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- Non-invasive multi-cancer detection using DNA hypomethylation of LINE-1 retrotransposons
Non-invasive multi-cancer detection using DNA hypomethylation of LINE-1 retrotransposons
Auteurs
Marc Michel, Maryam Heidary, Anissa Mechri, Kévin Da Silva, Marine Gorse, Victoria Dixon, Klaus von Grafenstein, Charline Bianchi, Caroline Hego, Aurore Rampanou, Constance Lamy, Maud Kamal, Christophe Le Tourneau, Mathieu Séné, Ivan Bieche, Cécile Reyes, David Gentien, Marc-Henri Stern, Olivier Lantz, Luc Cabel, Jean-Yves Pierga, Francois-Clement Bidard, Chloé-Agathe Azencott, Charlotte Proudhon
Résumé
Abstract
Purpose:
The detection of ctDNA, which allows noninvasive 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.
Experimental Design:
We implemented a new, highly sensitive strategy to detect bp resolution methylation patterns from plasma DNA and assessed the potential of hypomethylation of long interspersed nuclear element-1 retrotransposons as a noninvasive multicancer detection biomarker. The Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA method targets 30 to 40,000 young long interspersed nuclear element-1 retrotransposons scattered throughout the genome, covering about 100,000 CpG sites and is based on a reference-free analysis pipeline.
Results:
Resulting machine learning–based classifiers showed powerful correct classification rates discriminating healthy and tumor plasmas from six types of cancers (colorectal, breast, lung, ovarian, and gastric cancers and uveal melanoma, including localized stages) in two independent cohorts (AUC = 88%–100%, N = 747). The Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA method can also be used to perform copy number alteration analysis that improves cancer detection.
Conclusions:
This should lead to the development of more efficient noninvasive diagnostic tests adapted to all patients with cancer, based on the universality of these factors.
Membres
DAVID GENTIEN
Ingénieur de recherche
MARC-HENRI STERN
Directeur de recherche
CECILE REYES
Ingénieur d'études