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运用表面加强激光解吸电离-飞行时间-质谱技术建立结直肠癌预测诊断模型
引用本文:赖衍汉,许剑民,于新哲,钟芸诗,韦烨,任黎,朱德祥,刘银坤,牛伟新,秦新裕.运用表面加强激光解吸电离-飞行时间-质谱技术建立结直肠癌预测诊断模型[J].中华外科杂志,2008,46(13).
作者姓名:赖衍汉  许剑民  于新哲  钟芸诗  韦烨  任黎  朱德祥  刘银坤  牛伟新  秦新裕
作者单位:1. 上海复旦大学附属中山医院普外科,200032
2. 上海复旦大学附属中山医院肝癌研究所,200032
摘    要:目的 寻找与结直肠癌相关的蛋白质并建立结直肠癌血清蛋白指纹图谱诊断预测模型.方法 随机选取结直肠癌病例36例(结直肠癌组)和疝或行胆囊择期手术的患者36例(对照组),术前静脉采血,采用弱阳离子交换蛋白质芯片(CM10),经表面加强激光解吸电离-飞行时间-质谱(SELDI-TOF-MS)技术测定,建立结直肠癌的血清蛋白指纹图谱诊断预测模型;选取88例结直肠癌患者和44例正常对照进行盲法验证.结果 通过两组比较,得到5个差异蛋白峰,并以此建立诊断预测模型,其敏感性为100%,特异性为97.2%.盲法验证显示敏感性为71.6%,特异性为72.7%.其中质荷比为8908与13707的蛋白均存在于结直肠癌组和正常组的比较中,提示上述蛋白质与结直肠癌相关.结论 运用SELDI-TOF-MS技术建立的血清蛋白指纹图谱模型对诊断结直肠癌具有较高的敏感性与特异性.质荷比为8908与13707的蛋白可能成为结直肠癌的肿瘤标记物.

关 键 词:结直肠肿瘤  蛋白质阵列分析  表面加强激光解吸电离-飞行时间-质谱技术  预测模型

Establish predictive model of colorectal cancer by using surface enhanced laser desorption/ionization time of flight-mass spectrometry
LAI Yan-han,XU Jian-min,YU Xin-zhe,ZHONG Yun-shi,WEI Ye,REN Li,ZHU De-xiang,LIU Yin-kun,NIU Wei-xin,QIN Xin-yu.Establish predictive model of colorectal cancer by using surface enhanced laser desorption/ionization time of flight-mass spectrometry[J].Chinese Journal of Surgery,2008,46(13).
Authors:LAI Yan-han  XU Jian-min  YU Xin-zhe  ZHONG Yun-shi  WEI Ye  REN Li  ZHU De-xiang  LIU Yin-kun  NIU Wei-xin  QIN Xin-yu
Abstract:Objective To establish serum proteome fingerprinting predictive models and search for proteins associated with colorectal cancer.Methods Thirty-six randomly selected colorectal cancer patients and 36 cases with hernia or gall bladder diseases scheduled for elective operation were enrolled as cancer group and control group respectively.Peripheral venous blood samples were collected before the operations.Special serum protein or peptide fingerprint was investigated by using surface enhanced laser desorption/ionization-time of flight-mass spectrometry(SELDI-TOF-MS)measurement after blood sample had been treated with weak cation exchange protein chip(CM10)for each case.The obtained data were analyzed by Biomarker Wizard software to screen serum proteome tumor markers and set up diagnosis predictive model for eolorectal cancer.Blind validation of the model with 44 healthy controls and 88 colorectal cancer patients were carried out by using Biomarker Patterns Software.Results In comparing colorectal cancer group with control group,5 specific protein peaks(P<0.05)were found.The predictive model had a sensitivity of 100% and a specificity of 97.2%.A sensitivity of 71.6% and a specificity of 72.7% was got with the blind validation.The specific protein peaks with a mass-to-charge ratio(m/z)of 8908 and 13707 showed in all the results and it showed their strong relationship with colorectal cancer.Conclusions The predictive models built by the differences of serum proteome fingerprint could be a very useful diagnostic tool in colorectal cancer.Proteins with m/z of 8908 and 13707 would possibly be the tumor markers of colorectal cancer.
Keywords:Colorectal neoplasms  Protein array analysis  Surface enhanced laser desorption/ionization-time of flight-mass spectrometry:Predictive model
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