Peripheral blood immune cell methylation profiles are associated with nonhematopoietic cancers.
Peripheral blood immune cell methylation profiles are associated with nonhematopoietic cancers.
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DOI：
10.1158/1055-9965.epi-12-0361
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发表时间：
2012-08
期刊：
影响因子：
--
通讯作者：
Kelsey KT
中科院分区：
文献类型：
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作者：
Koestler DC;Marsit CJ;Christensen BC;Accomando W;Langevin SM;Houseman EA;Nelson HH;Karagas MR;Wiencke JK;Kelsey KT
实体瘤患者的血液白细胞表现出复杂且独特的癌症相关 DNA 甲基化模式。然而，这些模式背后的生物学机制仍然知之甚少。由于表观遗传生物标志物为癌症检测提供了巨大的临床潜力，我们试图解决最近发表的作品中的机制差距，假设基于血液的表观遗传变异可能是由于白细胞群体的变化造成的。我们利用来自健康供体的纯化外周血白细胞亚型的表观基因组 DNA 甲基化分析，鉴定了白细胞亚型之间的差异甲基化区域 (DMR)。然后使用来自不同癌症的三项独立病例对照研究的全表观基因组血液甲基化数据对这些白细胞标记 DMR 进行评估。与无癌对照相比，头颈鳞状细胞癌 (HNSCC) 病例和卵巢癌病例中前 50 个白细胞 DMR 中的很大一部分存在显着差异甲基化（50 例中分别为 48 例和 47 例）。来自白细胞 DMR 的甲基化类别分别与所有三种癌症类型（HNSCC、膀胱癌和卵巢癌）的癌症病例状态显着相关（p < 0.001、p < 0.03 和 p < 0.001），并且可以高度准确地预测癌症状态（AUC = 0.82、0.83 和 0.67）。这些结果表明，白细胞亚群的变化可能是实体瘤外周血 DNA 甲基化模式变异的很大一部分原因。这说明了 DNA 甲基化谱在识别代表疾病的白细胞群体变化方面的潜在效用，并且此类谱可能代表强大的新诊断工具，适用于一系列实体瘤。
Blood leukocytes from patients with solid tumors exhibit complex and distinct cancer-associated patterns of DNA methylation. However, the biological mechanisms underlying these patterns remain poorly understood. Since 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 (DMRs) 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 to cancer-free controls (48 and 47 out 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 (AUC = 0.82, 0.83, and 0.67). These results suggest that shifts in leukocyte sub-populations may account for a considerable proportion of variability in peripheral-blood DNA methylation patterns of solid tumors. This illustrates the potential utility 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.