Gene Expression Signatures in Inflammatory and Sclerotic Morphea Skin and Sera Distinguish Morphea from Systemic Sclerosis.

Morphea is an inflammatory fibrotic disorder of the skin that has been likened to systemic sclerosis (SSc). We sought to examine the molecular landscape of morphea by examining lesional skin gene expression and blood biomarkers and comparing the gene expression profiles with those from site-matched nonlesional and SSc lesional skin. We found the morphea transcriptome is dominated by IFN-γ-mediated T helper 1 immune dysregulation, with a relative paucity of fibrosis pathways. Specifically, expression profiles of morphea skin clustered with the SSc inflammatory subset and were distinct from the those of SSc fibroproliferative subset. Unaffected morphea skin also differed from unaffected SSc skin because it did not exhibit pathological gene expression signatures. Examination of downstream IFN-γ-mediated chemokines, CXCL9 and CXCL10, revealed increased transcription in the skin but not in circulation. In contrast to transcriptional activity, CXCL9 was elevated in serum and was associated with active, widespread cutaneous involvement. Taken together, these results indicate that morphea is a skin-directed process characterized by T helper 1 immune-mediated dysregulation, which contrasts with fibrotic signatures and systemic transcriptional changes associated with SSc. The similarity between morphea and the inflammatory subset of SSc on transcriptional profiling indicates that therapies under development for this subset of SSc are also promising for treatment of morphea.

CXCL9 Links Skin Inflammation and Fibrosis through CXCR3-Dependent Upregulation of Col1a1 in Fibroblasts.

Morphea is characterized by initial inflammation followed by fibrosis of the skin and soft tissue. Despite its substantial morbidity, the pathogenesis of morphea is poorly studied. Previous work showed that CXCR3 ligands CXCL9 and CXCL10 are highly upregulated in the sera and lesional skin of patients with morphea. We found that an early inflammatory subcutaneous bleomycin mouse model of dermal fibrosis mirrors the clinical, histological, and immune dysregulation observed in human morphea. We used this model to examine the role of the CXCR3 chemokine axis in the pathogenesis of cutaneous fibrosis. Using the REX3 (Reporting the Expression of CXCR3 ligands) mice, we characterized which cells produce CXCR3 ligands over time. We found that fibroblasts contribute the bulk of CXCL9-RFP and CXCL10-BFP by percentage, whereas macrophages produce high amounts on a per-cell basis. To determine whether these chemokines are mechanistically involved in pathogenesis, we treated Cxcl9-, Cxcl10-, or Cxcr3-deficient mice with bleomycin and found that fibrosis is dependent on CXCL9 and CXCR3. Addition of recombinant CXCL9 but not CXCL10 to cultured mouse fibroblasts induced Col1a1 mRNA expression, indicating that the chemokine itself contributes to fibrosis. Taken together, our studies provide evidence that CXCL9 and its receptor CXCR3 are functionally required for inflammatory fibrosis.

Clinical and Molecular Findings After Autologous Stem Cell Transplantation or Cyclophosphamide for Scleroderma: Handling Missing Longitudinal Data.

OBJECTIVE: Among individuals with systemic sclerosis (SSc) randomized to cyclophosphamide (CYC) (n = 34) or hematopoietic stem cell transplantation (HSCT) (n = 33), we examined longitudinal trends of clinical, pulmonary function, and quality of life measures while accounting for the influence of early failures on treatment comparisons. METHODS: Assuming that data were missing at random, mixed-effects regression models were used to estimate longitudinal trends for clinical measures when comparing treatment groups. Results were compared to observed means and to longitudinal trends estimated from shared parameter models, assuming that data were missing not at random. Longitudinal trends for SSc intrinsic molecular subsets defined by baseline gene expression signatures (normal-like, inflammatory, and fibroproliferative signatures) were also studied. RESULTS: Available observed means for pulmonary function tests appeared to improve over time in both arms. However, after accounting for participant loss, forced vital capacity in HSCT recipients increased by 0.77 percentage points/year but worsened by -3.70/year for CYC (P = 0.004). Similar results were found for diffusing capacity for carbon monoxide and quality of life indicators. Results for both analytic models were consistent. HSCT recipients in the inflammatory (n = 20) and fibroproliferative (n = 20) subsets had superior long-term trends compared to CYC for pulmonary and quality of life measures. HSCT was also superior for modified Rodnan skin thickness scores in the fibroproliferative subset. For the normal-like subset (n = 22), superiority of HSCT was less apparent. CONCLUSION: Longitudinal trends estimated from 2 statistical models affirm the efficacy of HSCT over CYC in severe SSc. Failure to account for early loss of participants may distort estimated clinical trends over the long term.

