Discovery and confirmation of a protein biomarker panel with potential to predict response to biological therapy in psoriatic arthritis

Annals of the Rheumatic Diseases

Volumn 75, Issue 1, 2016, Pages 234-241

  Ademowo, Opeyemi S ^a   Hernandez, Belinda ^a   Collins, Emily ^a,b   Rooney, Cathy ^a   Fearon, Ursula ^a,b   Van Kuijk, Arno W ^c   Tak, Paul P ^c   Gerlag, Danielle M ^c   FitzGerald, Oliver ^a,b   Pennington, Stephen R ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

^b ST VINCENT S UNIVERSITY HOSPITAL   (Ireland)

^c UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ADALIMUMAB; BIOLOGICAL MARKER; CALGRANULIN A; COLLAGEN ALPHA2; FIBRINOGEN ALPHA; FIBRINOGEN GAMMA; HAPTOGLOBIN; IMMUNOGLOBULIN KAPPA CHAIN C; LIPOCORTIN 1; LIPOCORTIN 2; OROSOMUCOID; PLACEBO; S100 A10 PROTEIN; UNCLASSIFIED DRUG; VITRONECTIN; ANTIRHEUMATIC AGENT; PROTEIN;

ARTICLE; CLINICAL ARTICLE; CLINICAL TRIAL; DAS28; DRUG RESPONSE; HUMAN; HUMAN TISSUE; PRIORITY JOURNAL; PROTEOMICS; PSORIATIC ARTHRITIS; REVERSED PHASE LIQUID CHROMATOGRAPHY; SYNOVIUM; TANDEM MASS SPECTROMETRY; ARTHRITIS, PSORIATIC; CONTROLLED STUDY; DOUBLE BLIND PROCEDURE; FEMALE; MALE; METABOLISM; PROCEDURES; PROGNOSIS; RANDOMIZED CONTROLLED TRIAL; TREATMENT OUTCOME;

ADALIMUMAB; ANTIRHEUMATIC AGENTS; ARTHRITIS, PSORIATIC; BIOMARKERS; DOUBLE-BLIND METHOD; FEMALE; HUMANS; MALE; PROGNOSIS; PROTEINS; PROTEOMICS; SYNOVIAL MEMBRANE; TREATMENT OUTCOME;

EID: 84954326224     PISSN: 00034967     EISSN: 14682060     Source Type: Journal    
DOI: 10.1136/annrheumdis-2014-205417     Document Type: Article

References (53)

