血清蛋白质谱结合人工神经网络在胃癌诊断中的研究
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摘要
目的:因早期症状不明显,大部分胃癌患者就诊时己是中晚期。寻找能早期发现和诊断胃癌的标志物已成为目前临床和基础研究的主要方向。近年来表面增强激光解吸电离飞行时间质谱(SELDI-TOF-MS)技术已在许多肿瘤标志物研究中应用并取得成功。本研究应用血清蛋白质谱技术结合人工神经网络建立胃癌患者的诊断模型,并评价其诊断价值。方法:对84例胃癌患者和75例对照者(胃溃疡31例,慢性萎缩性胃炎20例,健康人群24例)的血清样本随机分为训练集(共106例,54例胃癌患者和52例对照)和测试集(共53例,30例胃癌患者和23例对照),以上研究对象均经胃镜及组织活检明确诊断,所有胃癌患者在胃镜检查之前均未进行任何形式的肿瘤治疗,所有血清样本均在研究对象空腹时采集,并以-80℃冻存备用。另取10份正常人血清进行混合,制成混合对照血清,分装后-80℃保存。首先应用表面加强激光解吸电离飞行时间质谱技术及弱阳离子交换表面(CM10)蛋白芯片检测所研究样本及混合对照血清,利用Ciphergen Proteinchip软件对获得的混合对照血清图谱进行分析并计算其差异性,以变异系数(CV)值表示,设定CV<15%时,满足蛋白质谱检查可重复性的要求。采用Biomarker Wizard 3.1软件分析患者组和对照组血清蛋白指纹图谱,两组间蛋白质峰值比较时,对初步筛选的蛋白质峰进行t检验,P<0.01的蛋白质峰差异具有统计学意义。结合反向传播人工神经网络的方法利用训练集建立诊断模型。人工神经网络根据训练集中的输入数据和输出数据,学习和记忆数据之间的内部联系。一旦人工神经网络模型被建立,它可分析新输入数据而预测输出结果。使用人工神经网络模型检测测试集样本并评价该模型的诊断价值。结果:1)对混合对照血清中所得蛋白质谱图进行统计分析,结果CV值为13.50%。为避免基质峰可能存在的干扰,将2000M/Z以下的峰滤去。2)对胃癌患者和对照组血清进行分析,共检测到722个蛋白质峰,统计分析结果显示214个蛋白质峰P值<0.01。3)在214个具有明显表达差异的蛋白峰中,利用训练集样本,以质荷比(M/Z)分别为2175、2249、2927、3217、3236、3287、3545、6190和6450的9个蛋白质峰作为标志蛋白建立人工神经网络诊断模型,正确地区分开了训练集中胃癌患者和对照者。4)利用建立的模型对测试集中样本进行盲法测试,结果显示:30例胃癌患者中有3例判错;而在23例对照中出现2例判错,其对胃癌的诊断灵敏度和特异度分别为90.0%和91.3%。结论:1)表面加强激光解吸电离飞行时间质谱技术运用于胃癌的研究具有明显的优势,有可能发现特异的胃癌诊断的生物标志。2)血清蛋白质谱结合人工神经网络可建立胃癌患者的诊断模型,该模型诊断胃癌具有较高的灵敏度和特异度。
Objective:Most patients of gastric cancer have developed to advanced stages at the time of diagnosis and more than a half have either unresectable tumors or radiographically visible metastases.However,early detection of cancer truly depends on the discovery of specific and sensitive molecular biomarkers.Promising diagnostic patterns have recently been reported using surface enhanced laser desorption/ionization-time of flight-mass spectrometry technology(SELDI-TOF-MS).We performed surface-enhanced desorption ionization Time-of-flight mass spectrometry (SELDI-TOF-MS) using a multi-layer artificial neural network (ANN) to develop and evaluate a proteomic diagnosis approach for gastric cancer. METHODS:Serum samples from 84 gastric cancer patients and 75 controls(included 31 cases of gastric ulcer;20 cases of chronic atrophic gastritis;24 cases of healthy individuals) were randomized into training set (all 106 samples, included 54 gastric cancer patients and 52 controls) and test set(all 53 samples, included 30 gastric cancer patients and 23 controls).The diagnoses of all the gastric cancer patients and controls were identified by endoscopy and biopsy.None of the gastric cancer patients had received any form of cancer treatment before the time of gastroscopy.All serum samples were obtained on an empty stomach and stored at -80℃until used.The mixed serum samples were generated by mixing ten healthy individuals'serum and separately stored at -80℃.At first,we detected the mixed serum samples and the researched samples using SELDI mass spectrometry and CM10 protein chips.Ciphergen Proteinchip software analyzed the proteomic spectra from the mixed serum samples and computed the coefficient variation(CV).The coefficient variation was within 15% and so was satisfactory for the reproducibility of the protein profiling in the study. Biomarker Wizard Software 3.1 analyzed the gastric cancer patients and controls'serum proteomic spectra.To compare the mass peaks of the gastric cancer patients and controls,we used t-test to exam the mass peaks which were collected initially,and p<0.01 was considered statistically significant. Using a multi-layer ANN with a back propagation algorithm,we identified a proteomic pattern that could discriminate cancer from control samples in the training set.The ANN used input and output data (samples for training set) to define (learn) the interrelationships among the data.Once the ANN has been trained, it could then predict outcomes from new sets of input data .The discovered patern was then used to determine the accuracy of the classification system in the test set. RESULTS:1)The proteomic spectra from the mixed serum samples were statistically analyzed,and the CV value was 13.50%. The matric peaks whose mass-to-charge ratio were less than 2000 were excluded to avoid the interference.2)The 722 mass peaks which were found by detecting the gastric cancer patients and controls'serum samples were statistically analyzed.Among the 722 mass peaks,214 mass peaks'p values were less than 0.01. 