- Email: [email protected]
Mycophenolate Mofetil Treatment of Systemic Sclerosis Reduces Myeloid Cell Numbers and Attenuates the Inflammatory Gene Signature in Skin
Accepted Manuscript Mycophenolate mofetil treatment of systemic sclerosis reduces myeloid cell numbers and attenuates the inflammatory gene signature in skin Monique Hinchcliff, MD MS, Diana M. Toledo, MS, Jaclyn N. Taroni, PhD, Tammara A. Wood, MA, Jennifer M. Franks, BS, Michael S. Ball, BS, Aileen Hoffmann, MS, Sapna M. Amin, MD, Ainah U. Tan, MD, Kevin Tom, Yolanda Nesbeth, PhD, Jungwha Lee, PhD, Madeleine Ma, MS, Kathleen Aren, MPH, Mary A. Carns, MS, Patricia A. Pioli, PhD, Michael L. Whitfield, PhD PII:
S0022-202X(18)30023-X
DOI:
10.1016/j.jid.2018.01.006
Reference:
JID 1254
To appear in:
The Journal of Investigative Dermatology
Received Date: 16 September 2016 Revised Date:
8 December 2017
Accepted Date: 4 January 2018
Please cite this article as: Hinchcliff M, Toledo DM, Taroni JN, Wood TA, Franks JM, Ball MS, Hoffmann A, Amin SM, Tan AU, Tom K, Nesbeth Y, Lee J, Ma M, Aren K, Carns MA, Pioli PA, Whitfield ML, Mycophenolate mofetil treatment of systemic sclerosis reduces myeloid cell numbers and attenuates the inflammatory gene signature in skin, The Journal of Investigative Dermatology (2018), doi: 10.1016/ j.jid.2018.01.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Mycophenolate mofetil treatment of systemic sclerosis reduces myeloid cell numbers and attenuates the inflammatory gene signature in skin
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Monique Hinchcliff MD MS1, 2,#, Diana M. Toledo MS3,#, Jaclyn N. Taroni PhD3, Tammara A. Wood MA3, Jennifer M. Franks BS3, Michael S. Ball BS7, Aileen Hoffmann MS1, Sapna M. Amin MD4, Ainah U. Tan MD4, Kevin Tom1, Yolanda Nesbeth PhD6, Jungwha Lee PhD2, 5, Madeleine Ma MS2, 5, Kathleen Aren MPH1, Mary A. Carns MS1, Patricia A. Pioli PhD7,
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Michael L. Whitfield PhD3
Northwestern University Feinberg School of Medicine, 1Department of Medicine, Division of Rheumatology, 240 E. Huron Street, Suite M-300, 2Institute of Public Health and Medicine, 633 N. St. Clair, 18th Floor 4Department of Dermatology, 676 N. St. Clair Street Suite 1600, Department of Preventive Medicine, 680 N. Lake Shore Drive, Suite 1400, Chicago, IL 60611,
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USA. Geisel School of Medicine at Dartmouth, 3Department of Molecular and Systems Biology, Hanover, NH 03755, 7Microbiology and Immunology, Lebanon, NH 03756, 6Celdara Medical
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LLC, Lebanon, NH 03766, USA.
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Short title: MMF reduces myeloid cell recruitment #Authors contributed equally Corresponding Authors: Monique Hinchcliff, MD MS Northwestern University Feinberg School of Medicine Division of Rheumatology 240 E Huron Street, Suite M300 Chicago, IL USA 60611 [email protected] Phone: 312-503-4844, fax: 312-503-0994
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Abbreviations used:
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ORCID Identifiers: Monique Hinchcliff: orcid.org/0000-0002-8652-9890 Diana M. Toledo: orcid.org/0000-0002-7501-8286 Jaclyn N. Taroni: orcid.org/0000-0003-4734-4508 Tammara A Wood: orcid.org/0000-0002-4370-1398 Jennifer M. Franks: orcid.org/0000-0003-2400-5431 Michael S. Ball: orcid.org/0000-0001-7322-7642 Aileen Hoffmann: orcid.org/ 0000-0002-2337-4190 Sapna M. Amin: orcid.org/0000-0002-4362-5727 Ainah Uy Tan: orcid.org/ 0000-0002-8202-7164 Kevin Tom: orcid.org/0000-0003-2098-7714 Yolanda Nesbeth: orcid.org/0000-0003-3347-8871 Jungwha Lee: orcid.org/0000-0002-0806-0847 Madeleine Ma: orcid.org/0000-0002-5823-5713 Kathleen Aren: orcid.org/0000-0003-4770-2643 Mary Carns: orcid.org/0000-0002-5063-156X Patricia A. Pioli: orcid.org/0000-0001-6896-7259 Michael L. Whitfield: orcid.org/0000-0002-0862-6003
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Michael L. Whitfield, PhD Department of Genetics Geisel School of Medicine at Dartmouth 7400 Remsen Hanover, NH 03755 [email protected] Phone: 603-650-1109, Fax: 603-650-1188
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SSc=systemic sclerosis mRSS=modified Rodnan skin score MMF=mycophenolate mofetil CCL2=C-C motif chemokine ligand 2 lc=limited cutaneous dc=diffuse cutaneous DC=dendritic cell mDC=myeloid dendritic cell FDR=false discovery rate CCR1/5=C-C chemokine receptor type 1/5 THBS1/2=thrombospondin type 1/2 COL8A1=collagen type VIII alpha 1 COL5A2=collagen type V alpha 2 FBN1=fibrillin type 1 FADS1=fatty acid desaturase type 1 FA2H=fatty acid 2-hydroxylase FABP7=fatty acid binding protein 7 GO=gene ontology
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QuSAGE= Quantitative Set Analysis for Gene Expression TLR=toll-like receptor NFKB2=nuclear factor kappa B subunit 2 IRF7=interferon regulatory factor 7 STAT1=signal transducer and activator of transcription 1 ssGSEA=single sample Gene Set Enrichment Analysis NES=normalized enrichment scores qRT-PCR=quantitative real time polymerase chain reaction
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Key Words: Biomarkers, genomics, systemic sclerosis, scleroderma, dendritic cells
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Twitter handle: @WhitfieldLab
Funding: This work was supported by the National Institutes of Health NICHD K12 HD055884
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(MH), NIAMS K23 AR059763 (MH), NIAMS R21 AR068035 (MH, MLW), NIAMS P30 AR061920 (MH, MLW), NIAMS R56 AR063985 (PAP), NIAMS R44 AR061920 (MH, YN, MLW), NIGMS T32 GM008704 (JNT), a Cancer Center Support Grant NCI CA060553 and by research awards from the Scleroderma Research Foundation (MH, MLW) and Scleroderma
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Foundation (PAP). JNT received support from the John H. Copenhaver, Jr. and William H. Thomas, MD 1952 Junior Fellowship from Dartmouth Graduate Studies. MSB received support from The John Osborn Polak Endowment. The Northwestern University Mouse Histology and
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Phenotyping Laboratory also provided project support. MH and MLW had full access to all the
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data in the study and had final responsibility for the decision to submit for publication.
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ABSTRACT Fewer than half of patients with systemic sclerosis (SSc) demonstrate modified Rodnan skin
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score (mRSS) improvement during mycophenolate mofetil (MMF) treatment. To understand the molecular basis for this observation, we extended our prior studies and characterized molecular and cellular changes in skin biopsies from subjects with SSc treated with MMF. Eleven subjects
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completed ≥24 months of MMF therapy. Two distinct skin gene expression trajectories were observed across six of these subjects. Three of the six subjects showed attenuation of the
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inflammatory signature by 24 months, paralleling reductions in CCL2 mRNA expression in skin and reduced numbers of macrophages and myeloid dendritic cells in skin biopsies. MMF cessation at 24 months resulted in an increased inflammatory score, increased CCL2 mRNA and protein levels, mRSS rebound, and increased numbers of skin myeloid cells in these subjects. In contrast, three other subjects remained on MMF >24 months and showed a persistent decrease in
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inflammatory score, decreasing or stable mRSS, CCL2 mRNA reductions, sera CCL2 protein levels trending downward, reduction in monocyte migration, and no increase in myeloid cell numbers. These data summarize molecular changes during MMF therapy that suggest reduction
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CCL2.
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of innate immune cell numbers, possibly by attenuating expression of chemokines including
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INTRODUCTION Systemic sclerosis (SSc; scleroderma) is a heterogeneous, multi-organ disease whose
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clinical hallmark is skin fibrosis (Hinchcliff and Varga, 2011; Taroni et al., 2015). Two clinical SSc subtypes, limited cutaneous (lc) and diffuse cutaneous (dc) are defined based on the modified Rodnan skin score (mRSS)(LeRoy et al., 1988). Immune modulators, including
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mycophenolate mofetil (MMF; CellCept®, Roche), are prescribed for active SSc lung and skin disease (Walker and Pope, 2012), yet substantial response heterogeneity exists (Herrick et al.,
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2010; Panopoulos et al., 2013).
Gene expression in SSc-derived skin biopsies provides insight into SSc clinical and treatment response heterogeneity. We previously published genome-wide gene expression analyses of SSc skin biopsies and identified four ‘intrinsic’ molecular subsets that were
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reproducible (inflammatory, fibroproliferative, limited and normal-like) (Milano et al., 2008; Pendergrass et al., 2012). We showed that a high baseline inflammatory gene expression signature in the skin of patients with SSc was associated with mRSS improvement during MMF
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therapy (Hinchcliff et al., 2013).
