Gene expression analysis in RA: Towards personalized medicine

Pharmacogenomics Journal

Volumn 14, Issue 2, 2014, Pages 93-106

  Burska, A N ^a   Roget, K ^b,i   Blits, M ^c   Soto Gomez, L ^d   Van De Loo, F ^e   Hazelwood, L D ^d   Verweij, C L ^c   Rowe, A ^f   Goulielmos, G N ^g   Van Baarsen, L G M ^h   Ponchel, F ^a  

^a UNIVERSITY OF LEEDS   (United Kingdom)

^b TcLand Expression ^*  (France)

^c VU UNIVERSITY MEDICAL CENTER   (Netherlands)

^d UNIVERSITY OF LEEDS   (United Kingdom)

^e RADBOUD UNIVERSITY MEDICAL CENTER   (Netherlands)

^f JANSSEN RESEARCH AND DEVELOPMENT   (Belgium)

^g UNIVERSITY OF CRETE   (Greece)

^h UNIVERSITY OF AMSTERDAM   (Netherlands)

ⁱ BioSIMS Technologies   (France)

Author keywords

Arthritis; Gene expression; Pharmacological biomarker; Rheumatoid

Indexed keywords

INFLIXIMAB; METHOTREXATE; MICRORNA; RECOMBINANT INTERLEUKIN 1 RECEPTOR BLOCKING AGENT; RITUXIMAB; TOCILIZUMAB; TUMOR NECROSIS FACTOR ANTIBODY;

ARTICLE; AUTOIMMUNE DISEASE; DIAGNOSTIC TEST; DISEASE ACTIVITY; DISEASE COURSE; DRUG MECHANISM; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENETIC ASSOCIATION; GENETIC SCREENING; HUMAN; IMMUNOPATHOGENESIS; NONHUMAN; OSTEOARTHRITIS; OUTCOME ASSESSMENT; PATHOPHYSIOLOGY; PERSONALIZED MEDICINE; PREDICTION; PRIORITY JOURNAL; PROGNOSIS; RHEUMATOID ARTHRITIS; RNA ANALYSIS; TREATMENT RESPONSE; ARTHRITIS, RHEUMATOID; GENE EXPRESSION REGULATION; GENETICS; PATHOLOGY;

ARTHRITIS, RHEUMATOID; GENE EXPRESSION REGULATION; HUMANS; INDIVIDUALIZED MEDICINE; PROGNOSIS;

EID: 84897424497     PISSN: 1470269X     EISSN: 14731150     Source Type: Journal    
DOI: 10.1038/tpj.2013.48     Document Type: Article

References (182)

