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Vascular Proteomics

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Vascular Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1000))

Abstract

Cardiovascular diseases constitute the largest of death in developed countries, being atherosclerosis the major contributor. Atherosclerosis is a process of chronic inflammation, characterized by the accumulation of lipids, cells, and fibrous elements in medium and large arteries. There is a continuum in atherosclerotic cardiovascular pathology that extends from the initial endothelial damage to diseases such as angina, myocardial infarction, and stroke. The extent of inflammation, proteolysis, calcification, and neovascularization influences the development of advanced lesions (atheroma plaques) on the arteries. Plaque rupture and the ensuing thrombosis cause the acute complications of atherosclerosis, i.e., myocardial infarction and cerebral ischemia. Thus, identification of early biomarkers of plaque unstability and susceptibility to rupture is of capital importance in preventing acute events. In recent years proteomics has been successfully applied to study proteins involved in these pathological processes. Thus, proteomic studies have been carried out focusing on different elements such as vascular tissues (arteries), artery layers, cells looking at proteomes and secretomes, plasma/serum, exosomes, lipoproteins, and metabolites. This chapter will provide an overview of latest advances in proteomic studies of atherosclerosis and related vascular diseases.

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References

  1. Davignon J, Ganz P (2004) Role of endothelial dysfunction in atherosclerosis. Circulation 109:III27–III32

    PubMed  Google Scholar 

  2. Alvarez-Llamas G, de la Cuesta F, Barderas MG, Darde V, Padial LR, Vivanco F (2008) Recent advances in atherosclerosis-based proteomics: new biomarkers and a future perspective. Expert Rev Proteomics 5:679–691

    Article  PubMed  CAS  Google Scholar 

  3. Biomarkers Definitions Working Group (2001) Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 69:89–95

    Article  Google Scholar 

  4. Finley Austin MJ, Babiss L (2006) Commentary: where and how could biomarkers be used in 2016. AAPS J 8:E185–E189

    Article  PubMed  CAS  Google Scholar 

  5. Sturgeon C, Hill R, Hortin GL, Thompson D (2010) Taking a new biomarker into routine use—a perspective from the routine clinical biochemistry laboratory. Proteomics Clin Appl 4:892–903

    Article  PubMed  CAS  Google Scholar 

  6. Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB (1998) Prediction of coronary heart disease using risk factor categories. Circulation 97:1837–1847

    Article  PubMed  CAS  Google Scholar 

  7. Apple FS, Collinson PO (2012) IFCC task force on clinical applications of cardiac biomarkers. Analytical characteristics of high-sensitivity cardiac troponin assays. Clin Chem 58:54–61

    Article  PubMed  CAS  Google Scholar 

  8. Di Angelantonio E, Chowdhury R, Sarwar N, Ray KK, Gobin R, Saleheen D et al (2009) B-type natriuretic peptides and cardiovascular risk: systematic review and meta-analysis of 40 prospective studies. Circulation 120:2177–2187

    Article  PubMed  Google Scholar 

  9. Nicholson JK, Lindon LC (2008) Systems ­biology: metabolomics. Nature 455:1054–1056

    Article  PubMed  CAS  Google Scholar 

  10. Wike RA, Mereedu RK, Moore JH (2008) The pathway less traveled: moving from candidate genes to candidate pathways in the analysis of genome-wide data from large scala pharmacogenetic association studies. Curr Pharmacogenomics Person Med 6:150–159

    Article  Google Scholar 

  11. Ozdemir V, Suarez-Kurtz G, Stenne E, Somoggyi A, Kayaalp O, Kolker E (2008) Risk assessment and communication tools for genotype associations with multifactorial phenotypes: The concept of “edge effect” and cultivating an ethical bridge between omics innovations and society. J Integr Biol 13:43–62

    Google Scholar 

  12. Beer LA, Tang H, Barnhart KT, Speicher DW (2011) Plasma biomarker discovery using 3D protein profiling coupled with label-free quantitation methods. Mol Biol 728:3–27

    CAS  Google Scholar 

  13. Thakur SS, Geiger T, Chatterjee B, Bandilla P, Fröhlich F, Cox J, Mann M (2011) Deep and highly sensitive proteome coverage by LC-MS/MS without prefractionation. Mol Cell Proteomics 10:M110.003699

