肿瘤研究与临床
腫瘤研究與臨床
종류연구여림상
CANCER RESEARCH AND CLINIC
2012年
12期
806-808,812
,共4页
许慧娟%郭向阳%张华一%王春艳%梁帅%杨瑞红%王福花%吴玉梅%郭素堂%李炘正
許慧娟%郭嚮暘%張華一%王春豔%樑帥%楊瑞紅%王福花%吳玉梅%郭素堂%李炘正
허혜연%곽향양%장화일%왕춘염%량수%양서홍%왕복화%오옥매%곽소당%리흔정
乳腺肿瘤%表面加强激光解析电离飞行时间质谱技术%诊断模型%蛋白质组学
乳腺腫瘤%錶麵加彊激光解析電離飛行時間質譜技術%診斷模型%蛋白質組學
유선종류%표면가강격광해석전리비행시간질보기술%진단모형%단백질조학
Breast neoplasms%Surface-enhanced laser desorption/ionization time-of-fight mass spectrometry%Diagnostic model%Proteomics
目的 探讨血清表面加强激光解析电离(SELDI)蛋白质谱技术在乳腺癌诊断方面的应用.方法 用表面加强激光解析电离飞行时间质谱技术(SELDI-TOF-MS)及WCX2蛋白获得病理确诊的101例乳腺癌患者手术前和45名健康人的血清蛋白指纹图谱,用Biomarker Wizard和BPS软件分析差异蛋白,建立乳腺癌的分类树诊断模型,并对其进行盲法验证.结果 乳腺癌组与健康对照组共有49个蛋白质差异有统计学意义(P＜0.05)；以其中3个蛋白质生物标志物(M/Z:5627、8124和2864)组建的诊断模型检测正确率为95％(139/146).经盲法验证,其灵敏度为97％(98/101),特异度为91％(41/45).结论 SELDI蛋白质谱技术可以有效的区分乳腺癌患者和健康人,其灵敏度和特异性高.SELDI-TOF-MS在乳腺癌的诊断及乳腺癌特异性的生物标志物分子的筛选方面具有一定的应用价值.
目的 探討血清錶麵加彊激光解析電離(SELDI)蛋白質譜技術在乳腺癌診斷方麵的應用.方法 用錶麵加彊激光解析電離飛行時間質譜技術(SELDI-TOF-MS)及WCX2蛋白穫得病理確診的101例乳腺癌患者手術前和45名健康人的血清蛋白指紋圖譜,用Biomarker Wizard和BPS軟件分析差異蛋白,建立乳腺癌的分類樹診斷模型,併對其進行盲法驗證.結果 乳腺癌組與健康對照組共有49箇蛋白質差異有統計學意義(P＜0.05)；以其中3箇蛋白質生物標誌物(M/Z:5627、8124和2864)組建的診斷模型檢測正確率為95％(139/146).經盲法驗證,其靈敏度為97％(98/101),特異度為91％(41/45).結論 SELDI蛋白質譜技術可以有效的區分乳腺癌患者和健康人,其靈敏度和特異性高.SELDI-TOF-MS在乳腺癌的診斷及乳腺癌特異性的生物標誌物分子的篩選方麵具有一定的應用價值.
목적 탐토혈청표면가강격광해석전리(SELDI)단백질보기술재유선암진단방면적응용.방법 용표면가강격광해석전리비행시간질보기술(SELDI-TOF-MS)급WCX2단백획득병리학진적101례유선암환자수술전화45명건강인적혈청단백지문도보,용Biomarker Wizard화BPS연건분석차이단백,건립유선암적분류수진단모형,병대기진행맹법험증.결과 유선암조여건강대조조공유49개단백질차이유통계학의의(P＜0.05)；이기중3개단백질생물표지물(M/Z:5627、8124화2864)조건적진단모형검측정학솔위95％(139/146).경맹법험증,기령민도위97％(98/101),특이도위91％(41/45).결론 SELDI단백질보기술가이유효적구분유선암환자화건강인,기령민도화특이성고.SELDI-TOF-MS재유선암적진단급유선암특이성적생물표지물분자적사선방면구유일정적응용개치.
Objective To explore the application of serum SELDI proteomic patterns to distinguish breast cancer patients from healthy individuals.Methods All serum samples from 101 breast cancer patients and 45 healthy individuals were analyzed by surface-enhanced laser desorption/ionization time-of-fight mass spectrometry (SELDI-TOF-MS).The spectra were generated on weak cation exchange (WCX2) chips,and protein peaks clustering and classification analysis were made using Biomaker Wizard software and Biomarker Pattern software (BPS).Then the pattern was evaluated by blinded test.Results 49 different proteins were found to have statistically differential expression levels between breast cancer and normal control sera (P ＜ 0.05).A diagnostic model consisting of three protein peaks (M/Z 5627,8124 and 2864) could do the best in the diagnosis between breast cancer and healthy individual.When the diagnostic model was tested with the blinded test set,it yielded a positive value of 95 ％ (139/146),a sensitivity of 97 ％ (98/101) and a specificity of 91％ (41/45).Conclusion These results suggested that serum SELDI protein profiling can distinguish breast cancer patients from normal subjects with relatively high sensitivity and specificity.SELDI-TOF-MS plays a valuable role in the diagnosis of breast cancer and the discovery of new tumor-specific protein biomarkers.