1. Reis-Filho JS, Pusztai L. Gene expression profiling in breast cancer: classification, prognostication, and prediction. Lancet 2011; 378: 1812-1823.
2. Sorlie T, Wang Y, Xiao C, Johnsen H, Naume B, Samaha RR et al. Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms. BMC Genomics 2006; 7: 127.
3. Colombo PE, Milanezi F, Weigelt B, Reis-Filho JS. Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction. Survival 2011; 5: 5.
4. Kreike B, Halfwerk H, Kristel P, Glas A, Peterse H, Bartelink H et al. Gene expression profiles of primary breast carcinomas from patients at high risk for local recurrence after breast-conserving therapy. Clin Cancer Res 2006; 12: 5705-5712.
5. Glas AM, Kersten MJ, Delahaye LJ, Witteveen AT, Kibbelaar RE, Velds A et al. Gene expression profiling in follicular lymphoma to assess clinical aggressiveness and to guide the choice of treatment. Blood 2005; 105: 301-307.
6. Beer DG, Kardia SLR, Huang CC, Giordano TJ, Levin AM, Misek DE et al. Geneexpression profiles predict survival of patients with lung adenocarcinoma. Nat Med 2002; 8: 816-824.
7. Fujiwara T, Hiramatsu M, Isagawa T, Ninomiya H, Inamura K, Ishikawa S et al. ASCL1-coexpression profiling but not single gene expression profiling defines lung adenocarcinomas of neuroendocrine nature with poor prognosis. Lung Cancer 2012; 75: 119-125.
8. Yeoh EJ, Ross ME, Shurtleff SA, Williams WK, Patel D, Mahfouz R et al. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell 2002; 1: 133-144.
9. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000; 403: 503-511.
10. Shipp MA, Ross KN, Tamayo P, Weng AP, Kutok JL, Aguiar RC et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat Med 2002; 8: 68-74.
11. Gutié rrez-Garća G, Cardesa-Salzmann T, Climent F, González-Barca E, Mercadal S, Mate JL et al. Gene-expression profiling and not immunophenotypic algorithms predicts prognosis in patients with diffuse large B-cell lymphoma treated with immunochemotherapy. Blood 2011; 117: 4836-4843.
12. Puyo S, Houede N, Kauffmann A, Richaud P, Robert J, Pourquier PA. Gene expression signature predicting high grade prostate cancer response to Oxaliplatin. Mol Pharmacol 2012; 82: 1205-1216.
13. Volinia S, Galasso M, Sana ME, Wise TF, Palatini J, Huebner K et al. Breast cancer signatures for invasiveness and prognosis defined by deep sequencing of microRNA. Proc Natl Acad Sci 2012; 109: 3024-3029.
14. Azim Jr HA, Michiels S, Bedard PL, Singhal SK, Criscitiello C, Ignatiadis M et al. Elucidating prognosis and biology of breast cancer arising in young women using gene expression profiling. Clin Cancer Res 2012; 18: 1341-1351.
15. Mannelqvist M, Stefansson IM, Bredholt G, Hellem Bo T, Oyan AM, Jonassen I et al. Gene expression patterns related to vascular invasion and aggressive features in endometrial cancer. Am J Pathol 2011; 178: 861-871.
16. Salazar R, Roepman P, Capella G, Moreno V, Simon I, Dreezen C et al. Gene expression signature to improve prognosis prediction of stage II and III colorectal cancer. J Clin Oncol 2011; 29: 17-24.
17. Chang SH, Suh KS, Yi NJ, Lee KH, Kim BY, Jang JJ. Predicting the prognosis of hepatocellular carcinoma using gene expression. J Surg Res 2011; 171: 524-531.
18. Villanueva A, Hoshida Y, Battiston C, Tovar V, Sia D, Alsinet C et al. Combining clinical, pathology, and gene expression data to predict recurrence of hepatocellular carcinoma. Gastroenterology 2011; 140: e1502.
19. Brettingham-Moore KH, Duong CP, Heriot AG, Thomas RJS, Phillips WA. Using gene expression profiling to predict response and prognosis in gastrointestinal cancers-the promise and the perils. Ann Surg Oncol 2011; 18: 1484-1491.
20. Lu X, Wang ZC, Iglehart JD, Zhang X, Richardson AL. Predicting features of breast cancer with gene expression patterns. Breast Cancer Res Treat 2008; 108: 191-201.
21. Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 2006; 98: 262-272.
22. Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res 2008; 10: R65.
23. Muffak-Granero K, Bueno P, Olmedo C, Comino A, Hassan L, Garcia-Alcalde F et al. Study of gene expression profile in liver transplant recipients with hepatitis C virus. Transplant Proc 2008; 40: 2971-2974.
24. Pham MX, Teuteberg JJ, Kfoury AG, Starling RC, Deng MC, Cappola TP et al. Gene-expression profiling for rejection surveillance after cardiac transplantation. N Engl J Med 2010; 362: 1890-1900.
25. Crespo-Leiro M, Stypmann J, Zuckermann A, Bara C, Ross H, Parameshwar J et al. Utility of Gene Expression Profiling Test (GEP) Score instability to predict future clinical outcomes in heart transplant: results from the CARGO 2 European-Based Multicenter Trial. J Heart Lung Transplant 2013; 32: S113-S114.
26. Deng M, Eisen H, Mehra M, Billingham M, Marboe C, Berry G et al. Noninvasive discrimination of rejection in cardiac allograft recipients using gene expression profiling. Am J Transplant 2006; 6: 150-160.
27. Pham MX, Deng MC, Kfoury AG, Teuteberg JJ, Starling RC, Valantine H. Molecular testing for long-term rejection surveillance in heart transplant recipients: design of the Invasive Monitoring Attenuation Through Gene Expression (IMAGE) trial. J Heart Lung Transplant 2007; 26: 808-814.
28. McAllister K, Eyre S, Orozco G. Genetics of rheumatoid arthritis: GWAS and beyond. Open Access Rheumatol Res Rev 2011; 3: 1-16.
29. Suzuki A, Kochi Y, Okada Y, Yamamoto K. Insight from genome-wide association studies in rheumatoid arthritis and multiple sclerosis. FEBS letters 2011; 585: 3627-3632.
30. Zhernakova A, Stahl EA, Trynka G, Raychaudhuri S, Festen EA, Franke L et al. Meta-analysis of genome-wide association studies in celiac disease and rheumatoid arthritis identifies fourteen non-HLA shared loci. PLoS Genet 2011; 7: e1002004.
