| Literature DB >> 30429608 |
Shu Yi Shen1, Rajat Singhania1, Gordon Fehringer2, Ankur Chakravarthy1, Michael H A Roehrl1,3,4, Dianne Chadwick1, Philip C Zuzarte5, Ayelet Borgida2, Ting Ting Wang1,4, Tiantian Li1, Olena Kis1, Zhen Zhao1, Anna Spreafico1, Tiago da Silva Medina1, Yadon Wang1, David Roulois1,6, Ilias Ettayebi1,4, Zhuo Chen1, Signy Chow1, Tracy Murphy1, Andrea Arruda1, Grainne M O'Kane1, Jessica Liu4, Mark Mansour4, John D McPherson7, Catherine O'Brien1, Natasha Leighl1, Philippe L Bedard1, Neil Fleshner1, Geoffrey Liu1,4,8, Mark D Minden1, Steven Gallinger9,10, Anna Goldenberg11, Trevor J Pugh1,4, Michael M Hoffman1,4,11, Scott V Bratman1,4, Rayjean J Hung12,13, Daniel D De Carvalho14,15.
Abstract
The use of liquid biopsies for cancer detection and management is rapidly gaining prominence1. 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 mutations2-5. By contrast, large-scale epigenetic alterations-which are tissue- and cancer-type specific-are not similarly constrained6 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 cell-free 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.Entities:
Mesh:
Substances:
Year: 2018 PMID: 30429608 DOI: 10.1038/s41586-018-0703-0
Source DB: PubMed Journal: Nature ISSN: 0028-0836 Impact factor: 49.962