A genomic meta-analysis of clinical variables and their association with intrinsic molecular subsets in systemic sclerosis.

OBJECTIVES: Four intrinsic molecular subsets (inflammatory, fibroproliferative, limited, normal-like) have previously been identified in SSc and are characterized by unique gene expression signatures and pathways. The intrinsic subsets have been linked to improvement with specific therapies. Here, we investigated associations between baseline demographics and intrinsic molecular subsets in a meta-analysis of published datasets. METHODS: Publicly available gene expression data from skin biopsies of 311 SSc patients measured by DNA microarray were classified into the intrinsic molecular subsets. RNA-sequencing data from 84 participants from the ASSET trial were used as a validation cohort. Baseline clinical demographics and intrinsic molecular subsets were tested for statistically significant associations. RESULTS: Males were more likely to be classified in the fibroproliferative subset (P = 0.0046). SSc patients who identified as African American/Black were 2.5 times more likely to be classified as fibroproliferative compared with White/Caucasian patients (P = 0.0378). ASSET participants sera positive for anti-RNA pol I and RNA pol III autoantibodies were enriched in the inflammatory subset (P = 5.8 × 10-5, P = 9.3 × 10-5, respectively), while anti-Scl-70 was enriched in the fibroproliferative subset. Mean modified Rodnan Skin Score (mRSS) was statistically higher in the inflammatory and fibroproliferative subsets compared with normal-like (P = 0.0027). The average disease duration for inflammatory subset was less than fibroproliferative and normal-like intrinsic subsets (P = 8.8 × 10-4). CONCLUSIONS: We identified multiple statistically significant differences in baseline demographics between the intrinsic subsets that may represent underlying features of disease pathogenesis (e.g. chronological stages of fibrosis) and have implications for treatments that are more likely to work in certain SSc populations.

Mast Cell Activation in the Systemic Sclerosis Esophagus.

INTRODUCTION: Previously, we discovered similar esophageal gene expression patterns in patients with systemic sclerosis (SSc) and eosinophilic esophagitis (EoE) where eosinophil/mast cell-targeted therapies are beneficial. Because SSc and EoE patients experience similar esophageal symptoms, we hypothesized that eosinophil/mast cell-directed therapy may potentially benefit SSc patients. Herein, we determine the association between esophageal mast cell quantities, gene expression and clinical parameters in order to identify SSc patients who may benefit from eosinophil/mast cell-directed therapy. METHODS: Esophageal biopsies from SSc patients and healthy participants were stained for tryptase, a mast cell marker, and associations with relevant clinical parameters including 24h esophageal pH testing were assessed. Intra-epithelial mast cell density was quantified by semi-automated microscopy. Microarray data were utilized for functional and gene set enrichment analyses and to identify intrinsic subset (IS) assignment, an SSc molecular classification system that includes inflammatory, proliferative, limited and normal-like subsets. RESULTS: Esophageal biopsies from 40 SSc patients (39 receiving proton pump inhibition) and eleven healthy participants were studied. Mast cell numbers in both the upper esophagus (rs = 0.638, p = 0.004) and the entire (upper + lower) esophagus (rs = 0.562, p = 0.019) significantly correlated with acid exposure time percentage. The inflammatory, fibroproliferative, and normal-like ISs originally defined in skin biopsies were identified in esophageal biopsies. Although esophageal mast cell numbers in SSc patients and healthy participants were similar, gene expression for mast cell-related pathways showed significant upregulation in the inflammatory IS of SSc patients compared to patients classified as proliferative or normal-like. DISCUSSION: Esophageal mast cell numbers are heterogeneous in SSc patients and may correlate with acid exposure. Patients with inflammatory IS profiles in the esophagus demonstrate more tryptase staining. Mast cell targeted therapy may be a useful therapeutic approach in SSc patients belonging to the inflammatory IS, but additional studies are warranted.

Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement.