Studies support a role for innate immune activation in SSc pathogenesis (Chia and Lu,
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2015; Christmann et al., 2011; Christmann et al., 2014; Higashi-Kuwata et al., 2010; Johnson et al., 2015). Alternatively activated macrophages have been identified in SSc skin (HigashiKuwata et al., 2010), consistent with elevated levels of IL-4 and IL-13 in SSc sera (Hasegawa et al., 1997, Riccieri et al., 2003). Our recent work shows elevated markers of alternatively activated macrophage in SSc skin across multiple independent gene expression datasets (Mahoney et al., 2015, Taroni et al. 2017), while enriched macrophage and dendritic cell (DC)
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gene expression signatures have been identified in SSc skin in an independent cohort (Assassi et al., 2015). Consistent with these results, genes associated with myeloid cell recruitment and
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differentiation are over-expressed in SSc compared with healthy subjects (Mahoney et al., 2015). The myeloid cell chemo-attractant CCL2 is highly expressed in the skin of SSc patients classified within the inflammatory intrinsic subset (Greenblatt et al., 2012; Milano et al., 2008),
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and has been shown to be required for the inflammatory-fibrotic phenotype of the sclGVHD mouse model of SSc (Greenblatt et al., 2012). Additionally, circulating CCL2 levels correlate
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with increased interstitial lung disease in SSc patients (Assassi et al., 2013), and predict a faster decline in forced vital capacity (FVC%) and decreased survival (Wu et al., 2017). These findings implicate altered innate immune cell activation and/or recruitment in SSc pathogenesis. Herein, we characterize the molecular and cellular changes in skin and sera during MMF
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therapy. We perform gene expression and immunohistochemical analyses of skin biopsies obtained over 36 months for SSc subjects who were prescribed MMF. We analyze changes in the inflammatory gene expression signature, in CCL2 mRNA and sera CCL2 levels, and in skin
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monocyte recruitment and immune cell numbers over time in these subjects. This study provides important insight into the mechanism by which innate immune cell populations in skin are
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influenced during MMF treatment in patients with SSc.
RESULTS
Study cohort
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Clinical characteristics are shown for 68 subjects with SSc (75% dcSSc), three subjects without SSc (one with morphea and two with connective tissue disease overlap syndromes) and 22 healthy controls (Table 1, Figure 1a, Table S1). The median (range) SSc disease duration
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between first Raynaud symptom and the baseline visit was 23 (0-237) months. Twenty-two subjects (32%) had anti-topoisomerase I/Scl-70, and 19 (28%) had anti-RNA polymerase III
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serum autoantibodies.
Thirty-five SSc subjects who were enrolled in the Northwestern Scleroderma Patient
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Registry, and were taking, or were intolerant to, MMF, underwent skin biopsies once at their baseline visit (91 arrays) (Figure 1a). Thirty-three MMF-naïve subjects who were prescribed MMF consented to longitudinal skin biopsies (Figure 1a, Supplemental Figure S1). Of these 33 subjects, five were lost to follow-up, and six had baseline mRSS< nine. Twenty-two subjects with baseline mRSS ≥ nine and mRSS assessments at 12 months were included in the MMF
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improvement analysis. Improvement was defined as ≥25% mRSS reduction (non-improvement <25% mRSS reduction) between baseline and 12 months (Khanna et al., 2006). Ten subjects fulfilled (Table S8), and twelve subjects did not fulfill (Table S9), the clinical improvement
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criterion. Study completers (11 out of 33, including one subject with baseline mRSS< nine) were
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defined as subjects who were prescribed MMF at baseline and underwent longitudinal skin biopsies at five time points (baseline, 6, 12, 24, 36 months). There were no statistically significant differences in sex, race, serum autoantibodies,
baseline mRSS, lcSSc vs. dcSSc, and SSc disease duration between improvers and nonimprovers. SSc intrinsic subset recapitulation
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Intrinsic subset was determined for baseline biopsies from 71 subjects and 22 healthy controls (163 total microarrays) (Milano et al., 2008). Intrinsic gene analysis was performed using 2500 probes with 1956 unique genes with a false discovery rate (FDR) ≤ 0.1422% (Figure
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1b, Supplemental Figure S2). Four SSc intrinsic subsets (normal-like (green), limited (yellow), inflammatory (purple), and fibroproliferative (red)) were recapitulated using average linkage hierarchical clustering. We observed a subset of patients that show a gradient of both
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inflammatory and fibroprolifereative signatures (Mahoney et al., 2015). The fibroproliferative subgroup continues to be defined by a strong proliferative signature in addition to an
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inflammatory signature. (Milano et al., 2008; Pendergrass et al., 2012; Hinchcliff et al., 2013). G:Profiler was used to identify pathways and biological processes significantly enriched in the different subsets (Reimand et al., 2011) (Figure 1b; Table S2, g:Profiler output; Table S13, full gene list; Table S14, intrinsic subset gene lists; Table S15, gene expression).
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Improvers tended to express an inflammatory or normal-like intrinsic gene expression signature at baseline (Table S8). Three subjects who were inflammatory-fibroproliferative at baseline also showed improvement. This suggests that subjects with an inflammatory signature
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in skin are more likely to improve while on MMF, and the majority of subjects who respond to
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MMF have an inflammatory signature. Skin score improvement in subjects classified as normallike may represent collagen degradation due to natural skin repair processes rather than a treatment response.
Immune-related gene expression alterations in patients that improve during MMF To understand molecular changes associated with mRSS improvement, we identified genes whose expression changed in 22 subjects prescribed MMF. We identified 651
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differentially expressed genes in ten improvers between baseline and the 12-month time point (FDR ≤ 5%; base vs. post Comparative Marker Selection; Figure 1c). Genes whose expression decreased during improvement were functionally enriched for the Gene Ontology (GO) terms
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innate immune response, leukocyte differentiation, apoptotic process, and angiogenesis (Table S3, Table S4). Pathway analysis with Quantitative Set Analysis for Gene Expression (QuSAGE) also demonstrated a decrease in inflammation-related pathways during improvement (Table S5).
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No changes in gene expression associated with immune processes were observed in 12 nonimprovers after 12 months of MMF treatment (FDR ≤ 5%; base vs. post Comparative Marker
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Selection; Figure 1d, Table S6, Table S7).
Longitudinal analysis shows loss of the inflammatory gene expression signature during MMF treatment
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Gene expression time course analyses were performed using longitudinal biopsies and mRSS for 11 completers (Figure 2a). Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to calculate the inflammatory normalized enrichment scores (NES; summarizes the
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inflammatory gene signature) that are displayed as a heatmap (Figure 2a) and line plots (Figure 2b-c) for each biopsy to examine longitudinal changes during treatment. We hierarchically
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clustered the inflammatory NES time courses for all 11 completers to identify groups of subjects with similar longitudinal trajectories. Six subjects with high inflammatory NES at baseline lost their inflammatory signature by
24 months of MMF treatment. In three subjects, the inflammatory NES rebounded after MMF discontinuation as indicated by the increase in NES between 24 months and 36 months (Figure 2b, termed Treatment Discontinued). Upon MMF cessation at 24 months, mRSS also increased
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in two of these three subjects concomitant with the inflammatory NES increase (Figure 2d-f). The other three subjects, who continued MMF treatment beyond 24 months, showed persistent decrease in their inflammatory NES scores at 36 months (Figure 2c, termed Treatment
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Continued) and demonstrated stable or decreasing mRSS (Figure 2g-i). Inflammatory NES scores and mRSS from the other five completers are shown in Supplemental Figure S3. In addition, the microarray gene expression of several alternatively and classically activated
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macrophage markers (including CCL2) for all completers are shown in Supplemental Figures S5
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and S6.
We calculated the correlation between the inflammatory NES scores for baseline biopsies and clinical covariates (Supplemental Figure S4).
Patients with higher mRSS had higher
inflammatory NES scores at baseline (r2=0.1784, p=0.0002).
Shorter SSc disease duration
correlated with higher baseline inflammatory NES score (r2=0.1817, p=0.0002). Additionally, a
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significantly lower inflammatory NES score was observed in forearm biopsies from clinically unaffected (mRSS=0) compared to clinically affected skin (mRSS=1 or 2; p=0.0241 and p=0.0019, respectively; Table S12). There was no significant difference in inflammatory NES
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score in subjects with forearm mRSS of 1, 2, or 3.
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CCL2 mRNA and serum protein levels change during MMF therapy To determine how MMF therapy modulates CCL2 mRNA levels in skin, qRT-PCR was
performed on RNA extracted from patients in the Treatment Discontinued and Treatment Continued groups at each time point. CCL2 mRNA levels parallel the inflammatory NES signature (Figure 3a-b). CCL2 mRNA levels decline during MMF treatment for all subjects and
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significantly increase at 36 months in subjects who discontinue MMF (p=0.005, Figure 3a), but remain low in subjects continuing MMF therapy (Figure 3b).
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CCL2 serum protein levels in SSc patients at baseline and during MMF treatment (at 3 months and >16 months of MMF) were compared to levels in healthy control subjects matched for age and sex. SSc patients had significantly higher CCL2 levels at each time point compared
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to controls (Figure 3c; p=0.004, p<0.0001, p<0.0001, respectively). In aggregate, serum CCL2 decreased during MMF treatment, although not significantly. For instance, CCL2 levels
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decreased from 988.2 pg/ml (baseline) to 617.5 pg/ml (24-month during MMF) in subject 17. Notably, this CCL2 decline was coupled with significant mRSS decrease (baseline mRSS=35 vs. 24-month=19, Figure 2h).
Monocyte recruitment toward SSc patient sera is significantly reduced over the course of
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MMF therapy
Monocyte migration towards patient sera was measured at baseline and during MMF treatment using a fluorescence-based Chemotaxis Cell Migration Assay (Figure 3d). There is
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significantly more monocyte chemotaxis toward SSc patient sera regardless of MMF treatment relative to healthy controls (p<0.05). Monocyte motility was highest toward SSc baseline (MMF-
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naïve) sera, with a significant decrease in monocyte migration observed between sera at baseline and after >16 months of continuous MMF treatment (p=0.012).
Consistent with CCL2
expression data, these results demonstrate that SSc sera is more chemotactic for monocytes compared with healthy control sera, and that prolonged MMF treatment inhibits the myeloid chemo-attracting capability of SSc sera. Cell type-specific gene expression signatures change during MMF therapy
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We then investigated changes in inflammatory cell populations in associated skin biopsies. First, we used ssGSEA to measure the relative expression of cell type-specific gene sets and calculated cell type-specific NES. Similar NES have been used to infer relative cell type
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proportions in other tissues (Bolen et al., 2011; Shen-Orr and Gaujoux, 2013). We calculated the correlation between fifteen different cell type-specific gene set NES scores (including a wide range of cell types and differentiation states) and the inflammatory NES in order to determine
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which cell types contributed most significantly to the inflammatory signature (Table S10, Table S11). A high correlation was observed between subjects’ inflammatory NES and dendritic cell
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(DC, r=0.83), T cell (r=0.77), monocyte (r=0.70), and macrophage (r=0.60) NES (Figure 4a). Interestingly, three out of three Treatment Discontinued subjects demonstrated a rebound (Figure 4b), while Treatment Continued subjects demonstrated a stable or persistent decrease (Figure 4c; Supplemental Figure S7; Supplemental Figure S8), in DC, T cell, and macrophage cell type-
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specific NES. These data suggest that DCs, T cells, and macrophages contribute to the inflammatory gene expression signature changes observed during MMF therapy.
