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Division of Rheumatology, Department of Internal Medicine, Northwestern University Feinberg School of Medicine, 240 E Huron Street, Suite M300, Chicago, Illinois 60611, USA
Department of Internal Medicine, Division of Rheumatology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USADepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USADepartment of Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
Heterogeneity in systemic sclerosis (SSc) confounds clinical trials. We previously identified “intrinsic” gene expression subsets by analysis of SSc skin. Here we test the hypotheses that skin gene expression signatures including intrinsic subset are associated with modified Rodnan skin score (MRSS) improvement during mycophenolate mofetil (MMF) treatment. Gene expression and intrinsic subset assignment were measured in 12 SSc patients’ biopsies and 10 controls at baseline, and from serial biopsies of 1 cyclophosphamide-treated patient and 9 MMF-treated patients. Gene expression changes during treatment were determined using paired t-tests corrected for multiple hypothesis testing. MRSS improved in four of seven MMF-treated patients classified as the inflammatory intrinsic subset. Three patients without MRSS improvement were classified as normal-like or fibroproliferative intrinsic subsets. A total of 321 genes (false discovery rate (FDR)<5%) were differentially expressed at baseline between patients with and without MRSS improvement during treatment. The expression of 571 genes (FDR<10%) changed between pre- and post-MMF treatment biopsies for patients showing MRSS improvement. Gene expression changes in skin are only seen in patients with MRSS improvement. Baseline gene expression in skin, including intrinsic subset assignment, may identify SSc patients whose MRSS will improve during MMF treatment, suggesting that gene expression in skin may allow targeted treatment in SSc.
Abbreviations
ANA
antinuclear antibody
COMP
cartilage oligomeric matrix protein
CTGF
connective tissue growth factor
dcSSc
diffuse cutaneous systemic sclerosis
FDR
false discovery rate
H&E
hematoxylin and eosin
HRCT
high-resolution computed tomography of the thorax
IL-6
interleukin-6
ILD
interstitial lung disease
MMF
mycophenolate mofetil
MRSS
modified Rodnan skin score
pFDR
positive false discovery rate
qRT–PCR
quantitative reverse transcriptase–PCR
SSc
systemic sclerosis
TSP-1
thrombospondin-1
Introduction
Systemic sclerosis (SSc; scleroderma) is a phenotypically diverse disease whose pathological hallmark is fibrosis (
Patterns and predictors of change in outcome measures in clinical trials in scleroderma: an individual patient meta-analysis of 629 subjects with diffuse cutaneous systemic sclerosis.
Patterns and predictors of change in outcome measures in clinical trials in scleroderma: an individual patient meta-analysis of 629 subjects with diffuse cutaneous systemic sclerosis.
). This approach has classified SSc patients into four pathway-centric “intrinsic” gene expression subsets termed fibroproliferative, inflammatory, limited, and normal-like (
). This study tests the hypotheses that the identification of gene expression signatures in skin, including intrinsic subset assignment, may identify patients who are likely to improve during mycophenolate mofetil/MMF (Cellcept, Roche) treatment, and that identification of changes in gene expression during treatment in improvers may elucidate important deregulated molecular pathways involved in SSc skin disease.
MMF inhibits purine synthesis, reduces lymphocyte proliferation, and attenuates fibrosis in vitro (
A pilot study of mycophenolate mofetil combined to intravenous methylprednisolone pulses and oral low-dose glucocorticoids in severe early systemic sclerosis.
). Moreover, a prospective study demonstrated that reduced expression of certain pro-fibrotic proteins in skin accompanied improvement in lung function in some MMF-treated patients (
) Unfortunately, no biomarkers to predict treatment response have been identified. The present study was conducted to determine whether analyses of gene expression in skin biopsies could identify useful biomarkers to predict response during MMF therapy.
Results
Subject selection and clinical characteristics
Thirty-two subjects (22 SSc patients and 10 controls) were included (Table 1). SSc-specific therapies included MMF (n=11), methotrexate (n=2), cyclophosphamide (n=1), and minocycline (n=1) (Supplementary Table 1 online). Of the 11 MMF-treated patients, 7 patients met MMF clinical response study entry criteria. Two patients prescribed MMF (SSc04 and SSc07) were ineligible with a baseline MRSS <11, and two patients (SScReg 1067 and 1156) were taking MMF at study entry. Of the seven MMF-naïve patients with baseline MRSS≥11 who were prescribed MMF, four were classified as improvers and three were classified as non-improvers (Supplementary Figure 1 online).
