Dissecting Hierarchies of Epigenetic Control in Gene Silencing

激素相关的雌激素受体(ER)α信号在乳腺癌细胞中已经得到了广泛的研究。我们最近的研究首次揭示了表观遗传学(即染色质重塑和DMA甲基化)对ERpha下游靶基因转录的影响，并为这一经典信号通路的研究提供了一个新的方向。我们假设，破坏癌细胞中正常的ERAlpha信号可能会导致一些受表观遗传机制支配的下游靶点长期沉默。在这个项目中，我们将使用计算和基于微阵列的方法来定义导致这种表观遗传学建立的分子序列。位置权重矩阵方法将是 用于比对和识别大约350个新的和已知的ERAlpha靶，其5‘端序列将被排列用于三重微阵列分析。在这项微阵列研究中，这些基因座的外显子部分(外显子1)将用于测量转录本的表达水平，其启动子序列将用于筛选染色质结构的变化状态，富含GC的区域将用于检测目标序列中DNA甲基化的变化。将使用三重微阵列来同时分析这些ERAlpha 培养的乳腺癌细胞中雌激素信号被小干扰RNA干扰的靶点。一个经验的贝叶斯方法将被用来模拟RNA干扰后的表观遗传改变的序列。还将进行更多的微阵列实验，通过用DNA脱甲基剂和/或组蛋白脱乙酰酶抑制剂处理乳腺癌细胞来逆转这种表观遗传事件。结果可能会建立这样一个模型，即当ERpha信号中断时，多梳抑制物和组蛋白去乙酰基酶 被招募来启动审问ERAlpha靶标的转录沉默。这一事件随后伴随着DNA甲基化在这些靶子的启动子区域逐渐积累，这将留下一个可遗传的标记，稳定地传递给细胞的后代。额外的计算模拟将用于探索其他表观遗传事件序列。这一体外发现将通过在原发乳腺肿瘤中进行甲基化微阵列分析来证实。这项拟议的研究有望提供新的信息，即乳腺癌的激素不敏感部分归因于表观遗传介导的多个ERpha靶点的沉默，并希望为乳腺癌的表观遗传治疗提供理论基础。

The hormone-related estrogen receptor (ER)alpha signaling has been intensively studied in breast cancer cells. Our recent study has implicated, for the first time, the epigenetic influence (i.e., chromatin remodeling and DMA methylation) on the transcription of ERalpha downstream target genes and provides a new direction of research in this classical signaling pathway. We hypothesize that disruption of normal ERalpha signaling in cancer cells may lead to long-term silencing of some downstream targets that are governed by epigenetic mechanisms. In this project, we will use computational and microarray-based approaches to define the molecular sequences leading to this epigenetic establishment. A positional weight matrix approach will be used to align and identify approximately 350 novel and known ERalpha targets, the 5'-end sequences of which will be arrayed for triple microarray analysis. In this microarray study, the exon-containing portions (exon 1) of these loci will be used for measuring expression levels of transcripts, their promoter sequences will be used for screening altered states of chromatin structure, and the GC-rich regions will be used for detecting changes of DNA methylation in the target sequences. Triple microarray will be used to simultaneously analyze these ERalpha targets in cultured breast cancer cells in which estrogen signaling is disrupted by small interference RNA. An empirical Bayesian approach will be used to model the sequences of epigenetic alterations after the RNA interference. Additional microarray experiments will also be conducted to reverse this epigenetic event by treating breast cancer cells with DNA demethylating agents and/or histone deacetylase inhibitors. The results may establish a model that upon ERalpha signal disruption, polycomb repressers and histone deacetylases are recruited to initiate transcriptional silencing in the interrogating ERalpha targets. This event is later accompanied by progressive accumulation of DNA methylation in the promoter regions of these targets, which leave a heritable mark that stably passes down to cells' progeny. Additional computation simulations will be used to explore other sequences of epigenetic events. The in vitro finding will be confirmed by conducting methylation microarray analysis in primary breast tumors. This proposed study is expected to give new information that hormonal insensitivity in breast cancer is, in part, attributed to epigenetically mediated silencing of multiple ERalpha targets and hope to provide a rationale for epigenetic therapies in breast cancer.