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Immunohistochemistry staining shows changes in myeloid cell numbers To validate cell type-specific NES changes using immunohistochemistry, skin biopsies
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were stained for CD163, a marker of alternatively activated macrophages, CD1c, a marker of myeloid dendritic cells (mDCs), and CD3, a T cell marker, and positively stained cells were quantified by two independent observers (interclass correlation coefficients were =0.99 (95% CI 0.98-1.00)) or using ImageJ software. In general, Treatment Discontinued subjects demonstrated significant increases (Figure 5a, e) in skin macrophage and mDC counts between 24 and 36 months. In comparison, Treatment Continued subjects showed stable counts (Figure 5b, f). For instance, macrophage staining for subject 17 (MMF Treatment Continued) was abundant at
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baseline (Figure 5c) and decreased substantially by 36 months (Figure 5d) coinciding with mRSS improvement (baseline mRSS=35 vs. 36-month=15). In contrast, mDC staining for subject 08 (MMF Treatment Discontinued) was abundant at baseline (Figure 5g), decreased by 24 months
baseline mRSS=12, 24-month=11, 36-month=12).
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during MMF (Figure 5h), and following MMF cessation, rebounded at 36 months (Figure 5i;
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Overall, macrophage and mDC quantification correlated with inflammatory NES, suggesting that these cell types, likely including substantial representation from pro-fibrotic,
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alternatively activated macrophages, may be key drivers of skin fibrosis in SSc (Figure 5). Notably, MMF treatment did not affect B cell NES or B cell numbers. Immunohistochemistry staining showed stable T cell numbers, while T cell NES scores decreased during MMF therapy, suggesting that treatment may alter the T cell activation state. Thus, MMF modulates myeloid cell mobilization and activation in SSc skin and may exert effects on T cells through its
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DISCUSSION
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interaction with antigen presenting cells including macrophages and DCs.
Two years of MMF versus one year of oral cyclophosphamide and placebo for treatment
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of interstitial lung disease in patients with SSc enrolled in the Scleroderma Lung Study II result in pulmonary function and mRSS improvement in both groups (Tashkin et al., 2016). Due to a more favorable safety profile, MMF has emerged as the new gold standard oral therapy for SSc lung and skin fibrosis (Tashkin et al., 2016), but not all patients demonstrate improvement and optimal duration of MMF therapy is unknown. Our previous study results support analysis of skin gene expression in patients with SSc to gain insights into SSc skin disease pathogenesis and treatment response heterogeneity (Hinchcliff et al., 2013).
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Consistent with prior results, we found MMF therapy may be most beneficial in patients classified in the inflammatory intrinsic subset, though not all inflammatory subjects improve while on MMF therapy. Importantly, only one out of ten subjects who improved during MMF
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therapy was classified as fibroproliferative and this individual still had a positive inflammatory NES score. This suggests that having a prominent inflammatory signature is a major quality of
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patients who respond to MMF therapy on the molecular level.
Importantly, our results suggest a role for MMF as a regulator of CCL2 gene expression.
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CCL2 has been implicated in the pathogenesis of many autoimmune diseases, including SSc and systemic lupus erythematosus (SLE). Intriguingly, a recent study showed significant reductions in CCL2 mRNA levels in peripheral blood mononuclear cells of SLE patients that received MMF treatment compared with control subjects (Dominguez-Gutierrez et al., 2014). We report that CCL2 mRNA expression is reduced in the skin of SSc patients treated with MMF, and CCL2
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transcript levels in skin may be an indicator of disease progression and response to therapy. Because of the important role of this chemokine in SSc disease initiation and progression
SSc treatment.
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(Greenblatt et al., 2012; Wu et al., 2017), MMF is likely to continue to play an important role in
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To gain insights into the cellular populations that underlie changes in skin inflammatory gene expression during MMF treatment, we conducted careful computational, functional, and immunohistochemical analyses. We found the most consistent correlations between cells of the innate immune system (monocytes, macrophages, DCs) and T cells. We saw negative associations between inflammatory NES and gene signatures for both naïve and memory B cells, as well as for resting CD4, CD8 and memory T cells. Given our prior results suggesting that the dermal macrophage/DC axis may play a pivotal role in SSc skin disease (Mahoney et al., 2015,
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Taroni et al., 2017), we stained biopsies for macrophages and mDCs and found a positive association with the inflammatory signature. We also found that CCL2 levels were significantly higher in SSc sera compared with healthy controls, and circulating CCL2 trends downward with
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prolonged MMF treatment. Although MMF attenuation of sera CCL2 expression failed to reach statistical significance, it is important to note that limited clinical samples from MMF-treated patients were available retrospectively, and thus it is likely that with an increased sample size,
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significance would be achieved. Alternatively, it is also possible that other chemokines, in addition to CCL2, that mediate myeloid migration and are being regulated by MMF.
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Nonetheless, monocyte migration toward SSc patient sera is highest at baseline and is significantly reduced after MMF treatment.
This suggests that MMF therapy inhibits
monocyte/macrophage migration systemically, potentially due to modulation of CCL2. Other gene expression studies implicate myeloid cells as potential key mediators of
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fibrosis in SSc (Christmann et al., 2014; Mahoney et al., 2015). Notably, antibody blockade of CCL2, which mediates recruitment and activation of monocytes, macrophages, and DCs, is protective against immune-fibrotic disease development and progression in the sclGVHD mouse
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model that resembles the inflammatory subset of patients with SSc (Greenblatt et al., 2012;
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Sargent et al., 2016). We now show that mRSS reduction or stabilization during MMF treatment is associated with decreased dermal expression of CCL2 mRNA and reduced sera CCL2 levels, findings that support the hypothesis that myeloid cell recruitment plays a role in SSc skin disease pathogenesis. Consistent with this hypothesis, our data demonstrate reduced monocyte migration toward patient sera following MMF treatment. In this regard, MMF treatment may also lead to attenuated production and release of myeloid-derived pro-fibrotic mediators that include CCL2.
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Study strengths include prospective study design, a clinically well-characterized SSc cohort including mRSS performed longitudinally by one investigator at the time of skin biopsies, and the collection of longitudinal biopsies over 36 months. Study limitations include open-label
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trial design, lack of a matched untreated SSc control population, higher proportion of female subjects in cases compared to the control group, younger subjects in the control group, lack of a validated method to define active skin disease, and small sample sizes of the cohort that
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completed biopsies at all time points. The study continues and additional interim results will be
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published.
The study findings support the role of innate immunity, specifically alternatively activated macrophages and DCs, in SSc dermal pathogenesis. Rebound in the inflammatory skin gene expression signature with increased skin myeloid cells with MMF cessation at 24 months
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suggests that led to a suggests optimal MMF therapy duration exceeds 24 months. MATERIALS & METHODS Patients
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The Northwestern University Institutional Review Board approved the study and participants provided written informed consent in accordance with the Declaration of Helsinki.
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Subjects fulfilled American College of Rheumatology SSc (1980) or three out of five CREST (calcinosis, Raynaud, esophageal dysmotility, sclerodactyly, telangiectasias) criteria. One physician performed mRSS (LeRoy et al., 1988). Serum autoantibodies were measured by indirect immunofluorescence at Specialty Laboratories, Valencia, CA. Subjects underwent four mm side-by-side skin biopsies between November 2008 and June 2014 as described (Hinchcliff et al., 2013). One biopsy pair (arm and flank) was placed in
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RNAlater (Applied Biosystems, Ambion®, Carlsbad, CA) and used for Agilent DNA microarray analysis; the other biopsy pair was placed in formalin for histology.
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93 individuals were enrolled and 359 total biopsies were collected including 39 biopsies from healthy controls. Patients with active skin disease in the opinion of the treating physician
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Skin Histology and Immunohistochemistry
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were prescribed two g/day MMF in divided doses (Figure 1a).
5-µm sections of formalin-fixed/paraffin-embedded dermal biopsies were obtained. Immunohistochemistry staining for macrophages (CD163, EDHu-1 clone, Bio-Rad MCA1853T, Hercules, CA, and MRQ-26 Cell Marque, Sigma-Aldrich, St. Louis, MO) and mDCs (CD1c,
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LSBio 10059, Seattle, WA) was performed in duplicate using the Labeled StreptAvidin Biotin Method and DAB substrate. Endogenous peroxidase activity was blocked using 3% H2O2 and labeled streptavidin was HRP-conjugated. For CD1c staining, a board-certified pathologist with
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subspecialty dermatopathology training and an independent dermatology reviewer who were blinded to clinical data quantified positively stained cells using an Olympus BX50 microscope.
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The “hot spot” method was utilized whereby the greatest staining area was determined at scanning magnification and positively stained cells were quantified in that area at 20x or 40x and in five consecutive fields (corresponds to one-two mm2). Interclass correlation coefficients were generated to assess the correlation between independent scores (one denotes perfect correlation). For CD163 staining, ImageJ Fiji software was used to quantify positively stained cells (Schneider et al., 2012, Schindelin et al., 2012).
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Statistical analyses of clinical covariates Continuous variables were summarized as mean with standard deviation. Categorical
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variables were summarized as frequency and proportion. Statistical significance was assessed with Fisher’s Exact or Wilcoxon-Mann-Whitney tests as appropriate. A P-value <0.05 was
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considered significant. All analyses were carried out using R statistical software (version 3).
Supplemental Methods
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DNA microarray analyses, differential gene expression, intrinsic subset assignment, cell type enrichment, qRT-PCR, ELISA, and the monocyte migration assay methods are available in
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supplementary materials.
