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Normal Cell-Type Epigenetics and Breast Cancer Classification: A Case Study of Cell Mixture–Adjusted Analysis of DNA Methylation Data from Tumors

机译:正常细胞类型的表观遗传学和乳腺癌分类:肿瘤DNA甲基化数据的细胞混合物校正分析的案例研究

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摘要

Historically, breast cancer classification has relied on prognostic subtypes. Thus, unlike hematopoietic cancers, breast tumor classification lacks phylogenetic rationale. The feasibility of phylogenetic classification of breast tumors has recently been demonstrated based on estrogen receptor (ER), androgen receptor (AR), vitamin D receptor (VDR) and Keratin 5 expression. Four hormonal states (HR0–3) comprising 11 cellular subtypes of breast cells have been proposed. This classification scheme has been shown to have relevance to clinical prognosis. We examine the implications of such phylogenetic classification on DNA methylation of both breast tumors and normal breast tissues by applying recently developed deconvolution algorithms to three DNA methylation data sets archived on Gene Expression Omnibus. We propose that breast tumors arising from a particular cell-of-origin essentially magnify the epigenetic state of their original cell type. We demonstrate that DNA methylation of tumors manifests patterns consistent with cell-specific epigenetic states, that these states correspond roughly to previously posited normal breast cell types, and that estimates of proportions of the underlying cell types are predictive of tumor phenotypes. Taken together, these findings suggest that the epigenetics of breast tumors is ultimately based on the underlying phylogeny of normal breast tissue.
机译:从历史上看,乳腺癌的分类依赖于预后的亚型。因此,与造血系统癌症不同,乳腺肿瘤分类缺乏系统发生的理由。最近已基于雌激素受体(ER),雄激素受体(AR),维生素D受体(VDR)和角蛋白5表达证明了对乳腺肿瘤进行系统发育分类的可行性。已经提出了包含11种乳腺癌细胞亚型的四种激素状态(HR0-3)。该分类方案已显示与临床预后相关。我们通过对基因表达综合总线上存档的三个DNA甲基化数据集应用最新开发的反卷积算法,研究了这种系统发育分类对乳腺肿瘤和正常乳腺组织的DNA甲基化的影响。我们提出,源自特定起源细胞的乳腺肿瘤实质上会放大其原始细胞类型的表观遗传状态。我们证明,肿瘤的DNA甲基化表现出与细胞特异性表观遗传状态一致的模式,这些状态大致对应于先前放置的正常乳腺细胞类型,并且对基础细胞类型比例的估计可预测肿瘤表型。综上所述,这些发现表明,乳腺肿瘤的表观遗传学最终基于正常乳腺组织的基础系统发育。

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