3)Total 214 differentially expressed proteins between the gastric cancer patients and controls were identified. Among them, nine proteins(M/Z at 2175、2249、2927、3217、3236、3287、3545、6190 and 6450) were chosen to develop ANN based diagnostic model in the training set.The model could correctly discriminate all the gastric cancer patients from controls in the training set.4) The model was blindly tested with the testing set for diagnosing gastric cancer,and the results indicated three false cases found in the 30 gastric cancer patients and two false cases found in the 23 controls. The sensitivity and specificity of the diagnostic model was 90.0% and 91.3% respectively. CONCLUSION:1)SELDI-TOF-MS is very excellent to study gastric cancer.The specific biomarkers to diagnose gastric cancer can be found by using SELDI-TOF-MS.2)The diagnostic model of gastric cancer can be developed by SELDI-TOF-MS in combination with ANN. The model is a useful tool to accurately identify patients with gastric cancer.
Objective:Most patients of gastric cancer have developed to advanced stages at the time of diagnosis and more than a half have either unresectable tumors or radiographically visible metastases.However,early detection of cancer truly depends on the discovery of specific and sensitive molecular biomarkers.Promising diagnostic patterns have recently been reported using surface enhanced laser desorption/ionization-time of flight-mass spectrometry technology(SELDI-TOF-MS).We performed surface-enhanced desorption ionization Time-of-flight mass spectrometry (SELDI-TOF-MS) using a multi-layer artificial neural network (ANN) to develop and evaluate a proteomic diagnosis approach for gastric cancer. METHODS:Serum samples from 84 gastric cancer patients and 75 controls(included 31 cases of gastric ulcer;20 cases of chronic atrophic gastritis;24 cases of healthy individuals) were randomized into training set (all 106 samples, included 54 gastric cancer patients and 52 controls) and test set(all 53 samples, included 30 gastric cancer patients and 23 controls).The diagnoses of all the gastric cancer patients and controls were identified by endoscopy and biopsy.None of the gastric cancer patients had received any form of cancer treatment before the time of gastroscopy.All serum samples were obtained on an empty stomach and stored at -80℃until used.The mixed serum samples were generated by mixing ten healthy individuals'serum and separately stored at -80℃.At first,we detected the mixed serum samples and the researched samples using SELDI mass spectrometry and CM10 protein chips.Ciphergen Proteinchip software analyzed the proteomic spectra from the mixed serum samples and computed the coefficient variation(CV).The coefficient variation was within 15% and so was satisfactory for the reproducibility of the protein profiling in the study. Biomarker Wizard Software 3.1 analyzed the gastric cancer patients and controls'serum proteomic spectra.To compare the mass peaks of the gastric cancer patients and controls,we used t-test to exam the mass peaks which were collected initially,and p<0.01 was considered statistically significant. Using a multi-layer ANN with a back propagation algorithm,we identified a proteomic pattern that could discriminate cancer from control samples in the training set.The ANN used input and output data (samples for training set) to define (learn) the interrelationships among the data.Once the ANN has been trained, it could then predict outcomes from new sets of input data .The discovered patern was then used to determine the accuracy of the classification system in the test set. RESULTS:1)The proteomic spectra from the mixed serum samples were statistically analyzed,and the CV value was 13.50%. The matric peaks whose mass-to-charge ratio were less than 2000 were excluded to avoid the interference.2)The 722 mass peaks which were found by detecting the gastric cancer patients and controls'serum samples were statistically analyzed.Among the 722 mass peaks,214 mass peaks'p values were less than 0.01. 