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CONFLICT OF INTEREST Dr. Michael Whitfield is a scientific founder of Celdara LLC, which is developing gene
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expression biomarkers in SSc. Dr. Yolanda Nesbeth is an employee at Celdara Medical LLC. Dr. Monique Hinchcliff, Dr. Michael Whitfield, and Celdara Medical have received NIH-Small Business Innovative Research Grant Awards. Dr. Monique Hinchcliff and Tammara A. Wood
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have been paid as consultants, and Dr. Michael Whitfield has received distributions from Celdara
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Medical LLC.
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ACKNOWLEDGEMENTS The authors thank the members of the Robert H. Lurie Comprehensive Cancer Center Pathology Core Facility and the Mouse Histology and Phenotyping Laboratory for their
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Whitfield. For clinical inquiries please contact Dr. Hinchcliff.
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assistance with immunohistochemistry. For gene expression inquiries please contact Dr.
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Assassi S, Swindell WR, Wu M, Tan FD, Khanna D, Furst DE, et al. (2015) Dissecting the heterogeneity of skin gene expression patterns in systemic sclerosis. Arthritis & rheumatology (Hoboken, NJ) 67:3016-26. Assassi S, Wu M, Tan FK, Chang J, Graham TA, Furst DE, et al. (2013) Skin gene expression correlates of severity of interstitial lung disease in systemic sclerosis. Arthritis Rheum 65:2917-27.
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Bolen CR, Uduman M, Kleinstein SH (2011) Cell subset prediction for blood genomic studies. BMC Bioinformatics 12:258.
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Chia JJ, Lu TT (2015) Update on macrophages and innate immunity in scleroderma. Curr Opin Rheumatol 27:530-6. Christmann RB, Hayes E, Pendergrass S, Padilla C, Farina G, Affandi AJ, et al. (2011) Interferon and alternative activation of monocyte/macrophages in systemic sclerosis-associated pulmonary arterial hypertension. Arthritis Rheum 63:1718-28.
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Christmann RB, Sampaio-Barros P, Stifano G, Borges CL, de Carvalho CR, Kairalla R, et al. (2014) Association of Interferon- and transforming growth factor beta-regulated genes and macrophage activation with systemic sclerosis-related progressive lung fibrosis. Arthritis & rheumatology (Hoboken, NJ) 66:714-25.
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Dominguez-Gutierrez PR, Ceribelli A, Satoh M, Sobel ES, Reeves WH, and Chan EKL (2014) Reduced levels of CCL2 and CXCL10 in systemic lupus erythematosus patients under treatment with prednisone, mycophenolate mofetil, or hydroxychloroquine, except in a high STAT1 subset. Arthritis Res Ther 16(1): R23. PMCID: PMC3978465.
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Greenblatt MB, Sargent JL, Farina G, Tsang K, Lafyatis R, Glimcher LH, et al. (2012) Interspecies comparison of human and murine scleroderma reveals IL-13 and CCL2 as disease subset-specific targets. Am J Pathol 180:1080-94. Hasegawa M, et al. (1997) Elevated Serum Levels of Interleukin 4 (IL-4), IL-10, and IL-13 in Patients with Systemic Sclerosis. J Rheumatol 24 (2), 328-332. Herrick AL, Lunt M, Whidby N, Ennis H, Silman A, McHugh N, et al. (2010) Observational study of treatment outcome in early diffuse cutaneous systemic sclerosis. J Rheumatol 37:116-24. Higashi-Kuwata N, Jinnin M, Makino T, Fukushima S, Inoue Y, Muchemwa FC, et al. (2010) Characterization of monocyte/macrophage subsets in the skin and peripheral blood derived from patients with systemic sclerosis. Arthritis Res Ther 12:R128.
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Hinchcliff M, Huang CC, Wood TA, Matthew Mahoney J, Martyanov V, Bhattacharyya S, et al. (2013) Molecular signatures in skin associated with clinical improvement during mycophenolate treatment in systemic sclerosis. J Invest Dermatol 133:1979-89.
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Hinchcliff M, Varga J (2011) Managing Systemic Sclerosis and its Complications. The Journal of Musculoskeletal Medicine 28:380.
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Johnson ME, Pioli PA, Whitfield ML (2015) Gene expression profiling offers insights into the role of innate immune signaling in SSc. Semin Immunopathol 37:501-9.
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Joshi-Tope G, Gillespie M, Vastrik I, D'Eustachio P, Schmidt E, de Bono B, et al. (2005) Reactome: a knowledgebase of biological pathways. Nucleic Acids Res 33:D428-32. Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28:27-30. Khanna D, Furst DE, Hays RD, Park GS, Wong WK, Seibold JR, et al. (2006) Minimally important difference in diffuse systemic sclerosis: results from the D-penicillamine study. Ann Rheum Dis 65:13259.
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LeRoy EC, Black C, Fleischmajer R, Jablonska S, Krieg T, Medsger TA, Jr., et al. (1988) Scleroderma (systemic sclerosis): classification, subsets and pathogenesis. J Rheumatol 15:202-5.
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Li J, Ning Y, Hedley W, Saunders B, Chen Y, Tindill N, et al. (2002) The Molecule Pages database. Nature 420:716-7.
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Mahoney JM, Taroni J, Martyanov V, Wood TA, Greene CS, Pioli PA, et al. (2015) Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms. PLoS computational biology 11:e1004005. Milano A, Pendergrass SA, Sargent JL, George LK, McCalmont TH, Connolly MK, et al. (2008) Molecular subsets in the gene expression signatures of scleroderma skin. PLoS One 3:e2696. Naba A, Clauser KR, Hoersch S, Liu H, Carr SA, Hynes RO (2012) The matrisome: in silico definition and in vivo characterization by proteomics of normal and tumor extracellular matrices. Mol Cell Proteomics 11:M111 014647. Nishimura D (2001) A View from the Web: BioCarta. Biotech Software & Internet Report 2:117-20.
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Panopoulos ST, Bournia VK, Trakada G, Giavri I, Kostopoulos C, Sfikakis PP (2013) Mycophenolate versus cyclophosphamide for progressive interstitial lung disease associated with systemic sclerosis: a 2-year case control study. Lung 191:483-9.
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Pendergrass SA, Lemaire R, Francis IP, Mahoney JM, Lafyatis R, Whitfield ML (2012) Intrinsic gene expression subsets of diffuse cutaneous systemic sclerosis are stable in serial skin biopsies. J Invest Dermatol 132:1363-73.
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Riccieri V, Rinaldi T, Spadaro A, Scrivo R, Ceccarelli F, Franco MD, Taccari E, Valesini G (2003) Interleukin13 in systemic sclerosis: relationship to nailfold capillaroscopy abnormalities. Clin Rheumatol 22(2):1026.
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Sargent JL, Li Z, Aliprantis AO, Greenblatt M, Lemaire R, Wu MH, et al. (2016) Interspecies comparative genomics identifies optimal mouse models of systemic sclerosis. Arthritis & rheumatology (Hoboken, NJ). Schaefer CF, Anthony K, Krupa S, Buchoff J, Day M, Hannay T, et al. (2009) PID: the Pathway Interaction Database. Nucleic Acids Res 37:D674-9. Schneider, C. A.; Rasband, W. S. & Eliceiri, K. W. (2012), "NIH Image to ImageJ: 25 years of image analysis", Nature methods 9(7): 671-675, PMID 22930834.
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Schindelin, J.; Arganda-Carreras, I. & Frise, E. et al. (2012), "Fiji: an open-source platform for biologicalimage analysis", Nature methods 9(7): 676-682, PMID 22743772
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Shen-Orr SS, Gaujoux R (2013) Computational deconvolution: extracting cell type-specific information from heterogeneous samples. Curr Opin Immunol 25:571-8.
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Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102:15545-50. Taroni JN, Martyanov V, Huang CC, Mahoney JM, Hirano I, Shetuni B, et al. (2015) Molecular characterization of systemic sclerosis esophageal pathology identifies inflammatory and proliferative signatures. Arthritis Res Ther 17:194.
Taroni JN, Greene CS, Martyanov V, Wood TA, Christmann RB, Farber HW, Lafyatis RA, Denton CP, Hinchcliff ME, Pioli PA, Mahoney JM, Whitfield ML (2017) A novel multi-network approach reveals tissue-specific cellular modulators of fibrosis in systemic sclerosis. Genome Medicine 9:27.
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Tashkin DP, Roth MD, Clements PJ, Furst DE, Khanna D, Kleerup EC, et al. (2016) Mycophenolate mofetil versus oral cyclophosphamide in scleroderma-related interstitial lung disease (SLS II): a randomised controlled, double-blind, parallel group trial. Lancet Respir Med.
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Walker KM, Pope J (2012) Treatment of systemic sclerosis complications: what to use when first-line treatment fails--a consensus of systemic sclerosis experts. Semin Arthritis Rheum 42:42-55.
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Wu M, Baron M, Pedroza C, Salazar GA, Ying J, Charles J, Agarwal SK, Hudson M, Pope J, Zhou X, Reveille JD, Fritzler MJ, Mayes MD, Assassi S (2017) CCL2 in the Circulation Predicts Long-Term Progression of Interstitial Lung Disease in Patients With Early Systemic Sclerosis: Data From Two Independent Cohorts. Arthritis & rheumatology 10.1002/art.40171.
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Yaari G, Bolen CR, Thakar J, Kleinstein SH (2013) Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations. Nucleic Acids Res 41:e170.
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All subjects with SSc (N = 68)
Improver during MMF Treatment at 12 mo. (N = 10)
Non-Improver during MMF Treatment at 12 mo. (N = 12)
Other subjects with SSc (N = 46)
41.6 (11.7)
50.25 (11.1)
49.5 (4.1)
55.08 (5.8)
49.2 (12.8)
Sex, N (%) women
15 (68%)
62 (91%)
9 (90%)
10 (83%)
43 (94%)
Race, N (%) white
15 (68%)
52 (76%)
9 (90%)
9 (75%)
34 (74%)
SSc subtype, N (%) diffuse mRSS at baseline
NA
51 (75%)
8 (80%)
12 (100%)
31 (67%)
NA
15.5 (9.8)
14.5 (3.9)
17.3 (8.8)
15.3 (11.0)
mRSS at 12 months
NA
13.6 (10.5)
7.4 (2.5)
18.6 (11.4)
13.8 (11.0)
Raynaud disease duration at baseline, median (range) mo. Disease duration from first non-Raynaud at baseline, median (range) mo. SSc-specific antibodies, N (%)
NA
23 (0-237)
12 (1-237)
9 (0-45)
36 (6-212)
NA
22 (1-225)
Scl-70
NA
22 (32%)
RNA Pol III
NA
19 (28%)
Age, years
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Mean (SD) or as indicated
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Control subjects (N = 22)
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SSc Subjects
15 (3-225)
10 (1-81)
27 (2-224)
2 (20%)
7 (58%)
13 (28%)
3 (30%)
3 (25%)
13 (28%)
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SSc=Systemic sclerosis, MMF=mycophenolate mofetil, mRSS=modified Rodnan Skin Score, Scl-70=anti-topoisomerase I, RNA pol III=RNA polymerase III, NA=not applicable.
