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1 Supplementary Appendix This appendix has been provided by the authors to give readers additiol information about their work. Supplement to: Saadoun D, Rosenzwajg M, Joly F, et al. Regulatory T-cell responses to low-dose interleukin-2 in HCV-induced vasculitis. N Engl J Med 211;365: (PDF updated February 4, 214.)

2 SUPPLEMENTARY APPENDIX SUPPLEMENTARY APPENDIX...1 Supplementary Methods...2 Immunochemistry...2 Flow cytometric alysis...2 Suppression T cell Assays...3 Transcriptome studies...4 References...5 Supplementary Table Supplementary figures...7 Supplementary Figure Supplementary Figure Supplementary Figure Supplementary Figure Supplementary Figure

3 Supplementary Methods Immunochemistry Antinuclear antibodies (ANA) were determined by indirect immunofluorescence on HEp2 cells (Immunoconcepts, Sacramento CA) (positive 1/8). Rheumatoid factor (RF) activity was assessed by ELISA (BMD, Marne La Vallée, France). Flow cytometric alysis The immunomonitoring was performed according to previously published routine methods used in the Pitié-Salpêtrière Biotherapy department 1. Briefly, peripheral blood mononuclear cell (PBMC) subsets (CD3 +, CD4 +, CD8 + T lymphocytes, CD19 + B lymphocytes and CD3 - CD56 + NK cell) counts (cells/μl) were established from fresh blood samples using CYTO-STAT tetrachrome kits with Flowcount fluorescents beads as interl standard and tetra CXP software with a FC5 cytometer according to manufacturer s instructions (Beckman Coulter, Villepinte, France). Subsets of these cells were alysed using multicolour flow cytometry and mabs directly conjugated to various fluorescent markers. Cells acquisition and alysis by flow cytometry were performed using a FC5 Cytometer (Beckman Coulter). Instrument setting parameters (gains, compensations, and threshold) were set with machine software (CXP Software; Beckman Coulter) in conjunction with calibration beads (Flow-set beads, Cytocomp kit, and CYTO- TROL Control Cells). Machine reproducibility was verified with standardized beads (Flow-check). Data were alyzed with CXP alysis software (Beckman Coulter). Subsets of these cells were alysed using multicolour flow cytometry and mabs directly conjugated either to Fluorescein isothiocyate (FITC), Phycoerythrin (PE), Phycoerythrin-Texas Red (ECD), Allophycocyanin (APC) or phycoerythrin-cyanyn 7 (PE-Cya7) were used for: CD3-ECD or -PC7, CD4-ECD or -PC7, CD8-APC or PC7, CD16-FITC, CD19-ECD and CD56-PE all from Beckman Coulter (Villepinte, France). CD25-PE, CD27-PE, and IgD-FITC, were from BD Biosciences (Le Pont De Claix, France). CD127-FITC was from e-biosciences (San Diego, CA, USA). Matched mouse isotype control 2

4 antibodies were used. Intranuclear FOXP3 labeling was performed after CD3, CD4, CD127 and CD25 membrane staining using APC anti-human Foxp3 kit (PCH11 clone, ebiosciences) according to manufacturer s instructions. Rat IGg2a APC was used as isotypic control (ebiosciences,). Cells acquisition and alysis by flow cytometry were performed using a FC5 Cytometer (Beckman Coulter). Instrument setting parameters (gains, compensations, and threshold) were set with machine software (CXP Software; Beckman Coulter) in conjunction with calibration beads (Flow-set beads, Cytocomp kit, and CYTO-TROL Control Cells). Machine reproducibility was verified with standardized beads (Flow-check). Data were alyzed with CXP alysis software and Kaluza software (Beckman Coulter) For detection of intracellular cytokine production, PBMC were stimulated with 5 ng/ml PMA and 1 mm ionomycin in the presence of Golgi-Stop (BD Biosciences) for 4 hr and then stained with anti- IFN-g-FITC (ebioscience), or anti-il-17-alexa Fluor 647 (e-bioscience) after fixation and permeabilization, according to the manufacturer's instructions. Suppression T cell Assays Cells suppression assay was performed as previously described 2. Briefly, PBMC were stained with appropriate combitions of mabs in order to purify by flow cytometer (FACS Aria, BD Biosciences) CD3 + CD4 + CD25 + CD127 low/ cells mely FACS-sorted. To test their suppressive activity, were assayed in round-bottomed 96-well tissue culture plates mixed at various cell ratios (1/1; 1/2; 1/4; 1/8; 1/16) with autologous Facs-sorted CD4 + CD25 cells as responder cells in the presence of 1 4 irradiated (15 grays) allogeneic PBMC as stimulator cells in 2 µl of complete culture medium. Triplicates were performed for each culture condition. After 4 days, cell proliferation was determined by incorporation of 1 µci (.37 MBq) of 3 H-thymidine (Amersham, Buckinghamshire, UK) for an additiol 16 h and measured using a β-counter (counter-wallac). Results were expressed in counts per minute (cpm) and percentage of suppression of proliferation was determined by proliferation of effector cells without treg / proliferation of effector cells with treg ratio. 3