3)Total 214 differentially expressed proteins between the gastric cancer patients and controls were identified. Among them, nine proteins(M/Z at 2175、2249、2927、3217、3236、3287、3545、6190 and 6450) were chosen to develop ANN based diagnostic model in the training set.The model could correctly discriminate all the gastric cancer patients from controls in the training set.4) The model was blindly tested with the testing set for diagnosing gastric cancer,and the results indicated three false cases found in the 30 gastric cancer patients and two false cases found in the 23 controls. The sensitivity and specificity of the diagnostic model was 90.0% and 91.3% respectively. CONCLUSION:1)SELDI-TOF-MS is very excellent to study gastric cancer.The specific biomarkers to diagnose gastric cancer can be found by using SELDI-TOF-MS.2)The diagnostic model of gastric cancer can be developed by SELDI-TOF-MS in combination with ANN. The model is a useful tool to accurately identify patients with gastric cancer.
引文
1. Wu ZZ, Wang JG, Zhang XL. Diagnostic model of saliva proteinfinger print analysis of patients with gastric cancer[J].World J Gastroenterol ,2009; 15(7): 865-870
2. Luo HZ, Mi DH, Jing TZ,et al. Risk Factors of Gastric Cancer in Wuwei City-an Endemic Region of Gastric Cancer[J].Ai Zheng,2005;24(5):563-566
3. Anita Mangia,Annalisa Chiriatti,Girolamo Ranieri,et al.H pylori status and angiogenesis factors in human gastric carcinoma[J].World J Gastroenterol,2006;12(34):5465-5472
4. Parkin DM,Bray F,Ferlay J,et al. Global cancer statistics,2002[J]. CA Cancer J Clin, 2005;55(2):74-108
5. Yalamarthi S, Witherspoon P, McCole D, et al. Missed diagnoses in patients with upper gastrointestinal cancers[J]. Endoscopy, 2004;36(10):874-879
6. Amin A,Gilmour H,Graham L,et al. Gastric adenocarcinoma missed at endoscopy[J]. J R Coll Surg Edinb,2002;47(5):681-684
7. Bramble MG,Suvakovic Z,Hungin AP.Detection of upper gastrointestinal cancer in patients taking antisecretory therapy prior to gastroscopy[J]. Gut,2000;46(4):464-467
8. Nakamura H, Yanai H, Satake M. Retrospective Analysis of the Results of Strip Biopsies to Determine the Indication forEndoscopic Submucosal Dissection for Early Gastric Cancer[J].J Gastrointest Cancer,2009;24(5):592-595
9. Voutilainen ME,Juhola MT. Evaluation of the diagnostic accuracy of gastroscopy to detect gastric tumours: clinicopathological features and prognosis of patients with gastric cancer missed on endoscopy[J]. Eur J Gastroenterol Hepatol,2005;17(12):1345-1349
10. Carneiro F,Oliveira C,Leite M.Molecular targets and biological modifiers in gastric cancer[J]. Semin Diagn Pathol,2008 ;25(4):274-287
11. Srinivas PR,Kramer BS,Srivastava S.Trends in biomarker research for cancer detection[J].Lancet Oncol,2001;2(11):698-704
12. Sidransky D.Emerging molecular markers of cancer[J]. Nat Rev Cancer, 2002;2(3):210- 219
13. Koike H,Ichikawa D,Ikoma H,et al. Comparison of serum aberrant methylation and conventional tumor markers in gastric cancer patients[J].Hepatogastroenterology,2005;52(64):1293-1296
14. Tirumalai RS,Chan KC,Prieto DA,et al.Characterization of the low molecular Weight human serum proteome[J].Mol Cell Protcomics, 2003;2(10): 1096-1103
15. Wadie BS, Badawi AM, Abdelwahed M,et al.Application of artificial neural network in prediction of bladder outlet obstruction:a model based on objective, noninvasive parameters[J].Urology,2006;68(6):1211-1214
16. Menges M. Diagnosis, staging and therapy of gastric cancer[J]. ZGastroenterol, 2004;42(8):767-773
17.吴阶平,裘法祖.黄家驯外科学[M].北京:人民卫生出版社,2000;1035-1036
18. Layke JC,Lopez PP.Gastric cancer:diagnosis and treatment options[J]. Am Fam Physician,2004;69(5):1133-1140
19. Hicks S.Gastric cancer: diagnosis, risk factors, treatment and life issues[J].Br J Nurs,2001; 10(8):529-536
20. Sigon R,Canzonieri V,Cannizzaro Ro.Early gastric cancer:diagnosis,surgical treatment and follow-up of 45 cases[J].Tumori,1998;84(5):547-551.
