中华肿瘤杂志
中華腫瘤雜誌
중화종류잡지
CHINESE JOURNAL OF ONCOLOGY
2008年
12期
910-913
,共4页
施益九%赵云%许剑民%赖衍翰%于新哲%钟芸诗%韦烨%任黎%朱德祥%刘银坤%牛伟新%秦新裕
施益九%趙雲%許劍民%賴衍翰%于新哲%鐘蕓詩%韋燁%任黎%硃德祥%劉銀坤%牛偉新%秦新裕
시익구%조운%허검민%뢰연한%우신철%종예시%위엽%임려%주덕상%류은곤%우위신%진신유
结直肠肿瘤%表面加强激光解吸电离-飞行时间-质谱%蛋白质指纹图谱%肝转移%诊断模型
結直腸腫瘤%錶麵加彊激光解吸電離-飛行時間-質譜%蛋白質指紋圖譜%肝轉移%診斷模型
결직장종류%표면가강격광해흡전리-비행시간-질보%단백질지문도보%간전이%진단모형
Colorectal neoplasms%SELDI-TOF-MS%Protein fingerprinting%Liver metastasis%Diagnostic model
目的 寻找与结直肠癌肝转移相关的蛋白质,建立结直肠癌肝转移的血清蛋白质指纹图谱诊断预测模型.方法 应用表面加强激光解吸电离-飞行时间-质谱(SELDI-TOF-MS)技术,对36例结直肠癌无肝转移患者和36例结直肠癌伴肝转移患者的术前空腹外周静脉血标本,进行蛋白质指纹图谱测定,运用Biomarker Wizard软件,建立结直肠癌肝转移的诊断预测模型.用44例结直肠癌患者和44例结直肠癌伴肝转移患者,对所建立的诊断预测模型进行盲法验证.结果 比较36例结直肠癌无肝转移患者和36例结直肠癌伴肝转移患者的血清蛋白质,得到10个差异蛋白峰(P<0.05),质荷比分别为2398、2814、4084、4289、4465、6422、6619、11 482、11 649和13 714.若以P<0.01为标准,则有3个蛋白质峰差异有统计学意义,质荷比分别为2398、2814和13714.建立终末节点数为9的诊断预测模型,其敏感性为91.7%,特异性为97.2%.验证结果显示,敏感性为75.0%,特异性为81.8%.结论 运用SELDI-TOF-MS技术所建立的血清蛋白指纹图谱模型,在预测结直肠癌肝转移中具有非常高的敏感性与特异性,可望成为预测诊断工具.
目的 尋找與結直腸癌肝轉移相關的蛋白質,建立結直腸癌肝轉移的血清蛋白質指紋圖譜診斷預測模型.方法 應用錶麵加彊激光解吸電離-飛行時間-質譜(SELDI-TOF-MS)技術,對36例結直腸癌無肝轉移患者和36例結直腸癌伴肝轉移患者的術前空腹外週靜脈血標本,進行蛋白質指紋圖譜測定,運用Biomarker Wizard軟件,建立結直腸癌肝轉移的診斷預測模型.用44例結直腸癌患者和44例結直腸癌伴肝轉移患者,對所建立的診斷預測模型進行盲法驗證.結果 比較36例結直腸癌無肝轉移患者和36例結直腸癌伴肝轉移患者的血清蛋白質,得到10箇差異蛋白峰(P<0.05),質荷比分彆為2398、2814、4084、4289、4465、6422、6619、11 482、11 649和13 714.若以P<0.01為標準,則有3箇蛋白質峰差異有統計學意義,質荷比分彆為2398、2814和13714.建立終末節點數為9的診斷預測模型,其敏感性為91.7%,特異性為97.2%.驗證結果顯示,敏感性為75.0%,特異性為81.8%.結論 運用SELDI-TOF-MS技術所建立的血清蛋白指紋圖譜模型,在預測結直腸癌肝轉移中具有非常高的敏感性與特異性,可望成為預測診斷工具.
목적 심조여결직장암간전이상관적단백질,건립결직장암간전이적혈청단백질지문도보진단예측모형.방법 응용표면가강격광해흡전리-비행시간-질보(SELDI-TOF-MS)기술,대36례결직장암무간전이환자화36례결직장암반간전이환자적술전공복외주정맥혈표본,진행단백질지문도보측정,운용Biomarker Wizard연건,건립결직장암간전이적진단예측모형.용44례결직장암환자화44례결직장암반간전이환자,대소건립적진단예측모형진행맹법험증.결과 비교36례결직장암무간전이환자화36례결직장암반간전이환자적혈청단백질,득도10개차이단백봉(P<0.05),질하비분별위2398、2814、4084、4289、4465、6422、6619、11 482、11 649화13 714.약이P<0.01위표준,칙유3개단백질봉차이유통계학의의,질하비분별위2398、2814화13714.건립종말절점수위9적진단예측모형,기민감성위91.7%,특이성위97.2%.험증결과현시,민감성위75.0%,특이성위81.8%.결론 운용SELDI-TOF-MS기술소건립적혈청단백지문도보모형,재예측결직장암간전이중구유비상고적민감성여특이성,가망성위예측진단공구.
Objective To establish a serum protein fingerprint model for prediction of liver metastasis from colorectal cancer by SELDI-TOF-MS analysis, and to determine the differentiatial proteins associated with the metastatic liver cancers. Methods Data were collected from the Department of General Surgery in Zhongshan Hospital. A group of patients with culorectal cancer (CRC) without liver metastasis ( n = 36) and another group with liver metastasis ( n = 36) were included in this study. Serum samples were collected from peripheral venous blood before operation. Special serum protein or peptide fingerprint was determined by surface-enhanced laser deserption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The obtained data were analyzed by Biomarker Wizard software to screen the serum protein markers discriminating colorectal cancer patients with and without liver metastasis. A serum protein fingerprint model was established. This model was blindly verified in of CRC patients with and 44 cases without liver metastasis. Results Comparing the characteristic proteins in those two groups of patients, 10 specific protein peaks were identified with statistical significance ( P < 0.05 ). According to m/z growing from small to large,they were: 2398, 2814, 4084, 4289, 4465, 6422, 6619, 11 482, 11 649 and 13 714. The predictive model had a sensitivity of 91.7% and a specificity of 97.2%. The validation showed a sensitivity of 75.0% and a specificity of 81.8%. Conclusion A predictive model based on differentiatial serum protein fingerprint with high sensitivity and specificity has been successfully established. It should be a very useful tool in detection and diagnosis of liver metastasis in colorectal cancer patients.
