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A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer

The human genome contains regulatory elements, such as enhancers, that are often rewired by cancer cells for the activation of genes that promote tumorigenesis and resistance to therapy. This is especially true for cancers that have little or no known driver mutations within protein coding genes, su...

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Autores principales: Kelly, Michael R., Wisniewska, Kamila, Regner, Matthew J., Lewis, Michael W., Perreault, Andrea A., Davis, Eric S., Phanstiel, Douglas H., Parker, Joel S., Franco, Hector L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307778/
https://www.ncbi.nlm.nih.gov/pubmed/35869079
http://dx.doi.org/10.1038/s41467-022-31919-8
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author Kelly, Michael R.
Wisniewska, Kamila
Regner, Matthew J.
Lewis, Michael W.
Perreault, Andrea A.
Davis, Eric S.
Phanstiel, Douglas H.
Parker, Joel S.
Franco, Hector L.
author_facet Kelly, Michael R.
Wisniewska, Kamila
Regner, Matthew J.
Lewis, Michael W.
Perreault, Andrea A.
Davis, Eric S.
Phanstiel, Douglas H.
Parker, Joel S.
Franco, Hector L.
author_sort Kelly, Michael R.
collection PubMed
description The human genome contains regulatory elements, such as enhancers, that are often rewired by cancer cells for the activation of genes that promote tumorigenesis and resistance to therapy. This is especially true for cancers that have little or no known driver mutations within protein coding genes, such as ovarian cancer. Herein, we utilize an integrated set of genomic and epigenomic datasets to identify clinically relevant super-enhancers that are preferentially amplified in ovarian cancer patients. We systematically probe the top 86 super-enhancers, using CRISPR-interference and CRISPR-deletion assays coupled to RNA-sequencing, to nominate two salient super-enhancers that drive proliferation and migration of cancer cells. Utilizing Hi-C, we construct chromatin interaction maps that enable the annotation of direct target genes for these super-enhancers and confirm their activity specifically within the cancer cell compartment of human tumors using single-cell genomics data. Together, our multi-omic approach examines a number of fundamental questions about how regulatory information encoded into super-enhancers drives gene expression networks that underlie the biology of ovarian cancer.
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spelling pubmed-93077782022-07-24 A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer Kelly, Michael R. Wisniewska, Kamila Regner, Matthew J. Lewis, Michael W. Perreault, Andrea A. Davis, Eric S. Phanstiel, Douglas H. Parker, Joel S. Franco, Hector L. Nat Commun Article The human genome contains regulatory elements, such as enhancers, that are often rewired by cancer cells for the activation of genes that promote tumorigenesis and resistance to therapy. This is especially true for cancers that have little or no known driver mutations within protein coding genes, such as ovarian cancer. Herein, we utilize an integrated set of genomic and epigenomic datasets to identify clinically relevant super-enhancers that are preferentially amplified in ovarian cancer patients. We systematically probe the top 86 super-enhancers, using CRISPR-interference and CRISPR-deletion assays coupled to RNA-sequencing, to nominate two salient super-enhancers that drive proliferation and migration of cancer cells. Utilizing Hi-C, we construct chromatin interaction maps that enable the annotation of direct target genes for these super-enhancers and confirm their activity specifically within the cancer cell compartment of human tumors using single-cell genomics data. Together, our multi-omic approach examines a number of fundamental questions about how regulatory information encoded into super-enhancers drives gene expression networks that underlie the biology of ovarian cancer. Nature Publishing Group UK 2022-07-22 /pmc/articles/PMC9307778/ /pubmed/35869079 http://dx.doi.org/10.1038/s41467-022-31919-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kelly, Michael R.
Wisniewska, Kamila
Regner, Matthew J.
Lewis, Michael W.
Perreault, Andrea A.
Davis, Eric S.
Phanstiel, Douglas H.
Parker, Joel S.
Franco, Hector L.
A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer
title A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer
title_full A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer
title_fullStr A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer
title_full_unstemmed A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer
title_short A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer
title_sort multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307778/
https://www.ncbi.nlm.nih.gov/pubmed/35869079
http://dx.doi.org/10.1038/s41467-022-31919-8
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