21. Ukrisana P,Wangwinyuvirat M. Evaluation of the sensitivity of the double-contrast upper gastrointestinal series in the diagnosis of gastric cancer[J]. J Med Assoc Thai,2004;87(1):80-86
22. Kobayashi M,Tajiri H,Seike E,et a1.Detection of early gastric cancer by a real-time autofluorescence imaging system[J].Cancer Lett,2001;165(2):155-159
23. Mataki N,Nagao S,Kawaguchi A,et a1.Clinical usefulness of a new infrared videoendoscope system for diagnosis of early stage gastric cancer[J].Gastrointest Endosc,2003;57(3):336-342
24. Tajiri H, Doi T, Endo H,et al.Routine endoscopy using a magnifying endoscope for gastric cancer diagnosis[J]. Endoscopy,2002;34(10):772-777
25. Broutet N,Plebani M ,Sakarovitch C,et a1.Pepsinogen A,pepsinogenC,and gastrin as markers of atrophic chronic gastritis in european dyspeptics[J].Br J Cancer,2003;88(8):1239-1247
26. Chen J, Rocken C, Malfertheiner P,et al. Recent advances in molecular diagnosis and therapy of gastric cancer[J]. Dig Dis,2004;22(4):380-385
27. Pusch W,Kostrzewa M.Application of MALDI-TOF mass spectrometry in screening and diagnostic research[J].Curr Pharm Des,2005;11(20):2577-2591
28. Henderson NA, Steele RJ.SELDI-TOF proteomic analysis and cancer detection[J].Surgeon,2005;3(6):383-390
29. Zhu H, Snyder M. Protein chip technology[J].Curr Opin Chem Biol, 2003;7(1):55-63
30. Seibert V, Wiesner A, Buschmann T,et al. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and ProteinChip technology in proteomics research[J].Pathol Res Pract, 2004;200(2):83-94
31. Batorfi J,Ye B,Mok SC,Cseh I,et al.Protein profiling of complete mole and normal placenta using Protein Chip analysis on laser capture microdissected cells[J].Gvnecol Oncol, 2003;88(3):424-428
32. Petricoin EF,Liotta LA. Proteomic analysis at the bedside:early detection of cancer[J].Trends Biotechnol,2002;20(12):30-34
33. Petricoin EF,Ardekani AM,Hitt BA,et al.Use of proteomic patterns in serum to identify ovarian cancer[J].Lancet,2002;359(9306):572-577
34. Lim JY,Cho JY,Paik YH,et al.Diagnostic application of serum proteomic patterns in gastric cancer patients by Protein Chip surface-enhanced laser desorption/ionization time-of-flight mass spectrometry[J]. Int J Biol Markers,2007;22(4):281-286
35. Diamandis EP. Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems[J].J Natl Cancer Inst, 2004;96(5):353-356
1.娄毅,何向民,宋清斌.Apaf-1基因在胃癌中的表达及临床意义[J].中华医学杂志,2006;86(30):2141-2143
2. Koike H,Ichikawa D,Ikoma H,et al.Comparison of serum aberrant methylation and conventional tumor markers in gastric cancer patients[J].Hepatogastroenterology,2005;52(64):1293-1296
3. Ciordia S,de Los Rios V,Albar JP. Contributions of advanced proteomics technologies to cancer diagnosis[J].Clin Transl Oncol,2006;8(8):566-580
4. Kobayashi M,Tajiri H,Seike E,et a1.Detection of early gastric cancer by a real-time autofluorescence imaging system[J].Cancer Lett,2001;165(2):155-159
5. Mataki N,Nagao S,Kawaguchi A,et a1.Clinical usefulness of a new infrared videoendoscope system for diagnosis of early stage gastric cancer[J].Gastrointest Endosc,2003;57(3):336-342
6. Onodera H,Jokunaga A,Yoshiyuki T.Surgical outcome of 483 patients with early gastric cancer.Best Prstoperative morbidity and mortality,and gastric remnant cancer[J].Hepatogastroengerology,2004;51(55):82-85
