ABSTRACT

Leukocyte cell proportion changes affect the detection of cancer-associated aberrant DNA methylation alterations in peripheral blood samples. We aimed to detect cellular DNA methylation changes in ovarian cancer (OVC) blood samples avoiding the above-mentioned cell-composition effects. Based on the within-sample relative methylation orderings (RMOs) of CpG loci in leukocyte subtypes, we developed the Ref-RMO method to detect aberrant methylation alterations from OVC blood samples. Stable CpG pairs with consistent RMOs in different leukocyte subtypes were determined, more than 99% of which retained their RMO patterns in peripheral whole blood (PWB) in independent datasets. Based on the stable CpG pairs, significantly reversed CpG pairs were detected from OVC PWB samples, which were relative to clinical information such as age, subtype, grade, stage, or CA125 level. Results showed 439 CpG loci were determined to be significant differential DNA methylations between OVC and healthy blood samples. They were mainly enriched in KEGG pathways, such as cytokine-cytokine receptor interaction, apoptosis, proteoglycans in cancer, and immune-associated Gene Ontology terms. STRING analysis showed that they tended to have functional interactions with cancer-associated genes recorded in the COSMIC database. Leukocyte cellular differential DNA methylations could be identified by the proposed RMO-based method from OVC PWB samples, which were cancer-associated aberrant signals against cell-composition effects.

摘要

白细胞比例变化影响外周血样本中癌症相关异常 DNA 甲基化改变的检测。我们旨在检测卵巢癌 (OVC) 血液样本中的细胞 DNA 甲基化变化，避免上述细胞组成效应。基于白细胞亚型中 CpG 基因座的样本内相对甲基化排序 (RMO)，我们开发了 Ref-RMO 方法来检测 OVC 血液样本中的异常甲基化改变。确定了在不同白细胞亚型中具有一致 RMO 的稳定 CpG 对，其中超过 99% 在独立数据集中保留了外周全血 (PWB) 中的 RMO 模式。基于稳定的 CpG 对，从 OVC PWB 样本中检测到显着逆转的 CpG 对，这些对与年龄、亚型、分级、分期等临床信息相关。或 CA125 级别。结果显示，439 个 CpG 基因座被确定为 OVC 和健康血液样本之间的显着差异 DNA 甲基化。它们主要富集于 KEGG 通路，例如细胞因子-细胞因子受体相互作用、细胞凋亡、癌症中的蛋白聚糖和免疫相关的基因本体论术语。STRING 分析表明，它们倾向于与 COSMIC 数据库中记录的癌症相关基因发生功能性相互作用。白细胞细胞差异 DNA 甲基化可以通过所提出的基于 RMO 的方法从 OVC PWB 样本中识别出来，这是与癌症相关的针对细胞组成效应的异常信号。例如细胞因子-细胞因子受体相互作用、细胞凋亡、癌症中的蛋白聚糖和免疫相关的基因本体论术语。STRING 分析表明，它们倾向于与 COSMIC 数据库中记录的癌症相关基因发生功能性相互作用。白细胞细胞差异 DNA 甲基化可以通过所提出的基于 RMO 的方法从 OVC PWB 样本中识别出来，这是与癌症相关的针对细胞组成效应的异常信号。例如细胞因子-细胞因子受体相互作用、细胞凋亡、癌症中的蛋白聚糖和免疫相关的基因本体论术语。STRING 分析表明，它们倾向于与 COSMIC 数据库中记录的癌症相关基因发生功能性相互作用。白细胞细胞差异 DNA 甲基化可以通过所提出的基于 RMO 的方法从 OVC PWB 样本中识别出来，这是与癌症相关的针对细胞组成效应的异常信号。