Reanalysis of the Rituximab in ANCA-Associated Vasculitis trial identifies granulocyte subsets as a novel early marker of successful treatment
Mazen Nasrallah, Yannick Pouliot, Bjoern Hartmann, Patrick Dunn, Elizabeth Thomson, Jeffrey Wiser, Atul J Butte, Mazen Nasrallah, Yannick Pouliot, Bjoern Hartmann, Patrick Dunn, Elizabeth Thomson, Jeffrey Wiser, Atul J Butte
Abstract
Introduction: In the present study, we sought to identify markers in patients with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) that distinguish those achieving remission at 6 months following rituximab or cyclophosphamide treatment from those for whom treatment failed in the Rituximab in ANCA-Associated Vasculitis (RAVE) trial.
Methods: Clinical and flow cytometry data from the RAVE trial were downloaded from the Immunology Database and Analysis Portal and Immune Tolerance Network TrialShare public repositories. Flow cytometry data were analyzed using validated automated gating and joined with clinical data. Lymphocyte and granulocyte populations were measured in patients who achieved or failed to achieve remission.
Results: There was no difference in lymphocyte subsets and treatment outcome with either treatment. We defined a Granularity Index (GI) that measures the difference between the percentage of hypergranular and hypogranular granulocytes. We found that rituximab-treated patients who achieved remission had a significantly higher GI at baseline than those who did not (p = 0.0085) and that this pattern was reversed in cyclophosphamide-treated patients (p = 0.037). We defined optimal cutoff values of the GI using the Youden index. Cyclophosphamide was superior to rituximab in inducing remission in patients with GI below -9.25% (67% vs. 30%, respectively; p = 0.033), whereas rituximab was superior to cyclophosphamide for patients with GI greater than 47.6% (83% vs. 33%, respectively; p = 0.0002).
Conclusions: We identified distinct subsets of granulocytes found at baseline in patients with AAV that predicted whether they were more likely to achieve remission with cyclophosphamide or rituximab. Profiling patients on the basis of the GI may lead to more successful trials and therapeutic courses in AAV.
Trial registration: ClinicalTrials.gov identifier (for original study from which data were obtained): NCT00104299 . Date of registration: 24 February 2005.
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References
- Berden A, Göçeroglu A, Jayne D, Luqmani R, Rasmussen N, Bruijn JA, et al. Diagnosis and management of ANCA associated vasculitis. BMJ. 2012;344:e26. doi: 10.1136/bmj.e26.
- Stone JH, Merkel PA, Spiera R, Seo P, Langford CA, Hoffman GS, et al. Rituximab versus cyclophosphamide for ANCA-associated vasculitis. N Engl J Med. 2010;363:221–32. doi: 10.1056/NEJMoa0909905.
- Specks U, Merkel PA, Seo P, Spiera R, Langford CA, Hoffman GS, et al. Efficacy of remission-induction regimens for ANCA-associated vasculitis. N Engl J Med. 2013;369:417–27. doi: 10.1056/NEJMoa1213277.
- Bhattacharya S, Andorf S, Gomes L, Dunn P, Schaefer H, Pontius J, et al. ImmPort: disseminating data to the public for the future of immunology. Immunol Res. 2014;58:234–9. doi: 10.1007/s12026-014-8516-1.
- Immune Tolerance Network’s (ITN) TrialShare. . Accessed 14 September 2015.
- Qian Y, Wei C, Eun-Hyung Lee F, Campbell J, Halliley J, Lee JA, et al. Elucidation of seventeen human peripheral blood B-cell subsets and quantification of the tetanus response using a density-based method for the automated identification of cell populations in multidimensional flow cytometry data. Cytometry B Clin Cytom. 2010;78:S69–82. doi: 10.1002/cyto.b.20554.
- ImmPort RAVE trial data. . Accessed 14 September 2015.
- Specks U, Merkel PA, Hoffman GS, Langford CA, Spiera R, Seo P, et al. Design of the Rituximab in ANCA-Associated Vasculitis (RAVE) Trial. Open Arthritis J. 2011;4:1–18. doi: 10.2174/1876539401104010001.
