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The integrative epigenomic-transcriptomic landscape of ER positive breast cancer

机译:ER阳性乳腺癌的综合表观基因组转录组学

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BackgroundWhile recent integrative analyses of copy number and gene expression data in breast cancer have revealed a complex molecular landscape with multiple subtypes and many oncogenic/tumour suppressor driver events, much less is known about the role of DNA methylation in shaping breast cancer taxonomy and defining driver events. ResultsHere, we applied a powerful integrative network algorithm to matched DNA methylation and RNA-Seq data for 724 estrogen receptor (ER)-positive (ER+) breast cancers and 111 normal adjacent tissue specimens from The Cancer Genome Atlas (TCGA) project, in order to identify putative epigenetic driver events and to explore the resulting molecular taxonomy. This revealed the existence of nine functionally deregulated epigenetic hotspots encompassing a total of 146 genes, which we were able to validate in independent data sets encompassing over 1000 ER+ breast cancers. Integrative clustering of the matched messenger RNA (mRNA) and DNA methylation data over these genes resulted in only two clusters, which correlated very strongly with the luminal-A and luminal B subtypes. Overall, luminal-A and luminal-B breast cancers shared the same epigenetically deregulated hotspots but with luminal-B cancers exhibiting increased aberrant DNA methylation patterns relative to normal tissue. We show that increased levels of DNA methylation and mRNA expression deviation from the normal state define a marker of poor prognosis. Our data further implicates epigenetic silencing of WNT signalling antagonists and bone morphogenetic proteins (BMP) as key events underlying both luminal subtypes but specially of luminal-B breast cancer. Finally, we show that DNA methylation changes within the identified epigenetic interactome hotspots do not exhibit mutually exclusive patterns within the same cancer sample, instead exhibiting coordinated changes within the sample. ConclusionsOur results indicate that the integrative DNA methylation and transcriptomic landscape of ER+ breast cancer is surprisingly homogeneous, defining two main subtypes which strongly correlate with luminal-A/B subtype status. In particular, we identify WNT and BMP signalling as key epigenetically deregulated tumour suppressor pathways in luminal ER+ breast cancer, with increased deregulation seen in luminal-B breast cancer.
机译:背景技术尽管最近对乳腺癌的拷贝数和基因表达数据进行了综合分析,发现具有多种亚型和许多致癌/肿瘤抑制因子驱动​​物事件的复杂分子格局,但人们对DNA甲基化在塑造乳腺癌分类学和确定驱动因子中的作用了解甚少。事件。结果在这里,我们应用了功能强大的集成网络算法,以匹配来自癌症基因组图谱(TCGA)项目的724种雌激素受体(ER)阳性(ER +)乳腺癌和111例正常相邻组织标本的DNA甲基化和RNA-Seq数据,以确定推定的表观遗传驱动事件,并探讨由此产生的分子分类学。这表明存在9个功能失调的表观遗传热点,涵盖总共146个基因,我们能够在包含1000多个ER +乳腺癌的独立数据集中进行验证。匹配的信使RNA(mRNA)和这些基因上的DNA甲基化数据的整合聚类仅产生两个聚类,这些聚类与luminal-A和luminal B亚型非常相关。总体而言,腔A型和腔B型乳腺癌具有相同的表观遗传学失调热点,但腔B型癌症相对于正常组织显示出异常的DNA甲基化模式。我们显示,DNA甲基化水平的增加和mRNA与正常状态之间的偏差定义了不良预后的标志。我们的数据进一步暗示WNT信号拮抗剂和骨形态发生蛋白(BMP)的表观遗传沉默是两种管腔亚型(尤其是管腔B型乳腺癌)的关键事件。最后,我们表明,在确定的表观遗传学相互作用组热点中的DNA甲基化变化在同一癌症样品中不表现出互斥的模式,而在样品中表现出协调的变化。结论我们的结果表明ER +乳腺癌的整体DNA甲基化和转录组构象令人惊讶地均一,定义了与腔A / B亚型状态密切相关的两个主要亚型。特别是,我们确定WNT和BMP信号是管腔ER +乳腺癌中关键的表观遗传学失调的肿瘤抑制通路,在管腔B乳腺癌中可见失调增加。

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