31. Eyre S, Bowes J, Diogo D, Lee A, Barton A, Martin P et al. High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis. Nat Genet 2012; 44: 1336-1340.
32. Klareskog L, Catrina AI, Paget S. Rheumatoid arthritis. Lancet 2009; 373: 659-672.
33. Viatte S, Plant D, Bowes J, Lunt M, Eyre S, Barton A et al. Genetic markers of rheumatoid arthritis susceptibility in anti-citrullinated peptide antibody negative patients. Ann Rheum Dis 2012; 71: 1984-1990.
34. Kurreeman F, Liao K, Chibnik L, Hickey B, Stahl E, Gainer V et al. Genetic basis of autoantibody positive and negative rheumatoid arthritis risk in a multi-ethnic cohort derived from electronic health records. Am J Hum Genet 2011; 88: 57-69.
35. Berglin E, Johansson T, Sundin U, Jidell E, Wadell G, Hallmans G et al. Radiological outcome in rheumatoid arthritis is predicted by presence of antibodies against cyclic citrullinated peptide before and at disease onset, and by IgA-RF at disease onset. Ann Rheum Dis 2006; 65: 453-458.
36. Del Amo NDV, Bosch RI, Manteca CF, Polo RG, Cortina EL. Anti-cyclic citrullinated peptide antibody in rheumatoid arthritis: relation with disease aggressiveness. Clin Exp Rheumatol 2006; 24: 281-286.
37. van der Helm-vanMil AHM, le Cessie S, van Dongen H, Breedveld FC, Toes REM, Huizinga TWJ. A prediction rule for disease outcome in patients with Recent-onset undifferentiated arthritis: how to guide individual treatment decisions. Arthritis Rheum 2007; 56: 433-440.
38. van Dongen H, van Aken J, Lard LR, Visser K, Ronday HK, Hulsmans HMJ et al. Efficacy of methotrexate treatment in patients with probable rheumatoid arthritis: A double-blind, randomized, placebo-controlled trial. Arthritis Rheum 2007; 56: 1424-1432.
39. van der Pouw Kraan TC, van Gaalen FA, Huizinga TW, Pieterman E, Breedveld FC, Verweij CL. Discovery of distinctive gene expression profiles in rheumatoid synovium using cDNA microarray technology: evidence for the existence of multiple pathways of tissue destruction and repair. Genes Immun 2003; 4: 187-196.
40. van der Pouw Kraan TCTM, van Gaalen FA, Kasperkovitz PV, Verbeet NL, Smeets TJM, Kraan MC et al. Rheumatoid arthritis is a heterogeneous disease: evidence for differences in the activation of the STAT-1 pathway between rheumatoid tissues. Arthritis Rheum 2003; 48: 2132-2145.
41. Batliwalla FM, Baechler EC, Xiao X, Li W, Balasubramanian S, Khalili H et al. Peripheral blood gene expression profiling in rheumatoid arthritis. Genes Immun 2005; 6: 388-397.
42. Toukap AN, Galant C, Theate I, Maudoux A, Lories R, Houssiau F et al. Identification of distinct gene expression profiles in the synovium of patients with systemic lupus erythematosus. Arthritis Rheum 2007; 56: 1579-1588.
43. Galligan CL, Baig E, Bykerk V, Keystone EC, Fish EN. Distinctive gene expression signatures in rheumatoid arthritis synovial tissue fibroblast cells: correlates with disease activity. Genes Immun 2007; 8: 480-491.
44. Tsubaki T, Arita N, Kawakami T, Shiratsuchi T, Yamamoto H, Takubo N et al. Characterization of histopathology and gene-expression profiles of synovitis in early rheumatoid arthritis using targeted biopsy specimens. Arthritis Res Ther 2005; 7: R825-R836.
45. Lequerre T, Bansard C, Vittecoq O, Derambure C, Hiron M, Daveau M et al. Early and long-standing rheumatoid arthritis: distinct molecular signatures identified by gene-expression profiling in synovia. Arthritis Res Ther 2009; 11: R99.
46. van Baarsen LG, Wijbrandts CA, Timmer TC, van der Pouw Kraan TC, Tak PP, Verweij CL. Synovial tissue heterogeneity in rheumatoid arthritis in relation to disease activity and biomarkers in peripheral blood. Arthritis Rheum 2010; 62: 1602-1607.
47. van de Stadt LA, Bos WH, Reynders MM, Wieringa H, Turkstra F, van der Laken CJ et al. The value of ultrasonography in predicting arthritis in auto-antibody positive arthralgia patients: a prospective cohort study. Arthritis Res Ther 2010; 12: R98.
48. Freeston JE, Wakefield RJ, Conaghan PG, Hensor EM, Stewart SP, Emery P. A diagnostic algorithm for persistence of very early inflammatory arthritis: the utility of power Doppler ultrasound when added to conventional assessment tools. Ann Rheum Dis 2010; 69: 417-419.
49. Mottonen T, Hannonen P, Korpela M, Nissila M, Kautiainen H, Ilonen J et al. Delay to institution of therapy and induction of remission using single-drug or combination-disease-modifying antirheumatic drug therapy in early rheumatoid arthritis. Arthritis Rheum 2002; 46: 894-898.
50. O'Dell JR. Treating rheumatoid arthritis early: a window of opportunity? Arthritis Rheum 2002; 46: 283-285.
51. Quinn M, Conaghan P, Emery P. The therapeutic approach of early intervention for rheumatoid arthritis: what is the evidence? Rheumatology 2001; 40: 1211-1220.
52. Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham 3rd CO et al. 2010rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Ann Rheum Dis 2010; 69: 1580-1588.
53. van der Helm-van Mil AH, Huizinga TW. The 2010 ACR/EULAR criteria for rheumatoid arthritis: do they affect the classification or diagnosis of rheumatoid arthritis? Ann Rheum Dis 2012; 71: 1596-1598.
54. Ali M, Ponchel F, Wilson KE, Francis MJD, Wu X, Verhoef A et al. Rheumatoid arthritis synovial T cells regulate transcription of several genes associated with antigen-induced anergy. J Clin Invest 2001; 107: 519-519.
55. Gatzka M, Walsh CM. Apoptotic signal transduction and T cell tolerance. Autoimmunity 2007; 40: 442-452.
56. Devauchelle V, Marion S, Cagnard N, Mistou S, Falgarone G, Breban M et al. DNA microarray allows molecular profiling of rheumatoid arthritis and identification of pathophysiological targets. Genes Immun 2004; 5: 597-608.
