Journal
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
Volume 21, Issue 8, Pages 1293-1302Publisher
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1055-9965.EPI-12-0361
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Funding
- U.S. NIH grants [R01 CA121147, R01 CA078609, R01 CA100679, P42 ES007373, R01 CA57494, RO1 CA52689, NIEHS ES06717, P50 CA097257]
- Flight Attendant Medical Research Institute [YCSA052341]
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Background: 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. Methods: 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. Results: 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). Conclusions: These results suggest that shifts ill leukocyte subpopulations may account for a considerable proportion of variability in peripheral blood DNA methylation patterns of solid tumors. Impact: 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. Cancer Epidemiol Biomarkers Prep; 21(8); 1293-302. (c) 2012 AACR.
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