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FIGURE LEGENDS
Figure 1: Overview of study design and intrinsic gene expression analysis.
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a. Flowchart of subjects through clinical study. b. 2500 probes were selected with a False Discovery Rate of 0.14% from 163 baseline arrays by intrinsic gene analysis by subject. This hierarchical clustering dendrogram shows the normal-like (green), limited (yellow),
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inflammatory (purple), and fibroproliferative (red) groups. Significance of clustering was determined by SigClust (p≤0.0001). c. 651 genes in improvers and d. 1067 genes in non-
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improvers were differentially expressed between baseline and 12-month (post) biopsies (FDR<5%; arm and flank biopsies used). The gene centroid (average of all arrays in a class) is displayed. Selected genes and pathways are displayed to the right of the centroid. Bolded gene
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symbols are annotated to the pathway/GO term in bold.
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Figure 2: The inflammatory signature is attenuated by MMF but rebounds in subjects that cease MMF treatment at 24 months.
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ssGSEA normalized enrichment scores (NES) were used to summarize changes in inflammatory gene expression during MMF treatment. a. The inflammatory NES of completers were hierarchically clustered and displayed as a heatmap b-c. and as line plots for select subjects. d-f.
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Three subjects lose their inflammatory signature during treatment and rebound at 36 months after treatment cessation. g-i. Three subjects who continue treatment do not show an increase in
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inflammatory signature. An arrow indicates when treatment began. A dashed line indicates when treatment stopped. The purple line indicates NES. The black dashed line indicates mRSS.
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*Subject 26 was never on MMF, and serves as a control.
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Figure 3: Changes in CCL2 expression in skin, CCL2 concentration in sera, and monocyte migration of SSc patients treated with MMF.
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CCL2 mRNA levels were quantified using qRT-PCR and normalized to beta-actin mRNA in the a. Treatment Discontinued and b. Treatment Continued groups. c. ELISA was used to measure circulating CCL2 of SSc patients at baseline (n=3), 3mo of MMF (n=2), and >16mo of MMF
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(n=4) and healthy controls (n=4, females, >30y) in pg/mL. d. Relative monocyte migration toward sera from SSc patients and sera or plasma from healthy controls (n=5, females, >30y)
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was measured. Relative fluorescence (y-axis) is the ratio of sample fluorescence and internal control fluorescence (media without additional CCL2). Unpaired T-Test used for all statistical
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analysis, mean with standard deviation (SD) shown.
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Figure 4. Myeloid dendritic cells, T-lymphocytes and macrophages contribute significantly to the inflammatory gene expression signature.
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a. Six subjects highlighted in figure 2 show a high correlation between their individual cell typespecific NES scores and their inflammatory NES scores across the time course for dendritic cells (DCs; r=0.83), macrophages (r=0.60), and T-lymphocytes (r=0.77). b-c. The cell type NES
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scores are plotted against time (base, 6mo, 12mo, 24mo, 36mo) and are split between subjects who discontinue MMF at 24 months (b. Treatment Discontinued) and subjects who continue
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MMF treatment (c. Treatment Continued). Treatment Discontinued are subjects SSc_03, 06, and 08 and Treatment Continued are subjects SSc_10, 17, and 28. Arrow indicates when a subject
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started MMF, and a dashed line indicates when a subject discontinued MMF.
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Figure 5: Immunohistochemistry shows reductions in DCs and macrophages during MMF treatment. a-b. Immunohistochemistry staining targeting CD163 (macrophage marker) of arm biopsy slides.
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CD163 counts were plotted over time for subjects 03, 06, 08, 10, 17, 28. cd. Immunohistochemistry staining for CD163 in baseline (c) and 36mo (d) biopsies from SSc_17 (Treatment Continued). e-f. Immunohistochemistry staining targeting CD1c (mDC marker) of
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arm biopsy slides. CD1c counts were plotted over time for the same subjects. g-i. Immunohistochemistry staining for CD1c in baseline (g), 24mo (h), and 36mo (i) biopsies from
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SSc_08 (MMF ceased at 24mo, Treatment Discontinued). Data not available for all subjects at all time points; missing data denoted by “x”. An arrow indicates when treatment started. A
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dashed line indicates when treatment stopped.
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S0022-202X(18)30023-X
DOI:
10.1016/j.jid.2018.01.006
Reference:
JID 1254
To appear in:
The Journal of Investigative Dermatology
Received Date: 16 September 2016 Revised Date:
8 December 2017
Accepted Date: 4 January 2018
Please cite this article as: Hinchcliff M, Toledo DM, Taroni JN, Wood TA, Franks JM, Ball MS, Hoffmann A, Amin SM, Tan AU, Tom K, Nesbeth Y, Lee J, Ma M, Aren K, Carns MA, Pioli PA, Whitfield ML, Mycophenolate mofetil treatment of systemic sclerosis reduces myeloid cell numbers and attenuates the inflammatory gene signature in skin, The Journal of Investigative Dermatology (2018), doi: 10.1016/ j.jid.2018.01.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Mycophenolate mofetil treatment of systemic sclerosis reduces myeloid cell numbers and attenuates the inflammatory gene signature in skin
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Monique Hinchcliff MD MS1, 2,#, Diana M. Toledo MS3,#, Jaclyn N. Taroni PhD3, Tammara A. Wood MA3, Jennifer M. Franks BS3, Michael S. Ball BS7, Aileen Hoffmann MS1, Sapna M. Amin MD4, Ainah U. Tan MD4, Kevin Tom1, Yolanda Nesbeth PhD6, Jungwha Lee PhD2, 5, Madeleine Ma MS2, 5, Kathleen Aren MPH1, Mary A. Carns MS1, Patricia A. Pioli PhD7,
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Michael L. Whitfield PhD3
Northwestern University Feinberg School of Medicine, 1Department of Medicine, Division of Rheumatology, 240 E. Huron Street, Suite M-300, 2Institute of Public Health and Medicine, 633 N. St. Clair, 18th Floor 4Department of Dermatology, 676 N. St. Clair Street Suite 1600, Department of Preventive Medicine, 680 N. Lake Shore Drive, Suite 1400, Chicago, IL 60611,
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USA. Geisel School of Medicine at Dartmouth, 3Department of Molecular and Systems Biology, Hanover, NH 03755, 7Microbiology and Immunology, Lebanon, NH 03756, 6Celdara Medical
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LLC, Lebanon, NH 03766, USA.
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Short title: MMF reduces myeloid cell recruitment #Authors contributed equally Corresponding Authors: Monique Hinchcliff, MD MS Northwestern University Feinberg School of Medicine Division of Rheumatology 240 E Huron Street, Suite M300 Chicago, IL USA 60611 [email protected] Phone: 312-503-4844, fax: 312-503-0994
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Abbreviations used:
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ORCID Identifiers: Monique Hinchcliff: orcid.org/0000-0002-8652-9890 Diana M. Toledo: orcid.org/0000-0002-7501-8286 Jaclyn N. Taroni: orcid.org/0000-0003-4734-4508 Tammara A Wood: orcid.org/0000-0002-4370-1398 Jennifer M. Franks: orcid.org/0000-0003-2400-5431 Michael S. Ball: orcid.org/0000-0001-7322-7642 Aileen Hoffmann: orcid.org/ 0000-0002-2337-4190 Sapna M. Amin: orcid.org/0000-0002-4362-5727 Ainah Uy Tan: orcid.org/ 0000-0002-8202-7164 Kevin Tom: orcid.org/0000-0003-2098-7714 Yolanda Nesbeth: orcid.org/0000-0003-3347-8871 Jungwha Lee: orcid.org/0000-0002-0806-0847 Madeleine Ma: orcid.org/0000-0002-5823-5713 Kathleen Aren: orcid.org/0000-0003-4770-2643 Mary Carns: orcid.org/0000-0002-5063-156X Patricia A. Pioli: orcid.org/0000-0001-6896-7259 Michael L. Whitfield: orcid.org/0000-0002-0862-6003
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Michael L. Whitfield, PhD Department of Genetics Geisel School of Medicine at Dartmouth 7400 Remsen Hanover, NH 03755 [email protected] Phone: 603-650-1109, Fax: 603-650-1188
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SSc=systemic sclerosis mRSS=modified Rodnan skin score MMF=mycophenolate mofetil CCL2=C-C motif chemokine ligand 2 lc=limited cutaneous dc=diffuse cutaneous DC=dendritic cell mDC=myeloid dendritic cell FDR=false discovery rate CCR1/5=C-C chemokine receptor type 1/5 THBS1/2=thrombospondin type 1/2 COL8A1=collagen type VIII alpha 1 COL5A2=collagen type V alpha 2 FBN1=fibrillin type 1 FADS1=fatty acid desaturase type 1 FA2H=fatty acid 2-hydroxylase FABP7=fatty acid binding protein 7 GO=gene ontology
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QuSAGE= Quantitative Set Analysis for Gene Expression TLR=toll-like receptor NFKB2=nuclear factor kappa B subunit 2 IRF7=interferon regulatory factor 7 STAT1=signal transducer and activator of transcription 1 ssGSEA=single sample Gene Set Enrichment Analysis NES=normalized enrichment scores qRT-PCR=quantitative real time polymerase chain reaction
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Key Words: Biomarkers, genomics, systemic sclerosis, scleroderma, dendritic cells
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Twitter handle: @WhitfieldLab
Funding: This work was supported by the National Institutes of Health NICHD K12 HD055884
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(MH), NIAMS K23 AR059763 (MH), NIAMS R21 AR068035 (MH, MLW), NIAMS P30 AR061920 (MH, MLW), NIAMS R56 AR063985 (PAP), NIAMS R44 AR061920 (MH, YN, MLW), NIGMS T32 GM008704 (JNT), a Cancer Center Support Grant NCI CA060553 and by research awards from the Scleroderma Research Foundation (MH, MLW) and Scleroderma
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Foundation (PAP). JNT received support from the John H. Copenhaver, Jr. and William H. Thomas, MD 1952 Junior Fellowship from Dartmouth Graduate Studies. MSB received support from The John Osborn Polak Endowment. The Northwestern University Mouse Histology and
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Phenotyping Laboratory also provided project support. MH and MLW had full access to all the
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data in the study and had final responsibility for the decision to submit for publication.
