良、恶性胸腔积液蛋白质组学研究
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摘要
良、恶性胸腔积液的蛋白质组学研究
【目的】利用蛋白质组学技术获得并分析良、恶性胸腔积液的蛋白质表达谱,寻找具有诊断意义的蛋白标志物及建立诊断模型,有利于恶性胸腔积液的诊断及良、恶性胸腔积液的鉴别。
【方法】收集一组恶性胸腔积液(8例肺腺癌癌性胸腔积液)和一组良性胸腔积液(共7例,4例为炎症性胸腔积液,3例为漏出液),经磁珠纯化(液体蛋白芯片技术)、基质辅助激光解析电离飞行时间质谱(MALDI-TOF-MS)分析及生物信息学方法获得并研究其蛋白质表达谱。
【结果】经良、恶性胸腔积液蛋白质图谱分析比较,找到两个具有显著统计学差异的蛋白,质核比(m／z)分别为3927.49Da及5865.49Da,在恶性胸腔积液中均呈低表达。建立了诊断模型,建模蛋白质为5534.81(m／z)、4963.18(m／z)、2788.87(m／z)。
【结论】利用液体蛋白芯片-飞行时间质谱技术对良、恶性胸腔积液进行蛋白质组学研究,获得了良、恶性胸腔积液的蛋白质图谱,得到了差异蛋白和诊断模型,为临床胸腔积液的诊断与鉴别诊断提供了新的思路和方法,差异蛋白质的鉴定结果可能为肺腺癌及恶性胸腔积液的诊断及治疗提供有价值的途径。
Objective Use the proteomics technology to acquire and analyze the protein profiles of the benign and malignant pleural effusion, to seek useful protein biomarkers with diagnostic value and to establish the diagnostic model, for diagnosis of the malignant pleural effusion and antidiastole between the benign and malignant pleural effusion.
Method Collect one group of malignant pleural effusion (8 samples from 8 lung adenocarcinoma patients) and one group of benign pleural effusion (total 7 samples including 4 inflammatory pleural effusion and 3 transudate), to acquire and analyze their protein profiles by functional magnetic bead based sample fractionation method (liquid protein chip technology) combinded with matrix-assisted laser desorption/ionization—time of flight—mass spectrometry (MALDI-TOF-MS) and bioinformatics method.
Results The protein profiles of benign and malignant pleural effusion were analyzed and compared. Two differential proteins with significant statistical difference were got, the mass-to-charge ratio (m/z) were 3927.49Da and 5865.49Da respectively, down-regulated in the malignant pleural effusion. The diagnostic model was established with three proteins which the mass-to-charge ratio (m/z) were 5534.81Da and 4963.18Da and 2788.87 respectively.
Conclusion Through the proteomic study of benign and malignant pleural effusion by using liquid protein chip technology combinded with time of flight—mass spectrometry method, we acquired the protein profiles of the benign and malignant pleural effusion, besides, got the differential proteins and diagnostic model. The result provided new thought and method for diagnosis and antidiastole of the malignant pleural effusion in clinics. Furthermore, the identification of differential proteins maybe provide valuable path to the diagnosis and therapy of lung adenocarcinoma and malignant pleural effusion.
【目的】利用蛋白质组学技术获得并分析良、恶性胸腔积液的蛋白质表达谱,寻找具有诊断意义的蛋白标志物及建立诊断模型,有利于恶性胸腔积液的诊断及良、恶性胸腔积液的鉴别。
【方法】收集一组恶性胸腔积液(8例肺腺癌癌性胸腔积液)和一组良性胸腔积液(共7例,4例为炎症性胸腔积液,3例为漏出液),经磁珠纯化(液体蛋白芯片技术)、基质辅助激光解析电离飞行时间质谱(MALDI-TOF-MS)分析及生物信息学方法获得并研究其蛋白质表达谱。
【结果】经良、恶性胸腔积液蛋白质图谱分析比较,找到两个具有显著统计学差异的蛋白,质核比(m／z)分别为3927.49Da及5865.49Da,在恶性胸腔积液中均呈低表达。建立了诊断模型,建模蛋白质为5534.81(m／z)、4963.18(m／z)、2788.87(m／z)。
【结论】利用液体蛋白芯片-飞行时间质谱技术对良、恶性胸腔积液进行蛋白质组学研究,获得了良、恶性胸腔积液的蛋白质图谱,得到了差异蛋白和诊断模型,为临床胸腔积液的诊断与鉴别诊断提供了新的思路和方法,差异蛋白质的鉴定结果可能为肺腺癌及恶性胸腔积液的诊断及治疗提供有价值的途径。
Objective Use the proteomics technology to acquire and analyze the protein profiles of the benign and malignant pleural effusion, to seek useful protein biomarkers with diagnostic value and to establish the diagnostic model, for diagnosis of the malignant pleural effusion and antidiastole between the benign and malignant pleural effusion.