57. Edwards CJ, Feldman JL, Beech J, Shields KM, Stover JA, Trepicchio WL et al. Molecular profile of peripheral blood mononuclear cells from patients with rheumatoid arthritis. Mol Med 2007; 13: 40-58.
58. Ng WF, Duggan PJ, Ponchel F, Matarese G, Lombardi G, Edwards AD et al. Human CD4 CD25 cells: a naturally occurring population of regulatory T cells. Blood 2001; 98: 2736-2744.
59. Pratt AG, Swan DC, Richardson S, Wilson G, Hilkens CM, Young DA et al. A CD4 T cell gene signature for early rheumatoid arthritis implicates interleukin 6-mediated STAT3 signalling, particularly in anti-citrullinated peptide antibodynegative disease. Ann Rheum Dis 2012; 71: 1374-1381.
60. Gerlag DM, Raza K, van Baarsen LG, Brouwer E, Buckley CD, Burmester GR et al. EULAR recommendations for terminology and research in individuals at risk of rheumatoid arthritis: report from the Study Group for Risk Factors for Rheumatoid Arthritis. Ann Rheum Dis 2012; 71: 638-641.
61. van de Sande M, De Hair M, Van der Leij C, Klarenbeek P, Bos W, Smith M et al. Different stages of rheumatoid arthritis: features of the synovium in the preclinical phase. Ann Rheum Dis 2011; 70: 772-777.
62. Rantapaa-Dahlqvist S, De Jong BA, Berglin E, Hallmans G, Wadell G, Stenlund H et al. Antibodies against cyclic citrullinated peptide and IgA rheumatoid factor predict the development of rheumatoid arthritis. Arthritis Rheum 2003; 48: 2741-2749.
63. Nielen M, van Schaardenburg D, Reesink H, van de Stadt R, van der Horst-Bruinsma I, de Koning M et al. Specific autoantibodies precede the symptoms of rheumatoid arthritis: a study of serial measurements in blood donors. Arthritis Rheum 2004; 50: 380-386.
64. Wooley PH, Whalen JD. Pristane-induced arthritis in mice. III. Lymphocyte phenotypic and functional abnormalities precede the development of pristaneinduced arthritis. Cell Immunol 1991; 138: 251-259.
65. Rodŕguez-Palmero M, Pelegŕ C, Ferri MJ, Castell M, Franch A, Castellote C. Alterations of lymphocyte populations in lymph nodes but not in spleen during the latency period of adjuvant arthritis. Inflammation 1999; 23: 153-165.
66. Li J, Kuzin I, Moshkani S, Proulx ST, Xing L, Skrombolas D et al. Expanded CD23/CD21hi B cells in inflamed lymph nodes are associated with the onset of inflammatory-erosive arthritis in TNF-transgenic mice and are targets of anti-CD20 therapy. J Immunol 2010; 184: 6142-6150.
67. de Hair MJ, Harty LC, Gerlag DM, Pitzalis C, Veale DJ, Tak PP. Synovial tissue analysis for the discovery of diagnostic and prognostic biomarkers in patients with early arthritis. J Rheumatol 2011; 38: 2068-2072.
68. van Baarsen LGM, De Hair M, Ramwadhdoebe T, van de Sande M, Zijlstra I, Maas M et al. Investigating the cellular composition of lymph nodes in preclinical and early inflammatory arthritis: a feasibility study. Ann Rheum Dis 2012; 71(Suppl 1): A20-A20.
69. van Baarsen LG, Bos WH, Rustenburg F, van der Pouw Kraan TC, Wolbink GJ, Dijkmans BA et al. Gene expression profiling in autoantibody-positive patients with arthralgia predicts development of arthritis. Arthritis Rheum 2010; 62: 694-704.
70. Lü bbers J, Brink M, van de Stadt LA, Vosslamber S, Wesseling JG, van Schaardenburg D et al. The type I IFN signature as a biomarker of preclinical rheumatoid arthritis. Ann Rheum Dis 2013; 72: 776-780.
71. Lubbers J, van de Stadt LA, Vosslamber S, Wesseling JG, Oztü rk S, van Schaardenburg D et al. A1. 7 interferon and B-cell gene signatures contribute to diagnosis of pre-clinical rheumatoid arthritis. Ann Rheum Dis 2013; 72(Suppl 1): A3.
72. Reynolds RJ, Cui X, Vaughan LK, Redden DT, Causey Z, Perkins E et al. Gene expression patterns in peripheral blood cells associated with radiographic severity in African Americans with early rheumatoid arthritis. Rheumatol Int 2012; 33: 129-137.
73. Plenge RM, Cotsapas C, Davies L, Price AL, de Bakker PIW, Maller J et al. Two independent alleles at 6q23 associated with risk of rheumatoid arthritis. Nat Genet 2007; 39: 1477-1482.
74. Lipsky P, van der Heijde D, St. Clair E, Furst D, Breedveld F, Kalden J et al. Infliximab and methotrexate in the treatment of rheumatoid arthritis. N Engl J Med 2000; 343: 1594-1602.
75. Zink A, Strangfeld A, Schneider M, Herzer P, Hierse F, Stoyanova-Scholz M et al. Effectiveness of tumor necrosis factor inhibitors in rheumatoid arthritis in an observational cohort study: comparison of patients according to their eligibility for major randomized clinical trials. Arthritis Rheum 2006; 54: 3399-3407.
76. Blits M, Jansen G, Assaraf YG, van de Wiel MA, Lems WF, Nurmohamed MT et al. Methotrexate normalizes up-regulated folate pathway genes in rheumatoid arthritis. Arthritis Rheum 2013; 65: 2791-2802.
77. Lequerré T, Gauthier-Jauneau AC, Bansard C, Derambure C, Hiron M, Vittecoq O et al. Gene profiling in white blood cells predicts infliximab responsiveness in rheumatoid arthritis. Arthritis Res Ther 2006; 8: R105.
78. Lindberg J, af Klint E, Catrina AI, Nilsson P, Klareskog L, Ulfgren AK et al. Effect of infliximab on mRNA expression profiles in synovial tissue of rheumatoid arthritis patients. Arthritis Res Ther 2006; 8: R179.
79. van der Pouw Kraan TC, Wijbrandts CA, van Baarsen LG, Rustenburg F, Baggen JM, Verweij CL et al. Responsiveness to anti-tumour necrosis factor alpha therapy is related to pre-treatment tissue inflammation levels in rheumatoid arthritis patients. Ann Rheum Dis 2008; 67: 563-566.
80. Lindberg J, Wijbrandts CA, Van Baarsen LG, Nader G, Klareskog L, Catrina A et al. The gene expression profile in the synovium as a predictor of the clinical response to infliximab treatment in rheumatoid arthritis. PLoS One 2010; 5: e11310.