Table 1Baseline clinical characteristics
Control subjects (N=10)
SSc patients
All SSc (N=22)
Improver during MMF treatment (N=4)
Non-improver during MMF treatment (N=3)
Other SSc patients (N=15)
Age, median (range) years
37 (30–63)
48 (21–65)
50 (40–54)
51 (51–65)
45 (21–60)
Sex, N (%) female
7 (70%)
21 (95%)
4 (100%)
3 (100%)
14 (93%)
Race, N (%) Caucasian
6 (60%)
13 (59%)
2 (50%)
2 (67%)
9 (60%)
SSc subtype, N (%) diffuse
NA
20 (91%)
4 (100%)
3 (100%)
13 (87%)
MRSS, median (range)
NA
14.5 (4–35)
18.5 (13–32)
14 (12–14)
15 (4–35)
Raynaud disease duration, median (range) months
NA
17.5 (2–152)
7.5 (4–13)
14 (5–124)
27 (2–152)
Disease duration from first non-Raynaud, median (range) months
To validate MRSS response, H&E histology and cartilage oligomeric protein (COMP) immunofluorescence were assessed using pre- and post-treatment arm biopsies from improvers and non-improvers (
Cartilage oligomeric matrix protein expression in systemic sclerosis reveals heterogeneity of dermal fibroblast responses to transforming growth factor beta.
). Patients’ biopsies demonstrated increased fibrosis compared with a representative control. Improvers, and one non-improver, whose arm MRSS decreased showed reduced fibrosis (Figure 1a). In contrast, two of three non-improvers demonstrated persistent fibrosis. COMP immunofluorescence was significantly reduced in improvers compared with non-improvers (Figure 1b) (P=0.0016 and P=0.35, respectively, two-sample t-test comparing the difference between pre- and post-treatment intensity). These data support the validity of MRSS as an outcome marker.
Figure 1Changing pathological factors in the skin during treatment. Hematoxylin and eosin–stained skin biopsies. (a) Arm biopsy from a healthy control subject (bar=20μm), and biopsy pairs (before and after treatment as indicated) from three non-improvers (upper panel) and four improvers (lower panel) during mycophenolate mofetil (MMF) treatment: representative photomicrographs. Total and arm modified Rodnan skin score (MRSS) and fibrosis score are listed below. (b) Cartilage oligomeric matrix protein (COMP) immunofluorescence for pre- and post-treatment biopsies for a healthy volunteer (N1000) and four improvers (SSc3, 5, 6, and 10) and three non-improvers (SSc8, 12, and 16) with quantification below. Bar=50μm.
Table 1 presents clinical characteristics. In all, 95/70% of patients/controls were women, respectively. Median SSc disease duration at biopsy was 19/17.5 months since the first Raynaud/non-Raynaud symptom. In all, 91% of patients had dcSSc, and 100% had positive ANAs. Fourteen patients (64%) had speckled ANA patterns, 12 patients (55%) had nucleolar ANA patterns, and 7 (32%) patients had homogenous ANA patterns. Anticentromere antibodies were absent, but seven (32%) patients had positive Scl-70, and 5 out of 11 (45%) had anti-RNA polymerase III autoantibodies. There were no statistically significant differences in age, sex, and ethnicity between patients and controls. There were no statistically significant differences in ANA pattern, SSc-specific serum autoantibodies, prior treatments, baseline MRSS, and disease duration (irrespective of the definition) between patients who were and were not prescribed MMF.
No MMF-treated patients had evidence of significant cardiac disease (Supplementary Table 3 online). In all, 8 out of 9 MMF-treated patients underwent high-resolution computed tomography of the thorax (HRCT) for suspected interstitial lung disease (ILD). Six had mild–moderate ILD (<50% lung involvement), and two had moderate–severe ILD (≥50% lung involvement; Supplementary Table 3 online).
