Article

Peripheral Blood Immune Cell Methylation Profiles Are Associated with Nonhematopoietic Cancers

Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA.
Cancer Epidemiology Biomarkers & Prevention (Impact Factor: 4.32). 06/2012; 21(8):1293-302. DOI: 10.1158/1055-9965.EPI-12-0361
Source: PubMed

ABSTRACT Blood leukocytes from patients with solid tumors exhibit complex and distinct cancer-associated patterns of DNA methylation. However, the biologic mechanisms underlying these patterns remain poorly understood. Because epigenetic biomarkers offer significant clinical potential for cancer detection, we sought to address a mechanistic gap in recently published works, hypothesizing that blood-based epigenetic variation may be due to shifts in leukocyte populations.
We identified differentially methylated regions (DMR) among leukocyte subtypes using epigenome-wide DNA methylation profiling of purified peripheral blood leukocyte subtypes from healthy donors. These leukocyte-tagging DMRs were then evaluated using epigenome-wide blood methylation data from three independent case-control studies of different cancers.
A substantial proportion of the top 50 leukocyte DMRs were significantly differentially methylated among head and neck squamous cell carcinoma (HNSCC) cases and ovarian cancer cases compared with cancer-free controls (48 and 47 of 50, respectively). Methylation classes derived from leukocyte DMRs were significantly associated cancer case status (P < 0.001, P < 0.03, and P < 0.001) for all three cancer types: HNSCC, bladder cancer, and ovarian cancer, respectively and predicted cancer status with a high degree of accuracy (area under the curve [AUC] = 0.82, 0.83, and 0.67).
These results suggest that shifts in leukocyte subpopulations may account for a considerable proportion of variability in peripheral blood DNA methylation patterns of solid tumors.
This illustrates the potential use of DNA methylation profiles for identifying shifts in leukocyte populations representative of disease, and that such profiles may represent powerful new diagnostic tools, applicable to a range of solid tumors.

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