On the development of plasma protein biomarkers

Journal of Proteome Research

Volumn 10, Issue 1, 2011, Pages 5-16

  Surinova, Silvia ^a,b   Schiess, Ralph ^a,c   Hüttenhain, Ruth ^a,b   Cerciello, Ferdinando ^a,d   Wollscheid, Bernd ^a,e   Aebersold, Ruedi ^a,f  

^a ETH ZURICH   (Switzerland)

^b Competence Center for Systems Physiology and Metabolic Diseases ^*  (Switzerland)

^c Switzerland   (Switzerland)

^d UNIVERSITY HOSPITAL ZURICH   (Switzerland)

^e NCCR Neuro Center for Proteomics   (Switzerland)

^f UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

Biomarker; Discovery; Mass spectrometry; MRM; Plasma; Protein; Reporting; SRM; Validation study design

Indexed keywords

BIOLOGICAL MARKER; PLASMA PROTEIN;

ANALYTIC METHOD; MASS SPECTROMETRY; PRACTICE GUIDELINE; PRIORITY JOURNAL; PROTEOMICS; REVIEW; STUDY DESIGN; VALIDATION PROCESS;

ANIMALS; BIOLOGICAL MARKERS; BLOOD PROTEINS; DIAGNOSTIC TECHNIQUES AND PROCEDURES; HUMANS; MASS SPECTROMETRY; PROTEOMICS;

EID: 79951530395     PISSN: 15353893     EISSN: 15353907     Source Type: Journal    
DOI: 10.1021/pr1008515     Document Type: Review

References (109)