81. Klaasen R, Thurlings RM, Wijbrandts CA, van Kuijk AW, Baeten D, Gerlag DM et al. The relationship between synovial lymphocyte aggregates and the clinical response to infliximab in rheumatoid arthritis: a prospective study. Arthritis Rheum 2009; 60: 3217-3224.
82. van Baarsen LG, Wijbrandts CA, Gerlag DM, Rustenburg F, van der Pouw Kraan TC, Dijkmans BA et al. Pharmacogenomics of infliximab treatment using peripheral blood cells of patients with rheumatoid arthritis. Genes Immun 2010; 11: 622-629.
83. Sekiguchi N, Kawauchi S, Furuya T, Inaba N, Matsuda K, Ando S et al. Messenger ribonucleic acid expression profile in peripheral blood cells from RA patients following treatment with an anti-TNF-alpha monoclonal antibody, infliximab. Rheumatology 2008; 47: 780-788.
84. van Baarsen LG, Wijbrandts CA, Rustenburg F, Cantaert T, van der Pouw Kraan TC, Baeten DL et al. Regulation of IFN response gene activity during infliximab treatment in rheumatoid arthritis is associated with clinical response to treatment. Arthritis Res Ther 2010; 12: R11.
85. Tanino M, Matoba R, Nakamura S, Kameda H, Amano K, Okayama T et al. Prediction of efficacy of anti-TNF biologic agent, infliximab, for rheumatoid arthritis patients using a comprehensive transcriptome analysis of white blood cells. Biochem Biophys Res Commun 2009; 387: 261-265.
86. Julia A, Erra A, Palacio C, Tomas C, Sans X, Barcelo P et al. An eight-gene blood expression profile predicts the response to infliximab in rheumatoid arthritis. PLoS One 2009; 4: e7556.
87. Stuhlmuller B, Haupl T, Hernandez MM, Grutzkau A, Kuban RJ, Tandon N et al. CD11c as a transcriptional biomarker to predict response to anti-TNF monotherapy with adalimumab in patients with rheumatoid arthritis. Clin Pharmacol Ther 2010; 87: 311-321.
88. Badot V, Galant C, Nzeusseu Toukap A, Theate I, Maudoux AL, Van den Eynde BJ et al. Gene expression profiling in the synovium identifies a predictive signature of absence of response to adalimumab therapy in rheumatoid arthritis. Arthritis Res Ther 2009; 11: R57.
89. Koczan D, Drynda S, Hecker M, Drynda A, Guthke R, Kekow J et al. Molecular discrimination of responders and nonresponders to anti-TNF alpha therapy in rheumatoid arthritis by etanercept. Arthritis Res Ther 2008; 10: R50.
90. Julia A, Barcelo M, Erra A, Palacio C, Marsal S. Identification of candidate genes for rituximab response in rheumatoid arthritis patients by microarray expression profiling in blood cells. Pharmacogenomics 2009; 10: 1697-1708.
91. Raterman HG, Vosslamber S, De Ridder S, Nurmohamed MT, Lems WF, Boers M et al. Interferon type I signature may predict non response upon rituximab in rheumatoid arthritis patients. Arthritis Res Ther 2012; 14: R95.
92. Thurlings RM, Boumans M, Tekstra J, van Roon JA, Vos K, van Westing DM et al. Relationship between the type I interferon signature and the response to rituximab in rheumatoid arthritis patients. Arthritis Rheum 2010; 62: 3607-3614.
93. Vosslamber S, Raterman H, van der Pouw Kraan T, Schreurs M, von Blomberg B, Nurmohamed M et al. Pharmacological induction of interferon type I activity following treatment with rituximab determines clinical response in rheumatoid arthritis. Ann Rheum Dis 2011; 70: 1153-1159.
94. Bansard C, Lequerre T, Derambure C, Vittecoq O, Hiron M, Daragon A et al. Gene profiling predicts rheumatoid arthritis responsiveness to IL-1Ra (anakinra). Rheumatology 2011; 50: 283-292.
95. Nishimoto N, Hashimoto J, Miyasaka N, Yamamoto K, Kawai S, Takeuchi T et al. Study of active controlled monotherapy used for rheumatoid arthritis, an IL-6 inhibitor (SAMURAI): evidence of clinical and radiographic benefit from an x ray reader-blinded randomised controlled trial of tocilizumab. Ann Rheum Dis 2007; 66: 1162-1167.
96. Jones G, Sebba A, Gu J, Lowenstein MB, Calvo A, Gomez-Reino JJ et al. Comparison of tocilizumab monotherapy versus methotrexate monotherapy in patients with moderate to severe rheumatoid arthritis: the AMBITION study. Ann Rheum Dis 2010; 69: 88-96.
97. Maini RN, Taylor PC, Szechinski J, Pavelka K, Brö ll J, Balint G et al. Double-blind randomized controlled clinical trial of the interleukin-6 receptor antagonist, tocilizumab, in European patients with rheumatoid arthritis who had an incomplete response to methotrexate. Arthritis Rheum 2006; 54: 2817-2829.
98. Mesko B, Poliska S, Szamosi S, Szekanecz Z, Podani J, Varadi C et al. Peripheral blood gene expression and igg glycosylation profiles as markers of tocilizumab treatment in rheumatoid arthritis. J Rheumatol 2012; 39: 916-928.
99. Ioannidis JP, Allison DB, Ball CA, Coulibaly I, Cui X, Culhane AC et al. Repeatability of published microarray gene expression analyses. Nat Genet 2009; 41: 149-155.
100. Cui J, Stahl EA, Saevarsdottir S, Miceli C, Diogo D, Trynka G et al. Genome-wide association study and gene expression analysis identifies CD84 as a predictor of response to etanercept therapy in rheumatoid arthritis. PLoS Genet 2013; 9: e1003394.
101. Toonen EJM, Gilissen C, Franke B, Kievit W, Eijsbouts AM, den Broeder AA et al. Validation study of existing gene expression signatures for anti-TNF treatment in patients with rheumatoid arthritis. PLoS One 2012; 7: e33199.
102. Bienkowska JR, Dalgin GS, Batliwalla F, Allaire N, Roubenoff R, Gregersen PK et al. Convergent Random Forest predictor: methodology for predicting drug response from genome-scale data applied to anti-TNF response. Genomics 2009; 94: 423-432.
103. Meugnier E, Coury F, Tebib J, Ferraro-Peyret C, Rome S, Bienvenu J et al. Gene expression profiling in peripheral blood cells of patients with rheumatoid arthritis in response to anti-TNF-a treatments. Physiol Genomics 2011; 43: 365-371.
