表面加强激光解析电离蛋白质谱技术在乳腺癌血清学诊断中的应用

 【摘要】 目的: 探讨血清SELDI蛋白质谱技术在乳腺癌诊断方面的应用。 方法: 用表面加强目的　探讨血清表面加强激光解析电离（SELDI）蛋白质谱技术在乳腺癌诊断方面的应用。方法　用表面加强激光解析电离飞行时间质谱技术（SELDI-TOF-MS）及WCX2蛋白获得病理确诊的101例乳腺癌患者手术前和45名健康人的血清蛋白指纹图谱，并用Biomarker Wizard和BPS软件分析差异蛋白，建立乳腺癌的分类树诊断模型，并对其进行盲法验证。 结果　乳腺癌组与健康对照组共有49个蛋白质差异有统计学意义（P＜0.05）；以其中3个蛋白质生物标志物（M／Z 5627，8124和2864）组建的诊断模型检测正确率为95 %（139／146）。经盲法验证，其灵敏度为97 %（98／101），特异度为91 %（41／45）。结论　SELDI蛋白质谱技术可以有效的区分乳腺癌患者和健康人，其灵敏度和特异性高。SELDI在乳腺癌的诊断及乳腺癌特异性的生物标志物分子的筛选方面具有一定的应用价值。

Application of SELDI proteomic patterns in serological diagnosis of breast cancer

Objective　To explore the application of serum SELDI proteomic patterns to distinguish breast cancer patients from healthy individuals. Methods　All serum samples from 101 breast cancer patients and 45 healthy individuals were analyzed by surface-enhanced laser desorption/ionization time-of-fight mass spectrometry (SELDI-TOF-MS). The spectra were generated on weak cation exchange (WCX2) chips, and protein peaks clustering and classification analysis were made using Biomaker Wizard software and Biomarker Pattern software (BPS). Then the pattern was evaluated by blinded test. Results　49 different proteins were found to have statistically differential expression levels between breast cancer and normal control sera (P < 0.05). A diagnostic model consisting of three protein peaks (m/z 5627, 8124 and 2864) could do the best in the diagnosis between breast cancer and healthy individual. When the diagnostic model was tested with the blinded test set, it yielded a positive value of 95 % (139/146), a sensitivity of 97 % (98/101) and a specificity of 91 % (41/45). Conclusion　These results suggested that serum SELDI protein profiling can distinguish breast cancer patients from normal subjects with relatively high sensitivity and specificity. SELDI-TOF-MS plays a valuable role in the diagnosis of breast cancer and the discovery of new tumor-specific protein biomarkers.