    Article  PubMed  Google Scholar 

  14. Mischak H, Coon JJ, Novak J, Weissinger EM, Schanstra J, Dominiczak AF (2009) Capillary electrophoresis—mass spectrometry as a powerful tool in biomarker discovery and clinical diagnosis: an update of recent developments. Mass Spectrom Rev 28:703–724

    Article  PubMed  CAS  Google Scholar 

  15. Barderas MG, Laborde CM, Posada M, de la Cuesta F, Zubiri I, Vivanco F, Alvarez-Llamas G (2011) Metabolomic profiling for identification of novel potential biomarkers in cardiovascular diseases. J Biomed Biotechnol doi: 10.1155/2011/790132.

    Google Scholar 

  16. Rhee EP, Gerszten RE (2012) Metabolomics and cardiovascular biomarker discovery. Clin Chem 58:139–147

    Article  PubMed  CAS  Google Scholar 

  17. McDonnell LA, Heeren RMA (2007) Imaging mass spectrometry. Mass Spectrom Rev 26:606–643

    Article  PubMed  CAS  Google Scholar 

  18. Wang J, Balu N, Canton G, Yuan C (2010) Imaging biomarkers of cardiovascular disease. J Magn Reson Imaging 32:502–515

    Article  PubMed  Google Scholar 

  19. Lange V, Picotti P, Domon B, Aebersold R (2008) Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol 4:222

    Article  PubMed  Google Scholar 

  20. Veenstra TD, Conrads TP, Hood BL, Avellino AM, Ellenbogen RG (2005) Biomarkers: mining the biofluid proteome. Mol Cell Proteomics 4:409–418

    Article  PubMed  CAS  Google Scholar 

  21. Anderson NL (2005) Candidate-based proteomics in the search for biomarkers of cardiovascular disease. J Physiol 563:23–60

    Article  PubMed  CAS  Google Scholar 

  22. Wang YY, Cheng P, Chan DW (2003) A simple affinity spin tube filter method for removing high-abundant common proteins or enriching low-abundant biomarkers for serum proteomic analysis. Proteomics 3:243–248

    Article  PubMed  CAS  Google Scholar 

  23. Bjorhall K, Miliotis T, Davidsson P (2005) Interest of major serum protein removal for surface-enhanced laser desorption/ionization—time of flight (SELDI-TOF) proteomic blood profiling. Proteomics 5:307–317

    Article  PubMed  Google Scholar 

  24. Seam N, Gonzales DA, Kern SJ, Hortin GL, Hoehn GT, Suffredini AF (2007) Quality control of serum albumin depletion for proteomic analysis. Clin Chem 53:1915–1920

    Article  PubMed  CAS  Google Scholar 

  25. Thongboonkerd V, McLeish KR, Arthur JM, Kelin JB (2002) Proteomic analysis of normal human urinary proteins isolated by acetone precipitation or ultracentrifugation. Kidney Int 62:1461–1469

    Article  PubMed  CAS  Google Scholar 

  26. Thongboonkerd V, Malasit P (2007) Renal and urinary proteomics: current applications and challenges. Proteomics 5:1033–1042

    Article  Google Scholar 

  27. Espina V et al (2008) A portrait of tissue phosphoprotein stability in the clinical tissue procurement process. Mol Cell Proteomics 7:1998–2018

    Article  PubMed  CAS  Google Scholar 

  28. Emmert-Buck MR et al (1996) Laser capture microdissection. Science 274:998–1001

    Article  PubMed  CAS  Google Scholar 

  29. Alvarez-Llamas G et al (2007) Characterization of the human visceral adipose tissue secretome. Mol Cell Proteomics 6:589–600

    Article  PubMed  CAS  Google Scholar 

  30. Hocking SL et al (2010) Intrinsic depot-specific differences in the secretome of adipose tissue, preadipocytes, and adipose tissue-derived microvascular endothelial cells. Diabetes 59:3008–3016

