蛋白质指纹图谱在乳腺癌诊断与随访中的应用研究

目的:应用表面加强激光解吸电离-飞行时间质谱(SELDI-TOF-MS)和CM10蛋白质芯片检测乳腺癌患者血清蛋白质指纹图谱,筛选候选肿瘤标志物,建立、验证诊断模型并初步探讨其在术后随访监测中的价值。方法:SELDI-TOF-MS技术及CM10芯片检测63例乳腺癌和40例健康人的指纹图谱,ZJU-PDAS软件筛选标志物、建立模型,在另23例乳腺癌和20例健康人中盲法验证模型;并检测16份术后标本以探索其随访监测价值。结果:质荷比(m/z)为3.9kD和5.6kD的2个蛋白质峰(分别命名为BC1和BC2)构建的模型诊断乳腺癌灵敏度为87.30%(55/63)、特异度为95.00%(38/40);盲法验证灵敏度为95.65%(22/23)、特异度为85.00%(17/20);对不同病期患者具有相同诊断效力(P0.05)。BC1手术后表达升高;BC2手术后表达降低,且复发转移组表达高于无瘤生存组(P0.05)。结论:该方法在乳腺癌的诊断、术后随访及肿瘤标志物筛选等方面具有一定价值,值得进一步研究。

Diagnostic and prognostic application of proteomic patterns in breast cancer

AIM: To detect the serum proteomic patterns in patients of breast cancer by the method of SELDI-TOF-MS and CM10 ProteinChip, and to screen the biomarker candidates, build and validate the diagnostic models, and evaluate its clinical value in surveillance and follow-up after operation. METHODS: The SELDI-TOF-MS technology and CM10 ProteinChip were used to detect the proteomic patterns of serum from 63 breast cancer patients and 40 healthy women. The biomarker candidates were screened and the diagnostic models were constructed by ZJU-PDAS software. Meanwhile, the model was blind-validated in another 23 patients and 20 healthy women. At the same time, 16 serum samples were detected to evaluate its value in surveillance and follow-up after operation. RESULTS: The best model was composed by two protein peaks (BC1/3.9 kD and BC2/5.6 kD) with its sensitivity and specificity of 87.30% (55/63) and 95.00% (38/40), respectively. The sensitivity and specificity in the blind-validation of new cases were 95.65% (22/23) and 85.00% (17/20), respectively. The diagnostic efficacies were the same to the patients of different stages (P>0.05). The expression of BC1 increased while BC2 decreased after operation. The expression of BC2 in the patients with recurrence or metastasis was higher than that in the tumor-free survivors (P<0.05). CONCLUSION: This method shows its potential in detection, surveillance and follow-up after operation. The method is also useful for screening the novel and better biomarkers in breast cancer.