OBJECTIVE: We sought to determine histologic and gene expression features of clinical improvement in early diffuse cutaneous systemic sclerosis (dcSSc; scleroderma). METHODS: Fifty-eight forearm biopsies were evaluated from 26 individuals with dcSSc in two clinical trials. Histologic/immunophenotypic assessments of global severity, alpha-smooth muscle actin (aSMA), CD34, collagen, inflammatory infiltrate, follicles and thickness were compared with gene expression and clinical data. Support vector machine learning was performed using scleroderma gene expression subset (normal-like, fibroproliferative, inflammatory) as classifiers and histology scores as inputs. Comparison of w-vector mean absolute weights was used to identify histologic features most predictive of gene expression subset. We then tested for differential gene expression according to histologic severity and compared those with clinical improvement (according to the Combined Response Index in Systemic Sclerosis). RESULTS: aSMA was highest and CD34 lowest in samples with highest local Modified Rodnan Skin Score. CD34 and aSMA changed significantly from baseline to 52 weeks in clinical improvers. CD34 and aSMA were the strongest predictors of gene expression subset, with highest CD34 staining in the normal-like subset (p<0.001) and highest aSMA staining in the inflammatory subset (p=0.016). Analysis of gene expression according to CD34 and aSMA binarised scores identified a 47-gene fibroblast polarisation signature that decreases over time only in improvers (vs non-improvers). Pathway analysis of these genes identified gene expression signatures of inflammatory fibroblasts. CONCLUSION: CD34 and aSMA stains describe distinct fibroblast polarisation states, are associated with gene expression subsets and clinical assessments, and may be useful biomarkers of clinical severity and improvement in dcSSc.

Machine learning predicts stem cell transplant response in severe scleroderma.

OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSCT) compared with cyclophosphamide (CYC). We mapped PBC (peripheral blood cell) samples from the SCOT clinical trial to scleroderma intrinsic subsets and tested the hypothesis that they predict long-term response to HSCT. METHODS: We analysed gene expression from PBCs of SCOT participants to identify differential treatment response. PBC gene expression data were generated from 63 SCOT participants at baseline and follow-up timepoints. Participants who completed treatment protocol were stratified by intrinsic gene expression subsets at baseline, evaluated for event-free survival (EFS) and analysed for differentially expressed genes (DEGs). RESULTS: Participants from the fibroproliferative subset on HSCT experienced significant improvement in EFS compared with fibroproliferative participants on CYC (p=0.0091). In contrast, EFS did not significantly differ between CYC and HSCT arms for the participants from the normal-like subset (p=0.77) or the inflammatory subset (p=0.1). At each timepoint, we observed considerably more DEGs in HSCT arm compared with CYC arm with HSCT arm showing significant changes in immune response pathways. CONCLUSIONS: Participants from the fibroproliferative subset showed the most significant long-term benefit from HSCT compared with CYC. This study suggests that intrinsic subset stratification of patients may be used to identify patients with SSc who receive significant benefit from HSCT.

Safety and Efficacy of Lenabasum in a Phase II, Randomized, Placebo-Controlled Trial in Adults With Systemic Sclerosis.

OBJECTIVE: To assess the safety and efficacy of lenabasum in diffuse cutaneous systemic sclerosis (dcSSc). METHODS: A randomized, double-blind, placebo-controlled, phase II study was conducted at 9 SSc clinics in the US. Adults with dcSSc of ≤6 years' duration who were receiving stable standard-of-care treatment were randomized to receive lenabasum (n = 27) or placebo (n = 15). Lenabasum doses were 5 mg once daily, 20 mg once daily, or 20 mg twice daily for 4 weeks, followed by 20 mg twice daily for 8 weeks. Safety and efficacy were assessed at weeks 4, 8, 12, and 16. RESULTS: Adverse events (AEs) occurred in 63% of the lenabasum group and 60% of the placebo group, with no serious AEs related to lenabasum. Compared to placebo, lenabasum treatment was associated with greater improvement in the American College of Rheumatology Combined Response Index in diffuse cutaneous Systemic Sclerosis (CRISS) score and other efficacy outcome measures that assessed overall disease, skin involvement, and patient-reported function. The median CRISS score increased in the lenabasum group during the study, reaching 0.33, versus 0.00 in the placebo group, at week 16 (P = 0.07 by 2-sided mixed-effects model repeated-measures analysis). Gene expression in inflammation and fibrosis pathways was reduced, and inflammation and fibrosis were improved on histologic evaluation of skin biopsy specimens, in the lenabasum group compared to the placebo group (all P ≤ 0.05). CONCLUSION: Despite a short trial duration in a small number of patients in this phase II study in dcSSc, our findings indicate that lenabasum improves efficacy outcomes and underlying disease pathology with a favorable safety profile.

