Novel Serum, Plasma, and Urine Biomarkers of Ovarian Can

本研究的目的是利用高通量质谱法和其他蛋白质组学技术，对接受降低风险输卵管卵巢切除术（RRSO）的高风险妇女的血清、血浆和尿液样本进行鉴定新的卵巢癌生物标志物。识别癌症生物标志物的一种常用方法是，在任何治疗干预之前，从已经被临床鉴定为患有目标癌症的受试者中获取样本，并与未患病受试者的样本进行比较。然后提出将病例与对照区分开的假定标记物作为进一步测试的候选物，特别是将早期病例与对照区分开的标记物。高通量质谱结合非线性统计分析最近表明，光谱中的峰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。首先，临床发现的早期疾病很可能是体积较大的、有症状的疾病，而发现的标志物可能只是癌变过程后期体积较大的疾病的指标。第二个问题是临床发现的早期疾病并不是早期检测项目的目标疾病。事实上，早期检测计划的目的是在早期疾病中识别无症状的受试者，而这些受试者在晚期疾病中会被临床识别出来。计划进行RRSO的受试者形成了一个理想的队列，用于鉴定对小体积、无症状、早期疾病敏感的生物标志物。通常，由于已知的BRCA突变或强烈的卵巢癌和乳腺癌家族史，接受RRSO的个体患卵巢癌的风险很高。大约10%的卵巢在RRSO后发现隐匿性卵巢癌。生物标本将从手术前后接受RRSO的大量受试者中获得。全面的病理检查将确定隐匿性卵巢癌患者（病例）和无卵巢癌患者（对照组）。将利用高通量质谱法和非线性统计分类方法来识别尽可能将病例与非病例分开的峰的模式。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。在确定最有希望的峰/点模式后，与峰/点对应的蛋白质和肽

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.