To identify factors that may be associated with clinical response regardless of treatment, data from 14 subjects with a baseline MRSS ≥11 and ≥1 follow-up MRSS were examined. Seven patients demonstrated MRSS improvement ≥5 (mean follow-up of 11 months). There were no statistically significant differences in ANA pattern, SSc-specific autoantibodies, and baseline MRSS or lung parameters between clinical improvers and non-improvers (Supplementary Table 4 online). These data suggest that the two patient groups (improvers and non-improvers during MMF treatment, and clinical improvers and non-improvers independent of treatment) were similar.
Recapitulation of the SSc intrinsic subsets
To assign patients to the “intrinsic” gene expression subsets defined previously (
), skin biopsies from the cohort were analyzed (Figure 2). To identify intrinsic genes, we performed intrinsic gene analysis and identified genes with consistent expression among forearm–back pairs from an individual, but with high variation across the cohort. A total of 2775 genes were identified (false discovery rate/FDR 3%) and used for intrinsic subset classification (Figure 2).
Figure 2Improvers cluster within the inflammatory intrinsic subset. We selected 2,775 intrinsic genes with a false discovery rate of 3%. Genes and microarray samples were clustered hierarchically. The sample dendrogram (a) shows the statistically significant intrinsic groups. Branch points above each asterisk (*) are significant at P≤0.005. The dendrogram branches are colored to reflect the major intrinsic subsets of normal-like (green), inflammatory (purple), and diffuse proliferation (red). Patient identifiers indicate systemic sclerosis samples (SSc) and normal healthy controls (Norm); those in the mycophenolate mofetil study are colored to reflect improvers (blue) and non-improvers (orange). (b) Overview of the gene expression profiles. (c, d) Inflammatory clusters; (e) mitotic fibroproliferative cluster; (f) DNA replication proliferation cluster.
We grouped genes and arrays by average linkage hierarchical clustering and identified significant clusters using SigClust with Bonferroni correction for multiple testing (
). Four SSc intrinsic subsets were delineated. Several branch points have low corrected P-values (P<0.005; Figure 2a), indicating significant differences in gene expression.
These data recapitulate the intrinsic subsets reported previously (
). These groups are normal-like (Figure 2a, green branches), inflammatory (purple), and fibroproliferative (red). We find consistent intrinsic subset assignment regardless of the time point analyzed and of treatment (Figure 2a;
). An overview of expression levels of the 2775 intrinsic genes is shown, with specific groups of genes indicated (Figure 2b). Groups of genes are found that correspond to the normal-like (NL), inflammatory (Figure 2c and d), and the fibroproliferative subsets (Figure 2e and f). This provides a third, independent validation of the SSc intrinsic subsets that includes longitudinally collected skin biopsies.
Select genes are shown in Figure 2c–f. These include CCL2, TNC, CTGF, PAI1, and Granzyme B in the inflammatory groups (Figure 2c and d). CCL2 stimulates chemotaxis of monocytes and basophils, and it was identified as a common target deregulated in the inflammatory intrinsic subset, the scleroderma graft versus host disease (sclGVHD) mouse model, and the fibroblasts IL-13 responsive gene signatures (
). Two proliferation groups are evident. One proliferation group includes genes involved in mitosis (Figure 2e) and the second includes genes associated with the process of DNA replication that show peak expression in G1/S phase (Figure 2f;
Improvers during MMF therapy map to the inflammatory SSc intrinsic subset
Next, the intrinsic subset of the seven MMF-naive patients who met the inclusion criteria was determined (four improvers: SSc03, 05, 06, 10, and three non-improvers: SSc08, 12, 16; Table 1). It was hypothesized that improvers would map to the inflammatory intrinsic subset because MMF decreases lymphocyte proliferation, and non-improvers would map to one of the other subsets. Median disease duration for improvers during MMF treatment was 7.5 and 14 months, defined as the time from the first Raynaud or non-Raynaud symptom to the baseline biopsy date, respectively. All improvers demonstrated ANAs (two had isolated speckled and two demonstrated nucleolar/speckled patterns) and had dcSSc. SSc-specific autoantibodies were observed in one treatment improver and one non-improver. All MMF non-improvers had dcSSc (Table 1).