Method Collect one group of malignant pleural effusion (8 samples from 8 lung adenocarcinoma patients) and one group of benign pleural effusion (total 7 samples including 4 inflammatory pleural effusion and 3 transudate), to acquire and analyze their protein profiles by functional magnetic bead based sample fractionation method (liquid protein chip technology) combinded with matrix-assisted laser desorption/ionization—time of flight—mass spectrometry (MALDI-TOF-MS) and bioinformatics method.
Results The protein profiles of benign and malignant pleural effusion were analyzed and compared. Two differential proteins with significant statistical difference were got, the mass-to-charge ratio (m/z) were 3927.49Da and 5865.49Da respectively, down-regulated in the malignant pleural effusion. The diagnostic model was established with three proteins which the mass-to-charge ratio (m/z) were 5534.81Da and 4963.18Da and 2788.87 respectively.
Conclusion Through the proteomic study of benign and malignant pleural effusion by using liquid protein chip technology combinded with time of flight—mass spectrometry method, we acquired the protein profiles of the benign and malignant pleural effusion, besides, got the differential proteins and diagnostic model. The result provided new thought and method for diagnosis and antidiastole of the malignant pleural effusion in clinics. Furthermore, the identification of differential proteins maybe provide valuable path to the diagnosis and therapy of lung adenocarcinoma and malignant pleural effusion.
引文
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[39]Valdes L, Alvarez D, Valle JM, et al. The etiology of pleural effusions in an area with high incidence of tuberculosis[J]. Chest,1996,109:158-162.
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[42]Pothur RS, Mukesh V, Yinming Z, et al. Proteomics for cancer biomarker discovery[J]. Clinical Chemistry,2002,48(8):1160-1169.
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[44]Lee WC, Lee KH. Applications of affinity chromatography in proteomics[J]. Anal Biochem,2004,324(1):1-10.
[45]Tyan YC, Wu HY, Lai WW, et al. Proteomic profiling of human pleural effusion using two-dimensional nano liquid chromatography tandem mass spectrometry[J]. Journal of Proteome Research,2005,4 (4):1274-1286.
[46]Tyan YC, Wu HY, Su WC, et al. Proteomic analysis of human pleural effusion[J]. Proteomics,2005,5(4):1062-1074.
[47]Hsieh WY, Chen MW, Ho HT, et al. Identification of differentially expressed proteins in human malignant pleural effusions [J].European Respiratory Journal,2006,28(6):1178-1185.
[48]Bard MP, Hegmans JP, Hemmes A,et al.Proteomic analysis of exosomes isolated from human malignant pleural effusions[J]. American Journal of Respiratory Cell and Molecular Biology,2004,31(1):114-121.
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[1]Wilkins MR, Sanchez JC, Cooley AA, et al. Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it. Biotechnol Genet Eng Rev,1996.13(1):19-50.
[2]Dove, A., Proteomics:translating genomics into products? Nature Biotechnology,1999,17 (3):233-236.
[3]Yu LR,Zeng R,Shao XX,et al.Identification of differentially expressed proteins between human hepatoma and normal liver cell lines by two-dimensional eletrophoresis and liquid chromatography-ion trap mass spectrometry. Eletrophoresis,2000,21:3058-3068.
[4]Steiner S,Witzmann FA.Proteomics:application and opportunities in preclinical drug development. Eletrophoresis,2000,21:2099-2104.
[5]Soskic V,Gorlach M,Poznanovic S,et al.Functional proteomics analysis of signal transduction pathways of the platelet-derived growth factor β receptor.Biochemistry,1999,38:1757-1764.
[6]Liotta LA, Kohn EC, Petricoin EF. Clinical promeotics:personalized molecular medicine. JAMA,2001,286 (18):2211-2214.
[7]陈主初,梁宋平,主编.肿瘤蛋白质组学[M].长沙：湖南科学技术出版社,2002,168.
[8]Pothur RS, Mukesh V, Yinming Z, et al. Proteomics for cancer biomarker discovery[J]. Clinical Chemistry,2002,48(8):1160-1169.