    Article  PubMed  CAS  Google Scholar 

  31. Danesh J, Wheeler JG, Hirschfield GM, Eda S, Eiriksdottir G, Rumley A, Lowe GD, Pepys MB, Gudnason V (2004) C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med 350:1387–1397

    Article  PubMed  CAS  Google Scholar 

  32. Sidney C, Smith J, Anderson JL, Cannon RO, Fadl YY, Koenig W, Libby P, Lipshultz SE, Mensah GA, Ridker PM, Rosenson R (2004) CDC/AHA Workshop on markers of inflammation and cardiovascular disease application to clinical and public health practice: report from the Clinical Practice Discussion Group. Circulation 110:e550–e555

    Article  Google Scholar 

  33. Mayr M, Mayr U, Chung YL, Yin X, Griffiths JR, Xu Q (2004) Vascular proteomics: linking proteomic and metabolomic changes. Proteomics 4:3751–3761

    Article  PubMed  CAS  Google Scholar 

  34. Marian AJ, Nambi V (2004) Biomarkers of cardiac disease. Expert Rev Mol Diagn 2004(4):805–820

    Article  Google Scholar 

  35. Berhane BT, Zong C, Liem DA, Huang A, Le S, Edmondson RD, Jones RC, Qiao X, Whitelegge JP, Ping P, Vondriska TM (2005) Cardiovascular-related proteins identified in human plasma by the HUPO Plasma Proteome Project pilot phase. Proteomics 5:3520–3530

    Article  PubMed  CAS  Google Scholar 

  36. Brea D, Sobrino T, Blanco M, Fraga M, Agulla J, Rodriguez-Yañez M, Rodriguez-Gonzalez R, Perez de la Ossa N, Leira R, Forteza J, Davalos A, Castillo J (2009) Usefulness of haptoglobin and serum amyloid A proteins as biomarkers for atherothrombotic ischemic stroke diagnoses confirmation. Atherosclerosis 205(2):561–567

    Article  PubMed  CAS  Google Scholar 

  37. Ganesh SK, Sharma Y, Dayhoff J, Fales HM, Van Eyk J, Kickler TS, Billings EM, Nabel EG (2007) Detection of venous thromboembolism by proteomic serum biomarkers. PLoS One 2(6):e544

    Article  PubMed  Google Scholar 

  38. Liu RX, Chen HB, Tu K, Zhao SH, Li SJ, Dai J, Li QR, Nie S, Li YX, Jia WP, Wu JR (2008) Localized-statistical quantification of human serum proteome associated with type 2 diabetes. PLoS One 3:e3224

    Article  Google Scholar 

  39. Zimmerli LU, Schiffer E, Zürbig P, Good DM, Kellmann M, Mouls L, Pitt AR, Coon JJ, Schmieder RE, Peter KH, Mischak H, Kolch W, Delles C, Dominiczak AF (2008) Urinary proteomic biomarkers in coronary artery disease. Mol Cell Proteomics 7:290–298

    PubMed  CAS  Google Scholar 

  40. Coon J, Zurbig P, Dakna M, Dominiczak A, Decramer S et al (2008) CE-MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics. Proteomics Clin Appl 2:964–973

    Article  PubMed  CAS  Google Scholar 

  41. Von zur Muhlen C, Schiffer E, Zuerbig P, Kellmann M, Brasse M, Meert N, Vanholder RC, Dominiczak AF, Chen YC, Mischak H, Bode C, Peter K (2009) Evaluation of urine proteome pattern analysis for its potential to reflect coronary artery atherosclerosis in symptomatic patients. J Proteome Res 8:335–345

    Article  PubMed  CAS  Google Scholar 

  42. Martinet W, Schrijvers DM, De Meyer GR, Herman AG, Kockx MM (2003) Western array analysis of human atherosclerotic plaques. Down regulation of apoptosis-linked gene 2. Cardiovasc Res 60:259–267

    Article  PubMed  CAS  Google Scholar 

  43. Martinet W (2006) Western array analysis of human atherosclerotic plaques. Methods Mol Biol 357:165–178

    Google Scholar 

  44. Donners M, Verluyten MJ, Bouwman FG, Mariman E, Devrese B et al (2005) Proteomic analysis of differential protein expression in human atherosclerotic plaque progression. J Pathol 206:39–45

