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Tumor fractions deciphered from circulating cell-free DNA methylation for cancer early diagnosis

Author

Listed:
  • Xiao Zhou

    (Tsinghua University)

  • Zhen Cheng

    (Tsinghua University)

  • Mingyu Dong

    (Tsinghua University)

  • Qi Liu

    (Tsinghua University)

  • Weiyang Yang

    (Tsinghua University)

  • Min Liu

    (Tsinghua University
    Guangdong Second Provincial General Hospital)

  • Junzhang Tian

    (Guangdong Second Provincial General Hospital)

  • Weibin Cheng

    (Guangdong Second Provincial General Hospital)

Abstract

Tumor-derived circulating cell-free DNA (cfDNA) provides critical clues for cancer early diagnosis, yet it often suffers from low sensitivity. Here, we present a cancer early diagnosis approach using tumor fractions deciphered from circulating cfDNA methylation signatures. We show that the estimated fractions of tumor-derived cfDNA from cancer patients increase significantly as cancer progresses in two independent datasets. Employing the predicted tumor fractions, we establish a Bayesian diagnostic model in which training samples are only derived from late-stage patients and healthy individuals. When validated on early-stage patients and healthy individuals, this model exhibits a sensitivity of 86.1% for cancer early detection and an average accuracy of 76.9% for tumor localization at a specificity of 94.7%. By highlighting the potential of tumor fractions on cancer early diagnosis, our approach can be further applied to cancer screening and tumor progression monitoring.

Suggested Citation

  • Xiao Zhou & Zhen Cheng & Mingyu Dong & Qi Liu & Weiyang Yang & Min Liu & Junzhang Tian & Weibin Cheng, 2022. "Tumor fractions deciphered from circulating cell-free DNA methylation for cancer early diagnosis," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-35320-3
    DOI: 10.1038/s41467-022-35320-3
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    1. Christa Caggiano & Barbara Celona & Fleur Garton & Joel Mefford & Brian L. Black & Robert Henderson & Catherine Lomen-Hoerth & Andrew Dahl & Noah Zaitlen, 2021. "Comprehensive cell type decomposition of circulating cell-free DNA with CelFiE," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    2. 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.
    3. Viktor A. Adalsteinsson & Gavin Ha & Samuel S. Freeman & Atish D. Choudhury & Daniel G. Stover & Heather A. Parsons & Gregory Gydush & Sarah C. Reed & Denisse Rotem & Justin Rhoades & Denis Loginov & , 2017. "Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors," Nature Communications, Nature, vol. 8(1), pages 1-13, December.
    4. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    5. 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.
    6. Joshua Moss & Judith Magenheim & Daniel Neiman & Hai Zemmour & Netanel Loyfer & Amit Korach & Yaacov Samet & Myriam Maoz & Henrik Druid & Peter Arner & Keng-Yeh Fu & Endre Kiss & Kirsty L. Spalding & , 2018. "Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    7. Xuran Wang & Jihwan Park & Katalin Susztak & Nancy R. Zhang & Mingyao Li, 2019. "Bulk tissue cell type deconvolution with multi-subject single-cell expression reference," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
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