[9]Ketterlinus R, Hsieh SY, Teng SH, et al. Fishing for biomarkers:analyzing mass spectrometry data with the new Clinprotools software[J]. Biotechniques,2005, Suppl:37-40.
[10]王胜林,王强斌,古宏晨,等.磁性微球的生物医学应用研究进展[J].化学世界,2001,42(7)：384-386.
[11]Quadroni,M., James,P.. Proteomics and automation. Electrophoresis,1999,20 (4-5):664-677.
[12]Cheng, A.J., et al., Oral cancer plasma tumor marker identified with bead-based affinity-fractionated proteomic technology.Clin Chem,2005.51(12):p.2236-44.
[13]李甜,谌宏鸣.应用液体蛋白芯片-飞行时间质谱技术从血清中筛选胃癌肿瘤标志蛋白[J].现代肿瘤医学,2009,(08).
[2]Dove, A., Proteomics:translating genomics into products? Nature Biotechnology,1999,17 (3):233-236.
[3]李佰良.功能蛋白质组学[J].生命的化学.1998,18(6)：1-3.
[4]Hille JM,Freed AL,Watzig H. Possibilities to improve automation,speed and precision of proteome analysis:a comparision of two-dimensional eletrophoresis and alternatives. Electrophoresis,2001,22:4035-4052.
[5]Yu LR,Zeng R,Shao XX,et al.Identification of differentially expressed proteins between human hepatoma and normal liver cell lines by two-dimensional eletrophoresis and liquid chromatography-ion trap mass spectrometry. Eletrophoresis,2000,21:3058-3068.
[6]Steiner S,Witzmann FA.Proteomics:application and opportunities in preclinical drug development. Eletrophoresis,2000,21:2099-2104.
[7]Soskic V,Gorlach M,Poznanovic S,et al.Functional proteomics analysis of signal transduction pathways of the platelet-derived growth factor β receptor.Biochemistry,1999,38:1757-1764.
[8]O'Farrel PH. High resolution two-dimensional electrophoresis of ptoteins. J BIOL Chem,1975,250:4007-4021.
[9]Too WA,Lee DY,Kim CW.Development of an effective sample preparation method for the proteome analysis of body fluid using 2-D gel electrophoresis. Biosci Biotechnol Biochem,2003,67:1574-1577.
[10]Manable T.Analysis of complex protein-polypeptide systems for proteomics studies.J Chromatogr B Analyt Technol Biomed Life Sci,2003,787:29-41.
[11]Aebersold R, Mann M. Mass spectrometry-based proteomics. Nature,2003,422: 198-207.
[12]Mayrhofer C,Krieger S,Allmaier G,et al.DIGE compatible labeling of surface proteins on vital cells in vitro and in vivo.Proteomics,2006,6:579-585.
[13]Fauq AH, Kache R, Khan MA, et al. Synthesis of acid-cleavable light isotope-coded affinity tags (icat-1) for potential use in proteomic expression profiling analysis.Bioconjug Chem,2006,17:248-254.
[14]Shui WQ,Liu YK,Fan HZ,et al.Enhancing TOF-TOF-based novo sequencing for high thoughput identification with amino acid coded mass tagging.J Proteome Research,2005,4:83-90.
[15]Wolters DA, Washburn M P, Yates JR. An automated multidimensional Protein identification technology for shotgun proteomics[J].Anal.Chem,2001,73, 5683-5690.
[16]Wu CC, MacCoss MJ, Howell KE, et al. A method for the comprehensive proteomic analysis of membrane Proteins[J].Nat Biotechnol,2003,21,532-538.
[17]Washburn MP, Wolters D, Yates JR, et al. Large scale analysis of the yeast proteome by multi dimensional protein identification technology [J]. Nature biotechnology,2001,19:242-247.
[18]Chambers G, Lawrie L, Cash P, et al. Proteomics:A new approach to the study of disease[J]. Journal of Pathology,2000,192 (3):280-288.
[19]Grazyna Kwapiszewska, Markus Meyer, Ralf Bogumil, et al.Identification of proteins in laser-microdissected small cell numbers by SELDI TOF and Tandem MS. BMC Biotechnol,2004,3(3):1472-1482.
[20]Fink L,Kohlhoff S, Stein MM, et al. cDNA array hybridization after laserrassisted microdisseetion from nonneoplastic tissue.Am J Pathol,2002,160 (1):81-90.