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ABSTRACT Fewer than half of patients with systemic sclerosis (SSc) demonstrate modified Rodnan skin
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score (mRSS) improvement during mycophenolate mofetil (MMF) treatment. To understand the molecular basis for this observation, we extended our prior studies and characterized molecular and cellular changes in skin biopsies from subjects with SSc treated with MMF. Eleven subjects
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completed ≥24 months of MMF therapy. Two distinct skin gene expression trajectories were observed across six of these subjects. Three of the six subjects showed attenuation of the
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inflammatory signature by 24 months, paralleling reductions in CCL2 mRNA expression in skin and reduced numbers of macrophages and myeloid dendritic cells in skin biopsies. MMF cessation at 24 months resulted in an increased inflammatory score, increased CCL2 mRNA and protein levels, mRSS rebound, and increased numbers of skin myeloid cells in these subjects. In contrast, three other subjects remained on MMF >24 months and showed a persistent decrease in
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inflammatory score, decreasing or stable mRSS, CCL2 mRNA reductions, sera CCL2 protein levels trending downward, reduction in monocyte migration, and no increase in myeloid cell numbers. These data summarize molecular changes during MMF therapy that suggest reduction
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CCL2.
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of innate immune cell numbers, possibly by attenuating expression of chemokines including
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INTRODUCTION Systemic sclerosis (SSc; scleroderma) is a heterogeneous, multi-organ disease whose
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clinical hallmark is skin fibrosis (Hinchcliff and Varga, 2011; Taroni et al., 2015). Two clinical SSc subtypes, limited cutaneous (lc) and diffuse cutaneous (dc) are defined based on the modified Rodnan skin score (mRSS)(LeRoy et al., 1988). Immune modulators, including
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mycophenolate mofetil (MMF; CellCept®, Roche), are prescribed for active SSc lung and skin disease (Walker and Pope, 2012), yet substantial response heterogeneity exists (Herrick et al.,
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2010; Panopoulos et al., 2013).
Gene expression in SSc-derived skin biopsies provides insight into SSc clinical and treatment response heterogeneity. We previously published genome-wide gene expression analyses of SSc skin biopsies and identified four ‘intrinsic’ molecular subsets that were
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reproducible (inflammatory, fibroproliferative, limited and normal-like) (Milano et al., 2008; Pendergrass et al., 2012). We showed that a high baseline inflammatory gene expression signature in the skin of patients with SSc was associated with mRSS improvement during MMF
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therapy (Hinchcliff et al., 2013).
Studies support a role for innate immune activation in SSc pathogenesis (Chia and Lu,
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2015; Christmann et al., 2011; Christmann et al., 2014; Higashi-Kuwata et al., 2010; Johnson et al., 2015). Alternatively activated macrophages have been identified in SSc skin (HigashiKuwata et al., 2010), consistent with elevated levels of IL-4 and IL-13 in SSc sera (Hasegawa et al., 1997, Riccieri et al., 2003). Our recent work shows elevated markers of alternatively activated macrophage in SSc skin across multiple independent gene expression datasets (Mahoney et al., 2015, Taroni et al. 2017), while enriched macrophage and dendritic cell (DC)
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gene expression signatures have been identified in SSc skin in an independent cohort (Assassi et al., 2015). Consistent with these results, genes associated with myeloid cell recruitment and
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differentiation are over-expressed in SSc compared with healthy subjects (Mahoney et al., 2015). The myeloid cell chemo-attractant CCL2 is highly expressed in the skin of SSc patients classified within the inflammatory intrinsic subset (Greenblatt et al., 2012; Milano et al., 2008),
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and has been shown to be required for the inflammatory-fibrotic phenotype of the sclGVHD mouse model of SSc (Greenblatt et al., 2012). Additionally, circulating CCL2 levels correlate
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with increased interstitial lung disease in SSc patients (Assassi et al., 2013), and predict a faster decline in forced vital capacity (FVC%) and decreased survival (Wu et al., 2017). These findings implicate altered innate immune cell activation and/or recruitment in SSc pathogenesis. Herein, we characterize the molecular and cellular changes in skin and sera during MMF
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therapy. We perform gene expression and immunohistochemical analyses of skin biopsies obtained over 36 months for SSc subjects who were prescribed MMF. We analyze changes in the inflammatory gene expression signature, in CCL2 mRNA and sera CCL2 levels, and in skin
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monocyte recruitment and immune cell numbers over time in these subjects. This study provides important insight into the mechanism by which innate immune cell populations in skin are
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influenced during MMF treatment in patients with SSc.
RESULTS
Study cohort
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Clinical characteristics are shown for 68 subjects with SSc (75% dcSSc), three subjects without SSc (one with morphea and two with connective tissue disease overlap syndromes) and 22 healthy controls (Table 1, Figure 1a, Table S1). The median (range) SSc disease duration
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between first Raynaud symptom and the baseline visit was 23 (0-237) months. Twenty-two subjects (32%) had anti-topoisomerase I/Scl-70, and 19 (28%) had anti-RNA polymerase III
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serum autoantibodies.
Thirty-five SSc subjects who were enrolled in the Northwestern Scleroderma Patient
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Registry, and were taking, or were intolerant to, MMF, underwent skin biopsies once at their baseline visit (91 arrays) (Figure 1a). Thirty-three MMF-naïve subjects who were prescribed MMF consented to longitudinal skin biopsies (Figure 1a, Supplemental Figure S1). Of these 33 subjects, five were lost to follow-up, and six had baseline mRSS< nine. Twenty-two subjects with baseline mRSS ≥ nine and mRSS assessments at 12 months were included in the MMF
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improvement analysis. Improvement was defined as ≥25% mRSS reduction (non-improvement <25% mRSS reduction) between baseline and 12 months (Khanna et al., 2006). Ten subjects fulfilled (Table S8), and twelve subjects did not fulfill (Table S9), the clinical improvement
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criterion. Study completers (11 out of 33, including one subject with baseline mRSS< nine) were
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defined as subjects who were prescribed MMF at baseline and underwent longitudinal skin biopsies at five time points (baseline, 6, 12, 24, 36 months). There were no statistically significant differences in sex, race, serum autoantibodies,
baseline mRSS, lcSSc vs. dcSSc, and SSc disease duration between improvers and nonimprovers. SSc intrinsic subset recapitulation
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Intrinsic subset was determined for baseline biopsies from 71 subjects and 22 healthy controls (163 total microarrays) (Milano et al., 2008). Intrinsic gene analysis was performed using 2500 probes with 1956 unique genes with a false discovery rate (FDR) ≤ 0.1422% (Figure
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1b, Supplemental Figure S2). Four SSc intrinsic subsets (normal-like (green), limited (yellow), inflammatory (purple), and fibroproliferative (red)) were recapitulated using average linkage hierarchical clustering. We observed a subset of patients that show a gradient of both
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inflammatory and fibroprolifereative signatures (Mahoney et al., 2015). The fibroproliferative subgroup continues to be defined by a strong proliferative signature in addition to an
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inflammatory signature. (Milano et al., 2008; Pendergrass et al., 2012; Hinchcliff et al., 2013). G:Profiler was used to identify pathways and biological processes significantly enriched in the different subsets (Reimand et al., 2011) (Figure 1b; Table S2, g:Profiler output; Table S13, full gene list; Table S14, intrinsic subset gene lists; Table S15, gene expression).
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Improvers tended to express an inflammatory or normal-like intrinsic gene expression signature at baseline (Table S8). Three subjects who were inflammatory-fibroproliferative at baseline also showed improvement. This suggests that subjects with an inflammatory signature
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in skin are more likely to improve while on MMF, and the majority of subjects who respond to
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MMF have an inflammatory signature. Skin score improvement in subjects classified as normallike may represent collagen degradation due to natural skin repair processes rather than a treatment response.
Immune-related gene expression alterations in patients that improve during MMF To understand molecular changes associated with mRSS improvement, we identified genes whose expression changed in 22 subjects prescribed MMF. We identified 651
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differentially expressed genes in ten improvers between baseline and the 12-month time point (FDR ≤ 5%; base vs. post Comparative Marker Selection; Figure 1c). Genes whose expression decreased during improvement were functionally enriched for the Gene Ontology (GO) terms
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innate immune response, leukocyte differentiation, apoptotic process, and angiogenesis (Table S3, Table S4). Pathway analysis with Quantitative Set Analysis for Gene Expression (QuSAGE) also demonstrated a decrease in inflammation-related pathways during improvement (Table S5).
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No changes in gene expression associated with immune processes were observed in 12 nonimprovers after 12 months of MMF treatment (FDR ≤ 5%; base vs. post Comparative Marker
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Selection; Figure 1d, Table S6, Table S7).