Patients with MRSS improvement during MMF treatment (Figure 2a; blue identifiers) were classified in the inflammatory intrinsic subset (P=0.029, Fisher’s exact test). Patients without clinical improvement during MMF were classified in the normal-like (SSc16) or fibroproliferative (SSc08 and SSc12) intrinsic subsets. The MRSS of one treatment-naïve patient in the inflammatory subset worsened; one patient previously receiving MMF for 1 month showed stable MRSS. These data indicate that a subset of SSc patients who demonstrate an inflammatory gene expression signature improve during MMF treatment, whereas patients with other intrinsic subset signatures are not likely to improve.
Biomarkers of clinical improvement during MMF therapy
To identify gene expression signatures that may predict MMF response, we examined gene expression at baseline in arm and back biopsies between patients with or without clinical improvement during MMF treatment. There were 393 probes (321 genes) whose expression differed at baseline between improvers and non-improvers (FDR<5%). In all, 113 probes (90 genes) were increased, and 280 probes (231 genes) were decreased in improvers relative to non-improvers during MMF treatment at baseline (Figure 3a and b).
Figure 3Comparison of baseline gene expression between improvers and non-improvers. Baseline gene expression in arm and back samples between improvers (Imp) and non-improvers (Non-imp) was compared. (a) Blue identifiers indicate improvers and gold indicates non-improvers. (b) There were 321 genes identified (false discovery rate <5%) with significant differential expression between improvers and non-improvers during mycophenolate mofetil treatment.
Analysis of enriched functional annotations in the 90 genes with high expression in improvers showed baseline differences in genes involved in purine metabolism and response to inflammation (PRPS1, NFKB2, CXCL1, FKBP1C). Improvers had higher expression levels of PRPS1 necessary for purine nucleotide biosynthesis, and NFKB2, a subunit of NFKB protein complex that activates inflammation and immune function genes. CXCL1 encodes a secreted growth factor that has a role in inflammation and as a chemoattractant for neutrophils; FKBP1C is similar to FKBP1A that maintains the inactive conformation of transforming growth factor beta-receptor 1 and blocks the activin signal. Genes with high expression in improvers showed enrichment for genes typically expressed in lymphocytes (P=0.004), monocytes (P=0.035), and cartilage (P=0.028; all Benjamini-corrected). Genes with decreased expression in improvers showed enrichment for genes associated with Ras signaling (P=0.018) and regulation of cell communication (P=0.036; both Benjamini corrected). The full list with nominal and corrected P-values are given in Supplementary Tables 5 and 6 online. Enrichment of NFKB signaling, and lymphocyte and chemokine chemoattractants, is consistent with assignment of improvers to the inflammatory intrinsic subset, whereas Ras signaling, which is decreased in improvers, is generally enriched in the fibroproliferative subset (
Gene expression changes during MMF treatment in improvers
To identify genes whose expression changed during MMF treatment, we analyzed the gene expression in skin biopsies from MMF-treated patients who met the inclusion and response criteria. There were 610 probes (571 genes; FDR <10%) whose expression significantly changed during MMF treatment in improvers exclusively (Figure 4). Genes with the highest fold change between baseline and post-treatment included PBEF1, CXCL1, HAT1, IL17D, SFRP2, PDGFRL, IL16, COL13A1, THBS2, IGFBP5, WNT3, DKK1/2, and WIF1.
Figure 4Gene expression changes during mycophenolate mofetil (MMF) treatment between improvers and non-improvers. (a) A total of 571 genes showed changes in expression during MMF treatment (false discovery rate <10%). Patients who were classified as non-improvers (b) show low levels expression of these genes, (c, d) which either do not change expression or show increased expression.
Genes whose expression increased during MMF treatment in the improvers were enriched in extracellular matrix component (P=0.004, Benjamini corrected). Genes whose expression decreased during MMF treatment in improvers were involved in cell cycle and cell division (e.g., organelle fission, P=6.55E−04, mitotic cell cycle, P=7.05E−04), as well as in the NOD-like receptor signaling pathway responsible for NFKB activation, cytokine production, and apoptosis (P=0.011). Complete lists with nominal and corrected P-values are provided (Supplementary Tables 7 and 8 online). There were no significant changes in gene expression between baseline and post treatment in the non-improvers during MMF treatment when corrected for multiple testing.