1. Aebersold, R.; Mann, M. Mass spectrometry-based proteomics. Nature 2003, 422 (6928), 198.
2. Patterson, S. D.; Aebersold, R. H. Proteomics: the first decade and beyond. Nat. Genet. 2003, 33 (Suppl), 311.
3. Cravatt, B. F.; Simon, G. M.; Yates, J. R., 3rd. The biological impact of mass-spectrometry-based proteomics. Nature 2007, 450 (7172), 991.
4. Shiess, R.; Wollscheid, B.; Aebersold, R. Targeted proteomic strategy for clinical biomarker discovery. Mol. Oncol. 2009, 3 (1), 33.
5. Faca, V.; Krasnoselsky, A.; Hanash, S. Innovative proteomic approaches for cancer biomarker discovery. Biotechniques 2007, 43 (3), 279.
6. polanski, M.; Anderson, N. L. A list of candidate cancer biomarkers for targeted proteomics. Biomark. Insights 2007, 1, 1.
7. FDA, FDA clears a test for ovarian cancer: Test can help identify potential malignancies, guide surgical decisions. http://www. fda.gov/NewsEvents/Newsroom/PressAnnouncements/ ucm18057.htm (Accessed November 2009. FDA news release).
8. Hanash, S. Building a foundation for the human proteome: the role of the Human Proteome Organization. J. Proteome Res. 2004, 3 (2), 197.
9. Omenn, G. S.; et al. Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. Proteomics 2005, 5 (13), 3226.
10. Muthusamy, B.; et al. Plasma Proteome Database as a resource for proteomics research. Proteomics 2005, 5 (13), 3531.
11. Domon, B.; Aebersold, R. Mass spectrometry and protein analysis. Science 2006, 312 (5771), 212.
12. de Godoy, L. M.; et al. Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast. Nature 2008, 455 (7217), 1251.
13. Aye, T. T.; et al. Proteome-wide protein concentrations in the human heart. Mol. Biosyst. 2010, 6 (10), 1917.
14. McCormack, A. L.; et al. Direct analysis and identification of proteins in mixtures by LC/MS/MS and database searching at the low-femtomole level. Anal. Chem. 1997, 69 (4), 767.
15. Elias, J. E.; Haas, W.; Faherty, B. K.; Gygi, S. P. Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations. Nat. Methods 2005, 2 (9), 667.
16. Wolf-Yadlin, A.; Hautaniemi, S.; Lauffenburger, D. A.; White, F. M. Multiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks. Proc. Natl. Acad. Sci. U.S.A. 2007, 104 (14), 5860.
17. Picotti, P.; et al. Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics. Cell 2009, 138 (4), 795.
18. Anderson, N. L.; Anderson, N. G. The human plasma proteome: history, character, and diagnostic prospects. Mol. Cell. Proteomics 2002, 1 (11), 845.
19. Zhang, H.; et al. Mass spectrometric detection of tissue proteins in plasma. Mol. Cell. Proteomics 2007, 6 (1), 64.
20. Haab, B. B.; et al. Immunoassay and antibody microarray analysis of the HUPO Plasma Proteome Project reference specimens: systematic variation between sample types and calibration of mass spectrometry data. Proteomics 2005, 5 (13), 3278.
21. Lange, V.; Picotti, P.; Domon, B.; Aebersold, R. Selected reaction monitoring for quantitative proteomics: a tutorial. Mol. Syst. Biol. 2008, 4, 222.
22. Anderson, L.; Hunter, C. L. Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins. Mol. Cell. Proteomics 2006, 5 (4), 573.
23. Kuzyk, M. A.; et al. Multiple reaction monitoring-based, multiplexed, absolute quantitation of 45 proteins in human plasma. Mol. Cell. Proteomics 2009, 8 (8), 1860.
24. Brand, J.; et al. Depletion efficiency and recovery of trace markers from a multiparameter immunodepletion column. Proteomics 2006, 6 (11), 3236.
25. Keshishian, H.; et al. Quantitative, multiplexed assays for low abundance proteins in plasma by targeted mass spectrometry and stable isotope dilution. Mol. Cell. Proteomics 2007, 6 (12), 2212.
26. Porath, J.; Carlsson, J.; Olsson, I.; Belfrage, G. Metal chelate affinity chromatography, a new approach to protein fractionation. Nature 1975, 258 (5536), 598.
27. Stensballe, A.; Andersen, S.; Jensen, O. N. Characterization of phosphoproteins from electrophoretic gels by nanoscale Fe(III) affinity chromatography with off-line mass spectrometry analysis. Proteomics 2001, 1 (2), 207.
28. Pinkse, M. W.; et al. Selective isolation at the femtomole level of phosphopeptides from proteolytic digests using 2D-NanoLC-ESIMS/ MS and titanium oxide precolumns. Anal. Chem. 2004, 76 (14), 3935.
29. Zhang, H.; Li, X. J.; Martin, D. B.; Aebersold, R. Identification and quantification of N-linked glycoproteins using hydrazide chemistry, stable isotope labeling and mass spectrometry. Nat. Biotechnol. 2003, 21 (6), 660.
