Objective: To explore the serum cyclic polypeptide biomarkers for ovarian cancer diagnosis. Methods: A total of 54 patients with epithelial ovarian cancer confirmed by pathology in Cancer Hospital, Chinese Academy of Medical Sciences from March 2018 to September 2018 were selected as the study subjects, and 40 healthy women with normal examination results in the cancer screening center were selected as the control. All of the samples were randomly divided into training set and validation set at the ratio of 1∶1 with a random number. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with magnetic bead technology was used for detecting peptide profiling in serum samples to screen significantly differently expressed peptides between ovarian cancer group and control group of the training set (score>5). Receiver operating characteristic (ROC) curve analysis was used to screen differential peptide peaks with area under curve (AUC) ≥0.8, sensitivity and specificity>90% in the training set and validation set. Liquid chromatography-mass spectrometry (LC-MS/MS) was further used to determine the composition of differentially expressed peptides. Results: By comparing the peptide profiles of the two groups, 102 differential peptide peaks were initially detected in the mass-to-charge ratio range of 1 000 to 10 000. ROC curve analysis showed that there were 42 differential peptide peaks with AUC ≥0.8 in both training set and validation set, 19 of which were highly expressed in ovarian cancer group, and 23 were lowly expressed. There were 15 different peptide peaks in highly expressed ovarian cancer group with sensitivity and specificity over 90%. The mass-to-charge ratios were 7 744.27, 5 913.41, 5 329.87, 4 634.21, 4 202.02, 3 879.26, 3 273.35, 3 253.79, 3 234.34, 2 950.33, 2 664.51, 2 018.38, 1 893.37, 1 498.69 and 1 287.55. There were 15 different peptide peaks in lowly expressed ovarian cancer group with sensitivity and specificity over 90%, the mass-to-charge ratios were 9 288.46, 7 759.77, 5 925.24, 4 652.77, 4 210.42, 3 887.02, 3 279.90, 3 240.82, 2 962.15, 2 932.70, 2 022.42, 1 897.16, 1 501.69, 1 337.38 and 1 290.13. No protein composition was identified in 15 different peptide peaks in lowly expressed ovarian cancer group. The two protein compositions identified in 15 different peptide peaks in highly expressed ovarian cancer group were recombinant serglycin (SRGN) and fibinogen alpha chain (FGA), the mass-to-charge ratios of which were 1 498.696 and 5 913.417, respectively. The sensitivity and specificity of the two proteins for ovarian cancer diagnosis were 100%, 100% and 90.9%, 100%, respectively. Conclusion: SRGN and FGA are highly expressed in the serum of ovarian cancer patients, which may be potential diagnostic markers for ovarian cancer.
目的： 探寻与卵巢癌诊断相关的血清循环多肽标志物。 方法： 以2018年3月至2018年9月中国医学科学院肿瘤医院妇瘤科收治的原发卵巢上皮癌患者54例(卵巢癌组)、同期在中国医学科学院肿瘤医院体检中心进行体检的健康女性40例(健康对照组)为研究对象。采用随机数字表法，将例卵巢癌患者和健康对照者各按1∶1随机分为训练集和验证集。采用基质辅助激光解吸离子飞行时间质谱(MALDI-TOF-MS)联合磁珠技术检测血清多肽峰，在训练集中筛选卵巢癌组与健康对照组间的差异多肽峰(评分>5)。采用受试者工作特征(ROC)曲线分析，在训练集和验证集中，筛选曲线下面积(AUC)均≥0.8、诊断卵巢癌的灵敏度和特异度均>90%的差异多肽峰。采用液相色谱-质谱/质谱(LC-MS/MS)技术鉴定差异多肽峰的成分。 结果： 在质荷比1 000~10 000范围内，卵巢癌组和健康对照组之间有102个差异多肽峰。ROC曲线分析显示，在训练集和验证集中，AUC均≥0.8的差异多肽峰有42个，其中19个在卵巢癌组血清中高表达，23个低表达；诊断卵巢癌灵敏度与特异度均≥90%的卵巢癌血清高表达差异多肽峰有15个，质荷比分别为7 744.27、5 913.41、5 329.87、4 634.21、4 202.02、3 879.26、3 273.35、3 253.79、3 234.34、2 950.33、2 664.51、2 018.38、1 893.37、1 498.69和1 287.55；诊断卵巢癌灵敏度与特异度均≥90%的卵巢癌血清低表达差异多肽峰有15个，质荷比分别为9 288.46、7 759.77、5 925.24、4 652.77、4 210.42、3 887.02、3 279.90、3 240.82、2 962.15、2 932.70、2 022.42、1 897.16、1 501.69、1 337.38和1 290.13。在卵巢癌患者血清低表达的15个差异多肽峰中未鉴定出多肽峰的蛋白成分，在卵巢癌患者血清高表达的15个差异多肽峰中鉴定出2个多肽峰的蛋白成分，质荷比为1 498.70者是丝甘蛋白聚糖(SRGN)，质荷比为5 913.42者是纤维蛋白原α链(FGA)，二者在全部研究对象中诊断卵巢癌的灵敏度均为100%，特异度分别为90.9%和100%。 结论： SRGN和FGA在卵巢癌患者血清中高表达，可能是潜在的卵巢癌诊断标志物。.
Keywords: Diagnosis; Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry; Ovarian neoplasms; Polypeptide.