乳腺癌患者血清蛋白质组的特征研究  

Serum proteomic analysis of serum of breast cancer patients

作　　者：陈锋涛[1] 高春芳[1] 郑国宝[1] 王秀丽[1] 赵光[1] 李冬晖[1] 

机构地区：[1]解放军150中心医院全军肛肠外科研究所,河南洛阳471031

出　　处：《解放军医学杂志》2010年第4期436-438,共3页Medical Journal of Chinese People's Liberation Army

基　　金：全军医学科研"十一五"基金(08Z006)

摘　　要：目的比较乳腺癌患者、乳腺良性病患者及健康女性血清蛋白质组的差异,以期发现可用于乳腺癌诊断的生物学指标。方法采用表面增强激光解吸离子化飞行时间质谱(SELDI-TOF-MS)蛋白芯片技术,检测46例乳腺癌患者、40例乳腺良性病患者及40例健康女性血清,筛选出有分类意义的差异蛋白并建立分类树模型。再从同期住院或健康体检人群中随机抽取乳腺癌患者、乳腺良性病患者及健康女性各10例组成测试组,对诊断分类树模型进行独立双盲验证。结果比较三组血清,共发现22种差异蛋白质(P<0.05),由其中质荷比(M/Z)为3162、3960、4213、4526、5908、5386、11383、11735、13892、6007的10种蛋白建立的诊断分类树模型,对乳腺癌、乳腺良性病、健康女性的分类准确率为98.4%(124/126),灵敏度及特异度分别为100.0%(46/46)和97.5%(78/80),经独立双盲验证该模型诊断乳腺癌的准确率、灵敏度及特异度分别为83.3%(25/30)、80.0%(8/10)、85.0%(17/20)。结论利用SELDI-TOF-MS技术建立的乳腺癌诊断分类树模型具有较高的敏感度和特异度,可用于乳腺癌的快速诊断。Objective To explore and determine the biologic markers for diagnosis of breast cancer by comparison of proteomic differences among patients with breast cancer,benign mastopathy,and healthy people.Methods The serum proteomics patterns of 46 cases of breast cancer,40 cases of benign mastopathy,and 40 healthy subjects were read with surface enhanced laser desorption/ionization-time of flight-mass spectrometry （SELDI-TOF-MS） to screen significantly differential proteins,and to develop the classification tree model for the diagnosis of breast cancer.Ten cases of breast cancer,10 cases of benign mastopathy and 10 healthy subjects were randomly selected at the same period and assigned as test groups for double-blind verification of the model.Results Twenty-two distinct proteins were identified from the three groups,and the classification tree model formed by 10 proteins （M/Z：3162,3960,4213,4526,5908,5386,11383,11735,13892 and 6007） could be used to identify breast cancer,benign mastopathy and healthy subjects with an accuracy of 98.4% （124/126）,sensitivity of 100.0% （46/46） and specificity of 97.5% （78/80）,respectively.The independent double-blind test challenged the model with an accuracy of 83.3% （25/30）,sensitivity of 80.0% （8/10） and specificity of 85.0% （17/20）.Conclusions The classification tree model constructed by SELDI-TOF-MS possesses a high sensitivity and specificity,and it can be used for rapid diagnosis of breast cancer.

关 键 词：乳腺肿瘤 光谱法 质量 表面增强激光解吸离子化飞行时间 蛋白质组学 生物学标记 

分 类 号：R737.9[医药卫生—肿瘤]