    Article  PubMed  CAS  Google Scholar 

  45. Slevin M, Elasbali AB, Turu M, Krupinski J, Badimon L et al (2006) Identification of differential protein expression associated with development of unstable human carotid plaques. Am J Pathol 168:1004–1021

    Article  PubMed  CAS  Google Scholar 

  46. Roelofsen H, Dijkstra M, Weening D, de Vries MP, Hoek A, Vonk RJ (2009) Comparison of isotope-labeled amino acid incorporation rates (CILAIR) provides a quantitative method to study tissue secretomes. Mol Cell Proteomics 8:316–324

    PubMed  CAS  Google Scholar 

  47. Durán MC, Mas S, Martin-Ventura JL, Meilhac O, Michel JB et al (2003) Proteomic analysis of human vessels: application to atherosclerotic plaques. Proteomics 3:973–978

    Article  PubMed  Google Scholar 

  48. Durán MC, Martin-Ventura JL, Mohammed S, Barderas MG, Mas S et al (2007) Atorvastatin modulates the profile of proteins released by human atherosclerotic plaques. Eur J Pharmacol 562(1–2):119–129

    Article  PubMed  Google Scholar 

  49. Duran MC, Martín-Ventura JL, Mas S, Barderas MG, Darde V et al (2006) Characterization of the human atherome plaque secretome by proteomic analysis. Methods Mol Biol 357:141–150

    Google Scholar 

  50. Vivanco F, Martin-Ventura JL, Duran MC, Barderas MG, Blanco-Colio L et al (2005) Quest for novel cardiovascular biomarkers by proteomic analysis. J Proteome Res 4:1181–1191

    Article  PubMed  CAS  Google Scholar 

  51. Martín-Ventura JL, Duran MC, Blanco-Colio L, Meilhac O, Leclercq A et al (2004) Identification by a differential proteomic approach of heat shock protein 27 as a potential marker of atherosclerosis. Circulation 110:2216–2219

    Article  PubMed  Google Scholar 

  52. Martin-Ventura JL, Nicolas V, Houard X, Blanco-Colio L, Leclercq A et al (2006) Biological significance of decreased HSP27 in human atherosclerosis. Arterioscler Thromb Vasc Biol 26:1337–1343

    Article  PubMed  CAS  Google Scholar 

  53. de la Cuesta F, Barderas MG, Calvo E, Zubiri I, Maroto AS, Darde VM, Martin-Rojas T, Gil-Dones F, Posada-Ayala M, Tejerina T, Lopez JA, Vivanco F, Alvarez-Llamas G (2011) Secretome analysis of atherosclerotic and non-atherosclerotic arteries reveals dynamic extracellular remodeling during pathogenesis. J Proteomics 75(10): 2960–2971

    Article  PubMed  Google Scholar 

  54. Fiehn O, Kopka J, Dormann P, Altmann T, Trethwey R, Wilmitzer J (2000) Metabolite profiling for plant functional genomics. Nat Biotechnol 18:1157–1161

    Article  PubMed  CAS  Google Scholar 

  55. Nicholson JK, Lindon J, Holmes E (1999) Metabolomics: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NRM spectroscopic data. Xenobiotica 29:1181–1189

    Article  PubMed  CAS  Google Scholar 

  56. Dunn W, Bailey N, Johnso H (2005) Measuring the metabolome: current analytical technologies. Analyst 130:606–625

    Article  PubMed  CAS  Google Scholar 

  57. Harrigan G, LaPlante R, Cosma G, Cockerell G, Goodacre R, Maddox J et al (2004) Application of high-throughput Fourier-transform infrared spectroscopy in toxicology studies: contribution to a study on the development of an animal model for idiosyncratic toxicity. Toxicol Lett 146:197–205

    Article  PubMed  CAS  Google Scholar 

  58. Lenz EM, Bright J, Wilson ID, Morgan SR, Nash AF (2003) A 1H NMR-based metabonomic study of urine and plasma samples obtained from healthy human subjects. J Pharm Biomed Anal 33:1103–1115