- ImmPort Web-based FLOCK service. . Accessed 14 September 2015.
- Aghaeepour N. Finak G; FlowCAP Consortium; DREAM Consortium, Hoos H, Mosmann TR, et al. Critical assessment of automated flow cytometry data analysis techniques. Nat Methods. 2013;10:228–38. doi: 10.1038/nmeth.2365.
- McArthur MA, Sztein MB. Heterogeneity of multifunctional IL-17A producing S. Typhi-specific CD8+ T cells in volunteers following Ty21a typhoid immunization. PLoS One. 2012;7:e38408. doi: 10.1371/journal.pone.0038408.
- McArthur MA, Sztein MB. Unexpected heterogeneity of multifunctional T cells in response to superantigen stimulation in humans. Clin Immunol. 2013;146:140–52. doi: 10.1016/j.clim.2012.12.003.
- Fletcher MP, Seligmann BE. Monitoring human neutrophil granule secretion by flow cytometry: secretion and membrane potential changes assessed by light scatter and a fluorescent probe of membrane potential. J Leukoc Biol. 1985;37:431–47.
- Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3:32–5. doi: 10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>;2-3.
- Song F, Parekh S, Hooper L, Loke YK, Ryder J, Sutton AJ, et al. Dissemination and publication of research findings: an updated review of related biases. Health Technol Assess. 2010;14(8):iii, ix-xi, 1-193
- Jackson T. Open data: seize the moment. BMJ. 2012;345:e7332. doi: 10.1136/bmj.e7332.
- Payne D. Tamiflu: the battle for secret drug data. BMJ. 2012;345:e7303. doi: 10.1136/bmj.e7303.
- Ross JS, Krumholz HM. Ushering in a new era of open science through data sharing: the wall must come down. JAMA. 2013;309:1355–6. doi: 10.1001/jama.2013.1299.
- Loder E. Sharing data from clinical trials: where we are and what lies ahead. BMJ. 2013;347:f4794. doi: 10.1136/bmj.f4794.
- Mello MM, Francer JK, Wilenzick M, Teden P, Bierer BE, Barnes M. Preparing for responsible sharing of clinical trial data. N Engl J Med. 2013;369:1651–8. doi: 10.1056/NEJMhle1309073.
- Butte AJ, Reis B, Kho A, Sun Y, Kohane IS. Analyzing functional genomic differences yields oncogenes and chromosomal breakpoints in ALL and AML. Nat Genet. 2001;27:45. doi: 10.1038/87022.
- Kodama K, Horikoshi M, Toda K, Yamada S, Hara K, Irie J, et al. Expression-based genome-wide association study links the receptor CD44 in adipose tissue with type 2 diabetes. Proc Natl Acad Sci U S A. 2012;109:7049–54. doi: 10.1073/pnas.1114513109.
- Sirota M, Dudley JT, Kim J, Chiang AP, Morgan AA, Sweet-Cordero A, et al. Discovery and preclinical validation of drug indications using compendia of public gene expression data. Sci Transl Med. 2011;3:96ra77.
- Jennette JC, Falk RJ, Hu P, Xiao H. Pathogenesis of antineutrophil cytoplasmic autoantibody–associated small-vessel vasculitis. Annu Rev Pathol Mech Dis. 2013;8:139–60. doi: 10.1146/annurev-pathol-011811-132453.
- Kettritz R. How anti-neutrophil cytoplasmic autoantibodies activate neutrophils. Clin Exp Immunol. 2012;169:220–8. doi: 10.1111/j.1365-2249.2012.04615.x.
- Kallenberg CGM. Pathogenesis of ANCA-associated vasculitides. Ann Rheum Dis. 2011;70:i59–63. doi: 10.1136/ard.2010.138024.
- Grayson PC, Carmona-Rivera C, Xu L, Lim N, Gao Z, Asare AL, et al. Neutrophil-related gene expression and low-density granulocytes associated with disease activity and response to treatment in antineutrophil cytoplasmic antibody–associated vasculitis. Arthritis Rheumatol. 2015;67:1922–32. doi: 10.1002/art.39153.
Source: PubMed