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.

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.

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 (r_s = 0.638, p = 0.004) and the entire (upper + lower) esophagus (r_s = 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.

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.

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 β 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.

Pro-fibrotic Activation of Human Macrophages in Systemic Sclerosis

Genome-wide gene expression studies implicate macrophages as mediators of fibrosis in Systemic sclerosis (SSc), and we have shown that macrophages constitute the dominant inflammatory signature in SSc tissue. However, little is known about how these cells contribute to fibrotic activation in SSc. Using a bioinformatics approach, we show that the gene expression profile of blood-derived human SSc macrophages is significantly enriched in SSc patient skin. We characterize the immunophenotype of human SSc macrophages as pro-fibrotic, demonstrating that these cells are activated under basal conditions, expressing elevated levels of surface markers associated with activation and releasing CCL2, IL-6, and TGF-beta. We also show that STAT3 is phosphorylated in macrophage from SSc patient compared to the healthy donor, and the phosphorylation is attenuated after IL-6 blockade, suggesting that increased expression of IL-6 by SSc macrophages accounts, at least in part, for increased signaling. Moreover, our results suggest that activation of SSc macrophages arises from soluble factors, as differentiation of healthy donor monocytes in SSc patient-derived plasma confers the immunophenotype of SSc patient macrophages. For the first time, we show that co-culture of human SSc macrophages with SSc fibroblasts induces fibroblast activation. Collectively, these studies implicate macrophages as likely drivers of fibrosis in SSc and suggest therapeutic targeting of these cells may be beneficial in ameliorating disease in SSc patients.

Redirecting Immune Activation in the Tumor Microenvironment of 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 immune suppression, 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 tumor-promoting to tumor-inhibiting in vitro. We show now for the first time 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 CD4+ T cells were reduced, while the proportion of CD8+ T cells was significantly increased in tumors and spleen. Moreover, mice fed CDDO-Me demonstrated significant reductions in numbers of tumor CD4+Foxp3+ regulatory T cells. These results demonstrate for the first time that CDDO-Me relieves immunosuppression in the breast TME and unleashes host adaptive anti-tumor immunity.

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.

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 (D_LCO), 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)-β 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.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-017-1360-7) contains supplementary material, which is available to authorized users.

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 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.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0417-1) contains supplementary material, which is available to authorized users.

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.

Nilotinib (Tasigna™) in the treatment of early diffuse systemic sclerosis: an open-label, pilot clinical trial

Introduction

Tyrosine kinase inhibitors (TKI) are medications of interest in the treatment of Systemic Sclerosis (SSc) because of their ability to inhibit pathways involved in fibrosis. In this open-label pilot trial, our objectives were to assess the safety, efficacy, and molecular change associated with treatment of patients with diffuse cutaneous (dc)SSc with the TKI nilotinib (Tasigna™).

Methods

Ten adult patients with early dcSSc were treated with nilotinib. Primary endpoints were safety and change in modified Rodnan Skin Score (MRSS) after 6 months. Lesional skin biopsies at baseline, 6 and 12 months of treatment were assessed by histopathology, immunohistochemistry, and DNA microarray.

Results

Patients had early and active dcSSc with median disease duration of 0.7 years (range 0.5, 1.7) and increasing MRSS in the month prior to baseline (mean +2.9, p=0.02). Seven out of ten patients completed 6 and 12 months of treatment. Seventy-one adverse events (AEs) including 2 serious AEs were observed, and 92 % of AEs were grade 1-2. Two patients discontinued the medication due to mild QTc prolongation. MRSS improved by a mean of 4.2 points (16 %) at 6 months and by 6.3 points (23 %) at 12 months in the 7 completers, p=0.02 and 0.01, respectively. Patients with a decrease in MRSS >20 % from baseline at 12 months (classified as improvers) had significantly higher expression of transforming growth factor beta receptor (TGFBR) and platelet-derived growth factor receptor beta (PDGFRB) signaling genes at baseline than non-improvers, and the expression of these genes significantly decreased in improvers post-treatment.

Conclusion

Nilotinib was well tolerated by the majority of patients in this study, with tolerability limited primarily by mild QTc-prolongation. Significant MRSS improvement was observed in these early, active patients, but is not conclusive of treatment effect given the open-label study-design and small number of patients in this pilot study. Improvers had higher levels of expression of genes associated with TGFBR and PDGFRB signaling at baseline, and a significant decrease in the expression of these genes occurred only in patients with higher MRSS improvement. The findings of this pilot study warrant more conclusive evaluation.

Trial registration

Clinicaltrials.gov NCT01166139, July 1, 2010.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0721-3) contains supplementary material, which is available to authorized users.

Molecular characterization of systemic sclerosis esophageal pathology identifies inflammatory and proliferative signatures

Introduction

Esophageal involvement in patients with systemic sclerosis (SSc) is common, but tissue-specific pathological mechanisms are poorly understood. There are no animal scleroderma esophagus models and esophageal smooth muscle cells dedifferentiate in culture prohibiting in vitro studies. Esophageal fibrosis is thought to disrupt smooth muscle function and lead to esophageal dilatation, but autopsy studies demonstrate esophageal smooth muscle atrophy and the absence of fibrosis in the majority of SSc cases. Herein, we perform a detailed characterization of SSc esophageal histopathology and molecular signatures at the level of gene expression.