CDDO-Me Alters the Tumor Microenvironment in Estrogen Receptor Negative Breast Cancer.

The tumor microenvironment (TME) is an essential contributor to the development and progression of malignancy. Within the TME, tumor associated macrophages (TAMs) mediate angiogenesis, metastasis, and immunosuppression, which inhibits infiltration of tumor-specific cytotoxic CD8+ T cells. In previous work, we demonstrated that the synthetic triterpenoid CDDO-methyl ester (CDDO-Me) converts breast TAMs from a tumor-promoting to a tumor-inhibiting activation state in vitro. We show now that CDDO-Me remodels the breast TME, redirecting TAM activation and T cell tumor infiltration in vivo. We demonstrate that CDDO-Me significantly attenuates IL-10 and VEGF expression but stimulates TNF production, and reduces surface expression of CD206 and CD115, markers of immunosuppressive TAMs. CDDO-Me treatment redirects the TAM transcriptional profile, inducing signaling pathways associated with immune stimulation, and inhibits TAM tumor infiltration, consistent with decreased expression of CCL2. In CDDO-Me-treated mice, both the absolute number and proportion of splenic CD4+ T cells were reduced, while the proportion of CD8+ T cells was significantly increased in both tumors and spleen. Moreover, mice fed CDDO-Me demonstrated significant reductions in numbers of CD4+ Foxp3+ regulatory T cells within tumors. These results demonstrate for the first time that CDDO-Me relieves immunosuppression in the breast TME and unleashes host adaptive anti-tumor immunity.

Profibrotic Activation of Human Macrophages in Systemic Sclerosis.

OBJECTIVE: Genome-wide gene expression studies implicate macrophages as mediators of fibrosis in systemic sclerosis (SSc), but little is known about how these cells contribute to fibrotic activation in SSc. We undertook this study to characterize the activation profile of SSc monocyte-derived macrophages and assessed their interaction with SSc fibroblasts. METHODS: Plasma and peripheral blood mononuclear cells (PBMCs) were obtained from whole blood from SSc patients (n = 24) and age- and sex-matched healthy controls (n = 12). Monocytes were cultured with autologous or allogeneic plasma to differentiate cells into macrophages. For reciprocal activation studies, macrophages were cocultured with fibroblasts using Transwell plates. RESULTS: The gene expression signature associated with blood-derived human SSc macrophages was enriched in SSc skin in an independent cohort and correlated with skin fibrosis. SSc macrophages expressed surface markers associated with activation and released CCL2, interleukin-6, and transforming growth factor ß under basal conditions (n = 8) (P < 0.05). Differentiation of healthy donor monocytes in plasma from SSc patients conferred the immunophenotype of SSc macrophages (n = 13) (P < 0.05). Transwell experiments demonstrated that coculture of SSc macrophages with SSc fibroblasts induced fibroblast activation (n = 3) (P < 0.05). CONCLUSION: These data demonstrate that the activation profile of SSc macrophages is profibrotic. SSc macrophages are activated under basal conditions and release mediators and express surface markers associated with both alternative and inflammatory macrophage activation. These findings also suggest that activation of SSc macrophages arises from soluble factors in local microenvironments. These studies implicate macrophages as likely drivers of fibrosis in SSc and suggest that therapeutic targeting of these cells may be beneficial in ameliorating disease in SSc patients.

A Machine Learning Classifier for Assigning Individual Patients With Systemic Sclerosis to Intrinsic Molecular Subsets.