104. Pheasant M, Mattick JS. Raising the estimate of functional human sequences. Genome Res 2007; 17: 1245-1253.
105. Soifer HS, Rossi JJ, Satrom P. MicroRNAs in disease and potential therapeutic applications. Mol Ther 2007; 15: 2070-2079.
106. Flynt AS, Lai EC. Biological principles of microRNA-mediated regulation: shared themes amid diversity. Nat Rev Genet 2008; 9: 831-842.
107. Duroux-Richard I, Jorgensen C, Apparailly F. miRNAs and rheumatoid arthritis- promising novel biomarkers. Swiss Med Wkly 2011; 141: w13175.
108. Zampetaki A, Kiechl S, Drozdov I, Willeit P, Mayr U, Prokopi M et al. Plasma microRNA profiling reveals loss of endothelial MiR-126 and other microRNAs in type 2 diabetes: novelty and significance. Circ Res 2010; 107: 810-817.
109. Lai CY, Yu SL, Hsieh MH, Chen CH, Chen HY, Wen CC et al. MicroRNA expression aberration as potential peripheral blood biomarkers for schizophrenia. PLoS One 2011; 6: e21635.
110. Li S, Zhu J, Zhang W, Chen Y, Zhang K, Popescu LM et al. Signature microRNA expression profile of essential hypertension and its novel link to human cytomegalovirus infection: clinical perspective. Circulation 2011; 124: 175-184.
111. Chhabra R, Dubey R, Saini N. Cooperative and individualistic functions of the microRNAs in the miR-23aB 27aB 24-2 cluster and its implication in human diseases. Mol Cancer 2010; 9: 232.
112. Alevizos I, Illei GG. MicroRNAs as biomarkers in rheumatic diseases. Nat Rev Rheumatol 2010; 6: 391-398.
113. Ha TY. MicroRNAs in human diseases: from cancer to cardiovascular disease. Immune Network 2011; 11: 135-154.
114. Meng F, Henson R, Lang M, Wehbe H, Maheshwari S, Mendell JT et al. Involvement of human micro-RNA in growth and response to chemotherapy in human cholangiocarcinoma cell lines. Gastroenterology 2006; 130: 2113-2129.
115. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D et al. MicroRNA expression profiles classify human cancers. Nature 2005; 435: 834-838.
116. Roldo C, Missiaglia E, Hagan JP, Falconi M, Capelli P, Bersani S et al. MicroRNA expression abnormalities in pancreatic endocrine and acinar tumors are associated with distinctive pathologic features and clinical behavior. J Clin Oncol 2006; 24: 4677-4684.
117. Zhang H, Yang JH, Zheng YS, Zhang P, Chen X, Wu J et al. Genome-wide analysis of small RNA and novel microRNA discovery in human acute lymphoblastic leukemia based on extensive sequencing approach. PLoS One 2009; 4: e6849.
118. Stagakis E, Bertsias G, Verginis P, Nakou M, Hatziapostolou M, Kritikos H et al. Identification of novel microRNA signatures linked to human lupus disease activity and pathogenesis: miR-21 regulates aberrant T cell responses through regulation of PDCD4 expression. Ann Rheum Dis 2011; 70: 1496-1506.
119. Duroux-Richard I, Presumey J, Courties G, Gay S, Gordeladze J, Jorgensen C et al. MicroRNAs as new player in rheumatoid arthritis. Joint Bone Spine 2011; 78: 17-22.
120. Li J, Wan Y, Guo Q, Zou L, Zhang J, Fang Y et al. Research article: altered microRNA expression profile with miR-146a upregulation in CD4 T cells from patients with rheumatoid arthritis. Arthritis Res Ther 2010; 12: R81.
121. Murata K, Furu M, Yoshitomi H, Ishikawa M, Shibuya H, Hashimoto M et al. Comprehensive microRNA analysis identifies miR-24 and miR-125a-5p as plasma biomarkers for rheumatoid arthritis. PLoS One 2013; 8: e69118.
122. Furer V, Greenberg JD, Attur M, Abramson SB, Pillinger MH. The role of microRNA in rheumatoid arthritis and other autoimmune diseases. Clin Immunol 2010; 136: 1-15.
123. Stanczyk J, Pedrioli DM, Brentano F, Sanchez-Pernaute O, Kolling C, Gay RE et al. Altered expression of microRNA in synovial fibroblasts and synovial tissue in rheumatoid arthritis. Arthritis Rheum 2008; 58: 1001-1009.
124. de la Rica L, Urquiza JM, Gó mez-Cabrero D, Islam AB, Ló pez-Bigas N, Tegnér J et al. Identification of novel markers in rheumatoid arthritis through integrated analysis of DNA methylation and microRNA expression. J Autoimmun 2013; 41: 6-16.
125. Nakamachi Y, Kawano S, Takenokuchi M, Nishimura K, Sakai Y, Chin T et al. MicroRNA-124a is a key regulator of proliferation and monocyte chemoattractant protein 1 secretion in fibroblast-like synoviocytes from patients with rheumatoid arthritis. Arthritis Rheum 2009; 60: 1294-1304.
126. Kawano S, Nakamachi Y. miR-124a as a key regulator of proliferation and MCP-1 secretion in synoviocytes from patients with rheumatoid arthritis. Ann Rheum Dis 2011; 70(Suppl 1): i88-i91.
127. Pauley KM, Satoh M, Chan AL, Bubb MR, Reeves WH, Chan EKL. Upregulated miR-146a expression in peripheral blood mononuclear cells from rheumatoid arthritis patients. Arthritis Res Ther 2008; 10: R101.
128. Alsaleh G, Suffert G, Semaan N, Juncker T, Frenzel L, Gottenberg JE et al. Bruton's tyrosine kinase is involved in miR-346-related regulation of IL-18 release by lipopolysaccharide-activated rheumatoid fibroblast-like synoviocytes. J Immunol 2009; 182: 5088-5097.
129. Niimoto T, Nakasa T, Ishikawa M, Okuhara A, Izumi B, Deie M et al. MicroRNA-146a expresses in interleukin-17 producing T cells in rheumatoid arthritis patients. BMC Musculoskelet Disord 2010; 11: 209.
130. Nakasa T, Miyaki S, Okubo A, Hashimoto M, Nishida K, Ochi M et al. Expression of microRNA-146 in rheumatoid arthritis synovial tissue. Arthritis Rheum 2008; 58: 1284-1292.
131. Stanczyk J, Ospelt C, Karouzakis E, Filer A, Raza K, Kolling C et al. Altered expression of microRNA-203 in rheumatoid arthritis synovial fibroblasts and its role in fibroblast activation. Arthritis Rheum 2011; 63: 373-381.
132. Bauer JW, Bilgic H, Baechler EC. Gene-expression profiling in rheumatic disease: tools and therapeutic potential. Nat Rev Rheumatol 2009; 5: 257-265.
