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Transcription factor–nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer
Genome-wide binding profiles of estrogen receptor (ER) and FOXA1 reflect cancer state in ER(+) breast cancer. However, routine profiling of tumor transcription factor (TF) binding is impractical in the clinic. Here, we show that plasma cell-free DNA (cfDNA) contains high-resolution ER and FOXA1 tumo...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9401618/ https://www.ncbi.nlm.nih.gov/pubmed/36001652 http://dx.doi.org/10.1126/sciadv.abm4358 |
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author | Rao, Satyanarayan Han, Amy L. Zukowski, Alexis Kopin, Etana Sartorius, Carol A. Kabos, Peter Ramachandran, Srinivas |
author_facet | Rao, Satyanarayan Han, Amy L. Zukowski, Alexis Kopin, Etana Sartorius, Carol A. Kabos, Peter Ramachandran, Srinivas |
author_sort | Rao, Satyanarayan |
collection | PubMed |
description | Genome-wide binding profiles of estrogen receptor (ER) and FOXA1 reflect cancer state in ER(+) breast cancer. However, routine profiling of tumor transcription factor (TF) binding is impractical in the clinic. Here, we show that plasma cell-free DNA (cfDNA) contains high-resolution ER and FOXA1 tumor binding profiles for breast cancer. Enrichment of TF footprints in plasma reflects the binding strength of the TF in originating tissue. We defined pure in vivo tumor TF signatures in plasma using ER(+) breast cancer xenografts, which can distinguish xenografts with distinct ER states. Furthermore, state-specific ER-binding signatures can partition human breast tumors into groups with significantly different ER expression and mortality. Last, TF footprints in human plasma samples can identify the presence of ER(+) breast cancer. Thus, plasma TF footprints enable minimally invasive mapping of the regulatory landscape of breast cancer in humans and open vast possibilities for clinical applications across multiple tumor types. |
format | Online Article Text |
id | pubmed-9401618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-94016182022-08-26 Transcription factor–nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer Rao, Satyanarayan Han, Amy L. Zukowski, Alexis Kopin, Etana Sartorius, Carol A. Kabos, Peter Ramachandran, Srinivas Sci Adv Biomedicine and Life Sciences Genome-wide binding profiles of estrogen receptor (ER) and FOXA1 reflect cancer state in ER(+) breast cancer. However, routine profiling of tumor transcription factor (TF) binding is impractical in the clinic. Here, we show that plasma cell-free DNA (cfDNA) contains high-resolution ER and FOXA1 tumor binding profiles for breast cancer. Enrichment of TF footprints in plasma reflects the binding strength of the TF in originating tissue. We defined pure in vivo tumor TF signatures in plasma using ER(+) breast cancer xenografts, which can distinguish xenografts with distinct ER states. Furthermore, state-specific ER-binding signatures can partition human breast tumors into groups with significantly different ER expression and mortality. Last, TF footprints in human plasma samples can identify the presence of ER(+) breast cancer. Thus, plasma TF footprints enable minimally invasive mapping of the regulatory landscape of breast cancer in humans and open vast possibilities for clinical applications across multiple tumor types. American Association for the Advancement of Science 2022-08-24 /pmc/articles/PMC9401618/ /pubmed/36001652 http://dx.doi.org/10.1126/sciadv.abm4358 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Biomedicine and Life Sciences Rao, Satyanarayan Han, Amy L. Zukowski, Alexis Kopin, Etana Sartorius, Carol A. Kabos, Peter Ramachandran, Srinivas Transcription factor–nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer |
title | Transcription factor–nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer |
title_full | Transcription factor–nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer |
title_fullStr | Transcription factor–nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer |
title_full_unstemmed | Transcription factor–nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer |
title_short | Transcription factor–nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer |
title_sort | transcription factor–nucleosome dynamics from plasma cfdna identifies er-driven states in breast cancer |
topic | Biomedicine and Life Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9401618/ https://www.ncbi.nlm.nih.gov/pubmed/36001652 http://dx.doi.org/10.1126/sciadv.abm4358 |
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