OBJECTIVE: High-throughput gene expression profiling of tissue samples from patients with systemic sclerosis (SSc) has identified 4 "intrinsic" gene expression subsets: inflammatory, fibroproliferative, normal-like, and limited. Prior methods required agglomerative clustering of many samples. In order to classify individual patients in clinical trials or for diagnostic purposes, supervised methods that can assign single samples to molecular subsets are required. We undertook this study to introduce a novel machine learning classifier as a robust accurate intrinsic subset predictor. METHODS: Three independent gene expression cohorts were curated and merged to create a data set covering 297 skin biopsy samples from 102 unique patients and controls, which was used to train a machine learning algorithm. We performed external validation using 3 independent SSc cohorts, including a gene expression data set generated by an independent laboratory on a different microarray platform. In total, 413 skin biopsy samples from 213 individuals were analyzed in the training and testing cohorts. RESULTS: Repeated cross-fold validation identified consistent and discriminative markers using multinomial elastic net, performing with an average classification accuracy of 87.1% with high sensitivity and specificity. In external validation, the classifier achieved an average accuracy of 85.4%. Reanalyzing data from a previous study, we identified subsets of patients that represent the canonical inflammatory, fibroproliferative, and normal-like subsets. CONCLUSION: We developed a highly accurate classifier for SSc molecular subsets for individual patient samples. The method can be used in SSc clinical trials to identify an intrinsic subset on individual samples. Our method provides a robust data-driven approach to aid clinical decision-making and interpretation of heterogeneous molecular information in SSc patients.

Belimumab for the Treatment of Early Diffuse Systemic Sclerosis: Results of a Randomized, Double-Blind, Placebo-Controlled, Pilot Trial.

OBJECTIVE: To assess the safety and efficacy of treatment with belimumab in patients with early diffuse cutaneous systemic sclerosis (dcSSc) treated with background mycophenolate mofetil (MMF). METHODS: In this 52-week, investigator-initiated, single-center, double-blind, placebo-controlled, pilot study, 20 patients with dcSSc recently started on MMF were randomized 1:1 to additionally receive belimumab at 10 mg/kg intravenously or placebo. We assessed safety, efficacy, and differential gene expression. RESULTS: In the belimumab group, the median modified Rodnan skin thickness score (MRSS) decreased from 27 (interquartile range [IQR] 26.5, 31) to 18 (IQR 11, 23) (P = 0.039). In the placebo group, the median MRSS decreased from 28 (IQR 22, 28) to 21 (IQR 14, 25) (P = 0.023). The median change in MRSS was -10 (IQR -13, -9) in the belimumab group and -3.0 (IQR -15, -1) in the placebo group (P = 0.411). There were no significant differences between the groups in the number of adverse events (AEs). A significant decrease in expression of B cell signaling and profibrotic genes and pathways was observed in patients with improved MRSS in the belimumab group but not in the placebo group. CONCLUSION: Patients in both treatment groups experienced significant improvements in MRSS. The median difference was greater in the belimumab group but did not achieve statistical significance in this small pilot study. AEs were similar between the groups. Changes in gene expression were consistent with mechanism of action and showed that clinical response to treatment with belimumab is associated with a significant decrease in profibrotic genes and pathways. Additional studies are needed to determine the role of belimumab in the treatment of dcSSc.

Novel lung imaging biomarkers and skin gene expression subsetting in dasatinib treatment of systemic sclerosis-associated interstitial lung disease.

BACKGROUND: There are no effective treatments or validated clinical response markers in systemic sclerosis (SSc). We assessed imaging biomarkers and performed gene expression profiling in a single-arm open-label clinical trial of tyrosine kinase inhibitor dasatinib in patients with SSc-associated interstitial lung disease (SSc-ILD). METHODS: Primary objectives were safety and pharmacokinetics. Secondary outcomes included clinical assessments, quantitative high-resolution computed tomography (HRCT) of the chest, serum biomarker assays and skin biopsy-based gene expression subset assignments. Clinical response was defined as decrease of >5 or >20% from baseline in the modified Rodnan Skin Score (MRSS). Pulmonary function was assessed at baseline and day 169. RESULTS: Dasatinib was well-tolerated in 31 patients receiving drug for a median of nine months. No significant changes in clinical assessments or serum biomarkers were seen at six months. By quantitative HRCT, 65% of patients showed no progression of lung fibrosis, and 39% showed no progression of total ILD. Among 12 subjects with available baseline and post-treatment skin biopsies, three were improvers and nine were non-improvers. Improvers mapped to the fibroproliferative or normal-like subsets, while seven out of nine non-improvers were in the inflammatory subset (p = 0.0455). Improvers showed stability in forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLCO), while both measures showed a decline in non-improvers (p = 0.1289 and p = 0.0195, respectively). Inflammatory gene expression subset was associated with higher baseline HRCT score (p = 0.0556). Non-improvers showed significant increase in lung fibrosis (p = 0.0313). CONCLUSIONS: In patients with SSc-ILD dasatinib treatment was associated with acceptable safety profile but no significant clinical efficacy. Patients in the inflammatory gene expression subset showed increase in skin fibrosis, decreasing pulmonary function and worsening lung fibrosis during the study. These findings suggest that target tissue-specific gene expression analyses can help match patients and therapeutic interventions in heterogeneous diseases such as SSc, and quantitative HRCT is useful for assessing clinical outcomes. TRIAL REGISTRATION: Clinicaltrials.gov NCT00764309.