133. Goverdhana S, Puntel M, Xiong W, Zirger JM, Barcia C, Curtin JF et al. Regulatable gene expression systems for gene therapy applications: progress and future challenges. Mol Ther 2005; 12: 189-211.
134. Manasco PK. Ethical and legal aspects of applied genomic technologies: practical solutions. Curr Mol Med 2005; 5: 23-28.
135. Neumaier M. Ethics and quality assessment in genetic testing. J Int Federation Clin Chem Lab Med 2005; 16: 2.
136. Consortium MQC. The MAQC-II Project: a comprehensive study of common practices for the development and validation of microarray-based predictive models. Nat Biotechnol 2010; 28: 827-838.
137. Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C et al. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 2001; 29: 365-371.
138. Knudsen TB, Daston GP. MIAME guidelines. Reprod Toxicol 2005; 19: 263.
139. van't Veer L, Dai H, van de Vijver M, He Y, Hart A, Mao M et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002; 415: 530-536.
140. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004; 351: 2817-2826.
141. Webber EM, Lin JS, Whitlock EP. Oncotype DX tumor gene expression profiling in stage II colon cancer. Application: prognostic, risk prediction. PLoS Currents 2009; 2: 1341.
142. Ma XJ, Salunga R, Dahiya S, Wang W, Carney E, Durbecq V et al. A five-gene molecular grade index and HOXB13: IL17BR are complementary prognostic factors in early stage breast cancer. Clin Cancer Res 2008; 14: 2601-2608.
143. Sotiriou C, Pusztai L. Gene-expression signatures in breast cancer. N Engl J Med 2009; 360: 790-800.
144. Jerevall PL, Ma XJ, Li H, Salunga R, Kesty NC, Erlander MG et al. Prognostic utility of HOXB13: IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br J Cancer 2011; 104: 1762-1769.
145. Ross JS, Hatzis C, Symmans WF, Pusztai L, Hortobagyi GN. Commercialized multigene predictors of clinical outcome for breast cancer. Oncologist 2008; 13: 477-493.
146. Ebbert MTW, Bastien RRL, Boucher KM, Mart́n M, Carrasco E, Caballero R et al. Characterization of uncertainty in the classification of multivariate assays: application to PAM50 centroid-based genomic predictors for breast cancer treatment plans. J Clin Bioinformatics 2011; 1: 1-9.
147. Bastien RRL, Rodŕguez-Lescure Á, Ebbert MTW, Prat A, Munárriz B, Rowe L et al. PAM50 breast cancer subtyping by RT-qPCR and concordance with standard clinical molecular markers. BMC Med Genomics 2012; 5: 44.
148. de Snoo F, Bender R, Glas A, Rutgers E. Gene expression profiling: decoding breast cancer. Surg Oncol 2009; 18: 366.
149. Hornberger J, Alvarado MD, Rebecca C, Gutierrez HR, Tiffany MY, Gradishar WJ. Clinical validity/utility, change in practice patterns, and economic implications of risk stratifiers to predict outcomes for early-stage breast cancer: a systematic review. J Natl Cancer Inst 2012; 104: 1068-1079.
150. Roedder S, Vitalone M, Khatri P, Sarwal MM. Biomarkers in solid organ transplantation: establishing personalized transplantation medicine. Genome Med 2011; 3: 37.
151. Rosenberg S, Elashoff MR, Lieu HD, Brown BO, Kraus WE, Schwartz RS et al. Whole blood gene expression testing for coronary artery disease in nondiabetic patients: major adverse cardiovascular events and interventions in the PREDICT trial. J Cardiovasc Transl Res 2012; 5: 1-9.
152. Voros S, Elashoff MR, Sehnert AJ, Lieu HD, Wingrove JA, Daniels SE et al. A validated, peripheral blood gene expression pattern correlates with coronary arterial plaque burden by quantitative coronary angiography and coronary artery calcium scoring. J Am Coll Cardiol 2011; 57: E1157-E1157.
153. Booij BB, Lindahl T, Wetterberg P, Skaane NV, Sabo S, Feten G et al. A gene expression pattern in blood for the early detection of Alzheimer's disease. J Alzheimer's Dis 2011; 23: 109-119.
154. Rye PD, Booij BB, Grave G, Lindahl T, Kristiansen L, Andersen HM et al. A novel blood test for the early detection of Alzheimer's disease. J Alzheimer's Dis 2011; 23: 121-129.
155. Costanzo MR, Dipchand A, Starling R, Anderson A, Chan M, Desai S et al. The International Society of Heart and Lung Transplantation Guidelines for the care of heart transplant recipients. J Heart Lung Transplant 2010; 29: 914-956.
156. van der Pouw Kraan T, Van Gaalen F, Huizinga T, Pieterman E, Breedveld F, Verweij C. Discovery of distinctive gene expression profiles in rheumatoid synovium using cDNA microarray technology: evidence for the existence of multiple pathways of tissue destruction and repair. Genes Immun 2003; 4: 187-196.
157. Lindberg J, af Klint E, Ulfgren AK, Stark A, Andersson T, Nilsson P et al. Variability in synovial inflammation in rheumatoid arthritis investigated by microarray technology. Arthritis Res Ther 2006; 8: R47.
158. Timmer TCG, Baltus B, Vondenhoff M, Huizinga TWJ, Tak PP, Verweij CL et al. Inflammation and ectopic lymphoid structures in rheumatoid arthritis synovial tissues dissected by genomics technology: Identification of the interleukin-7 signaling pathway in tissues with lymphoid neogenesis. Arthritis Rheum 2007; 56: 2492-2502.
159. Huber R, Hummert C, Gausmann U, Pohlers D, Koczan D, Guthke R et al. Identification of intra-group, inter-individual, and gene-specific variances in mRNA expression profiles in the rheumatoid arthritis synovial membrane. Arthritis Res Ther 2008; 10: R98.
160. Ungethuem U, Haeupl T, Witt H, Koczan D, Krenn V, Huber H et al. Molecular signatures and new candidates to target the pathogenesis of rheumatoid arthritis. Physiol Genomics 2010; 42A: 267-282.