7. Broutet N,Plebani M ,Sakarovitch C,et a1.Pepsinogen A,pepsinogen C,and gastrin as markers of atrophic chronic gastritis in european dyspeptics[J].Br J Cancer,2003;88(8):1239-1247
8. Pandey A,Mann M.Proteomics to study genes and genomes[J].Nature,2000;405(6788):8372834
9. Jiang Q,Engelhardt JF . Cellular heterogeneity of CFTR expression and function in the lung: implications for gene therapy of cystic fibrosis[J].Eur J Hum Genet,1998;6(1):12231
10. Brenner SE.Errors in genome annotation[J].Trends Genet,1999;15 (4):132-213
11. Anderson L ,Seilhamer J .A comparison of selected mRNA and protein abundances in human liver[J].Electrophoresis,1997 ;18(324):533-537
12. Pusch W, Kostrzewa M.Application of MALDI-TOF mass spectrometry in screening and diagnostic research[J].Curr Pharm Des, 2005;11(20):2577-2591
13. Henderson NA, Steele RJ.SELDI-TOF proteomic analysis and cancer detection[J].Surgeon,2005;3(6):383-390
14. Zhu H, Snyder M. Protein chip technology[J].Curr Opin Chem Biol, 2003;7(1):55-63
15. Seibert V, Wiesner A, Buschmann T,et al. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and Protein Chip technology in proteomics research[J].Pathol Res Pract, 2004;200(2):83-94
16. Batorfi J,Ye B,Mok SC,Cseh I,Berkowitz RS,Fulop V.Protein profiling of complete mole and normal placenta using Protein Chip analysis on laser capture microdissected cells[J] . Gvnecol Oncol, 2003;88(3):424-428
17. Liang Y, Fang M, Li J, et al. Serum proteomic patterns for gastric lesions as revealed by SELDI mass spectrometry[J].Exp Mol Pathol,2006;81(2):176-180
18. Lim JY, Cho JY, Paik YH, et al. Diagnostic application of serum proteomic patterns in gastric cancer patients by Protein Chip surface-enhanced laser desorption/ionization time-of-flight mass spectrometry[J]. Int J Biol Markers,2007 ;22(4):281-286
19. Su Y, Shen J, Qian H, et al. Diagnosis of gastric cancer using decision tree classification of mass spectral data[J].Cancer Sci,2007;98(1):37-43
20. Qian HG, Shen J, Ma H, et al. Preliminary study on proteomics of gastric carcinoma and its clinical significance[J].World J Gastroenterol ,2005;11(40):6249-6253
21. Ebert MP, Meuer J, Wiemer JC, et al. Identification of gastric cancer patients by serum protein profiling[J].J Proteome Res ,2004;3(6):1261-1266
22.赵长宏,陆海波,马玉彦等,血清蛋白指纹图谱检测诊断早期胃癌临床意义[J].肿瘤防治研究,2006;33(10):750-753
23. Hayashida Y, Honda K, Osaka Y, et al. Possible prediction of chemoradio sensitivity of esophageal cancer by serum protein profiling[J].Clin Cancer Res,2005;11(22):8042-8047
24. Caspersen MB, Sorensen NM, Schrohl AS, et al. Investigation of tissue inhibitor of metalloproteinases 1 in plasma from colorectalcancer patients and blood donors by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry[J].Int J Biol Markers,2007;22(2):89-94
25. Castagna A, Cecconi D, Sennels L, et al. Exploring the hidden human urinary proteome via ligand library beads[J].J Proteome Res ,2005;4(6):1917-1930
26. Chen EI, Hewel J, Felding-Habermann B, et al. Large scale protein profiling by combination of protein fractionation and multidimensional protein identification technology (MudPIT) [J]. Mol Cell Proteomics,2006;5(1):53-56