30. Glinski, M.; Weckwerth, W. Differential multisite phosphorylation of the trehalose-6-phosphate synthase gene family in Arabidopsis thaliana: a mass spectrometry-based process for multiparallel peptide library phosphorylation analysis. Mol. Cell. Proteomics 2005, 4 (10), 1614.
31. Mayya, V.; et al. Absolute quantification of multisite phosphorylation by selective reaction monitoring mass spectrometry: determination of inhibitory phosphorylation status of cyclindependent kinases. Mol. Cell. Proteomics 2006, 5 (6), 1146.
32. Ciccimaro, E.; Hanks, S. K.; Yu, K. H.; Blair, I. A. Absolute quantification of phosphorylation on the kinase activation loop of cellular focal adhesion kinase by stable isotope dilution liquid chromatography/mass spectrometry. Anal. Chem. 2009, 81 (9), 3304.
33. Stahl-Zeng, J.; et al. High sensitivity detection of plasma proteins by multiple reaction monitoring of N-glycosites. Mol. Cell. Proteomics 2007, 6 (10), 1809.
34. Nicol, G. R.; et al. Use of an immunoaffinity-mass spectrometrybased approach for the quantification of protein biomarkers from serum samples of lung cancer patients. Mol. Cell. Proteomics 2008, 7 (10), 1974.
35. Kuhn, E.; et al. Developing multiplexed assays for troponin I and interleukin-33 in plasma by peptide immunoaffinity enrichment and targeted mass spectrometry. Clin. Chem. 2009, 55 (6), 1108.
36. Paulovich, A. G.; Whiteaker, J. R.; Hoofnagle, A. N.; Wang, P. The interface between biomarker discovery and clinical validation: The tar pit of the protein biomarker pipeline. Proteomics Clin. Appl. 2008, 2 (10-11), 1386.
37. Addona, T. A.; et al. Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma. Nat. Biotechnol. 2009, 27 (7), 633.
38. Rifai, N.; Gillette, M. A.; Carr, S. A. Protein biomarker discovery and validation: the long and uncertain path to clinical utility. Nat. Biotechnol. 2006, 24 (8), 971.
39. Huttenhain, R.; Malmstrom, J.; Picotti, P.; Aebersold, R. Perspectives of targeted mass spectrometry for protein biomarker verification. Curr. Opin. Chem. Biol. 2009, 13 (5-6), 518.
40. Xue, H.; et al. Identification of serum biomarkers for colorectal cancer metastasis using a differential secretome approach. J. Proteome Res. 2010, 9 (1), 545.
41. Solassol, J.; et al. Serum protein signature may improve detection of ductal carcinoma in situ of the breast. Oncogene 2010, 29 (4), 550.
42. Faca, V. M.; et al. A mouse to human search for plasma proteome changes associated with pancreatic tumor development. PLoS Med. 2008, 5 (6), e123.
43. Pitteri, S. J.; et al. Integrated proteomic analysis of human cancer cells and plasma from tumor bearing mice for ovarian cancer biomarker discovery. PLoS One 2009, 4 (11), e7916.
44. Planque, C.; et al. Identification of five candidate lung cancer biomarkers by proteomics analysis of conditioned media of four lung cancer cell lines. Mol. Cell. Proteomics 2009, 8 (12), 2746.
45. Picotti, P.; et al. High-throughput generation of selected reactionmonitoring assays for proteins and proteomes. Nat. Methods 2010, 7 (1), 43.
46. Desiere, F.; et al. Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometry. Genome Biol. 2005, 6 (1), R9.
47. Desiere, F.; et al. The PeptideAtlas project. Nucleic Acids Res. 2006, 34 (Database issue), D655.
48. Deutsch, E. W.; et al. Human Plasma PeptideAtlas. Proteomics 2005, 5 (13), 3497.
49. Zhang, H.; et al. UniPep-a database for human N-linked glycosites: a resource for biomarker discovery. Genome Biol. 2006, 7 (8), R73.
50. MacLean, B.; et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 2010, 26 (7), 966.
51. Abbatiello, S. E.; Mani, D. R.; Keshishian, H.; Carr, S. A. Automated detection of inaccurate and imprecise transitions in peptide quantification by multiple reaction monitoring mass spectrometry. Clin. Chem. 2010, 56 (2), 291.
52. Keller, A.; Nesvizhskii, A. I.; Kolker, E.; Aebersold, R. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem. 2002, 74 (20), 5383.
53. Nesvizhskii, A. I.; Keller, A.; Kolker, E.; Aebersold, R. A statistical model for identifying proteins by tandem mass spectrometry. Anal. Chem. 2003, 75 (17), 4646.
54. Ludwig, J. A.; Weinstein, J. N. Biomarkers in cancer staging, prognosis and treatment selection. Nat. Rev. Cancer 2005, 5 (11), 845.
55. Hartwell, L.; et al. Cancer biomarkers: a systems approach. Nat. Biotechnol. 2006, 24 (8), 905.