    Article  PubMed  CAS  Google Scholar 

  59. Musiek ES, Yin H, Milne GL, Morrow JD (2005) Recent advances in the biochemistry and clinical relevance of the isoprostane pathway. Lipids 40:987–994

    Article  PubMed  CAS  Google Scholar 

  60. Cho HJ, Kim JD, Lee WY, Chung BC, Choi MH (2009) Quantitative metabolic profiling of 21 endogenous corticosteroids in urine by liquid chromatography-triple quadrupole-mass spectrometry. Anal Chim Acta 632:101–108

    Article  PubMed  CAS  Google Scholar 

  61. Wang Z, Tang WH, Cho L, Brennan DM, Hazen SL (2009) Targeted metabolomic evaluation of arginine methylation and cardiovascular risks: potential mechanisms beyond nitric oxide synthase inhibition. Arterioscler Thromb Vasc Biol 29:1383–1391

    Article  PubMed  CAS  Google Scholar 

  62. Teul J, Ruperez FJ, Garcia A, Vaysse J, Balayssac S, Gilard V et al (2009) Improving metabolite knowledge in stable atherosclerosis patients by association and correlation of GC-MS and 1H NMR fingerprints. J Proteome Res 8: 5580–5589

    Article  PubMed  CAS  Google Scholar 

  63. Mayr M, Yusuf S, Weir G, Chung YL, Mayr U, Yin X et al (2008) Combined metabolomic and proteomic analysis of human atrial fibrillation. J Am Coll Cardiol 51:585–594

    Article  PubMed  CAS  Google Scholar 

  64. Chen X, Liu L, Palacios G, Gao J, Zhang N, Li G, Lu J, Song T, Zhang Y (2010) Plasma metabolomics reveals biomarkers of the atherosclerosis. J Sep Sci 33:2776–2783

    Article  PubMed  CAS  Google Scholar 

  65. Zhang F, Jia Z, Gao P, Kong H, Li X, Chen J et al (2009) Metabonomics study of atherosclerosis rats by ultra fast liquid chromatography coupled with ion trap-time of flight mass spectrometry. Talanta 79:836–844

    Article  PubMed  CAS  Google Scholar 

  66. Turer AT, Stevens RD, Bain JR, Muehlbauer MJ, van der WJ, Mathew JP et al (2009) Metabolomic profiling reveals distinct patterns of myocardial substrate use in humans with coronary artery disease or left ventricular dysfunction during surgical ischemia/reperfusion. Circulation 119:1736–1746

    Article  PubMed  CAS  Google Scholar 

  67. Zhao G, Jeoung NH, Burgess SC, Rosaaen-Stowe KA, Inagaki T, Latif S et al (2008) Overexpression of pyruvate dehydrogenase kinase 4 in heart perturbs metabolism and exacerbates calcineurin-induced cardiomyopathy. Am J Physiol Heart Circ Physiol 294:H936–H943

    Article  PubMed  CAS  Google Scholar 

  68. Lewis GD, Wei R, Liu E, Yang E, Shi X, Martinovic M et al (2008) Metabolite profiling of blood from individuals undergoing planned myocardial infarction reveals early markers of myocardial injury. J Clin Invest 118:3503–3512

    Article  PubMed  CAS  Google Scholar 

  69. Vallejo M, Garcia A, Tunon J, Garcia-Martinez D, Angulo S, Martin-Ventura JL et al (2009) Plasma fingerprinting with GC-MS in acute coronary syndrome. Anal Bioanal Chem 394:1517–1524

    Article  PubMed  CAS  Google Scholar 

  70. von Zur Muhlen C, Schiffer E, Zuerbig P, Kellmann M, Brasse M, Meert N et al (2009) Evaluation of urine proteome pattern analysis for its potential to reflect coronary artery atherosclerosis in symptomatic patients. J Proteome Res 8:335–345

    Article  Google Scholar 

  71. Schwartz SA, Reyzer ML, Capriol RM (2003) Direct tissue analysis using matrix-assisted laser desorption/ionization mass spectrometry: practical aspects of sample preparation. J Mass Spectrom 38:699–708