5 Transcriptome studies RNAs were generated using RNeasy Mini Kit (QIAGEN, requis, CA) according to the manufacturer s instructions. RNA integrity was assessed using an Agilent Bioalyser showing a quality of RNA integrity number of (Agilent Technologies). RNA yield was assessed using a NanoDrop 1 spectrophotometer (NanoDrop Products, Thermo Fisher Scientific). Total RNA was amplified and converted to biotinylated crna according to the manufacturer s protocol (Illumi TotalPrep RNA Amplification Kit; Ambion). Labelled crna were hybridized overnight to Illumi Human HT-12 V3 BeadChip arrays (Illumi), which contained more than 48, probes. The arrays were then washed, blocked, stained and scanned on an Illumi BeadStation following the manufacturer s protocols. Illumi BeadStudio software (Illumi) was used to generate sigl intensity values from the scans. Raw data have been deposited in the NCBI GEO database; Accession number: in process. Data were normalized according to the quantiles method and supervised hierarchical clustering was performed on 435 selected transcripts that were significantly modulated after treatment in at least 3 out of 6 patients. Modulation threshold ratios were set up at.6 and 1.5 for down and upregulated transcripts respectively. One patient presenting too divergent modulation profiles from the others was excluded from the clustering alysis. Gene sigtures were alyzed to generate functiol networks using the PredictSearch TM software (Prediguard), a datamining bioinformatic solution dedicated to identify relevant correlations between genes and concepts, was used to generate functiol networks. This tool is daily updated with the whole NCBI Pubmed database and seeks for relevant correlations between gene-gene or gene-concept within abstracts cocitations. Correlations are also retrieved from the crosscomparison to the whole set (>18) of transcriptiol sigtures deposited in NCBI GEO database and extracted with the DBF-MCL algorithm using TranscriptomeBrowser tool. Furthermore PredictSearchTM allows the annotation of modulated genes according to KEGG and Biocarta pathways as well as to GO ontology 3. 4

6 For unsupervised alyses, potential molecular sigtures were extracted using unsupervised Independent Component Alysis (ICA). Those sigtures were added to the Gene Set Enrichment Alysis (GSEA) sigture database and tested for their significance on our microarray data using GSEA software. GSEA leading edges of statistically significant molecular sigtures (FDR q.value<.5) were annotated for their GO terms and KEGG pathways enrichment. Sigtures with enrichment for GO terms related to inflammation, immune response and autoimmune pathologies were selected. A Khi2 test was used to determine whether these selected sigtures were preferentially up- or down-regulated in IL2-treated samples as compared to the overall distribution of up- or down-regulated sigtures. References 1. Maury S, Lemoine FM, Hicheri Y, et al. CD4+CD25+ regulatory T cell depletion improves the graft-versus-tumor effect of donor lymphocytes after allogeneic hematopoietic stem cell transplantation. Sci Transl Med;2:41ra Guillot-Delost M, Cherai M, Hamel Y, et al. Clinical-grade preparation of human tural regulatory T-cells encoding the thymidine kise suicide gene as a safety gene. J Gene Med 28;1: Lopez F, Textoris J, Bergon A, et al. TranscriptomeBrowser: a powerful and flexible toolbox to explore productively the transcriptiol landscape of the Gene Expression Omnibus database. PLoS One 28;3:e41. 5

7 Supplementary Table 1 Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient 9 Patient 1 Baseline,22 3,7,75 4,4,17 3,2 4 3,3 4,2 6,98 4,4 1,64 1,8 2,78 3,4 3,8 C1,24 5,95 6,8 6,4 15 3,7 6,8 7,9 6,2 1, ,8 8 C2,4 9,3 1,3 11,5, , , ,37 24 C3,8 9,1,68 27, ,26 3,2,2 11 7,5 17 9,19 29 C4 6 1,5 12,17 7,1 14,47 8, Post IL ,8,91 3 7,8,23 6,8 5,86 3,8 6 2,94 8,61 5,5 globulin () serum level (g/l) and % of /CD4+T cells are indicated for each patient and for each time of follow-up 6

8 FoxP3 SS CD3 CD127 Supplementary figures Supplementary Figure 1 in CD3+CD4+ cells CD25 FS CD4 CD25 Supplementary Figure 1. Phenotypic characterization of CD4 + by Flow cytometry. Representative lymphocyte gate for identification of the CD3 + CD4 + T subset is shown. Within the CD3 + CD4 + T cells, s were identified as CD25 high CD127 - FoxP3 + cells. Supplementary Figure HTdR (cpm) Responder 1/1 1/2 1/4 1/8 Supressor/Responder ratio Supplementary Figure 2. Suppressive activity of cells in HCV induced vasculitis patients under IL-2 treatment FACS purified were assayed for their capacity to suppress autologous effector T cells proliferation at different ratios (1/1 to 1/8) under allogeneic stimulation. Results are expressed in cpm. The experiment shown is representative of 4. 7

9 SS CD27 SS CD3 FoxP3 Supplementary Figure 3 in CD3+CD8+ cells FS CD8 CD25 Supplementary Figure 3. Phenotypic characterization of CD8 + by Flow cytometry. Representative lymphocyte gates for the identification of CD3 + CD8 + are shown. Within CD3 + CD8 + T cells, s were identified as CD25 + FoxP3 + cells. Supplementary Figure 4 In CD19+B cells FS CD19 IgD Supplementary Figure 4. CD19 + B cells subsets characterization by flow cytometry B cell subset populations were defined as ïve (IgD + CD27 - ), memory (IgD - CD27 + ), margil zone(igd + CD27 + ). 8

10 Supplementary Figure 5 BEFORE IL-2 AFTER IL-2 CCL CCL3L 3 1 CCL3L IER3 CXCR 7 OLR1 PDE4 8 PTGS2 IL1B IL1A CCL2 IL6 CLECL 1 CD79A BLK CCL4L2 EBF1 CCL4L1 BAFF R 4-1BBL PLAU R NLRP3 RIPK2 NAMPT- PBEF1 TNFRSF21-DR6 ETS2 MAPK3K8- GOS2 CD83 Supplementary Figure 5: Low dose IL-2 induces a global decrease of inflammation revealed by transcriptome alyses Hierarchical clustering alysis of PBMCs of patients with HCV induced vasculitis before and after IL-2 treatment 9

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