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血清蛋白质谱诊断模型在乳腺癌辅助诊断中的价值
引用本文:Ying MG,Chen Q,Ye YB,Chen HJ,Chen X,Zheng HY,Wu F. 血清蛋白质谱诊断模型在乳腺癌辅助诊断中的价值[J]. 中华肿瘤杂志, 2010, 32(9): 698-702. DOI: 10.3760/cma.j.issn.0253-3766.2010.09.015
作者姓名:Ying MG  Chen Q  Ye YB  Chen HJ  Chen X  Zheng HY  Wu F
作者单位:1. 福建医科大学教学医院福建省肿瘤医院外科,福州,350014
2. 福建医科大学教学医院福建省肿瘤医院内科,福州,350014
3. 福建医科大学教学医院福建省肿瘤医院肿瘤免疫学研究室,福州,350014
摘    要:目的 建立乳腺癌的血清蛋白质谱诊断模型,评价其在乳腺癌辅助诊断中的价值.方法 应用表面增强激光解析电离飞行时间质谱(SELDI-TOF-MS)技术检测113例乳腺癌患者、103例乳腺良性肿瘤患者及92例健康女性的血清蛋白质谱,采用Biomarker Pattern(BPS)软件分析蛋白质谱,建立分类树模型,然后对模型进行盲筛验证.结果 比较乳腺癌患者与健康女性的血清蛋白质谱,筛选出12个差异蛋白质峰.经验证,所建立的分类树模型Ⅰ诊断乳腺癌的灵敏度为91.9%,特异度为81.2%.比较乳腺良性肿瘤患者与健康女性的血清蛋白质谱,筛选出11个差异蛋白质峰.经验证,所建立的分类树模型Ⅱ诊断乳腺良性肿瘤的灵敏度为87.9%,特异度为81.2%.比较乳腺癌与乳腺良性肿瘤患者的血清蛋白质谱,筛选出2个差异蛋白质峰.经验证,所建立的分类树模型Ⅲ诊断乳腺癌的灵敏度为81.8%,特异度为78.3%.应用这些差异蛋白及分类树模型,分别对93例CA15-3阴性乳腺癌患者与36例乳腺良性疾病患者的血清、20例CA15-3阳性乳腺癌患者与36例乳腺良性疾病患者的血清进行盲筛,诊断乳腺癌的敏感度和特异度分别为80.6%和91.7%、75.0%和91.7%,明显高于传统的乳腺癌标志物CA15-3,而CA15-3阴性与CA15-3阳性乳腺癌未见明显的差异蛋白质峰.结论 应用SELDI-TOF-MS技术可筛选出乳腺癌、乳腺良性肿瘤和健康女性血清蛋白质谱存在的差异蛋白质峰,据此建立的诊断模型可用于乳腺癌的辅助诊断.

关 键 词:乳腺肿瘤  表面增强激光解析电离飞行时间质谱  蛋白质组学  诊断模型

Application of serum proteomic mass spectrum analysis in breast cancer
Ying Min-gang,Chen Qiang,Ye Yun-bin,Chen Hui-jing,Chen Xia,Zheng Hong-yu,Wu Fan. Application of serum proteomic mass spectrum analysis in breast cancer[J]. Chinese Journal of Oncology, 2010, 32(9): 698-702. DOI: 10.3760/cma.j.issn.0253-3766.2010.09.015
Authors:Ying Min-gang  Chen Qiang  Ye Yun-bin  Chen Hui-jing  Chen Xia  Zheng Hong-yu  Wu Fan
Affiliation:Department of Surgery, Fujian Tumor Hospital, Fuzhou 350014, China. yingmg@163.com
Abstract:Objective To analyze the characteristics of serum proteins mass spectra in healthy controls,benign breast tumors, and CA15-3 negative or CA15-3 positive breast cancer patients by surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS). Methods Tissue samples of 113 cases of breast cancer (93 case of CA15-3 negtive, 20 case of CA15-3 postive), 103 cases of benign breast tumor and 92 cases of healthy controls were examined and analyzed by SELDI and protein chip (CM10) techniques. Biomarker Pattern Software (BPS) was used to detect the protein peaks significantly different between them and establish a diagnostic pattern which was further evaluated by a blind test. Results Twelve significantly different protein peaks were found in serum samples between breast cancer patients and healthy controls. Eleven significantly different peaks were found between benign breast tumor patients and healthy controls. By combined analysis of those three different protein mass spectra, the peak 15 952 was found to be significantly different between breast cancer group and healthy controls, and the peak 7985 was significantly different among breast cancer group, benign breast tumor group and health controls. The blind test with the differential proteins for the serum samples of 93 cases of CA15-3 negative breast cancer and 36 cases of benign breast tumors showed that the sensitivity was 80.6% and specificity was 91.7%. The blind test in 20 cases of CA15-3 positive breast cancer and 36 cases of benign breast tumors showed that the sensitivity was 75.0% and specificity was 91.7%. Four significantly different protein peaks were found between the benign breast tumor patients and CA15-3 negtive breast cancer patiens. No significantly different protein were found between CA15-3 negative and CA15-3 positive patients. Conclusion Significantly different protein peaks can be screened out in breast cancer, benign breast tumor patients and healthy controls by SELDI-TOF-MS analysis.
Keywords:Breast neoplasms  SELDI-TOF-MS  Proteomics  Diagnostic pattern
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