[21]Ketterlinus R, Hsieh SY, Teng SH, et al. Fishing for biomarkers:analyzing mass spectrometry data with the new Clinprotools software[J]. Biotechniques,2005, Suppl:37-40.
[22]王胜林,王强斌,古宏晨,等.磁性微球的生物医学应用研究进展[J].化学世界,2001,42(7)：384-386.
[23]Gygi SP, Corthals GL, Zhang Y. et al. Evaluation of twodimensional gel electrophoresis-based proteome analysis technology. Proe Natl Acad Sci USA. 2000,97:9390-9395.
[24]Ledue TB, Garfin D. Manual of clinic laboratory microbiology.5th eds. Washington DC:American Society for Microbiology,1997.pp54-64.
[25]Puig O,Caspary F,Rigaut G,et al.The tandem affinity purification (TAP) method:a general procedure of protein complex purification. Methods,2001,24:218-229.
[26]Michael J, Simon J. Advances in mass spectrometry for proteome analysis [J]. Current Opinion in Biotechnology,2000,11:384-390.
[27]Chambers, G., Lawrie, L., Cash, P., et al. Proteomics:A new approach to the study of disease. Journal of Pathology,2000,192 (3):280-288.
[28]Karas, M., Hillenkamp, F..Laser desorption ionization of proteins with molecular masses exceeding 10000 daltons. Anal Chem,1988,60(20):2299-2301Fenn JB, Mann M,
[29]Merchant M, Weinberger SR. Recent advancements in surface-enhanced laser desorption/ionization-time of flight-mass spectrometry.Electrophoresis.2000,21: 1164-1177.
[30]Quadroni,M., James,P.. Proteomics and automation. Electrophoresis,1999,20 (4-5):664-677.
[31]Mann M, Wilm M. Error to lerant identification of peptides in sequence databases by peptide sequence tags[J]. Anal Chem,1994,66(24):4390-4399.
[32]张宏一.蛋白质组学研究技术及其进展.生物技术通报,2005,21(4)：31-36.
[33]Wolters DA, Washburn M P, Yates JR. An automated multidimensional Protein identification technology for shotgun proteomics [J]. Anal.Chem, 2001,73,5683-5690.
[34]Liotta LA, Kohn EC, Petricoin EF. Clinical promeotics:personalized molecular medicine. JAMA,2001,286 (18):2211-2214.
[35]陈主初,梁宋平,主编.肿瘤蛋白质组学[M].长沙：湖南科学技术出版社,2002,168.
[36]Albertini RJ. Biomarker responses in human populations:towards a worldwide map[J]. Mutation Res,1999,428(1-2):217-226.
[37]Wulfkuhle JD, Liotta LA, Pericoin EF. Proteomic applications for the early detection of cancer[J]. Nat Rev Cancer,2003,3(4):267-275.
[38]陈灏珠,主编.实用内科学[M].第12版.北京：人民卫生出版社,2005,1757.
[39]Valdes L, Alvarez D, Valle JM, et al. The etiology of pleural effusions in an area with high incidence of tuberculosis[J]. Chest,1996,109:158-162.
[40]Marel M, Zrustova M, Stasny B, Light RW. The incidence of pleural effusion in a well-defined region:epidemiologic study in central Bohemia[J]. Chest,1993,104:1486-1489.
[41]DeCamp MM, Mentzer SJ, Swanson SJ, et al. Malignant effusive disease of the pleura and pericardium. Chest,1997,112:291-295.
[42]Pothur RS, Mukesh V, Yinming Z, et al. Proteomics for cancer biomarker discovery[J]. Clinical Chemistry,2002,48(8):1160-1169.
[43]樊英,李龙芸.良恶性胸腔积液的鉴别诊断[J].癌症进展杂志,2005,3(2)：135-138.
[44]Lee WC, Lee KH. Applications of affinity chromatography in proteomics[J]. Anal Biochem,2004,324(1):1-10.
[45]Tyan YC, Wu HY, Lai WW, et al. Proteomic profiling of human pleural effusion using two-dimensional nano liquid chromatography tandem mass spectrometry[J]. Journal of Proteome Research,2005,4 (4):1274-1286.
[46]Tyan YC, Wu HY, Su WC, et al. Proteomic analysis of human pleural effusion[J]. Proteomics,2005,5(4):1062-1074.
[47]Hsieh WY, Chen MW, Ho HT, et al. Identification of differentially expressed proteins in human malignant pleural effusions [J].European Respiratory Journal,2006,28(6):1178-1185.
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