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Sensitive tumour detection and classification using plasma cell-free DNA methylomes

Shu Yi Shen 1 Rajat Singhania 1 Gordon Fehringer 2 Ankur Chakravarthy 1 Michael H. A. Roehrl 1, 3 Dianne Chadwick 1 Philip C. Zuzarte 4 Ayelet Borgida 2 Ting Ting Wang 1 Tiantian Li 1 Olena Kis 1 Zhen Zhao 1 Anna Spreafico 1 Tiago da Silva Medina 1 Yadon Wang 1 David Roulois 5, 1 Ilias Ettayebi 1 Zhuo Chen 1 Signy Chow 1 Tracy Murphy 1 Andrea Arruda 1 Grainne M. O'Kane 1 Jessica Liu 6 Mark Mansour 6 John D. Mcpherson Catherine O'Brien 1 Natasha Leighl 1 Philippe L. Bedard 1 Neil Fleshner 1 Geoffrey Liu 1, 6 Mark D. Minden 1 Steven Gallinger 7 Anna Goldenberg 6 Trevor J. Pugh 1 Michael M. Hoffman 1, 6 Scott V. Bratman 1 Rayjean J. Hung 1, 6 Daniel D. de Carvalho 1, 6
1 Princess Margaret Hospital
2 MSH - Mount Sinai Hospital [Toronto, Canada]
3 Memorial Sloane Kettering Cancer Center [New York]
4 OICR - Ontario Institute for Cancer Research [Canada]
5 MICMAC - Microenvironment, Cell Differentiation, Immunology and Cancer
6 University of Toronto
7 TGHRI - Toronto General Hospital Research Institute [Canada]
Abstract : The use of liquid biopsies for cancer detection and management is rapidly gaining prominence(1). Current methods for the detection of circulating tumour DNA involve sequencing somatic mutations using cell-free DNA, but the sensitivity of these methods may be low among patients with early-stage cancer given the limited number of recurrent mutations(2-5). By contrast, large-scale epigenetic alterations-which are tissue-and cancer-type specific-are not similarly constrained(6) and therefore potentially have greater ability to detect and classify cancers in patients with early-stage disease. Here we develop a sensitive, immunoprecipitation-based protocol to analyse the methylome of small quantities of circulating cellfree DNA, and demonstrate the ability to detect large-scale DNA methylation changes that are enriched for tumour-specific patterns. We also demonstrate robust performance in cancer detection and classification across an extensive collection of plasma samples from several tumour types. This work sets the stage to establish biomarkers for the minimally invasive detection, interception and classification of early-stage cancers based on plasma cell-free DNA methylation patterns.
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Submitted on : Monday, January 14, 2019 - 2:23:45 PM
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UNIV-RENNES1 | UR1-UFR-SVE | UNIV-RENNES | MICMAC | BIOSIT | U917

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Shu Yi Shen, Rajat Singhania, Gordon Fehringer, Ankur Chakravarthy, Michael H. A. Roehrl, et al.. Sensitive tumour detection and classification using plasma cell-free DNA methylomes. Nature, Nature Publishing Group, 2018, 563 (7732), pp.579-583. ⟨10.1038/s41586-018-0703-0⟩. ⟨hal-01974928⟩

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