27. Thulasiraman V, Lin S, Gheorghiu L, et al. Reduction of the concentration difference of proteins in biological liquids using a library of combinatorial ligands[J].Electrophoresis,2005;26(18):3561-3571
28. Issaq HJ, Conrads TP, Prieto DA,et al. SELDI-TOF-MS for diagnostic proteomics[J].Anal Chem,2003;75(7):148-155
29. Diamandis EP. Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems[J].J Natl Cancer Inst, 2004;96(5):353-356
2. Luo HZ, Mi DH, Jing TZ,et al. Risk Factors of Gastric Cancer in Wuwei City-an Endemic Region of Gastric Cancer[J].Ai Zheng,2005;24(5):563-566
3. Anita Mangia,Annalisa Chiriatti,Girolamo Ranieri,et al.H pylori status and angiogenesis factors in human gastric carcinoma[J].World J Gastroenterol,2006;12(34):5465-5472
4. Parkin DM,Bray F,Ferlay J,et al. Global cancer statistics,2002[J]. CA Cancer J Clin, 2005;55(2):74-108
5. Yalamarthi S, Witherspoon P, McCole D, et al. Missed diagnoses in patients with upper gastrointestinal cancers[J]. Endoscopy, 2004;36(10):874-879
6. Amin A,Gilmour H,Graham L,et al. Gastric adenocarcinoma missed at endoscopy[J]. J R Coll Surg Edinb,2002;47(5):681-684
7. Bramble MG,Suvakovic Z,Hungin AP.Detection of upper gastrointestinal cancer in patients taking antisecretory therapy prior to gastroscopy[J]. Gut,2000;46(4):464-467
8. Nakamura H, Yanai H, Satake M. Retrospective Analysis of the Results of Strip Biopsies to Determine the Indication forEndoscopic Submucosal Dissection for Early Gastric Cancer[J].J Gastrointest Cancer,2009;24(5):592-595
9. Voutilainen ME,Juhola MT. Evaluation of the diagnostic accuracy of gastroscopy to detect gastric tumours: clinicopathological features and prognosis of patients with gastric cancer missed on endoscopy[J]. Eur J Gastroenterol Hepatol,2005;17(12):1345-1349
10. Carneiro F,Oliveira C,Leite M.Molecular targets and biological modifiers in gastric cancer[J]. Semin Diagn Pathol,2008 ;25(4):274-287
11. Srinivas PR,Kramer BS,Srivastava S.Trends in biomarker research for cancer detection[J].Lancet Oncol,2001;2(11):698-704
12. Sidransky D.Emerging molecular markers of cancer[J]. Nat Rev Cancer, 2002;2(3):210- 219
13. Koike H,Ichikawa D,Ikoma H,et al. Comparison of serum aberrant methylation and conventional tumor markers in gastric cancer patients[J].Hepatogastroenterology,2005;52(64):1293-1296
14. Tirumalai RS,Chan KC,Prieto DA,et al.Characterization of the low molecular Weight human serum proteome[J].Mol Cell Protcomics, 2003;2(10): 1096-1103
15. Wadie BS, Badawi AM, Abdelwahed M,et al.Application of artificial neural network in prediction of bladder outlet obstruction:a model based on objective, noninvasive parameters[J].Urology,2006;68(6):1211-1214
16. Menges M. Diagnosis, staging and therapy of gastric cancer[J]. ZGastroenterol, 2004;42(8):767-773
17.吴阶平,裘法祖.黄家驯外科学[M].北京:人民卫生出版社,2000;1035-1036
18. Layke JC,Lopez PP.Gastric cancer:diagnosis and treatment options[J]. Am Fam Physician,2004;69(5):1133-1140
19. Hicks S.Gastric cancer: diagnosis, risk factors, treatment and life issues[J].Br J Nurs,2001; 10(8):529-536
20. Sigon R,Canzonieri V,Cannizzaro Ro.Early gastric cancer:diagnosis,surgical treatment and follow-up of 45 cases[J].Tumori,1998;84(5):547-551.
