Zhang Hui, Kong Beihua, Qu Xun, Jia Lin, Deng Biping, Yang Qifeng
Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Ji'nan 250012, Shandong Province, PR China.
Gynecol Oncol. 2006 Jul;102(1):61-6. doi: 10.1016/j.ygyno.2005.11.029. Epub 2006 Jan 5.
The purpose of this study is to discover potential biomarkers for the detection and monitoring of adjuvant chemotherapy for ovarian cancer.
Serum samples from ovarian cancers and non-cancer controls were analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). To discover the possible diagnostic biomarker for ovarian cancer, a preliminary training set of spectra derived from 31 primary ovarian cancer patients, 16 patients with benign ovarian diseases, and 25 healthy women was used to develop a proteomic model that discriminated cancer from non-cancer effectively. A blind test set, including 43 new cases, was used to validate the sensitivity and specificity of this multivariate model. To explore treatment-induced serum protein change, the protein profiles generated from 16 postoperative patients before chemotherapy are compared with those obtained after chemotherapy.
A Four-peak model was established in the training set that discriminated cancer from non-cancer with sensitivity of 90.8% and specificity of 93.5%. A sensitivity of 87.0% and a specificity of 95.0% for the blind test were obtained, compared with 60.7%, 55% for CA125 for the same samples. These 4 markers performed significantly better than the current standard marker, CA125 (P < 0.05). One protein peak (mass/charge ratio [m/z], 4,475) was identified in 12 of 16 (75%) postoperative patients after chemotherapy, but was absent before chemotherapy.
The proteins represented by these peaks are candidate biomarkers for ovarian cancer diagnosis and/or monitoring treatment response.
本研究旨在发现用于检测和监测卵巢癌辅助化疗的潜在生物标志物。
采用表面增强激光解吸/电离飞行时间质谱（SELDI-TOF-MS）分析卵巢癌患者和非癌对照者的血清样本。为发现卵巢癌可能的诊断生物标志物，使用来自31例原发性卵巢癌患者、16例良性卵巢疾病患者和25名健康女性的光谱初步训练集，建立能有效区分癌症与非癌症的蛋白质组学模型。使用包括43例新病例的盲测集来验证该多变量模型的敏感性和特异性。为探索治疗引起的血清蛋白变化，将16例术后患者化疗前产生的蛋白质谱与化疗后获得的蛋白质谱进行比较。
在训练集中建立了一个四峰模型，区分癌症与非癌症的敏感性为90.8%，特异性为93.5%。盲测的敏感性为87.0%，特异性为95.0%，而相同样本的CA125敏感性为60.7%，特异性为55%。这4种标志物的表现明显优于当前标准标志物CA125（P<0.05）。在16例术后患者中的12例（75%）化疗后鉴定出一个蛋白峰（质荷比[m/z]为4475），但化疗前不存在。
这些峰所代表的蛋白质是卵巢癌诊断和/或监测治疗反应的候选生物标志物。