Longitudinal analysis shows loss of the inflammatory gene expression signature during MMF treatment
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Gene expression time course analyses were performed using longitudinal biopsies and mRSS for 11 completers (Figure 2a). Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to calculate the inflammatory normalized enrichment scores (NES; summarizes the
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inflammatory gene signature) that are displayed as a heatmap (Figure 2a) and line plots (Figure 2b-c) for each biopsy to examine longitudinal changes during treatment. We hierarchically
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clustered the inflammatory NES time courses for all 11 completers to identify groups of subjects with similar longitudinal trajectories. Six subjects with high inflammatory NES at baseline lost their inflammatory signature by
24 months of MMF treatment. In three subjects, the inflammatory NES rebounded after MMF discontinuation as indicated by the increase in NES between 24 months and 36 months (Figure 2b, termed Treatment Discontinued). Upon MMF cessation at 24 months, mRSS also increased
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in two of these three subjects concomitant with the inflammatory NES increase (Figure 2d-f). The other three subjects, who continued MMF treatment beyond 24 months, showed persistent decrease in their inflammatory NES scores at 36 months (Figure 2c, termed Treatment
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Continued) and demonstrated stable or decreasing mRSS (Figure 2g-i). Inflammatory NES scores and mRSS from the other five completers are shown in Supplemental Figure S3. In addition, the microarray gene expression of several alternatively and classically activated
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macrophage markers (including CCL2) for all completers are shown in Supplemental Figures S5
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and S6.
We calculated the correlation between the inflammatory NES scores for baseline biopsies and clinical covariates (Supplemental Figure S4).
Patients with higher mRSS had higher
inflammatory NES scores at baseline (r2=0.1784, p=0.0002).
Shorter SSc disease duration
correlated with higher baseline inflammatory NES score (r2=0.1817, p=0.0002). Additionally, a
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significantly lower inflammatory NES score was observed in forearm biopsies from clinically unaffected (mRSS=0) compared to clinically affected skin (mRSS=1 or 2; p=0.0241 and p=0.0019, respectively; Table S12). There was no significant difference in inflammatory NES
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score in subjects with forearm mRSS of 1, 2, or 3.
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CCL2 mRNA and serum protein levels change during MMF therapy To determine how MMF therapy modulates CCL2 mRNA levels in skin, qRT-PCR was
performed on RNA extracted from patients in the Treatment Discontinued and Treatment Continued groups at each time point. CCL2 mRNA levels parallel the inflammatory NES signature (Figure 3a-b). CCL2 mRNA levels decline during MMF treatment for all subjects and
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significantly increase at 36 months in subjects who discontinue MMF (p=0.005, Figure 3a), but remain low in subjects continuing MMF therapy (Figure 3b).
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CCL2 serum protein levels in SSc patients at baseline and during MMF treatment (at 3 months and >16 months of MMF) were compared to levels in healthy control subjects matched for age and sex. SSc patients had significantly higher CCL2 levels at each time point compared
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to controls (Figure 3c; p=0.004, p<0.0001, p<0.0001, respectively). In aggregate, serum CCL2 decreased during MMF treatment, although not significantly. For instance, CCL2 levels
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decreased from 988.2 pg/ml (baseline) to 617.5 pg/ml (24-month during MMF) in subject 17. Notably, this CCL2 decline was coupled with significant mRSS decrease (baseline mRSS=35 vs. 24-month=19, Figure 2h).
Monocyte recruitment toward SSc patient sera is significantly reduced over the course of
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MMF therapy
Monocyte migration towards patient sera was measured at baseline and during MMF treatment using a fluorescence-based Chemotaxis Cell Migration Assay (Figure 3d). There is
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significantly more monocyte chemotaxis toward SSc patient sera regardless of MMF treatment relative to healthy controls (p<0.05). Monocyte motility was highest toward SSc baseline (MMF-
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naïve) sera, with a significant decrease in monocyte migration observed between sera at baseline and after >16 months of continuous MMF treatment (p=0.012).
Consistent with CCL2
expression data, these results demonstrate that SSc sera is more chemotactic for monocytes compared with healthy control sera, and that prolonged MMF treatment inhibits the myeloid chemo-attracting capability of SSc sera. Cell type-specific gene expression signatures change during MMF therapy
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We then investigated changes in inflammatory cell populations in associated skin biopsies. First, we used ssGSEA to measure the relative expression of cell type-specific gene sets and calculated cell type-specific NES. Similar NES have been used to infer relative cell type
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proportions in other tissues (Bolen et al., 2011; Shen-Orr and Gaujoux, 2013). We calculated the correlation between fifteen different cell type-specific gene set NES scores (including a wide range of cell types and differentiation states) and the inflammatory NES in order to determine
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which cell types contributed most significantly to the inflammatory signature (Table S10, Table S11). A high correlation was observed between subjects’ inflammatory NES and dendritic cell
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(DC, r=0.83), T cell (r=0.77), monocyte (r=0.70), and macrophage (r=0.60) NES (Figure 4a). Interestingly, three out of three Treatment Discontinued subjects demonstrated a rebound (Figure 4b), while Treatment Continued subjects demonstrated a stable or persistent decrease (Figure 4c; Supplemental Figure S7; Supplemental Figure S8), in DC, T cell, and macrophage cell type-
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specific NES. These data suggest that DCs, T cells, and macrophages contribute to the inflammatory gene expression signature changes observed during MMF therapy.
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Immunohistochemistry staining shows changes in myeloid cell numbers To validate cell type-specific NES changes using immunohistochemistry, skin biopsies
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were stained for CD163, a marker of alternatively activated macrophages, CD1c, a marker of myeloid dendritic cells (mDCs), and CD3, a T cell marker, and positively stained cells were quantified by two independent observers (interclass correlation coefficients were =0.99 (95% CI 0.98-1.00)) or using ImageJ software. In general, Treatment Discontinued subjects demonstrated significant increases (Figure 5a, e) in skin macrophage and mDC counts between 24 and 36 months. In comparison, Treatment Continued subjects showed stable counts (Figure 5b, f). For instance, macrophage staining for subject 17 (MMF Treatment Continued) was abundant at
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baseline (Figure 5c) and decreased substantially by 36 months (Figure 5d) coinciding with mRSS improvement (baseline mRSS=35 vs. 36-month=15). In contrast, mDC staining for subject 08 (MMF Treatment Discontinued) was abundant at baseline (Figure 5g), decreased by 24 months
baseline mRSS=12, 24-month=11, 36-month=12).
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during MMF (Figure 5h), and following MMF cessation, rebounded at 36 months (Figure 5i;
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Overall, macrophage and mDC quantification correlated with inflammatory NES, suggesting that these cell types, likely including substantial representation from pro-fibrotic,
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alternatively activated macrophages, may be key drivers of skin fibrosis in SSc (Figure 5). Notably, MMF treatment did not affect B cell NES or B cell numbers. Immunohistochemistry staining showed stable T cell numbers, while T cell NES scores decreased during MMF therapy, suggesting that treatment may alter the T cell activation state. Thus, MMF modulates myeloid cell mobilization and activation in SSc skin and may exert effects on T cells through its
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DISCUSSION
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interaction with antigen presenting cells including macrophages and DCs.
Two years of MMF versus one year of oral cyclophosphamide and placebo for treatment
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of interstitial lung disease in patients with SSc enrolled in the Scleroderma Lung Study II result in pulmonary function and mRSS improvement in both groups (Tashkin et al., 2016). Due to a more favorable safety profile, MMF has emerged as the new gold standard oral therapy for SSc lung and skin fibrosis (Tashkin et al., 2016), but not all patients demonstrate improvement and optimal duration of MMF therapy is unknown. Our previous study results support analysis of skin gene expression in patients with SSc to gain insights into SSc skin disease pathogenesis and treatment response heterogeneity (Hinchcliff et al., 2013).
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Consistent with prior results, we found MMF therapy may be most beneficial in patients classified in the inflammatory intrinsic subset, though not all inflammatory subjects improve while on MMF therapy. Importantly, only one out of ten subjects who improved during MMF
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therapy was classified as fibroproliferative and this individual still had a positive inflammatory NES score. This suggests that having a prominent inflammatory signature is a major quality of
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patients who respond to MMF therapy on the molecular level.
Importantly, our results suggest a role for MMF as a regulator of CCL2 gene expression.
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CCL2 has been implicated in the pathogenesis of many autoimmune diseases, including SSc and systemic lupus erythematosus (SLE). Intriguingly, a recent study showed significant reductions in CCL2 mRNA levels in peripheral blood mononuclear cells of SLE patients that received MMF treatment compared with control subjects (Dominguez-Gutierrez et al., 2014). We report that CCL2 mRNA expression is reduced in the skin of SSc patients treated with MMF, and CCL2
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transcript levels in skin may be an indicator of disease progression and response to therapy. Because of the important role of this chemokine in SSc disease initiation and progression
SSc treatment.
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(Greenblatt et al., 2012; Wu et al., 2017), MMF is likely to continue to play an important role in
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To gain insights into the cellular populations that underlie changes in skin inflammatory gene expression during MMF treatment, we conducted careful computational, functional, and immunohistochemical analyses. We found the most consistent correlations between cells of the innate immune system (monocytes, macrophages, DCs) and T cells. We saw negative associations between inflammatory NES and gene signatures for both naïve and memory B cells, as well as for resting CD4, CD8 and memory T cells. Given our prior results suggesting that the dermal macrophage/DC axis may play a pivotal role in SSc skin disease (Mahoney et al., 2015,
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Taroni et al., 2017), we stained biopsies for macrophages and mDCs and found a positive association with the inflammatory signature. We also found that CCL2 levels were significantly higher in SSc sera compared with healthy controls, and circulating CCL2 trends downward with
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prolonged MMF treatment. Although MMF attenuation of sera CCL2 expression failed to reach statistical significance, it is important to note that limited clinical samples from MMF-treated patients were available retrospectively, and thus it is likely that with an increased sample size,
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significance would be achieved. Alternatively, it is also possible that other chemokines, in addition to CCL2, that mediate myeloid migration and are being regulated by MMF.
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Nonetheless, monocyte migration toward SSc patient sera is highest at baseline and is significantly reduced after MMF treatment.
This suggests that MMF therapy inhibits
monocyte/macrophage migration systemically, potentially due to modulation of CCL2. Other gene expression studies implicate myeloid cells as potential key mediators of
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fibrosis in SSc (Christmann et al., 2014; Mahoney et al., 2015). Notably, antibody blockade of CCL2, which mediates recruitment and activation of monocytes, macrophages, and DCs, is protective against immune-fibrotic disease development and progression in the sclGVHD mouse
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model that resembles the inflammatory subset of patients with SSc (Greenblatt et al., 2012;
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Sargent et al., 2016). We now show that mRSS reduction or stabilization during MMF treatment is associated with decreased dermal expression of CCL2 mRNA and reduced sera CCL2 levels, findings that support the hypothesis that myeloid cell recruitment plays a role in SSc skin disease pathogenesis. Consistent with this hypothesis, our data demonstrate reduced monocyte migration toward patient sera following MMF treatment. In this regard, MMF treatment may also lead to attenuated production and release of myeloid-derived pro-fibrotic mediators that include CCL2.
