中华实验外科杂志
中華實驗外科雜誌
중화실험외과잡지
CHINESE JOURNAL OF EXPERIMENTAL SURGERY
2014年
12期
2864-2865
,共2页
宋军%宋虎%付海啸%徐溢新%张迎东%徐为%郑骏年
宋軍%宋虎%付海嘯%徐溢新%張迎東%徐為%鄭駿年
송군%송호%부해소%서일신%장영동%서위%정준년
胃癌%代谢组学%诊断
胃癌%代謝組學%診斷
위암%대사조학%진단
Gastric cancer%Metabolic profiling%Diagnosis
目的 探讨应用人血清代谢谱检测诊断胃癌的价值.方法 利用气相色谱联合质谱分析技术,对40例胃癌患者和40例正常对照者的血清代谢谱进行检测.获得的代谢组学数据通过多维统计分析方法建立胃癌诊断模型,并对该模型进行验证.结果 通过气相色谱联合质谱分析共获得44种代谢物,其中包括氨基酸、有机酸、碳水化合物、脂肪酸和类固醇等多种代谢物,利用正交偏最小二乘判别分析(OPLS-DA)建模后可以较好地区分胃癌组和对照组(R2Ycum=0.854,Q2cum=0.768,P<0.05),但不能区别不同TNM分期的各组胃癌(R2Ycum=0.438,Q2cum=0.289,P>0.05).该模型对于胃癌的诊断敏感性和特异性可达到92%和80%.结论 血清代谢谱检测有助于胃癌诊断.
目的 探討應用人血清代謝譜檢測診斷胃癌的價值.方法 利用氣相色譜聯閤質譜分析技術,對40例胃癌患者和40例正常對照者的血清代謝譜進行檢測.穫得的代謝組學數據通過多維統計分析方法建立胃癌診斷模型,併對該模型進行驗證.結果 通過氣相色譜聯閤質譜分析共穫得44種代謝物,其中包括氨基痠、有機痠、碳水化閤物、脂肪痠和類固醇等多種代謝物,利用正交偏最小二乘判彆分析(OPLS-DA)建模後可以較好地區分胃癌組和對照組(R2Ycum=0.854,Q2cum=0.768,P<0.05),但不能區彆不同TNM分期的各組胃癌(R2Ycum=0.438,Q2cum=0.289,P>0.05).該模型對于胃癌的診斷敏感性和特異性可達到92%和80%.結論 血清代謝譜檢測有助于胃癌診斷.
목적 탐토응용인혈청대사보검측진단위암적개치.방법 이용기상색보연합질보분석기술,대40례위암환자화40례정상대조자적혈청대사보진행검측.획득적대사조학수거통과다유통계분석방법건립위암진단모형,병대해모형진행험증.결과 통과기상색보연합질보분석공획득44충대사물,기중포괄안기산、유궤산、탄수화합물、지방산화류고순등다충대사물,이용정교편최소이승판별분석(OPLS-DA)건모후가이교호지구분위암조화대조조(R2Ycum=0.854,Q2cum=0.768,P<0.05),단불능구별불동TNM분기적각조위암(R2Ycum=0.438,Q2cum=0.289,P>0.05).해모형대우위암적진단민감성화특이성가체도92%화80%.결론 혈청대사보검측유조우위암진단.
Objective To explore the applied value of serum metabolic profiling in diagnosis of human gastric cancer.Methods Serum metabolites of 40 gastric cancer patients and 40 normal subjects were detected by gas chromatography/mass spectrometry (GC/MS).The acquired metabolic data were analyzed using multivariate analysis and a diagnostic model was established using orthogonal partial least squares discriminant analysis (OPLS-DA).The model was also validated.Results A total of 44 compounds of endogenous metabolites,such as amino acids,organic acids,carbohydrates,fatty acids and steroids,were detected using GC/MS and the OPLS-DA model generated from serum metabolic profile data showed robust discrimination from gastric cancer patients and healthy controls (R2Ycum =0.854,Q2cum =0.768,P < 0.05),while the model failed to discriminate different pathological stages (Ⅰ-Ⅳ) of gastric cancer patients (R2Ycum =0.438,Q2cum =0.289,P > 0.05).The sensitivity and specificity of the model was respectively 92% and 80%.Conclusion These results suggest that serum metabolic profiling has a great potential in detecting gastric cancer.