    Article  PubMed  CAS  Google Scholar 

  72. Zaima N, Sasaki T, Tanaka H, Cheng XW, Onoue K, Hayasaka T, Goto-Inoue N, Enomoto H, Unno N, Kuzuya M, Setou M (2011) Imaging mass spectrometry-based histopathologic examination of atherosclerotic lesions. Atherosclerosis 217:427–432

    Article  PubMed  CAS  Google Scholar 

  73. Grey AC, Gelasco AK, Section J, Moreno-Rodriguez RA, Krug EL, Schey KL (2010) Molecular morphology of the chick heart visualized by MALDI imaging mass spectrometry. Anat Rec (Hoboken) 293:821–828

    Article  CAS  Google Scholar 

  74. Menger RF, Stutts WL, Anbukumar DS, Bowden JA, Ford DA, Yost RA (2012) MALDI mass spectrometric imaging of cardiac tissue following myocardial infarction in a rat coronary artery ligation model. Anal Chem 84:1117–1125

    Article  PubMed  CAS  Google Scholar 

  75. Chughtai K, Heeren RM (2010) Mass spectrometric imaging for biomedical tissue ­analysis. Chem Rev 110:3237–3277

    Article  PubMed  CAS  Google Scholar 

  76. Seeley EH, Caprioli RM (2011) MALDI imaging mass spectrometry of human tissue: method challenges and clinical perspectives. Trends Biotechnol 29:136–143

    Article  PubMed  CAS  Google Scholar 

  77. Wheelock CE, Wheelock AM, Kawashima S, Diez D, Kanehisa M, van Erk M, Kleemann R, Haeggström JZ, Goto S (2009) Systems biology approaches and pathway tools for investigating cardiovascular disease. Mol BioSyst 5:588–602

    Article  PubMed  CAS  Google Scholar 

  78. Ramsey SA, Gold ES, Aderem A (2010) A ­systems biology approach to understanding atherosclerosis. EMBO Mol Med 2:79–89

    Article  PubMed  CAS  Google Scholar 

  79. Jain KK (2010) Technologies for discovery of biomarkers. In: The handbook of biomarkers. Springer, New York. Jain Pharma-Biotech, Basel, Switzerland

    Google Scholar 

  80. Lusis AJ, Weiss JN (2010) Cardiovascular networks: systems-based approaches to cardiovascular disease. Circulation 121:157–170

    Article  PubMed  Google Scholar 

  81. de la Cuesta F, Barderas MG, Calvo E, Zubiri I, Maroto AS, Darde VM, Martin-Rojas T, Gil-Dones F, Posada-Ayala M, Tejerina T, Lopez JA, Vivanco F, Alvarez-Llamas G (2012) Secretome analysis of atherosclerotic and non-atherosclerotic arteries reveals dynamic extracellular remodeling during pathogenesis. J Proteomics 75:2960–2971

    Article  PubMed  Google Scholar 

  82. Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P, Doerks T, Stark M, Muller J, Bork P, Jense LJ, von Mering C (2011) The STRING database in 2011: functional interaction networks of proteins globally integrated and scored. Nucleic Acids Res 39:D561–8

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

Work in the authors’ laboratories has been supported by grants FIS PI11/01401.

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Authors and Affiliations

  1. Department of Vascular Physiopathology, SESCAM, Hospital Nacional de Parapléjicos, Toledo, Spain

    Maria G. Barderas

  2. Department of Immunology, IIS-Fundacion Jimenez Diaz, Madrid, Spain

    Fernando Vivanco & Gloria Alvarez-Llamas

  3. Department of Biochemistry and Molecular Biology I, Universidad Complutense, Madrid, Spain

    Fernando Vivanco

Authors
  1. Maria G. Barderas
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  2. Fernando Vivanco
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  3. Gloria Alvarez-Llamas
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Editors and Affiliations

  1. Depto. Immunología, Fundación Jiménez Díaz, Avda. Reyes Catolicos 2, Madrid, 28040, Spain

    Fernando Vivanco

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Barderas, M.G., Vivanco, F., Alvarez-Llamas, G. (2013). Vascular Proteomics. In: Vivanco, F. (eds) Vascular Proteomics. Methods in Molecular Biology, vol 1000. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-405-0_1

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  • DOI: https://doi.org/10.1007/978-1-62703-405-0_1

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