56. Sandusky, G.; Dumaual, C.; Cheng, L. Review paper: Human tissues for discovery biomarker pharmaceutical research: the experience of the Indiana University Simon Cancer Center-Lilly Research Labs Tissue/Fluid BioBank. Vet. Pathol. 2009, 46 (1), 2.
57. Hood, B. L.; et al. Proteomic analysis of formalin-fixed prostate cancer tissue. Mol. Cell. Proteomics 2005, 4 (11), 1741.
58. Ostasiewicz, P.; Zielinska, D. F.; Mann, M.; Wisniewski, J. R. Proteome, phosphoproteome, and N-glycoproteome are quantitatively preserved in formalin-fixed paraffin-embedded tissue and analyzable by high-resolution mass spectrometry. J Proteome Res 2010, 9 (7), 3688.
59. Madoz-Gurpide, J.; et al. A proteomics analysis of cell signaling alterations in colorectal cancer. Mol. Cell. Proteomics 2007, 6 (12), 2150.
60. Banks, R.E. ; et al. The potential use of laser capture microdissection to selectively obtain distinct populations of cells for proteomic analysis-preliminary findings. Electrophoresis 1999, 20 (4-5), 689.
61. Gutstein, H.B. ; Morris, J.S. Laser capture sampling and analytical issues in proteomics. Expert Rev. Proteomics 2007, 4 (5), 627.
62. Schmidt, A.; Aebersold, R. High-accuracy proteome maps of human body fluids. Genome Biol. 2006, 7 (11), 242.
63. Hu, S.; Loo, J.A. ; Wong, D.T. Human body fluid proteome analysis. Proteomics 2006, 6 (23), 6326.
64. Teng, P.N. ; Bateman, N.W. ; Hood, B.L. ; Conrads, T.P. Advances in proximal fluid proteomics for disease biomarker discovery. J. Proteome Res. 2010; DOI: 10.1021/pr100904q.
65. Celis, J. E.; et al. Proteomic characterization of the interstitial fluid perfusing the breast tumor microenvironment: a novel resource for biomarker and therapeutic target discovery. Mol. Cell. Proteomics 2004, 3 (4), 327.
66. Kuk, C.; et al. Mining the ovarian cancer ascites proteome for potential ovarian cancer biomarkers. Mol. Cell. Proteomics 2009, 8 (4), 661.
67. Stoop, M. P.; et al. Quantitative proteomics and metabolomics analysis of normal human cerebrospinal fluid samples. Mol. Cell. Proteomics 2010, 9 (9), 2063.
68. Jamaspishvili, T.; et al. Urine markers in monitoring for prostate cancer. Prostate Cancer Prostatic Dis. 2010, 13 (1), 12.
69. Pawlik, T. M.; et al. Proteomic analysis of nipple aspirate fluid from women with early-stage breast cancer using isotope-coded affinity tags and tandem mass spectrometry reveals differential expression of vitamin D binding protein. BMC Cancer 2006, 6, 68.
70. Chen, R.; et al. Elevated level of anterior gradient-2 in pancreatic juice from patients with pre-malignant pancreatic neoplasia. Mol. Cancer 2010, 9, 149.
71. Fogar, P.; et al. Portal but not peripheral serum levels of interleukin 6 could interfere with glucose metabolism in patients with pancreatic cancer. Clin. Chim. Acta 1998, 277 (2), 181.
72. Frederiksen, C.; et al. Tissue inhibitor of metalloproteinase-1 levels in plasma from tumour arteries and veins of patients with rectal cancer. Scand. J. Clin. Lab. Invest. 2007, 67 (5), 545.
73. Rosty, C.; et al. Identification of hepatocarcinoma-intestinepancreas/ pancreatitis-associated protein I as a biomarker for pancreatic ductal adenocarcinoma by protein biochip technology. Cancer Res. 2002, 62 (6), 1868.
74. Sedlaczek, P.; et al. Comparative analysis of CA125, tissue polypeptide specific antigen, and soluble interleukin-2 receptor alpha levels in sera, cyst, and ascitic fluids from patients with ovarian carcinoma. Cancer 2002, 95 (9), 1886.
75. Maser, R. S.; et al. Chromosomally unstable mouse tumours have genomic alterations similar to diverse human cancers. Nature 2007, 447 (7147), 966.
76. Van Dyke, T.; Jacks, T. Cancer modeling in the modern era: progress and challenges. Cell 2002, 108 (2), 135.
77. Taketo, M. M.; Edelmann, W. Mouse models of colon cancer. Gastroenterology 2009, 136 (3), 780.
78. Kelly-Spratt, K. S.; Kasarda, A. E.; Igra, M.; Kemp, C. J. A mouse model repository for cancer biomarker discovery. J. Proteome Res. 2008, 7 (8), 3613.
79. Krupke, D. M.; et al. The Mouse Tumor Biology database. Nat. Rev. Cancer 2008, 8 (6), 459.
80. Balmain, A.; Harris, C. C. Carcinogenesis in mouse and human cells: parallels and paradoxes. Carcinogenesis 2000, 21 (3), 371.
81. Kulasingam, V.; Diamandis, E. P. Tissue culture-based breast cancer biomarker discovery platform. Int. J. Cancer 2008, 123 (9), 2007.