21. Ukrisana P,Wangwinyuvirat M. Evaluation of the sensitivity of the double-contrast upper gastrointestinal series in the diagnosis of gastric cancer[J]. J Med Assoc Thai,2004;87(1):80-86
22. Kobayashi M,Tajiri H,Seike E,et a1.Detection of early gastric cancer by a real-time autofluorescence imaging system[J].Cancer Lett,2001;165(2):155-159
23. Mataki N,Nagao S,Kawaguchi A,et a1.Clinical usefulness of a new infrared videoendoscope system for diagnosis of early stage gastric cancer[J].Gastrointest Endosc,2003;57(3):336-342
24. Tajiri H, Doi T, Endo H,et al.Routine endoscopy using a magnifying endoscope for gastric cancer diagnosis[J]. Endoscopy,2002;34(10):772-777
25. Broutet N,Plebani M ,Sakarovitch C,et a1.Pepsinogen A,pepsinogenC,and gastrin as markers of atrophic chronic gastritis in european dyspeptics[J].Br J Cancer,2003;88(8):1239-1247
26. Chen J, Rocken C, Malfertheiner P,et al. Recent advances in molecular diagnosis and therapy of gastric cancer[J]. Dig Dis,2004;22(4):380-385
27. Pusch W,Kostrzewa M.Application of MALDI-TOF mass spectrometry in screening and diagnostic research[J].Curr Pharm Des,2005;11(20):2577-2591
28. Henderson NA, Steele RJ.SELDI-TOF proteomic analysis and cancer detection[J].Surgeon,2005;3(6):383-390
29. Zhu H, Snyder M. Protein chip technology[J].Curr Opin Chem Biol, 2003;7(1):55-63
30. Seibert V, Wiesner A, Buschmann T,et al. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and ProteinChip technology in proteomics research[J].Pathol Res Pract, 2004;200(2):83-94
31. Batorfi J,Ye B,Mok SC,Cseh I,et al.Protein profiling of complete mole and normal placenta using Protein Chip analysis on laser capture microdissected cells[J].Gvnecol Oncol, 2003;88(3):424-428
32. Petricoin EF,Liotta LA. Proteomic analysis at the bedside:early detection of cancer[J].Trends Biotechnol,2002;20(12):30-34
33. Petricoin EF,Ardekani AM,Hitt BA,et al.Use of proteomic patterns in serum to identify ovarian cancer[J].Lancet,2002;359(9306):572-577
34. Lim JY,Cho JY,Paik YH,et al.Diagnostic application of serum proteomic patterns in gastric cancer patients by Protein Chip surface-enhanced laser desorption/ionization time-of-flight mass spectrometry[J]. Int J Biol Markers,2007;22(4):281-286
35. Diamandis EP. Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems[J].J Natl Cancer Inst, 2004;96(5):353-356
1.娄毅,何向民,宋清斌.Apaf-1基因在胃癌中的表达及临床意义[J].中华医学杂志,2006;86(30):2141-2143
2. Koike H,Ichikawa D,Ikoma H,et al.Comparison of serum aberrant methylation and conventional tumor markers in gastric cancer patients[J].Hepatogastroenterology,2005;52(64):1293-1296
3. Ciordia S,de Los Rios V,Albar JP. Contributions of advanced proteomics technologies to cancer diagnosis[J].Clin Transl Oncol,2006;8(8):566-580
4. Kobayashi M,Tajiri H,Seike E,et a1.Detection of early gastric cancer by a real-time autofluorescence imaging system[J].Cancer Lett,2001;165(2):155-159
5. Mataki N,Nagao S,Kawaguchi A,et a1.Clinical usefulness of a new infrared videoendoscope system for diagnosis of early stage gastric cancer[J].Gastrointest Endosc,2003;57(3):336-342
6. Onodera H,Jokunaga A,Yoshiyuki T.Surgical outcome of 483 patients with early gastric cancer.Best Prstoperative morbidity and mortality,and gastric remnant cancer[J].Hepatogastroengerology,2004;51(55):82-85
7. Broutet N,Plebani M ,Sakarovitch C,et a1.Pepsinogen A,pepsinogen C,and gastrin as markers of atrophic chronic gastritis in european dyspeptics[J].Br J Cancer,2003;88(8):1239-1247
