Author:
Michel Marc,Heidary Maryam,Mechri Anissa,Silva Kévin Da,Gorse Marine,Dixon Victoria,von Grafenstein Klaus,Hego Caroline,Rampanou Aurore,Lamy Constance,Kamal Maud,Tourneau Christophe Le,Séné Mathieu,Bièche Ivan,Reyes Cecile,Gentien David,Stern Marc-Henri,Lantz Olivier,Cabel Luc,Pierga Jean-Yves,Bidard François-Clément,Azencott Chloé-Agathe,Proudhon Charlotte
Abstract
AbstractThe detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We implemented a new highly sensitive strategy to detect base-pair resolution methylation patterns from plasma DNA and assessed the potential of hypomethylation of LINE-1 retrotransposons as a non-invasive multi-cancer detection biomarker. Resulting machine learning-based classifiers showed powerful correct classification rates discriminating healthy and tumor plasmas from 6 types of cancers in two independent cohorts (AUC = 88% to 100%, N = 747). This should lead to the development of more efficient non-invasive diagnostic tests adapted to all cancer patients, based on the universality of these factors.One-Sentence SummaryLINE-1 retrotransposons hypomethylation is a sensitive and specific biomarker to detect multiple forms of cancer non-invasively.
Publisher
Cold Spring Harbor Laboratory