DNA Methylation and Ovarian Cancer

卵巢癌是女性癌症中死亡率最高的。这种疾病的基本生物学知识知之甚少，现有的诊断和预后方法也不充分。基于CpG岛的甲基化改变在癌症中起重要作用的假设，我们开发了一种基于微阵列的技术，称为差异甲基化杂交(DMH)。DMH可以对肿瘤基因组中的CpG岛甲基化进行全球分析，这是一种确定癌细胞甲基化特征的方法，并有可能作为一种特定部位的诊断方法来测试是否可以识别特定位点的去甲基化。此前，我们使用DMH对一小部分患者进行了卵巢癌的甲基化分析，建立了概念验证，并为全基因组甲基化筛查奠定了基础，以检查卵巢癌的表观类型-表型关系。在本研究中，我们将使用包含21,000个CpG岛的DMH阵列对卵巢癌进行甲基化分析。诊断为早期和晚期卵巢癌患者的卵巢肿瘤甲基化情况将与正常卵巢表面上皮细胞进行比较。总体甲基化模式将被用来作为表观遗传特征来描述特定类型和阶段的卵巢癌，这些分子特征将与患者的临床病理参数相关联。确定的特定甲基化模式稍后可以用于在临床环境中预测患者的结果。得到的阵列数据将用于鉴定卵巢癌中经常发生甲基化的特定CpG岛序列。由于这些基因在成人组织中通常不甲基化，CpG岛甲基化是迄今发现的最常见的肿瘤特异性标记物之一。当与特定基因相关时，CpG岛甲基化可能会对卵巢肿瘤类型产生影响。此外，我们还通过使用表达的CpG岛序列标签(ECIST)进一步提纯了DMH，用于双重检测癌细胞中的CpG高甲基化和基因表达/沉默。ECIST存在于基因组中，其富含GC的片段可用于筛查癌细胞中异常甲基化的CpG位点。含有外显子的部分可以用来同时测量基因表达水平。使用我们最近开发的ECIST小组，我们将识别卵巢癌样本中的高甲基化基因座，同时确认它们与基因沉默的关联。这种方法还将使我们能够研究卵巢癌中基因启动子的活性，并评估筛选基因启动子功能在这种疾病中的重要性。总而言之，这项研究将解决为卵巢癌筛查和分期开发更好工具的明显需要，以及确定充分解决这种疾病复杂性的新标记物的需要。卵巢肿瘤的甲基化图谱可以为甲基化沉默的基因作为治疗靶点的重新激活提供更有针对性的测试，从而为旨在改变卵巢癌这一基本过程的新的临床策略提供合理的基础。

Ovarian cancer has the highest mortality rates of female cancers. The underlying biology of this disease is poorly understood and the existing approaches for diagnosis and prognosis are inadequate. Based on the hypothesis that methylation changes at CpG islands play a prominent role in cancer, we developed a microarray-based technique called differential methylation hybridization (DMH). DMH allows for the global analysis of CpG island methylation in tumor genomes, a method to determine methylation profiles of cancer cells, and has the potential use as a site specific diagnostic approach to test whether demethylation at specific loci can be identified. Previously, we used DMH on a small group of patients to perform methylation profiling of ovarian cancer, establish proof-of- concept and lay the foundation for genome wide screening of methylation to examine epigenotype-phenotype relationships in ovarian cancer. In the present study, we will perform methylation profiling of ovarian cancer using DMH arrays containing 21,000 CpG islands. Methylation profiles of ovarian tumors from patients diagnosed with early and advanced ovarian cancer will be compared to normal ovarian surface epithelium. Overall methylation patterns will be used as an "epigenetic signature" to characterize specific types and stages of ovarian cancer, and these molecular signatures will be correlated with clinicopathological parameters of the patients. Specific methylation patterns identified can later be applied to predict patients' outcome in clinical settings. The resulting array data will be used to identify the specific CpG island sequences frequently hypermethylated in ovarian cancer. As these are not normally methylated in adult tissues, CpG island methylation represents one of the most prevalent tumor specific markers yet identified. When associated with specific genes, CpG island methylation may have consequences for ovarian tumor types. In addition, we have further refined DMH by using expressed CpG island sequence tags (ECISTs) for dual detection of CpG hypermethylation and gene expression/silencing in cancer cells. ECISTs exist in the genome, and their GC-rich fragments can be used to screen aberrantly methylated CpG sites in cancer cells. The exon-containing portions can be employed to measure levels of gene expression simultaneously. Using an ECIST panel we have recently developed, we will identify hypermethylated loci and at the same time confirm their association with gene silencing in the ovarian cancer samples. This approach will also allow us to study gene promoter activity in ovarian cancer and assess the importance of screening for gene promoter functions in this disease. In summary, this study will address the clear need for developing better tools for the screening and staging of ovarian cancer, as well as the need to identify new markers that adequately address the complexity of this disease. Methylation profiling of ovarian tumors could provide a more focused test for reactivation of methylation-silenced genes as therapeutic targets and thus play a role in the rational basis for new clinical strategies designed to alter this fundamental process in ovarian cancer.