Limited cutaneous systemic sclerosis skin demonstrates distinct molecular subsets separated by a cardiovascular development gene expression signature.

BACKGROUND: Systemic sclerosis (SSc; scleroderma) is an uncommon autoimmune rheumatic disease characterised by autoimmunity, vasculopathy and fibrosis. Gene expression profiling distinguishes scleroderma from normal skin, and can detect different subsets of disease, with potential to identify prognostic biomarkers of organ involvement or response to therapy. We have performed gene expression profiling in skin samples from patients with limited cutaneous SSc (lcSSc). METHODS: Total RNA was extracted from clinically uninvolved skin biopsies of 15 patients with lcSSc and 8 healthy controls (HC). Gene expression profiling was performed on a DNA oligonucleotide microarray chip. Differentially expressed genes (DEG) were identified using significance analysis of microarrays (SAM). Functional enrichment analysis of gene signatures was done via g:Profiler. RESULTS: There were 218 DEG between lcSSc and HC samples (false discovery rate <10%): 181/218 DEG were upregulated in lcSSc samples. Hierarchical clustering of DEG suggested the presence of two separate groups of lcSSc samples: "limited 1" and "limited 2". The limited-1 group (13 samples, 10 unique patients) showed upregulation of genes involved in cell adhesion, cardiovascular system (CVS) development, extracellular matrix and immune and inflammatory response. The CVS development signature was of particular interest as its genes showed very strong enrichment in response to wounding, response to transforming growth factor (TGF)-ß and kinase cascade. Neither limited-2 samples (six samples, five unique patients) nor HC samples showed functional enrichment. There were no significant differences in demographic or clinical parameters between these two groups. These results were confirmed using a second independent cohort. CONCLUSIONS: Our study suggests the presence of molecular subsets in lcSSc based on gene expression profiling of biopsies from uninvolved skin. This may reflect important differences in pathogenesis within these patient groups. We identify differential expression of a subset of genes that relate to CVS and are enriched in fibrotic signalling. This may shed light on mechanisms of vascular disease in SSc. The enrichment in profibrotic profile suggests that dysregulated gene expression may contribute to vasculopathy and fibrosis in different disease subsets.

A novel multi-network approach reveals tissue-specific cellular modulators of fibrosis in systemic sclerosis.

BACKGROUND: Systemic sclerosis (SSc) is a multi-organ autoimmune disease characterized by skin fibrosis. Internal organ involvement is heterogeneous. It is unknown whether disease mechanisms are common across all involved affected tissues or if each manifestation has a distinct underlying pathology. METHODS: We used consensus clustering to compare gene expression profiles of biopsies from four SSc-affected tissues (skin, lung, esophagus, and peripheral blood) from patients with SSc, and the related conditions pulmonary fibrosis (PF) and pulmonary arterial hypertension, and derived a consensus disease-associate signature across all tissues. We used this signature to query tissue-specific functional genomic networks. We performed novel network analyses to contrast the skin and lung microenvironments and to assess the functional role of the inflammatory and fibrotic genes in each organ. Lastly, we tested the expression of macrophage activation state-associated gene sets for enrichment in skin and lung using a Wilcoxon rank sum test. RESULTS: We identified a common pathogenic gene expression signature-an immune-fibrotic axis-indicative of pro-fibrotic macrophages (MØs) in multiple tissues (skin, lung, esophagus, and peripheral blood mononuclear cells) affected by SSc. While the co-expression of these genes is common to all tissues, the functional consequences of this upregulation differ by organ. We used this disease-associated signature to query tissue-specific functional genomic networks to identify common and tissue-specific pathologies of SSc and related conditions. In contrast to skin, in the lung-specific functional network we identify a distinct lung-resident MØ signature associated with lipid stimulation and alternative activation. In keeping with our network results, we find distinct MØ alternative activation transcriptional programs in SSc-associated PF lung and in the skin of patients with an "inflammatory" SSc gene expression signature. CONCLUSIONS: Our results suggest that the innate immune system is central to SSc disease processes but that subtle distinctions exist between tissues. Our approach provides a framework for examining molecular signatures of disease in fibrosis and autoimmune diseases and for leveraging publicly available data to understand common and tissue-specific disease processes in complex human diseases.

