Identifying Novel Serum, Plasma, and Urine Biomarkers of Occult Ovarian Cancer

本研究的目的是使用高通量质谱和其他蛋白质组学技术对来自接受风险降低输卵管卵巢切除术（RRSO）的高危女性的血清、血浆和尿液样本进行鉴定新的卵巢癌生物标志物。鉴定癌症生物标志物的常用方法是从临床上已经鉴定为患有靶癌症但在任何治疗干预之前的受试者获得样品，并与来自未患该疾病的受试者的样品进行比较。然后提出将病例与对照很好地分开的推定标记作为进一步测试的候选者，特别是将早期病例与对照分开的标记。结合非线性统计分析的高通量质谱最近证明，谱中的峰的模式可以将所有病例与大多数对照分开。然而，使用术前样本会出现两个问题。第一个是，临床鉴定的早期疾病可能是体积大的、有症状的疾病，并且鉴定的标记物可能仅是癌变过程后期体积大的疾病的指标。第二个问题是，临床确定的早期疾病不是早期检测计划的目标疾病。事实上，早期检测计划旨在识别早期疾病中的无症状受试者，这些受试者将在临床上被识别为晚期疾病。计划进行RRSO的受试者形成了用于鉴定对低容量、无症状、早期疾病敏感的生物标志物的理想队列。通常，由于已知的BRCA突变或卵巢癌和乳腺癌的强烈家族史，接受RRSO的个体处于卵巢癌的高风险中。在RRSO后大约10%的卵巢中发现了隐匿性卵巢癌。将在术前和术后从接受RRSO的大型受试者队列中获得生物标本。全面的病理学审查将确定患有隐匿性卵巢癌的受试者（病例）和没有卵巢癌的受试者（对照）。将采用高通量质谱法，然后采用非线性统计分类方法，以识别尽可能将病例与非病例分开的峰模式。另一种方法，2D DIGE（二维数字凝胶电泳）也将用于鉴定潜在的血清/血浆或尿液生物标志物。在鉴定最有希望的峰/点模式之后，确定对应于峰/点的蛋白质和肽 将通过LC-MS/MS进行鉴定。将针对模式中六种最重要的蛋白质/肽开发单克隆抗体，从抗体开发免疫测定，并最终针对剩余的生物样本等分试样进行测试，以通过进一步应用非线性分类方法来验证和增强模式鉴定。

The aim of this study is to identify novel ovarian cancer biomarkers using high throughput mass spectrometry and other proteomic techniques on serum, plasma, and urine samples from high risk women undergoing risk reducing salpingo oophorectomy (RRSO). An often used approach to identifying cancer biomarkers is to obtain samples from subjects already clinically identified as having the target cancer but prior to any treatment intervention, and compare with samples from subjects without the disease. Putative markers which separate well the cases from the controls are then proposed as candidates for further testing, especially markers which separate early stage cases from controls. High throughput mass spectroscopy coupled with non-linear statistical analyses has recently demonstrated that patterns of peaks in the spectra can separate all cases from most controls. However, two issues arise with using pre-operative samples. The first is that clinically identified early stage disease is likely to be bulky, symptomatic disease, and the markers identified may be indicators only of bulky disease late in the carcinogenesis process. The second issue is that clinically identified early stage disease is not the target disease for an early detection program. In fact, an early detection program aims to identify asymptomatic subjects in early stage disease that would have been clinically identified in late stage disease. Subjects planning on RRSO form an ideal cohort for identification of biomarkers which are sensitive to low volume, asymptomatic, early stage disease. Usually individuals who undergo RRSO are at high risk of ovarian cancer due to known BRCA mutations or a strong family history of ovarian and breast cancer. Occult ovarian cancer has been identified in approximately 10% of ovaries following RRSO. Biospecimens will be obtained from a large cohort of subjects undergoing RRSO prior to and following surgery. A comprehensive pathology review will identify the subjects with occult ovarian cancer (cases) and subjects without ovarian cancer (controls). High throughput mass spectrometry followed by non-linear statistical classification methods will be utilized to identify patterns of peaks which separate cases as much as possible from non-cases. An alternative methodology, 2D DIGE (2 dimensional digital gel electrophoresis) will also be applied to identify potential serum/plasma or urine biomarkers. Following identification of the most promising peak/spot pattern, proteins and peptides corresponding to the peaks/spots will be identified through LC-MS/MS. Monoclonal antibodies will be developed for the six most important proteins/peptides in the pattern, immunoassays developed from the antibodies, and finally tested against the remaining aliquots ofbiospecimens to verify and enhance pattern identification through further application of non-linear classification methods.