| 唾液蛋白指纹图谱在乳腺癌中医辨证分型中的应用初探 |
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| 引用本文： | 曹美群,李映红,吴正治,孙珂焕. 唾液蛋白指纹图谱在乳腺癌中医辨证分型中的应用初探[J]. 深圳中西医结合杂志, 2011, 21(4): 200-203,207 |
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| 作者姓名： | 曹美群 李映红 吴正治 孙珂焕 |
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| 作者单位： | 1. 深圳市人民医院深圳市老年医学研究所,广东深圳,518020
2. 深圳市第二人民医院深圳市中西医结合临床研究所,广东深圳,518035 |
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| 基金项目： | 国家自然科学基金项目(30640071); 广东省自然科学基金(9152408801000016); 深圳市科技计划重点项目(201001011) |
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| 摘 要： | 目的：应用表面增强激光解吸电离飞行时间质谱（SELDI-TOF-MS）技术检测乳腺癌肝郁气滞证和肝肾阴虚证患者唾液蛋白质,筛选特异的蛋白质标记物,构建用于区分乳腺癌肝郁气滞证和肝肾阴虚证的唾液蛋白质指纹图谱模型。方法：SELDI-TOF-MS技术测定47例唾液标本（其中乳腺癌肝郁气滞证26例,肝肾阴虚证21例）的蛋白质质谱,建立乳腺癌中医证候诊断模型。结果：样本共检测到243个蛋白质峰,其中33个蛋白质峰在两组间差异有统计学意义。获得M/Z为8087.575和3378.142Da2个蛋白质组成的诊断模型,可将乳腺癌肝郁气滞证和肝肾阴虚证正确区分,26例乳腺癌肝郁气滞证有25例被准确诊断,21例肝肾阴虚证患者被准确排除,灵敏度96.15%（25/26）;特异度为80.95%（17/21）。结论：SELDI-TOF-MS技术建立乳腺癌中医证候唾液蛋白质指纹图谱模型为中医证候的辨别提供了一种特异性强、敏感性高的新方法,值得进一步研究和应用
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| 关 键 词： | 乳腺癌 证候 蛋白质组 SELDI-TOF-MS 唾液 诊断模型 |
Application of Salivary Protein Fingerprint Model in the Syndrome Differentiation of Breast Cancer |
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| CAO Mei-Qun,LI Ying-hong,WU Zheng-zhi,SUN Ke-huan. Application of Salivary Protein Fingerprint Model in the Syndrome Differentiation of Breast Cancer[J]. Shenzhen Journal of Integrated Traditional Chinese and Western Medicine, 2011, 21(4): 200-203,207 |
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| Authors: | CAO Mei-Qun LI Ying-hong WU Zheng-zhi SUN Ke-huan |
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| Affiliation: | CAO Mei-Qun1,LI Ying-hong2,WU Zheng-zhi1,SUN Ke-huan1(1.Shenzhen Institute of Geriatric Medicine,Shenzhen People's Hospital,Guangdong Shenzhen 518020,2.Institute of Integrated Traditional Chinese and Western Medicine,The Second People's Hospital of Shenzhen,Guangdong Shenzhen 518035) |
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| Abstract: | Objective To find new biomarkers and establish salivary protein fingerprint models for the syndrome differentiation of breast cancer by SELDI-TOF-MS technology.Methods 47 salivary samples(including 26 cases of stagnation of Hepatic Qi syndrome of breast cancer and 21 deficiency of syndrome of both liver and kidney-YIN of breast cancer) were tested by SELDI-TOF-MS technology.The data of spectra were analyzed by bioinformatics tools and biomarker pattern discrimination software to establish diagnosis model.Re... |
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| Keywords: | Breast cancer Syndrome Proteomics SELDI-TOF-MS Salivary Diagnosis model |
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