4.8 Article

Transcription factor-nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer

Journal

SCIENCE ADVANCES
Volume 8, Issue 34, Pages -

Publisher

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/sciadv.abm4358

Keywords

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Funding

  1. RNA Bioscience Initiative, University of Colorado School of Medicine
  2. American Cancer Society [16-184-56]
  3. National Cancer Institute grants [R01CA140985, R01CA205044]
  4. University of Colorado Cancer Center's Oncology Research Information Exchange Network
  5. University of Colorado Cancer Center Pathology Shared Resource [P30CA046934]
  6. Colorado Lung Cancer Specialized Program of Research Excellence [P50 CA058187]
  7. Pew-Stewart Scholar for Cancer Research
  8. Pew Charitable Trusts
  9. Alexander and Margaret Stewart Trust
  10. American Cancer Society-Virginia Cochary Award for Excellence in Breast Cancer Research Postdoctoral Fellowship [PF-20-095-01-DMC]
  11. Earlier.org-Friends for an Earlier Breast Cancer Test

Ask authors/readers for more resources

Plasma TF footprints can be used to diagnose breast cancer and identify different states and prognosis of tumors. This provides new possibilities for clinical applications.
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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