namely E2F6, can attenuate the function of miR-193a in two ways, one through a competition of E2F6 and c-KIT transcripts for miR-193a, and second by binding of E2F6 protein, in association with a polycomb complex, to the promoter of miR-193a to down-regulate its transcription. Our model predicts that this bimodal control increases the expression of c-KIT and that the second mode of epigenetic regulation is required to generate a switching behavior in c-KIT and E2F6 expressions. Additional analysis of the TCGA ovarian cancer dataset demonstrates that ovarian cancer patients with low expression of EZH2, a polycomb-group family protein, show positive correlation between E2F6 and c-KIT. We conjecture that a simultaneous EZH2 inhibition and anti-estrogen therapy can constitute an effective combined therapeutic strategy against ovarian cancer.
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spelling pubmed-42788422015-01-05 A Mathematical Model of Bimodal Epigenetic Control of miR-193a in Ovarian Cancer Stem Cells Cheng, Frank H. C. Aguda, Baltazar D. Tsai, Je-Chiang Kochańczyk, Marek Lin, Jora M. J. Chen, Gary C. W. Lai, Hung-Cheng Nephew, Kenneth P. Hwang, Tzy-Wei Chan, Michael W. Y. PLoS One Research Article Accumulating data indicate that cancer stem cells contribute to tumor chemoresistance and their persistence alters clinical outcome. Our previous study has shown that ovarian cancer may be initiated by ovarian cancer initiating cells (OCIC) characterized by surface antigen CD44 and c-KIT (CD117). It has been experimentally demonstrated that a microRNA, namely miR-193a, targets c-KIT mRNA for degradation and could play a crucial role in ovarian cancer development. How miR-193a is regulated is poorly understood and the emerging picture is complex. To unravel this complexity, we propose a mathematical model to explore how estrogen-mediated up-regulation of another target of miR-193a, namely E2F6, can attenuate the function of miR-193a in two ways, one through a competition of E2F6 and c-KIT transcripts for miR-193a, and second by binding of E2F6 protein, in association with a polycomb complex, to the promoter of miR-193a to down-regulate its transcription. Our model predicts that this bimodal control increases the expression of c-KIT and that the second mode of epigenetic regulation is required to generate a switching behavior in c-KIT and E2F6 expressions. Additional analysis of the TCGA ovarian cancer dataset demonstrates that ovarian cancer patients with low expression of EZH2, a polycomb-group family protein, show positive correlation between E2F6 and c-KIT. We conjecture that a simultaneous EZH2 inhibition and anti-estrogen therapy can constitute an effective combined therapeutic strategy against ovarian cancer. Public Library of Science 2014-12-29 /pmc/articles/PMC4278842/ /pubmed/25545504 http://dx.doi.org/10.1371/journal.pone.0116050 Text en © 2014 Cheng 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
Cheng, Frank H. C.
Aguda, Baltazar D.
Tsai, Je-Chiang
Kochańczyk, Marek
Lin, Jora M. J.
Chen, Gary C. W.
Lai, Hung-Cheng
Nephew, Kenneth P.
Hwang, Tzy-Wei
Chan, Michael W. Y.
A Mathematical Model of Bimodal Epigenetic Control of miR-193a in Ovarian Cancer Stem Cells
title A Mathematical Model of Bimodal Epigenetic Control of miR-193a in Ovarian Cancer Stem Cells
title_full A Mathematical Model of Bimodal Epigenetic Control of miR-193a in Ovarian Cancer Stem Cells
title_fullStr A Mathematical Model of Bimodal Epigenetic Control of miR-193a in Ovarian Cancer Stem Cells
title_full_unstemmed A Mathematical Model of Bimodal Epigenetic Control of miR-193a in Ovarian Cancer Stem Cells
title_short A Mathematical Model of Bimodal Epigenetic Control of miR-193a in Ovarian Cancer Stem Cells
title_sort mathematical model of bimodal epigenetic control of mir-193a in ovarian cancer stem cells
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4278842/
https://www.ncbi.nlm.nih.gov/pubmed/25545504
http://dx.doi.org/10.1371/journal.pone.0116050
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