Quantitative RT–PCR validation
The expression of genes from the inflammatory intrinsic subset or those that changed during MMF treatment was validated. RNA was examined in duplicate by quantitative reverse transcriptase–PCR (qRT–PCR). Figure 5 shows connective tissue growth factor ((CTGF) and interleukin-6 (IL-6); inflammatory intrinsic subset) and thrombospondin-1 (TSP-1; change during MMF treatment) expression values. Mirroring microarray data, improvers, as compared with non-improvers, demonstrated higher baseline CTGF, IL-6, and TSP-1 expression during MMF treatment. CTGF decreased during treatment in improvers and increased or remained stable in non-improvers, although the changes were significant in one improver (P=0.006). Pre-treatment IL-6 and TSP-1 levels were higher in improvers than in non-improvers (P=0.003 and P=0.10, respectively). IL-6 and TSP-1 expression decreased during treatment in improvers, and either remained stable or increased in non-improvers (P=0.25 and P=0.14, respectively).
Figure 5Validation of biologically relevant microarray findings using quantitative reverse transcription PCR immunofluorescence. Results are the relative expression values normalized to the mean expression in arm samples of control subjects, *P<0.05. CTGF, connective tissue growth factor; TSP, thrombospondin.
). The reproducibility of the SSc intrinsic subsets in the present cohort, as well as in the two previously recruited cohorts, suggests that intrinsic subset classification will be a useful SSc classification method.
We found that biopsies from improvers during MMF therapy mapped to the inflammatory intrinsic subset, whereas non-improvers were classified as fibroproliferative and normal-like subsets. Additionally, a specific 321-gene baseline expression signature was identified in skin that was associated with MRSS improvement during MMF treatment was absent in non-improvers. Measuring the 321-gene baseline signature and/or intrinsic subset classification may be useful for selection of appropriate patients for MMF therapy to treat SSc skin disease.
There were 571 genes whose expression changed significantly during MMF treatment in improvers, but not in non-improvers. Interestingly, many of the genes that are implicated in fibrosis, such as COL1A1, COL1A2, TIMP2, and ACTA2, demonstrated statistically significant increases in expression during MMF treatment in improvers. This was an unexpected finding that suggests that dermal repair and tissue remodeling cause transient increased expression of genes classically considered “pro-fibrotic”.
Improvers during MMF treatment had longer disease duration at study entry compared with non-improvers, and thus shorter disease duration does not explain response heterogeneity. Baseline clinical characteristics were similar between the seven MMF-treated patients and the entire SSc cohort, and between the clinical improvers and non-improvers independent of treatment (Table 1 and Supplementary Tables 3 and 4 online). Importantly, clinical response was not associated with autoantibody status. These data suggest that skin gene expression provides additional information that may have clinical relevance.
Results demonstrate that only improvers demonstrate significant changes in gene expression in longitudinally collected skin biopsies. Similar findings were noted in imatinib-treated patients as well (
). Importantly, gene expression changes can precede MRSS improvement ((e.g., SSc10 demonstrated gene expression response at 6mo (data not shown), and MRSS response at 12mo (i.e., baseline and 6mo MRSS=13, 12mo MRSS=7)).
Study strengths include prospective study design, clinically well-characterized study population, performance of skin scores, and biopsies by one investigator. Study limitations include lack of validated definition of active skin disease, randomization and washout procedures, open-label trial design, and small sample size.
The results herein demonstrate that intrinsic subset assignment is a clinically relevant SSc classification method. We provide proof of concept that quantitative measurement of genome-wide gene expression in skin using DNA microarray may be useful to identify appropriate patients to receive MMF, and to elucidate genes that are involved in the pathogenesis of SSc skin disease and its resolution during MMF treatment.
