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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...

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Autores principales: Rao, Satyanarayan, Han, Amy L., Zukowski, Alexis, Kopin, Etana, Sartorius, Carol A., Kabos, Peter, Ramachandran, Srinivas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2022
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.
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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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