Early Detection of Ovarian Cancer Through Epigenetic Factors in the WHI

描述（由申请人提供）：卵巢癌是美国女性癌症死亡的第五大原因; 62%的病例在晚期被诊断，其中只有27%的患者存活超过5年。然而，当卵巢癌在局部阶段被检测到时（15%的病例），5年生存率为94%。由于如果早期诊断，生存率会大大提高，因此通过加强风险评估改善早期发现的方法，从而更有针对性地进行初级预防和筛查至关重要。Rosner和Pfeiffer的两个经过验证的风险评估模型识别出卵巢癌风险较高的女性，但只有适度的区分能力。目前，没有有效的筛查模式存在卵巢癌。以前在平均风险人群中使用单一标志物如CA-125进行筛查的方法一直不成功，并导致许多假阳性结果。识别对早期癌变重要的新的标志物组是关键;表观遗传事件（DNA甲基化）被注意到在癌变早期发生，并反映环境损伤和遗传脆弱性。测量游离DNA中的DNA甲基化已经显示出用于早期检测和筛查其他癌症的前景。新出现的证据表明，在组织和血浆中测量的选定基因的DNA甲基化导致检测卵巢癌的灵敏度>75%。然而，卵巢癌的所有证据都来自小型横断面或回顾性临床研究，没有或只有有限的流行病学数据，引起了对时间性和混淆的担忧。我们建议通过鉴定一组可以早期检测卵巢癌的DNA甲基化标志物来复制和建立这些有希望的发现。利用美国最大的女性健康前瞻性研究之一女性健康倡议（WHI），我们将验证肿瘤与邻近非肿瘤组织中测量的96个关键基因（由癌症基因组图谱（TCGA）发现）的DNA甲基化差异。使用高通量靶向重测序。从这96个TCGA基因中，我们将鉴定通过组织学差异甲基化的前10个基因（n对=200;目标1）。在巢式病例对照（ncases=610; Aim 2）中，我们将检查血浆中测量的这10个基因的DNA甲基化是否是癌症诊断前几年卵巢癌风险的预测因子。在目标3中，我们将评估DNA甲基化标志物的整体性能，以增强现有卵巢癌风险模型的准确性，区分度和假阳性（n= 161，808名女性）。我们将在一个独立的前瞻性队列中验证我们的发现，乳腺癌家族登记（BCFR）; n= 11，950个家庭; ncases=164; Aim 4）。WHI和BCFR是实现这些目标的理想研究;两者都收集了生物标本和详细的流行病学数据。我们将采用一种新的双层方法来早期检测卵巢癌，该方法检查卵巢癌风险谱（一级预防）中有希望的生物标志物（二级预防）。我们的目标是通过准确识别高风险个体和早期检测的可靠标志物，我们将减少卵巢癌的假阳性，发病率和死亡率。

DESCRIPTION (provided by applicant): Ovarian cancer is the 5th leading cause of cancer death among US women; 62% of cases are diagnosed at advanced stages in which only 27% survive past 5 years. Yet, when ovarian cancer is detected at the localized stage (15% of cases), the 5 year survival rate is 94%. As survival is drastically improved if diagnosed early, methods to improve early detection through enhanced risk assessment, leading to better targeted primary prevention and screening are critical. The two validated risk assessment models from Rosner and Pfeiffer identify women at higher risk for ovarian cancer, but only have modest discriminatory power. Currently, no effective screening modality exists for ovarian cancer. Previous approaches for screening using single markers such as CA-125 in average risk populations have been unsuccessful, and led to many false positive results. Identifying novel panels of markers important to early carcinogenesis is key; epigenetic events (DNA methylation) are noted to occur early in carcinogenesis and reflect environmental insults and genetic vulnerability. Measurement of DNA methylation in cell free DNA has shown promise for early detection and screening for other cancers. Emerging evidence has shown that DNA methylation of select genes measured in tissue and plasma results in sensitivities >75% for detecting ovarian cancer. Yet, all evidence for ovarian cancer comes from small cross-sectional or retrospective clinical studies with no or limited epidemiologic data, raising concerns about temporality and confounding. We propose to replicate and build upon these promising findings by identifying a panel of DNA methylation markers that can detect ovarian cancer early. Using the Women's Health Initiative (WHI), one of the largest prospective studies in the US for women's health, we will verify differences in DNA methylation of 96 key genes (discovered by The Cancer Genome Atlas (TCGA)) measured in tumor vs. adjacent non tumor tissue using high throughput targeted resequencing. From these 96 TCGA genes, we will identify the top 10 genes that are differentially methylated by histology (npairs=200; Aim 1). In a nested case control (ncases=610; Aim 2), we will examine if DNA methylation of these top 10 genes measured in plasma are predictors of ovarian cancer risk years prior to cancer diagnosis. In Aim 3, we will evaluate the overall performance of DNA methylation markers to enhance existing ovarian cancer risk models in terms of accuracy, discrimination and false positives (n=161,808 women). We will validate our findings in an independent prospective cohort, the Breast Cancer Family Registry ((BCFR); n=11,950 families; ncases=164; Aim 4). The WHI and BCFR are ideal studies to conduct these aims; both have collected biospecimens and detailed epidemiologic data. We will employ a novel two-tiered approach for early detection of ovarian cancer that examines promising biomarkers (secondary prevention) across the spectrum of ovarian cancer risk (primary prevention). Our goal is through accurate identification of high risk individuals and reliable markers of early detection, we will reduce false positives, morbidity and mortality from ovarian cancer.