161. Watanabe N, Ando K, Yoshida S, Inuzuka S, Kobayashi M, Matsui N et al. Gene expression profile analysis of rheumatoid synovial fibroblast cultures revealing the overexpression of genes responsible for tumor-like growth of rheumatoid synovium. Biochem Biophys Res Commun 2002; 294: 1121-1129.
162. Kasperkovitz PV, Timmer TCG, Smeets TJ, Verbeet NL, Tak PP, Baltus B et al. Fibroblast-like synoviocytes derived from patients with rheumatoid arthritis show the imprint of synovial tissue heterogeneity: Evidence of a link between an increased myofibroblast-like phenotype and high-inflammation synovitis. Arthritis Rheum 2005; 52: 430-441.
163. Van der Pouw Kraan T, Wijbrandts C, van Baarsen L, Voskuyl A, Rustenburg F, Baggen J et al. Rheumatoid arthritis subtypes identified by genomic profiling of peripheral blood cells: assignment of a type I interferon signature in a subpopulation of patients. Ann Rheum Dis 2007; 66: 1008-1014.
164. van der Pouw Kraan T, van Baarsen L, Wijbrandts C, Voskuyl A, Rustenburg F, Baggen J et al. Expression of a pathogen-response programin peripheral blood cells defines a subgroup of rheumatoid arthritis patients. Genes Immun 2007; 9: 16-22.
165. Bovin LF, Rieneck K, Workman C, Nielsen H, Sorensen SF, Skjodt H et al. Blood cell gene expression profiling in rheumatoid arthritis: discriminative genes and effect of rheumatoid factor. Immunol Lett 2004; 93: 217-226.
166. Olsen N, Sokka T, Seehorn C, Kraft B, Maas K, Moore J et al. A gene expression signature for recent onset rheumatoid arthritis in peripheral blood mononuclear cells. Ann Rheum Dis 2004; 63: 1387-1392.
167. Batliwalla F, Baechler E, Xiao X, Li W, Balasubramanian S, Khalili H et al. Peripheral blood gene expression profiling in rheumatoid arthritis. Genes Immun 2005; 6: 388-397.
168. Teixeira VH, Olaso R, Martin-Magniette M-L, Lasbleiz S, Jacq L, Oliveira CR et al. Transcriptome analysis describing new immunity and defense genes in peripheral blood mononuclear cells of rheumatoid arthritis patients. PLoS One 2009; 4: e6803.
169. Junta CM, Sandrin-Garcia P, Fachin-Saltoratto AL, Mello SS, Oliveira RDR, Rassi DM et al. Differential gene expression of peripheral blood mononuclear cells from rheumatoid arthritis patients may discriminate immunogenetic, pathogenic and treatment features. Immunology 2009; 127: 365-372.
170. Grcevic D, Jajic Z, Kovacic N, Lukic I, Velagic V, Grubisic F et al. Peripheral blood expression profiles of bone morphogenetic proteins, tumor necrosis factorsuperfamily molecules, and transcription factor Runx2 could be used as markers of the form of arthritis, disease activity, and therapeutic responsiveness. J Rheumatol 2010; 37: 246-256.
171. Liu Z, Sokka T, Maas K, Olsen NJ, Aune TM. Prediction of disease severity in patients with early rheumatoid arthritis by gene expression profiling. Hum Genomics Proteomics 2009; 2009: 10; doi:10. 4061/2009/484351.
172. Szodoray P, Alex P, Frank M, Turner M, Turner S, Knowlton N et al. A genomescale assessment of peripheral blood B-cell molecular homeostasis in patients with rheumatoid arthritis. Rheumatology 2006; 45: 1466-1476.
173. Haas CS, Creighton CJ, Pi X, Maine I, Koch AE, Haines GK et al. Identification of genes modulated in rheumatoid arthritis using complementary DNA microarray analysis of lymphoblastoid B cell lines from disease-discordant monozygotic twins. Arthritis Rheum 2006; 54: 2047-2060.
174. Lee HM, Sugino H, Aoki C, Shimaoka Y, Suzuki R, Ochi K et al. Abnormal networks of immune response-related molecules in bone marrow cells from patients with rheumatoid arthritis as revealed by DNA microarray analysis. Arthritis Res Ther 2011; 13: R89.
175. Pratt A, Brown P, Cockell S, Wilson G, Isaacs J. A3. 2 A CD4 T-cell gene expression signature predicts drug survival on methotrexate monotherapy in early rheumatoid arthritis. Ann Rheum Dis 2013; 72(Suppl 1): A13-A14.
176. Mans K, Tandon N, Sohnrey C, Bolle S, Grü tzkau A, Burmester G et al. A7. 17 microarray gene expression profiling of rheumatoid arthritis patients for prediction of response to methotrexate treatment. Ann Rheum Dis 2013; 72(Suppl 1): A54.
177. Soldano S, Villaggio B, Gallo F, Montagna P, Brizzolara R, Cutolo M. Modulation of gene expression by leflunomide and prednisone during treatment of early rheumatoid arthritis. Ann Rheum Dis 2010; 69(Suppl 2): A31-A32.
178. Szekanecz Z, Meskó B, Poliska S, Váncsa A, Palatka K, Holló Z et al. A7. 20 response to infliximab therapy can be predicted using distinct, non-overlapping gene panels of peripheral blood gene expression in rheumatoid arthritis and crohn's disease. Ann Rheum Dis 2013; 72(Suppl 1): A55.
179. Gutierrez-Roelens I, Galant C, Théate I, Lories R, Durez P, Nzeusseu-Toukap A et al. Rituximab treatment induces the expression of genes involved in healing processes in the rheumatoid arthritis synovium. Arthritis Rheum 2011; 63: 1246-1254.
180. Hogan VE, Holweg CTJ, Choy DF, Kummerfeld SK, Hackney JA, Teng YKO et al. Pretreatment synovial transcriptional profile is associated with early and late clinical response in rheumatoid arthritis patients treated with rituximab. Ann Rheum Dis 2012
181. Oliveira RDR, Fontana V, Junta CM, Marques MMC, Macedo C, Rassi DM et al. Differential gene expression profiles may differentiate responder and nonresponder patients with rheumatoid arthritis for methotrexate (MTX) monotherapy and MTX plus tumor necrosis factor inhibitor combined therapy. J Rheumatol 2012; 39: 1524-1532.
182. Parker A, Izmailova ES, Narang J, Badola S, Le T, Roubenoff R et al. Peripheral blood expression of nuclear factor-kappab-regulated genes is associated with rheumatoid arthritis disease activity and responds differentially to anti-tumor necrosis factor-alpha versus methotrexate. J Rheumatol 2007; 34: 1817-1822.