Buffy coat signatures of breast cancer risk in a prospective cohort study

Chung, Felicia Fei Lei * and Maldonado, Sandra Gonzalez and Nemc, Amelie and Bouaoun, Liacine and Cahais, Vincent and Cuenin, Cyrille and Salle, Aurelie and Johnson, Theron and Erguner, Bekir and Laplana, Marina and Datlinger, Paul and Jeschke, Jana and Weiderpass, Elisabete and Kristensen, Vessela and Delaloge, Suzette and Fuks, Francois and Risch, Angela and Ghantous, Akram and Plass, Christoph and Bock, Christoph and Kaaks, Rudolf and Herceg, Zdenko (2023) Buffy coat signatures of breast cancer risk in a prospective cohort study. Clinical Epigenetics, 15 (1). ISSN 1868-7075

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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.

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