CAJ | 학술논문

目的检测胰腺癌相关糖尿病的血清蛋白标志物,并建立诊断模型.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17例胰腺癌相关糖尿病与17例新发2型糖尿病、17例健康对照者血清的差异表达蛋白,用Biomarker Patterns Software 5.0软件建立胰腺癌相关糖尿病诊断模型并验证.结果在胰腺癌相关糖尿病、新发2型糖尿病,健康者各10例的蛋白指纹图谱中筛选出12个差异表达蛋白峰,其中质荷比为6116、6695、8936 Da的蛋白峰被选为建立胰腺癌相关糖尿病诊断模型的蛋白峰.该诊断模型的诊断正确率为90％.盲法验证各组另7例样本,正确诊断胰腺癌相关糖尿病患者达100％,新发2型糖尿病患者为71％,健康人群为86％.经检索蛋白质数据库,与以上3种差异表达蛋白分子质量最为接近的蛋白分别为金属硫蛋白、胰腺干细胞增殖分化因子和成纤维细胞生长因子 1.结论通过SELDI方法筛选出3种胰腺癌相关糖尿病的血清蛋白标志物,建立了可靠的胰腺癌相关糖尿病的诊断模型.
목적 검측이선암상관당뇨병적혈청단백표지물,병건립진단모형.방법 응용표면증강격광해석전리비행시간질보( SELDI-TOF-MS)기술검측17례이선암상관당뇨병여17례신발2형당뇨병、17례건강대조자혈청적차이표체단백,용Biomarker Patterns Software 5.0연건건립이선암상관당뇨병진단모형병험증.결과 재이선암상관당뇨병、신발2형당뇨병,건강자각10례적단백지문도보중사선출12개차이표체단백봉,기중질하비위6116、6695、8936 Da적단백봉피선위건립이선암상관당뇨병진단모형적단백봉.해진단모형적진단정학솔위90％.맹법험증각조령7례양본,정학진단이선암상관당뇨병환자체100％,신발2형당뇨병환자위71％,건강인군위86％.경검색단백질수거고,여이상3충차이표체단백분자질량최위접근적단백분별위금속류단백、이선간세포증식분화인자화성섬유세포생장인자 1.결론 통과SELDI방법사선출3충이선암상관당뇨병적혈청단백표지물,건립료가고적이선암상관당뇨병적진단모형.
Objective To detect serum biomarkers for pancreatic cancer associated diabetes and establish a model for diagnosis.Methods SELDI-TOF-MS was used to detect the differentially expressed serum proteins from 17 pancreatic cancer associated diabetes patients,17 new-onset type Ⅱ diabetes patients and 17 healthy controls,then a model of biomarkers was constructed and validated by Biomarker Patterns Software 5.0.Results Twelve discriminating m/z peaks were identified in the protein fingerprints in 10 pancreatic cancer associated diabetes patients,10 new-onset type Ⅱ diabetes patients and 10 healthy controls.Among them,the three biomarkers of mass/charge ratio 6116,6695 and 8936 were used to construct the model,which could diagnose 90％ pancreatic cancer associated diabetes form control groups.Blind test of other7 samples of three groups showed that 100％ pancreatic cancer associated diabetes,71％ new-onset diabetes and 86％ healthy controls were correctly classified.After searching protein database,there were metallothionein,pancreatic progenitor cell differentiation and proliferation factor-like protein,and fibroblastic growth factor 1,which were close to the weights of the above mentioned 3 differentially expressed proteins.Conclusions SELDI can identify 3 biomarkers for pancreatic cancer associated diabetes and a reliable model for diagnosis of pancreatic cancer associated diabetes is established.