8. Pandey A,Mann M.Proteomics to study genes and genomes[J].Nature,2000;405(6788):8372834
9. Jiang Q,Engelhardt JF . Cellular heterogeneity of CFTR expression and function in the lung: implications for gene therapy of cystic fibrosis[J].Eur J Hum Genet,1998;6(1):12231
10. Brenner SE.Errors in genome annotation[J].Trends Genet,1999;15 (4):132-213
11. Anderson L ,Seilhamer J .A comparison of selected mRNA and protein abundances in human liver[J].Electrophoresis,1997 ;18(324):533-537
12. Pusch W, Kostrzewa M.Application of MALDI-TOF mass spectrometry in screening and diagnostic research[J].Curr Pharm Des, 2005;11(20):2577-2591
13. Henderson NA, Steele RJ.SELDI-TOF proteomic analysis and cancer detection[J].Surgeon,2005;3(6):383-390
14. Zhu H, Snyder M. Protein chip technology[J].Curr Opin Chem Biol, 2003;7(1):55-63
15. Seibert V, Wiesner A, Buschmann T,et al. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and Protein Chip technology in proteomics research[J].Pathol Res Pract, 2004;200(2):83-94
16. Batorfi J,Ye B,Mok SC,Cseh I,Berkowitz RS,Fulop V.Protein profiling of complete mole and normal placenta using Protein Chip analysis on laser capture microdissected cells[J] . Gvnecol Oncol, 2003;88(3):424-428
17. Liang Y, Fang M, Li J, et al. Serum proteomic patterns for gastric lesions as revealed by SELDI mass spectrometry[J].Exp Mol Pathol,2006;81(2):176-180
18. Lim JY, Cho JY, Paik YH, et al. Diagnostic application of serum proteomic patterns in gastric cancer patients by Protein Chip surface-enhanced laser desorption/ionization time-of-flight mass spectrometry[J]. Int J Biol Markers,2007 ;22(4):281-286
19. Su Y, Shen J, Qian H, et al. Diagnosis of gastric cancer using decision tree classification of mass spectral data[J].Cancer Sci,2007;98(1):37-43
20. Qian HG, Shen J, Ma H, et al. Preliminary study on proteomics of gastric carcinoma and its clinical significance[J].World J Gastroenterol ,2005;11(40):6249-6253
21. Ebert MP, Meuer J, Wiemer JC, et al. Identification of gastric cancer patients by serum protein profiling[J].J Proteome Res ,2004;3(6):1261-1266
22.赵长宏,陆海波,马玉彦等,血清蛋白指纹图谱检测诊断早期胃癌临床意义[J].肿瘤防治研究,2006;33(10):750-753
23. Hayashida Y, Honda K, Osaka Y, et al. Possible prediction of chemoradio sensitivity of esophageal cancer by serum protein profiling[J].Clin Cancer Res,2005;11(22):8042-8047
24. Caspersen MB, Sorensen NM, Schrohl AS, et al. Investigation of tissue inhibitor of metalloproteinases 1 in plasma from colorectalcancer patients and blood donors by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry[J].Int J Biol Markers,2007;22(2):89-94
25. Castagna A, Cecconi D, Sennels L, et al. Exploring the hidden human urinary proteome via ligand library beads[J].J Proteome Res ,2005;4(6):1917-1930
26. Chen EI, Hewel J, Felding-Habermann B, et al. Large scale protein profiling by combination of protein fractionation and multidimensional protein identification technology (MudPIT) [J]. Mol Cell Proteomics,2006;5(1):53-56
27. Thulasiraman V, Lin S, Gheorghiu L, et al. Reduction of the concentration difference of proteins in biological liquids using a library of combinatorial ligands[J].Electrophoresis,2005;26(18):3561-3571
28. Issaq HJ, Conrads TP, Prieto DA,et al. SELDI-TOF-MS for diagnostic proteomics[J].Anal Chem,2003;75(7):148-155
29. Diamandis EP. Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems[J].J Natl Cancer Inst, 2004;96(5):353-356
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