1. Gladman DD. Early psoriatic arthritis. Rheum Dis Clin North Am 2012;38:373-86.
2. McInnes IB, Schett G. Cytokines in the pathogenesis of rheumatoid arthritis. Nat Rev Immunol 2007;7:429-42.
3. Gladman DD, Antoni C, Mease P, et al. Psoriatic arthritis: epidemiology, clinical features, course, and outcome. Ann Rheum Dis 2005;64(Suppl 2):14-7.
4. FitzGerald O. Diagnosis: screening for arthritis in patients with psoriasis. Nat Rev Rheumatol 2012;8:640-1.
5. Gladman DD. Psoriatic arthritis. Dermatol Ther 2009;22:40-55.
6. Matthews C, Rogers S, FitzGerald O. Development of new onset psoriasis while on anti TNF treatment. Ann Rheum Dis 2006;65:1529.
7. Winchester R, Minevich G, Steshenko V, et al. HLA associations reveal genetic heterogeneity in psoriatic arthritis and in the psoriasis phenotype. Arthritis Rheum 2012;64:1134-44.
8. Dougados M, Hochberg M. Why is the concept of spondyloarthropathies important? Best Pract Res Clin Rheumatol 2002;16:495-505.
9. Myers WA, Gottlieb AB, Mease P. Psoriasis and psoriatic arthritis: clinical features and disease mechanisms. Clin Dermatol 2006;24:438-47.
10. Melis L, Vandooren B, Kruithof E, et al. Systemic levels of IL-23 are strongly associated with disease activity in rheumatoid arthritis but not spondyloarthritis. Ann Rheum Dis 2010;69:618-23.
11. Iwamoto T, Okamoto H, Toyama Y, et al. Molecular aspects of rheumatoid arthritis: chemokines in the joints of patients. FEBS J 2008;275:4448-55.
12. McGonagle D, Gibbon W, Emery P. Classification of inflammatory arthritis by enthesitis. Lancet 1998;352:1137-40.
13. Veale DJ, Ritchlin C, FitzGerald O. Immunopathology of psoriasis and psoriatic arthritis. Ann Rheum Dis 2005;64(Suppl 2):ii26-ii29.
14. Feldmann M, Maini SRN. Role of cytokines in rheumatoid arthritis: an education in pathophysiology and therapeutics. Immunol Rev 2008;223:7-19.
15. FitzGerald O, Winchester R. Psoriatic arthritis: from pathogenesis to therapy. Arthritis Res Ther 2009;11:214.
16. America AHP, Cordewener JHG. Comparative LC MS: a landscape of peaks and valleys. Proteomics 2008;8:731-49.
17. Lundgren DH, Hwang S-I, Wu L, et al. Role of spectral counting in quantitative proteomics. Expert Rev Proteomics 2010;7:39-53.
18. Schmidt A, Claassen M, Aebersold R, et al. Directed mass spectrometry: towards hypothesis-driven proteomics. Curr Opin Chem Biol 2009;13:510-7.
19. Domon B, Aebersold R. Options and considerations when selecting a quantitative proteomics strategy. Nat Biotechnol 2010;28:710-21.
20. Collins BC, Miller CA, Sposny A, et al. Development of a pharmaceutical hepatotoxicity biomarker panel using a discovery to targeted proteomics approach. Mol Cell Proteomics 2012;11:394-410.
21. Lange V, Picotti P, Domon B, et al. Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol 2008;4:222.
22. Kitteringham NR, Jenkins RE, Lane CS, et al. Multiple reaction monitoring for quantitative biomarker analysis in proteomics and metabolomics. J Chromatogr B 2009;877:1229-39.
23. Jovanovic M, Reiter L, Picotti P, et al. A quantitative targeted proteomics approach to validate predicted microRNA targets in C. Elegans. Nat Methods 2010;7:837-42.
24. Lange V, Malmström JA, Didion J, et al. Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring. Mol Cell Proteomics 2008;7:1489-500.
25. Picotti P, Bodenmiller B, Mueller LN, et al. Full Dynamic Range Proteome Analysis of S. Cerevisiae by Targeted Proteomics. Cell 2009;138:795-806.
26. Addona TA, Abbatiello SE, Schilling B, et al. Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma. Nat Biotechnol 2009;27:633-41.
27. Schiess R, Wollscheid B, Aebersold R. Targeted proteomic strategy for clinical biomarker discovery. Mol Oncol 2009;3:33-44.
28. Whiteaker JR, Zhang H, Zhao L, et al. Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer. J Proteome Res 2007;6:3962-75.
29. Pan S, Aebersold R, Chen R, et al. Mass spectrometry based targeted protein quantification: methods and applications. J Proteome Res 2008;8:787-97.
30. Cham Mead JA, Bianco L, Bessant C. Free computational resources for designing selected reaction monitoring transitions. Proteomics 2010;10:1106-26.
31. Deutsch EW, Lam H, Aebersold R. PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows. EMBO Rep 2008;9:429-34.
32. MacLean B, Tomazela DM, Shulman N, et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 2010;26:966-8.
33. Picotti P, Rinner O, Stallmach R, et al. High-throughput generation of selected reaction-monitoring assays for proteins and proteomes. Nat Methods 2010;7:43-6.
34. Patel T, Gordon KB. Adalimumab: efficacy and safety in psoriasis and rheumatoid arthritis. Dermatol Ther 2004;17:427-31.
35. Taylor W, Gladman D, Helliwell P, et al. Classification criteria for psoriatic arthritis: development of new criteria from a large international study. Arthritis Rheum 2006;54:2665-73.
36. Van Kuijk AW, Gerlag DM, Vos K, et al. A prospective, randomised, placebo-controlled study to identify biomarkers associated with active treatment in psoriatic arthritis: effects of adalimumab treatment on synovial tissue. Ann Rheum Dis 2009;68:1303-9.
37. Fransen J, van Riel PL. The Disease Activity Score and the EULAR response criteria. Clin Exp Rheumatol 2005;23:S93-9.
38. Bradford MM. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 1976;72:248-54.
39. Vizcaíno JA, Côté RG, Csordas A, et al. The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013. Nucleic Acids Res 2013;41: D1063-9.
40. Hernández B, Parnell A, Pennington SR. Why have so few proteomic biomarkers "survived" validation? (Sample size and independent validation considerations). Proteomics 2014;14:1587-92.
41. Liao H, Wu J, Kuhn E, et al. Use of mass spectrometry to identify protein biomarkers of disease severity in the synovial fluid and serum of patients with rheumatoid arthritis. Arthritis Rheum 2004;50:3792-803.
42. Hueber W, Kidd B, Tomooka B, et al. Antigen microarray profiling of autoantibodies in rheumatoid arthritis. Arthritis Rheum 2005;52:2645-55.
43. Sinz A, Bantscheff M, Mikkat S, et al. Mass spectrometric proteome analyses of synovial fluids and plasmas from patients suffering from rheumatoid arthritis and comparison to reactive arthritis or osteoarthritis. Electrophoresis 2002;23:3445-56.
44. Cesaro A, Anceriz N, Plante A, et al. An inflammation loop orchestrated by S100A9 and calprotectin is critical for development of arthritis. PLoS ONE 2012;7:e45478.
45. Kwon M, MacLeod TJ, Waisman YZ, et al. S100A10, annexin A2, and annexin a2 heterotetramer as candidate plasminogen receptors. Front Biosci 2005;10:300-25.
46. O'Connell PA, Surette AP, Liwski RS, et al. S100A10 regulates plasminogen-dependent macrophage invasion. Blood 2010;116:1136-46.
47. Chan JK, Roth J, Oppenheim JJ, et al. Alarmins: awaiting a clinical response. J Clin Invest 2012;122:2711-9.
48. Veering B, Burm A, Souverijn J, et al. The effect of age on serum concentrations of albumin and α1-acid glycoprotein. Br J Clin Pharmacol 1990;29:201-6.
49. Chambers AG, Percy AJ, Yang J, et al. Multiplexed quantitation of endogenous proteins in dried blood spots by multiple reaction monitoring-mass spectrometry. Mol Cell Proteomics 2013;12:781-91.
50. Lambrecht S, Deforce D, Elewaut D. Entering the era of proteomics in rheumatology. Expert Opin Drug Discov 2006;1:539-48.
51. Gibson DS, Banha J, Penque D, et al. Diagnostic and prognostic biomarker discovery strategies for autoimmune disorders. J Proteomics 2010;73:1045-60.
52. Ademowo OS, Staunton L, Fitzgerald O, et al. Biomarkers of inflammatory arthritis and proteomics. In: SA S, ed. Genes and autoimmunity-intracellular signalling and microbiome contribution. INTECH, 2013:237-67.
53. Tilleman K, Van Beneden K, Dhondt A, et al. Chronically inflamed synovium from spondyloarthropathy and rheumatoid arthritis investigated by protein expression profiling followed by tandem mass spectrometry. Proteomics 2005;5:2247-57.