Author:
Chung Felicia Fei-Lei,Maldonado Sandra González,Nemc Amelie,Bouaoun Liacine,Cahais Vincent,Cuenin Cyrille,Salle Aurelie,Johnson Theron,Ergüner Bekir,Laplana Marina,Datlinger Paul,Jeschke Jana,Weiderpass Elisabete,Kristensen Vessela,Delaloge Suzette,Fuks François,Risch Angela,Ghantous Akram,Plass Christoph,Bock Christoph,Kaaks Rudolf,Herceg Zdenko
Abstract
Abstract
Background
Epigenetic alterations are a near-universal feature of human malignancy and have been detected in malignant cells as well as in easily accessible specimens such as blood and urine. These findings offer promising applications in cancer detection, subtyping, and treatment monitoring. However, much of the current evidence is based on findings in retrospective studies and may reflect epigenetic patterns that have already been influenced by the onset of the disease.
Methods
Studying breast cancer, we established genome-scale DNA methylation profiles of prospectively collected buffy coat samples (n = 702) from a case–control study nested within the EPIC-Heidelberg cohort using reduced representation bisulphite sequencing (RRBS).
Results
We observed cancer-specific DNA methylation events in buffy coat samples. Increased DNA methylation in genomic regions associated with SURF6 and REXO1/CTB31O20.3 was linked to the length of time to diagnosis in the prospectively collected buffy coat DNA from individuals who subsequently developed breast cancer. Using machine learning methods, we piloted a DNA methylation-based classifier that predicted case–control status in a held-out validation set with 76.5% accuracy, in some cases up to 15 years before clinical diagnosis of the disease.
Conclusions
Taken together, our findings suggest a model of gradual accumulation of cancer-associated DNA methylation patterns in peripheral blood, which may be detected long before clinical manifestation of cancer. Such changes may provide useful markers for risk stratification and, ultimately, personalized cancer prevention.
Funder
European Commission (EC) Seventh Framework Programme (FP7) Translational Cancer Research (TRANSCAN) Framework
Institut National Du Cancer
Fondation ARC pour la Recherche sur le Cancer
Ligue Contre le Cancer
Publisher
Springer Science and Business Media LLC
Subject
Genetics (clinical),Developmental Biology,Genetics,Molecular Biology
Cited by
4 articles.
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