Chloé-Agathe Azencott

Noninvasive Multicancer Detection Using DNA Hypomethylation of LINE-1 Retrotransposons

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. See related commentary by Szymanski et al., p. 1179