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Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer

Author

Listed:
  • Mary L. Stackpole

    (University of California at Los Angeles
    EarlyDiagnostics, Inc.)

  • Weihua Zeng

    (University of California at Los Angeles)

  • Shuo Li

    (University of California at Los Angeles
    EarlyDiagnostics, Inc.)

  • Chun-Chi Liu

    (EarlyDiagnostics, Inc.)

  • Yonggang Zhou

    (University of California at Los Angeles)

  • Shanshan He

    (University of California at Los Angeles)

  • Angela Yeh

    (University of California at Los Angeles)

  • Ziye Wang

    (University of California at Los Angeles)

  • Fengzhu Sun

    (University of Southern California)

  • Qingjiao Li

    (Sun Yat-Sen University)

  • Zuyang Yuan

    (University of California at Los Angeles)

  • Asli Yildirim

    (University of California at Los Angeles)

  • Pin-Jung Chen

    (University of California at Los Angeles)

  • Paul Winograd

    (University of California at Los Angeles)

  • Benjamin Tran

    (University of California at Los Angeles)

  • Yi-Te Lee

    (University of California at Los Angeles)

  • Paul Shize Li

    (Westlake High School)

  • Zorawar Noor

    (University of California at Los Angeles)

  • Megumi Yokomizo

    (University of California at Los Angeles)

  • Preeti Ahuja

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Yazhen Zhu

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Hsian-Rong Tseng

    (University of California at Los Angeles
    University of California at Los Angeles)

  • James S. Tomlinson

    (University of California at Los Angeles
    University of California at Los Angeles
    University of California at Los Angeles
    VA Greater Los Angeles Health Care System)

  • Edward Garon

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Samuel French

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Clara E. Magyar

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Sarah Dry

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Clara Lajonchere

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Daniel Geschwind

    (University of California at Los Angeles)

  • Gina Choi

    (University of California at Los Angeles)

  • Sammy Saab

    (University of California at Los Angeles)

  • Frank Alber

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Wing Hung Wong

    (Stanford University
    Stanford University)

  • Steven M. Dubinett

    (University of California at Los Angeles
    University of California at Los Angeles
    University of California at Los Angeles
    University of California at Los Angeles)

  • Denise R. Aberle

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Vatche Agopian

    (University of California at Los Angeles
    University of California at Los Angeles)

  • Steven-Huy B. Han

    (University of California at Los Angeles)

  • Xiaohui Ni

    (EarlyDiagnostics, Inc.)

  • Wenyuan Li

    (University of California at Los Angeles)

  • Xianghong Jasmine Zhou

    (University of California at Los Angeles
    University of California at Los Angeles
    University of California at Los Angeles)

Abstract

Early cancer detection by cell-free DNA faces multiple challenges: low fraction of tumor cell-free DNA, molecular heterogeneity of cancer, and sample sizes that are not sufficient to reflect diverse patient populations. Here, we develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of the cell-free DNA methylome (with > 12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our approach to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, allowing us to learn new features and expand to other cancer types as training cohorts grow.

Suggested Citation

  • Mary L. Stackpole & Weihua Zeng & Shuo Li & Chun-Chi Liu & Yonggang Zhou & Shanshan He & Angela Yeh & Ziye Wang & Fengzhu Sun & Qingjiao Li & Zuyang Yuan & Asli Yildirim & Pin-Jung Chen & Paul Winogra, 2022. "Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32995-6
    DOI: 10.1038/s41467-022-32995-6
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    References listed on IDEAS

    as
    1. Jacob J. Chabon & Emily G. Hamilton & David M. Kurtz & Mohammad S. Esfahani & Everett J. Moding & Henning Stehr & Joseph Schroers-Martin & Barzin Y. Nabet & Binbin Chen & Aadel A. Chaudhuri & Chih Lon, 2020. "Integrating genomic features for non-invasive early lung cancer detection," Nature, Nature, vol. 580(7802), pages 245-251, April.
    2. Xingdong Chen & Jeffrey Gole & Athurva Gore & Qiye He & Ming Lu & Jun Min & Ziyu Yuan & Xiaorong Yang & Yanfeng Jiang & Tiejun Zhang & Chen Suo & Xiaojie Li & Lei Cheng & Zhenhua Zhang & Hongyu Niu & , 2020. "Non-invasive early detection of cancer four years before conventional diagnosis using a blood test," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    3. Stephen Cristiano & Alessandro Leal & Jillian Phallen & Jacob Fiksel & Vilmos Adleff & Daniel C. Bruhm & Sarah Østrup Jensen & Jamie E. Medina & Carolyn Hruban & James R. White & Doreen N. Palsgrove &, 2019. "Genome-wide cell-free DNA fragmentation in patients with cancer," Nature, Nature, vol. 570(7761), pages 385-389, June.
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