血清蛋白质指纹图谱在甲状腺癌诊断中的应用

目的 检测甲状腺癌、甲状腺良性结节和正常人血清中蛋白质组图谱，筛选特异的蛋白质标记物。构建用于甲状腺癌早期诊断的血清蛋白质指纹图谱模型。方法 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108例血清标本的蛋白质质谱，其中甲状腺癌40例（Ⅰ～Ⅱ期26例，Ⅲ～Ⅳ期14例），甲状腺良性结节36例，正常人32例。随机抽取87例标本（甲状腺癌32例，甲状腺良性结节30例，正常人25例）作为训练组，应用支持向量机和判别分析的方法分析质谱数据，建立甲状腺癌诊断模型，留一法交叉验证。结果区分甲状腺癌和正常人的诊断模型交叉检验敏感性87．5％，特异性80．0％，用15例未知血清盲法测试敏感性100％。特异性86％。区分甲状腺癌和甲状腺良性结节的诊断模型交叉检验敏感性81％，特异性87％，用14例未知血清盲法测试敏感性88％，特异性83％。结论 SELDI-TOF-MS技术结合生物信息学方法检测甲状腺癌血清蛋白质指纹图谱是早期诊断甲状腺癌的一种特异性强。敏感性高的新方法。值得进一步研究。

Application of serum protein fingerprint model in diagnosis of thyroid cancer

Objective To find new biomarkers and to establish serum protein fingerprint models for early detection and diagnosis of thyroid cancer by SELDI-TOF-MS and bioinformatics tools.Methods One hundred and eight serum samples(including 40 cases of thyroid cancer,36 cases of benign thyroid nodes,and 32 healthy individuals)were randomly divided into training set(n=87,32 cases of thyroid cancer,30 cases of benign thyroid nodes,25 healthy individuals)and test set(n=21).The serum protein was bound to WCX2 chip and tested by surface enhance laser desorption/ionization time of flight-mass spectrometry(SELDI-TOF-MS).The data of spectra were analyzed by bioinformatics tools like support vector machine(SVM)and discriminant analysis to establish diagnostic model.Results The detective model combined with 3 biomarkers could differentiate thyroid cancer from healthy individuals with speci- ficity of 86%,the sensitivity of 100%.The diagnostic model combined with 5 biomarkers could differen- tiate thyroid cancer from benign thyroid nodes with specificity of 83%,sensitivity of 88%.Conclusion The combination of SELDI with bioinformatics tools is a novel effective method for thyroid cancer detec- tion and diagnosis.