基于蛋白组学技术筛选卵巢癌早期诊断生物学标记物的前瞻性研究

The study will use quantitative proteomic approaches to identify predictive proteins in bio-samples from ovarian cancer patients，including tissue and serum，compared to those from benign tumor patients and healthy control people，respectively．Tissues and serum from patients in early pathological stage and middle-late stages are regarded as two independent groups in this quantitative proteomics study．Ultra high resolution OrbiTrap mass spectrometry coupled with 2D-nano-LC of extensive protein fractionation (2D-nano-LC-ESI- OrbiTrap MS/MS) was used in this study．Quantitation was achieved by isobaric tags for relative and absolute quantitation (iTRAQ)．We propose to obtain quantitatively expressed proteins in bio-samples from ovarian cancer patients，compared to those from benign tumor patients and the healthy people．Proteins with expression ratios of over 1.5-fold in increase or decrease were considered differentially expressed．Among the differential expressed proteins，we will interpret 3-6 most important differential proteins　and validate them using Western Blotting technology．We wish we will find some useful differentially expressed proteins in this study，potentially to be used as biomarkers for the predictive or early detection of ovarian cancer in the clinical service．

卵巢癌死亡率有逐年上升趋势，位居妇科恶性肿瘤之首，严重危害新疆各族妇女的健康及社会和谐发展。由于缺乏有效的早期诊断方法，70％卵巢癌患者确诊时已为晚期，治疗费用高且预后差。而早期诊断可以明显降低卵巢癌患者的死亡率。早期诊断的一个途径是寻找理想的肿瘤标志物。目前卵巢癌临床使用的标记物CA125敏感性和特异性均不能满足早期诊断的需要。蛋白质组学技术为筛选早期诊断的肿瘤标记物提供了有效途径。课题应用shotgun蛋白组学研究方法，基于相对和绝对定量同位素标记（iTRAQ）和两维高效液相色谱-电喷雾-OrbiTrap质谱分离检测技术平台对早、中晚期卵巢癌、良性卵巢囊肿、正常生物样本（组织和血清）进行定量蛋白组学研究，建立卵巢癌差异蛋白列表，筛选区别早卵巢癌有意义的3-6个差异蛋白，采用Western-blot进行临床样本差异蛋白验证,建立ROC曲线，为探寻卵巢癌早期诊断标记物奠定一定的基础。

课题应用shotgun蛋白组学研究方法，基于相对和绝对定量同位素标记（iTRAQ）和两维高效液相色谱-电喷雾-OrbiTrap质谱分离检测技术平台对早、中晚期卵巢癌、良性卵巢囊肿、正常生物样本（组织和血清）进行定量蛋白组学研究，得出结果：1）卵巢癌患者血清中的差异代谢物主要涉及的受扰动的代谢通路包括: 糖酵解、三羧酸循环、尿素循环、谷氨酰胺与谷氨酸代谢、脂肪酸代谢和脯氨酸代谢等；2）以定量蛋白测定结果中早期卵巢癌、良性卵巢肿瘤和正常对照卵巢组织的三组样本，差异倍数>2倍筛选，共得到682个差异蛋白。基于差异倍数和Kruskal-Wallis检验分析，从蛋白组学研究中得到的显著差异蛋白中，选择了5个显著差异的蛋白质，包括P4HB、KRT18、DES、AOC1和IDH2蛋白；3）差异蛋白AOC1在临床上常用的受试者工作特征曲线分析中ROC曲线下面积为0.820 [0.820；95%置信区间(95%CI)，0.689-0.951]，显示出很好的和灵敏度和特异度，可以用于区分早期卵巢癌组织和CA-125升高的良性卵巢肿瘤。为探寻卵巢癌早期诊断标记物奠定一定的基础。