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Study strengths include prospective study design, a clinically well-characterized SSc cohort including mRSS performed longitudinally by one investigator at the time of skin biopsies, and the collection of longitudinal biopsies over 36 months. Study limitations include open-label
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trial design, lack of a matched untreated SSc control population, higher proportion of female subjects in cases compared to the control group, younger subjects in the control group, lack of a validated method to define active skin disease, and small sample sizes of the cohort that
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completed biopsies at all time points. The study continues and additional interim results will be
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published.
The study findings support the role of innate immunity, specifically alternatively activated macrophages and DCs, in SSc dermal pathogenesis. Rebound in the inflammatory skin gene expression signature with increased skin myeloid cells with MMF cessation at 24 months
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suggests that led to a suggests optimal MMF therapy duration exceeds 24 months. MATERIALS & METHODS Patients
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The Northwestern University Institutional Review Board approved the study and participants provided written informed consent in accordance with the Declaration of Helsinki.
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Subjects fulfilled American College of Rheumatology SSc (1980) or three out of five CREST (calcinosis, Raynaud, esophageal dysmotility, sclerodactyly, telangiectasias) criteria. One physician performed mRSS (LeRoy et al., 1988). Serum autoantibodies were measured by indirect immunofluorescence at Specialty Laboratories, Valencia, CA. Subjects underwent four mm side-by-side skin biopsies between November 2008 and June 2014 as described (Hinchcliff et al., 2013). One biopsy pair (arm and flank) was placed in
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RNAlater (Applied Biosystems, Ambion®, Carlsbad, CA) and used for Agilent DNA microarray analysis; the other biopsy pair was placed in formalin for histology.
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93 individuals were enrolled and 359 total biopsies were collected including 39 biopsies from healthy controls. Patients with active skin disease in the opinion of the treating physician
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Skin Histology and Immunohistochemistry
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were prescribed two g/day MMF in divided doses (Figure 1a).
5-µm sections of formalin-fixed/paraffin-embedded dermal biopsies were obtained. Immunohistochemistry staining for macrophages (CD163, EDHu-1 clone, Bio-Rad MCA1853T, Hercules, CA, and MRQ-26 Cell Marque, Sigma-Aldrich, St. Louis, MO) and mDCs (CD1c,
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LSBio 10059, Seattle, WA) was performed in duplicate using the Labeled StreptAvidin Biotin Method and DAB substrate. Endogenous peroxidase activity was blocked using 3% H2O2 and labeled streptavidin was HRP-conjugated. For CD1c staining, a board-certified pathologist with
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subspecialty dermatopathology training and an independent dermatology reviewer who were blinded to clinical data quantified positively stained cells using an Olympus BX50 microscope.
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The “hot spot” method was utilized whereby the greatest staining area was determined at scanning magnification and positively stained cells were quantified in that area at 20x or 40x and in five consecutive fields (corresponds to one-two mm2). Interclass correlation coefficients were generated to assess the correlation between independent scores (one denotes perfect correlation). For CD163 staining, ImageJ Fiji software was used to quantify positively stained cells (Schneider et al., 2012, Schindelin et al., 2012).
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Statistical analyses of clinical covariates Continuous variables were summarized as mean with standard deviation. Categorical
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variables were summarized as frequency and proportion. Statistical significance was assessed with Fisher’s Exact or Wilcoxon-Mann-Whitney tests as appropriate. A P-value <0.05 was
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considered significant. All analyses were carried out using R statistical software (version 3).
Supplemental Methods
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DNA microarray analyses, differential gene expression, intrinsic subset assignment, cell type enrichment, qRT-PCR, ELISA, and the monocyte migration assay methods are available in
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supplementary materials.
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CONFLICT OF INTEREST Dr. Michael Whitfield is a scientific founder of Celdara LLC, which is developing gene
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expression biomarkers in SSc. Dr. Yolanda Nesbeth is an employee at Celdara Medical LLC. Dr. Monique Hinchcliff, Dr. Michael Whitfield, and Celdara Medical have received NIH-Small Business Innovative Research Grant Awards. Dr. Monique Hinchcliff and Tammara A. Wood
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have been paid as consultants, and Dr. Michael Whitfield has received distributions from Celdara
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Medical LLC.
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ACKNOWLEDGEMENTS The authors thank the members of the Robert H. Lurie Comprehensive Cancer Center Pathology Core Facility and the Mouse Histology and Phenotyping Laboratory for their
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Whitfield. For clinical inquiries please contact Dr. Hinchcliff.
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assistance with immunohistochemistry. For gene expression inquiries please contact Dr.
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ACCEPTED MANUSCRIPT TABLE 1. Baseline Clinical Characteristics
All subjects with SSc (N = 68)
Improver during MMF Treatment at 12 mo. (N = 10)
Non-Improver during MMF Treatment at 12 mo. (N = 12)
Other subjects with SSc (N = 46)
41.6 (11.7)
50.25 (11.1)
49.5 (4.1)
55.08 (5.8)
49.2 (12.8)
Sex, N (%) women
15 (68%)
62 (91%)
9 (90%)
10 (83%)
43 (94%)
Race, N (%) white
15 (68%)
52 (76%)
9 (90%)
9 (75%)
34 (74%)
SSc subtype, N (%) diffuse mRSS at baseline
NA
51 (75%)
8 (80%)
12 (100%)
31 (67%)
NA
15.5 (9.8)
14.5 (3.9)
17.3 (8.8)
15.3 (11.0)
mRSS at 12 months
NA
13.6 (10.5)
7.4 (2.5)
18.6 (11.4)
13.8 (11.0)
Raynaud disease duration at baseline, median (range) mo. Disease duration from first non-Raynaud at baseline, median (range) mo. SSc-specific antibodies, N (%)
NA
23 (0-237)
12 (1-237)
9 (0-45)
36 (6-212)
NA
22 (1-225)
Scl-70
NA
22 (32%)
RNA Pol III
NA
19 (28%)
Age, years
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Mean (SD) or as indicated
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Control subjects (N = 22)
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SSc Subjects
15 (3-225)
10 (1-81)
27 (2-224)
2 (20%)
7 (58%)
13 (28%)
3 (30%)
3 (25%)
13 (28%)
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SSc=Systemic sclerosis, MMF=mycophenolate mofetil, mRSS=modified Rodnan Skin Score, Scl-70=anti-topoisomerase I, RNA pol III=RNA polymerase III, NA=not applicable.
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FIGURE LEGENDS
Figure 1: Overview of study design and intrinsic gene expression analysis.
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a. Flowchart of subjects through clinical study. b. 2500 probes were selected with a False Discovery Rate of 0.14% from 163 baseline arrays by intrinsic gene analysis by subject. This hierarchical clustering dendrogram shows the normal-like (green), limited (yellow),
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inflammatory (purple), and fibroproliferative (red) groups. Significance of clustering was determined by SigClust (p≤0.0001). c. 651 genes in improvers and d. 1067 genes in non-
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improvers were differentially expressed between baseline and 12-month (post) biopsies (FDR<5%; arm and flank biopsies used). The gene centroid (average of all arrays in a class) is displayed. Selected genes and pathways are displayed to the right of the centroid. Bolded gene
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symbols are annotated to the pathway/GO term in bold.
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Figure 2: The inflammatory signature is attenuated by MMF but rebounds in subjects that cease MMF treatment at 24 months.
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ssGSEA normalized enrichment scores (NES) were used to summarize changes in inflammatory gene expression during MMF treatment. a. The inflammatory NES of completers were hierarchically clustered and displayed as a heatmap b-c. and as line plots for select subjects. d-f.
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Three subjects lose their inflammatory signature during treatment and rebound at 36 months after treatment cessation. g-i. Three subjects who continue treatment do not show an increase in
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inflammatory signature. An arrow indicates when treatment began. A dashed line indicates when treatment stopped. The purple line indicates NES. The black dashed line indicates mRSS.
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Figure 3: Changes in CCL2 expression in skin, CCL2 concentration in sera, and monocyte migration of SSc patients treated with MMF.
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CCL2 mRNA levels were quantified using qRT-PCR and normalized to beta-actin mRNA in the a. Treatment Discontinued and b. Treatment Continued groups. c. ELISA was used to measure circulating CCL2 of SSc patients at baseline (n=3), 3mo of MMF (n=2), and >16mo of MMF
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(n=4) and healthy controls (n=4, females, >30y) in pg/mL. d. Relative monocyte migration toward sera from SSc patients and sera or plasma from healthy controls (n=5, females, >30y)
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Figure 4. Myeloid dendritic cells, T-lymphocytes and macrophages contribute significantly to the inflammatory gene expression signature.
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a. Six subjects highlighted in figure 2 show a high correlation between their individual cell typespecific NES scores and their inflammatory NES scores across the time course for dendritic cells (DCs; r=0.83), macrophages (r=0.60), and T-lymphocytes (r=0.77). b-c. The cell type NES
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scores are plotted against time (base, 6mo, 12mo, 24mo, 36mo) and are split between subjects who discontinue MMF at 24 months (b. Treatment Discontinued) and subjects who continue
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Figure 5: Immunohistochemistry shows reductions in DCs and macrophages during MMF treatment. a-b. Immunohistochemistry staining targeting CD163 (macrophage marker) of arm biopsy slides.
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CD163 counts were plotted over time for subjects 03, 06, 08, 10, 17, 28. cd. Immunohistochemistry staining for CD163 in baseline (c) and 36mo (d) biopsies from SSc_17 (Treatment Continued). e-f. Immunohistochemistry staining targeting CD1c (mDC marker) of
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arm biopsy slides. CD1c counts were plotted over time for the same subjects. g-i. Immunohistochemistry staining for CD1c in baseline (g), 24mo (h), and 36mo (i) biopsies from
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SSc_08 (MMF ceased at 24mo, Treatment Discontinued). Data not available for all subjects at all time points; missing data denoted by “x”. An arrow indicates when treatment started. A
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