Myeloid Cells That Impair Immunotherapy Are Restored in Melanomas with Acquired Resistance to BRAF Inhibitors.

Acquired resistance to BRAFV600E inhibitors (BRAFi) in melanoma remains a common clinical obstacle, as is the case for any targeted drug therapy that can be developed given the plastic nature of cancers. Although there has been significant focus on the cancer cell-intrinsic properties of BRAFi resistance, the impact of BRAFi resistance on host immunity has not been explored. Here we provide preclinical evidence that resistance to BRAFi in an autochthonous mouse model of melanoma is associated with restoration of myeloid-derived suppressor cells (MDSC) in the tumor microenvironment, initially reduced by BRAFi treatment. In contrast to restoration of MDSCs, levels of T regulatory cells remained reduced in BRAFi-resistant tumors. Accordingly, tumor gene expression signatures specific for myeloid cell chemotaxis and homeostasis reappeared in BRAFi-resistant tumors. Notably, MDSC restoration relied upon MAPK pathway reactivation and downstream production of the myeloid attractant CCL2 in BRAFi-resistant melanoma cells. Strikingly, although combination checkpoint blockade (anti-CTLA-4 + anti-PD-1) was ineffective against BRAFi-resistant melanomas, the addition of MDSC depletion/blockade (anti-Gr-1 + CCR2 antagonist) prevented outgrowth of BRAFi-resistant tumors. Our results illustrate how extrinsic pathways of immunosuppression elaborated by melanoma cells dominate the tumor microenvironment and highlight the need to target extrinsic as well as intrinsic mechanisms of drug resistance. Cancer Res; 77(7); 1599-610. ©2017 AACR.

A Functional Genomic Meta-Analysis of Clinical Trials in Systemic Sclerosis: Toward Precision Medicine and Combination Therapy.

Systemic sclerosis is an orphan, systemic autoimmune disease with no FDA-approved treatments. Its heterogeneity and rarity often result in underpowered clinical trials making the analysis and interpretation of associated molecular data challenging. We performed a meta-analysis of gene expression data from skin biopsies of patients with systemic sclerosis treated with five therapies: mycophenolate mofetil, rituximab, abatacept, nilotinib, and fresolimumab. A common clinical improvement criterion of -20% or -5 modified Rodnan skin score was applied to each study. We applied a machine learning approach that captured features beyond differential expression and was better at identifying targets of therapies than the differential expression alone. Regardless of treatment mechanism, abrogation of inflammatory pathways accompanied clinical improvement in multiple studies suggesting that high expression of immune-related genes indicates active and targetable disease. Our framework allowed us to compare different trials and ask if patients who failed one therapy would likely improve on a different therapy, based on changes in gene expression. Genes with high expression at baseline in fresolimumab nonimprovers were downregulated in mycophenolate mofetil improvers, suggesting that immunomodulatory or combination therapy may have benefitted these patients. This approach can be broadly applied to increase tissue specificity and sensitivity of differential expression results.

Molecular stratification and precision medicine in systemic sclerosis from genomic and proteomic data.

PURPOSE OF REVIEW: The goal of this review is to summarize recent advances into the pathogenesis and treatment of systemic sclerosis (SSc) from genomic and proteomic studies. RECENT FINDINGS: Intrinsic gene expression-driven molecular subtypes of SSc are reproducible across three independent datasets. These subsets are a consistent feature of SSc and are found in multiple end-target tissues, such as skin and esophagus. Intrinsic subsets as well as baseline levels of molecular target pathways are potentially predictive of clinical response to specific therapeutics, based on three recent clinical trials. A gene expression-based biomarker of modified Rodnan skin score, a measure of SSc skin severity, can be used as a surrogate outcome metric and has been validated in a recent trial. Proteome analyses have identified novel biomarkers of SSc that correlate with SSc clinical phenotypes. SUMMARY: Integrating intrinsic gene expression subset data, baseline molecular pathway information, and serum biomarkers along with surrogate measures of modified Rodnan skin score provides molecular context in SSc clinical trials. With validation, these approaches could be used to match patients with the therapies from which they are most likely to benefit and thus increase the likelihood of clinical improvement.