Materials and Methods
Inclusion criteria for intrinsic subset analysis
Patients fulfilling the American College of Rheumatology SSc criteria (1980) or three out of five criteria for CREST (calcinosis, Raynauds, esophageal dysmotility, sclerodactyly, telangiectasias) were eligible. In all, 22 out of 31 subjects who underwent skin biopsies between November 2008 and September 2010 were included. Nine patients were prescribed MMF (2,000mg per day), and one received oral cyclophosphamide (2mgkg−1 per day) in divided doses for active SSc skin disease in the treating physician’s opinion. In addition, two patients were taking MMF (2,000mg per day) at baseline biopsy time. Biopsy pairs (4mm) from the clinically involved (dorsal forearm, 15cm proximal to the ulnar styloid) and clinically uninvolved (back, posterior iliac crest midway between lumbar spinous process and anterior superior iliac spine) skin from the non-dominant side of the body were obtained at baseline. Serial biopsies 3mm proximal (arm) or inferior (back) to previous biopsies were performed at 6 and 12 months for MMF-treated patients. Arm and back biopsies from 10 biologically unrelated control subjects recruited from Northwestern University were obtained. One biopsy pair (forearm and back) was placed in RNAlater (Applied Biosystems, Ambion, Carlsbad, CA) and used for DNA microarray analysis; the other biopsy pair was placed in formalin for histology. A single forearm biopsy was obtained for DNA microarray analyses from 12 SSc patients with stable skin disease in order to have power to detect intrinsic subsets (Supplementary Table 1 online).
Subjects gave written informed consent in accordance with the Declaration of Helsinki Protocols and Northwestern University Institutional Review Board Guidelines. Control subjects completed demographic and prior medical history questionnaires. Medical histories and physical examinations were completed at study visits. One physician blinded to gene expression and clinical data performed MRSS (
). Serum ANA, anti-topoisomerase I, anticentromere, and anti-RNA polymerase III antibody titers were measured by indirect immunofluorescence at Specialty Laboratories, Valencia, CA.
Patients underwent cardiopulmonary disease screening with Doppler echocardiography, pulmonary function tests, and HRCT of the thorax within 3 months of the baseline visit. An echocardiographer, blinded to clinical data, performed quantitative measurements on echocardiograms using a preestablished research protocol. One chest radiologist, also blinded to clinical data, scored HRCT examinations (
Thin-section CT obtained at 10-mm increments versus limited three-level thin-section CT for idiopathic pulmonary fibrosis: correlation with pathologic scoring.
). Five lung lobes were scored (0=no, 1=1–5%, 2=6–25%, 3=26-50%, 4=51–75%, and 5=76–100% involvement) for total lung disease degree.
Inclusion and response criteria for improvement during MMF study
Patients with baseline MRSS ≥11, newly prescribed MMF for active skin disease, willingness to undergo serial skin biopsies, and referral to MH for study participation were included. Patients were classified as improvers if the MRSS improved ≥5 from baseline (the minimal clinically important difference) (
). A baseline skin score ≥11 was required for inclusion, because sclerodactyly contributes 1–6 MRSS points, and enrolling patients with MRSS <11 would confound detection of meaningful change.
Skin pathology
Pre- and post-treatment arm biopsies were paraffin-embedded, and 4-μm sections were H&E stained. Photomicrographs were taken using an Olympus BX41 microscope and an Olympus DP71 camera at × 4 magnification (Olympus, Center Valley, PA). Two dermatopathologists blinded to clinical data scored dermal fibrosis (0=no fibrosis to 3=severe fibrosis) (
COMP levels were assessed. Sections (4 μm) were incubated with primary antibodies against COMP (Accurate Chemical & Scientific, Westbury, NY, 1:20 dilution), followed by mouse Alexa-fluor secondary antibodies (Invitrogen, 1:100). Nuclei were identified using DAPI. Immunofluorescence was evaluated in randomly selected fields under a Zeiss UV Meta 510 confocal microscope (Carl Zeiss, Jena, Germany), and staining intensity was quantified with Image J (NIH).
DNA microarray hybridization
Tissue homogenization was performed using Qiagen TissueLyser II. RNA purification was carried out in QIAcube with Qiagen’s RNeasy Fibrous Tissue Mini Kit (Qiagen, Gaithersburg, MD). The Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA) assessed RNA integrity. Samples had RNA integrity numbers>7. RNA concentration was measured with Thermo Scientific NanoDrop 2000 Spectrophotometer (Wilmington, DE). A measure of 200ng of total RNA was amplified and labeled with Agilent Quick-Amp Labeling Kits (
). Cy3-labeled sample and Cy5-labeled Universal Human Reference RNA (Stratagene, La Jolla, CA) were co-hybridized to Agilent Human Genome (4 × 44K) Microarrays (G4112F). Data were Log2 Lowess-normalized and filtered for probes with intensity ≥1.5-fold over local background in Cy3 or Cy5 channels. Data were multiplied by -1 to convert them to Log2(Cy3/Cy5) ratios. Probes with >20% missing data were excluded. Microarray data from this paper is available from NCBI GEO (http://www.ncbi.nlm.nih.gov/geo/) using accession number GSE45485.