82. Volmer, M. W.; et al. Differential proteome analysis of conditioned media to detect Smad4 regulated secreted biomarkers in colon cancer. Proteomics 2005, 5 (10), 2587.
83. Sardana, G.; Marshall, J.; Diamandis, E. P. Discovery of candidate tumor markers for prostate cancer via proteomic analysis of cell culture-conditioned medium. Clin. Chem. 2007, 53 (3), 429.
84. Kulasingam, V.; Diamandis, E. P. Proteomics analysis of conditioned media from three breast cancer cell lines: a mine for biomarkers and therapeutic targets. Mol. Cell. Proteomics 2007, 6 (11), 1997.
85. Pepe, M. S.; et al. Phases of biomarker development for early detection of cancer. J. Natl. Cancer Inst. 2001, 93 (14), 1054.
86. Semmes, O. J.; et al. Discrete serum protein signatures discriminate between human retrovirus-associated hematologic and neurologic disease. Leukemia 2005, 19 (7), 1229.
87. Alonzo, T. A.; Pepe, M. S.; Moskowitz, C. S. Sample size calculations for comparative studies of medical tests for detecting presence of disease. Stat. Med. 2002, 21 (6), 835.
88. Rai, A. J.; et al. HUPO Plasma Proteome Project specimen collection and handling: towards the standardization of parameters for plasma proteome samples. Proteomics 2005, 5 (13), 3262.
89. Schrohl, A. S.; et al. Banking of biological fluids for studies of disease-associated protein biomarkers. Mol. Cell. Proteomics 2008, 7 (10), 2061.
90. Thorpe, J. D.; et al. Effects of blood collection conditions on ovarian cancer serum markers. PLoS One 2007, 2 (12), e1281.
91. McLerran, D.; et al. Analytical validation of serum proteomic profiling for diagnosis of prostate cancer: sources of sample bias. Clin Chem 2008, 54 (1), 44.
92. Tuck, M. K.; et al. Standard operating procedures for serum and plasma collection: early detection research network consensus statement standard operating procedure integration working group. J. Proteome Res. 2009, 8 (1), 113.
93. Su, A. I.; et al. Large-scale analysis of the human and mouse transcriptomes. Proc. Natl. Acad. Sci. U.S.A. 2002, 99 (7), 4465.
94. Vogelstein, B.; Kinzler, K. W. Cancer genes and the pathways they control. Nat. Med. 2004, 10 (8), 789.
95. Harris, T. J.; McCormick, F. The molecular pathology of cancer. Nat. Rev. Clin. Oncol. 2010, 7 (5), 251.
96. Hudson, T. J.; et al. International network of cancer genome projects. Nature 2010, 464 (7291), 993.
97. Lawlor, K.; et al. Pathway-based biomarker search by highthroughput proteomics profiling of secretomes. J. Proteome Res. 2009, 8 (3), 1489.
98. Cerami, E.; et al. Automated network analysis identifies core pathways in glioblastoma. PLoS One 2010, 5 (2), e8918.
99. Karapetis, C. S.; et al. K-ras mutations and benefit from cetuximab in advanced colorectal cancer. N. Engl. J. Med. 2008, 359 (17), 1757.
100. Lutz, A. M.; et al. Cancer screening: a mathematical model relating secreted blood biomarker levels to tumor sizes. PLoS Med. 2008, 5 (8), e170.
101. Gutman, S.; Kessler, L. G. The US Food and Drug Administration perspective on cancer biomarker development. Nat. Rev. Cancer 2006, 6 (7), 565.
102. FDA, (Food and Drug Administration). U.S. Department of Health and Human Services., Draft Guidance for Industry, Clinical Laboratories, and FDA Staff. In Vitro Diagnostic Multivariate Index Assays, 2007.
103. Manolio, T. A.; Bailey-Wilson, J. E.; Collins, F. S. Genes, environment and the value of prospective cohort studies. Nat. Rev. Genet. 2006, 7 (10), 812.
104. Woods, W. G.; et al. A population-based study of the usefulness of screening for neuroblastoma. Lancet 1996, 348 (9043), 1682.
105. Sackett, D. L.; Haynes, R. B. The architecture of diagnostic research. BMJ 2002, 324 (7336), 539.
106. McShane, L. M.; et al. Reporting recommendations for tumor marker prognostic studies (remark). Exp Oncol. 2006, 28 (2), 99.
107. Bossuyt, P. M.; et al. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Standards for Reporting of Diagnostic Accuracy. Clin. Chem. 2003, 49 (1), 1.
108. Mallett, S.; Timmer, A.; Sauerbrei, W.; Altman, D. G. Reporting of prognostic studies of tumour markers: a review of published articles in relation to REMARK guidelines. Br. J. Cancer 2010, 102 (1), 173.
109. States, D. J.; et al. Challenges in deriving high-confidence protein identifications from data gathered by a HUPO plasma proteome collaborative study. Nat. Biotechnol. 2006, 24 (3), 333.