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A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA

Author

Listed:
  • Anna-Lisa Doebley

    (Fred Hutchinson Cancer Center
    University of Washington
    University of Washington)

  • Minjeong Ko

    (Fred Hutchinson Cancer Center)

  • Hanna Liao

    (University of Washington
    University of Washington)

  • A. Eden Cruikshank

    (Fred Hutchinson Cancer Center
    University of Washington)

  • Katheryn Santos

    (Dana-Farber Cancer Institute)

  • Caroline Kikawa

    (University of Washington)

  • Joseph B. Hiatt

    (Fred Hutchinson Cancer Center
    University of Washington)

  • Robert D. Patton

    (Fred Hutchinson Cancer Center)

  • Navonil De Sarkar

    (Fred Hutchinson Cancer Center)

  • Katharine A. Collier

    (Ohio State University Comprehensive Cancer Center)

  • Anna C. H. Hoge

    (Fred Hutchinson Cancer Center)

  • Katharine Chen

    (University of Washington)

  • Anat Zimmer

    (Fred Hutchinson Cancer Center)

  • Zachary T. Weber

    (Ohio State University Comprehensive Cancer Center)

  • Mohamed Adil

    (Fred Hutchinson Cancer Center
    University of Washington)

  • Jonathan B. Reichel

    (Fred Hutchinson Cancer Center
    University of Washington
    Brotman Baty Institute for Precision Medicine)

  • Paz Polak

    (Mount Sinai)

  • Viktor A. Adalsteinsson

    (Broad Institute of MIT and Harvard)

  • Peter S. Nelson

    (Fred Hutchinson Cancer Center
    University of Washington
    University of Washington
    University of Washington)

  • David MacPherson

    (Fred Hutchinson Cancer Center
    University of Washington)

  • Heather A. Parsons

    (Dana-Farber Cancer Institute)

  • Daniel G. Stover

    (Ohio State University Comprehensive Cancer Center)

  • Gavin Ha

    (Fred Hutchinson Cancer Center
    University of Washington
    Brotman Baty Institute for Precision Medicine)

Abstract

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we develop Griffin, a framework for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing data. Griffin employs a GC correction procedure tailored to variable cfDNA fragment sizes, which generates a better representation of chromatin accessibility and improves the accuracy of cancer detection and tumor subtype classification. We demonstrate estrogen receptor subtyping from cfDNA in metastatic breast cancer. We predict estrogen receptor subtype in 139 patients with at least 5% detectable circulating tumor DNA with an area under the receive operator characteristic curve (AUC) of 0.89 and validate performance in independent cohorts (AUC = 0.96). In summary, Griffin is a framework for accurate tumor subtyping and can be generalizable to other cancer types for precision oncology applications.

Suggested Citation

  • Anna-Lisa Doebley & Minjeong Ko & Hanna Liao & A. Eden Cruikshank & Katheryn Santos & Caroline Kikawa & Joseph B. Hiatt & Robert D. Patton & Navonil De Sarkar & Katharine A. Collier & Anna C. H. Hoge , 2022. "A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-35076-w
    DOI: 10.1038/s41467-022-35076-w
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