Intrinsic subset assignment
Intrinsic subsets were determined as previously described (
). FDR for each intrinsic score was assessed by permuting rows and columns and counting the genes that received≥same score in each of 100 data randomizations. At an FDR of 3%, 2775 genes were identified and used to assign the intrinsic subset.
Data were organized by two-dimensional average linkage hierarchical clustering using Pearson correlation. SigClust was used to determine statistical significance of array clustering (
). Amplicons were analyzed by PCR using SYBR Green PCR Master Mix (Applied Biosystems, Foster City, CA) on the Applied Biosystems 7500 Prism Sequence Detection System (Supplementary Table 2 online). Results are fold-change relative to the mean expression for control arm samples.
Baseline gene expression signature associated with clinical improvement
Genes differentially expressed at baseline between clinical improvers and non-improvers were identified. Lowess-normalized Log2(Cy3/Cy5) gene expression measures for arm and back samples were centered on the median expression value across samples. Gene expression differences were detected using two-sample t-tests. The probability of false positives was assessed using the positive FDR (pFDR) method (
) to calculate q-values for each test statistic using the Bioconductor package: QVALUE. Genes with an FDR<5% were investigated. Functional enrichment was performed with g:GOSt within g:Profiler (
). Agilent probe IDs were converted to Ensembl gene IDs via g:Convert. g:GOSt analyses were performed with default options limiting output to significant results (P-value<0.05 after multiple testing correction). For DAVID, the following annotations were analyzed: Gene Ontology, KEGG, and REACTOME pathways, as well as CGAP SAGE tissue expression. Terms with Benjamini-corrected P-value<0.05 were evaluated.
Clinical improvement gene expression signature
A clinical improvement signature was identified by comparing gene expression in arm and back samples between baseline and post treatment. The last biopsy obtained was analyzed for non-improvers. Biopsy at the time of MRSS improvement was used for improvers. Data were centered, significant changes in gene expression were identified (FDR<10%), and functional enrichment analyses were conducted as previously described.
Statistical analyses
Continuous variables were expressed by median and range. Statistically significant differences were assessed by t-tests or Wilcoxon Rank Sum test. Categorical variables were compared by chi-squared statistic or Fisher’s exact test. For all analyses, a two-sided P-value <0.05 was considered significant. Stata version 10.1 (College Station, TX) was used.
ACKNOWLEDGMENTS
We thank Pedram Gerami and Joan Guitart, Department of Dermatology, Feinberg School of Medicine, for evaluating dermatopathology. This work was supported in part by the NIH K12 HD055884 from the NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (MH), a research award from the Arthritis Foundation and the Scleroderma Foundation (MH), NIH 610-532-800-6001417 (C-CH), the Scleroderma Research Foundation (MH, MLW), Actelion Entelligence Grant Award (SJS), NIH U01 AR055063 (MLW and RL), NIH-NCI R25CA134286 (JMM), NIH-NIAMS P60 AR48098 (C-CH, JL, RWC), and NIH P50AR060780 (MLW, RL).
Preliminary criteria for the classification of systemic sclerosis (scleroderma). Subcommittee for scleroderma criteria of the American Rheumatism Association Diagnostic and Therapeutic Criteria Committee.
Cartilage oligomeric matrix protein expression in systemic sclerosis reveals heterogeneity of dermal fibroblast responses to transforming growth factor beta.
Thin-section CT obtained at 10-mm increments versus limited three-level thin-section CT for idiopathic pulmonary fibrosis: correlation with pathologic scoring.
Patterns and predictors of change in outcome measures in clinical trials in scleroderma: an individual patient meta-analysis of 629 subjects with diffuse cutaneous systemic sclerosis.
A pilot study of mycophenolate mofetil combined to intravenous methylprednisolone pulses and oral low-dose glucocorticoids in severe early systemic sclerosis.
accepted article preview online 14 March 2013 published online 16 April 2013
Footnotes
MLW, MH, RL, and CCH have filed patent applications for gene expression biomarkers in scleroderma. MLW is a scientific founder and holds an interest in Celdara Medical, LLC.
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