中华外科杂志
中華外科雜誌
중화외과잡지
CHINESE JOURNAL OF SURGERY
2008年
12期
932-935
,共4页
马宁%葛春林%栾凤鸣%胡朝军%李永哲%刘永锋
馬寧%葛春林%欒鳳鳴%鬍朝軍%李永哲%劉永鋒
마저%갈춘림%란봉명%호조군%리영철%류영봉
胰腺肿瘤%蛋白质组学%SELDI-TOF-MS技术%诊断模型
胰腺腫瘤%蛋白質組學%SELDI-TOF-MS技術%診斷模型
이선종류%단백질조학%SELDI-TOF-MS기술%진단모형
Pancreatic neoplasms%Proteomics%Surface enhanced laser desorption/ionization time of flight mass spectrometry%Classification model
目的 应用表面增强激光解析/离子化飞行时间质谱技术(SELDI-TOF-MS)从胰腺癌患者血清中筛选标志蛋白,找出最佳的标志蛋白组合模式作为临床诊断指标.方法 收集29例胰腺癌患者血清标本和57例年龄、性别相匹配的非癌人群血清标本作为对照.采用SELDI技术检测其蛋白质指纹图谱表达,所得到的结果采用Biomarker Wizard及Biomarker Patterns system软件分析,筛选最终可能用于胰腺癌诊断的蛋白标志物并优化组合建立胰腺癌诊断模型.结果 发现胰腺癌患者和对照组血清蛋白质指纹图谱之间有26个差异表达特异性蛋白,分析系统筛选出一组包含4个标志蛋白(5705、4935、5318和3243 Da)建立起一个胰腺癌的诊断模型,对胰腺癌诊断的敏感性为100%,特异性97.4%.盲法验证此模型敏感性88.9%、特异性89.5%.结论 SELDI-TOF-MS技术的特异性及敏感性远远高于目前所采用的某一单独标志物的血清学诊断,其结果对进一步研究胰腺癌的蛋白质组学改变及其临床诊断应用可能具有重要意义.
目的 應用錶麵增彊激光解析/離子化飛行時間質譜技術(SELDI-TOF-MS)從胰腺癌患者血清中篩選標誌蛋白,找齣最佳的標誌蛋白組閤模式作為臨床診斷指標.方法 收集29例胰腺癌患者血清標本和57例年齡、性彆相匹配的非癌人群血清標本作為對照.採用SELDI技術檢測其蛋白質指紋圖譜錶達,所得到的結果採用Biomarker Wizard及Biomarker Patterns system軟件分析,篩選最終可能用于胰腺癌診斷的蛋白標誌物併優化組閤建立胰腺癌診斷模型.結果 髮現胰腺癌患者和對照組血清蛋白質指紋圖譜之間有26箇差異錶達特異性蛋白,分析繫統篩選齣一組包含4箇標誌蛋白(5705、4935、5318和3243 Da)建立起一箇胰腺癌的診斷模型,對胰腺癌診斷的敏感性為100%,特異性97.4%.盲法驗證此模型敏感性88.9%、特異性89.5%.結論 SELDI-TOF-MS技術的特異性及敏感性遠遠高于目前所採用的某一單獨標誌物的血清學診斷,其結果對進一步研究胰腺癌的蛋白質組學改變及其臨床診斷應用可能具有重要意義.
목적 응용표면증강격광해석/리자화비행시간질보기술(SELDI-TOF-MS)종이선암환자혈청중사선표지단백,조출최가적표지단백조합모식작위림상진단지표.방법 수집29례이선암환자혈청표본화57례년령、성별상필배적비암인군혈청표본작위대조.채용SELDI기술검측기단백질지문도보표체,소득도적결과채용Biomarker Wizard급Biomarker Patterns system연건분석,사선최종가능용우이선암진단적단백표지물병우화조합건립이선암진단모형.결과 발현이선암환자화대조조혈청단백질지문도보지간유26개차이표체특이성단백,분석계통사선출일조포함4개표지단백(5705、4935、5318화3243 Da)건립기일개이선암적진단모형,대이선암진단적민감성위100%,특이성97.4%.맹법험증차모형민감성88.9%、특이성89.5%.결론 SELDI-TOF-MS기술적특이성급민감성원원고우목전소채용적모일단독표지물적혈청학진단,기결과대진일보연구이선암적단백질조학개변급기림상진단응용가능구유중요의의.
Objective To detect the serum specific proteins in pancreatic cancer patients and establish diagnostic model by surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS)technique.Methods Twenty-nine serum samples from patients of pancreatic cancer were collected before surgery and an additional 57 serum samples from age and sex matched individuals without cancer were used as controls.SELDI-TOF-MS technique and WCX magnetic beads were used to detect the protein fingerprint expression of all the serum samples and the resulting profiles between pancreatic cancer patients and controls were analyzed with biomarker wizard system,established the model using biomarker patterns system software.A double-blind test was used to determine the sensitivity and specificity of the classification model.Results A panel of four biomarkers(relative molecular weight are 5705,4935,5318 and 3243 Da)were selected to set up a decision trees as the classification model for screening pancreatic cancer effectively.The result yielded a sensitivity of 100%.specificity of 97.4%.The doubleblind test challenged the model with a sensitivity of 88.9%and a specificity of 89.5%.Conclusions SELDI-TOF-MS offers a unique platform for the proteomic detection of serum in pancreatic cancer patients.It also offers a noninvasive method to further study the proteomic changes in the development and progression of pancreatic cancer.