Methods

Esophageal biopsies were prospectively obtained during esophagogastroduodenoscopy in 16 consecutive SSc patients and 7 subjects without SSc. Upper and lower esophageal biopsies were evaluated for histopathology and gene expression.

Results

Individual patient’s upper and lower esophageal biopsies showed nearly identical patterns of gene expression. Similar to skin, inflammatory and proliferative gene expression signatures were identified suggesting that molecular subsets are a universal feature of SSc end-target organ pathology. The inflammatory signature was present in biopsies without high numbers of infiltrating lymphocytes. Molecular classification of esophageal biopsies was independent of SSc skin subtype, serum autoantibodies and esophagitis.

Conclusions

Proliferative and inflammatory molecular gene expression subsets in tissues from patients with SSc may be a conserved, reproducible component of SSc pathogenesis. The inflammatory signature is observed in biopsies that lack large inflammatory infiltrates suggesting that immune activation is a major driver of SSc esophageal pathogenesis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0695-1) contains supplementary material, which is available to authorized users.

Gene expression changes reflect clinical response in a placebo-controlled randomized trial of abatacept in patients with diffuse cutaneous systemic sclerosis

Introduction

Systemic sclerosis is an autoimmune disease characterized by inflammation and fibrosis of the skin and internal organs. We sought to assess the clinical and molecular effects associated with response to intravenous abatacept in patients with diffuse cutaneous systemic.

Methods

Adult diffuse cutaneous systemic sclerosis patients were randomized in a 2:1 double-blinded fashion to receive abatacept or placebo over 24 weeks. Primary outcomes were safety and the change in modified Rodnan Skin Score (mRSS) at week 24 compared with baseline. Improvers were defined as patients with a decrease in mRSS of ≥30 % post-treatment compared to baseline. Skin biopsies were obtained for differential gene expression and pathway enrichment analyses and intrinsic gene expression subset assignment.

Results

Ten subjects were randomized to abatacept (n = 7) or placebo (n = 3). Disease duration from first non-Raynaud’s symptom was significantly longer (8.8 ± 3.8 years vs. 2.4 ± 1.6 years, p = 0.004) and median mRSS was higher (30 vs. 22, p = 0.05) in the placebo compared to abatacept group. Adverse events were similar in the two groups. Five out of seven patients (71 %) randomized to abatacept and one out of three patients (33 %) randomized to placebo experienced ≥30 % improvement in skin score. Subjects receiving abatacept showed a trend toward improvement in mRSS at week 24 (−8.6 ± 7.5, p = 0.0625) while those in the placebo group did not (−2.3 ± 15, p = 0.75). After adjusting for disease duration, mRSS significantly improved in the abatacept compared with the placebo group (abatacept vs. placebo mRSS decrease estimate −9.8, 95 % confidence interval −16.7 to −3.0, p = 0.0114). In the abatacept group, the patients in the inflammatory intrinsic subset showed a trend toward greater improvement in skin score at 24 weeks compared with the patients in the normal-like intrinsic subset (−13.5 ± 3.1 vs. −4.5 ± 6.4, p = 0.067). Abatacept resulted in decreased CD28 co-stimulatory gene expression in improvers consistent with its mechanism of action. Improvers mapped to the inflammatory intrinsic subset and showed decreased gene expression in inflammatory pathways, while non-improver and placebos showed stable or reverse gene expression over 24 weeks.

Conclusions

Clinical improvement following abatacept therapy was associated with modulation of inflammatory pathways in skin.

Trial registration

ClinicalTrials.gov NCT00442611. Registered 1 March 2007.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0669-3) contains supplementary material, which is available to authorized users.

Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms

Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6–12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk.

Systemic sclerosis (SSc) is a rare autoimmune disease characterized by skin thickening (fibrosis) and progressive organ failure. Previous studies of SSc skin biopsies have identified molecular subsets of SSc based upon gene expression termed the inflammatory, fibroproliferative, normal-like, and limited intrinsic subsets. These gene expression signatures are large and although the biological processes are conserved, the exact list of genes can vary across datasets due to random variation, as well as minor differences in the composition of the study cohorts (e.g. early vs. late disease). We developed a computational tool to identify the consensus genes underlying the subsets across heterogeneous data and characterized the biological role of the consensus genes in SSc in order to obtain a systems level perspective of the SSc subsets. Our analysis reveals a complex network of genes connecting two of the major SSc intrinsic subsets, inflammatory and fibroproliferative. Many genetic loci associated with SSc risk show connections with the consensus genes of the intrinsic subsets, indicating that differential expression of genes defining the subsets may be related to genetic risk for SSc, thus for the first time placing the genetic risk factors in the context of, and showing putative relationships with, the intrinsic gene expression subsets.

Identification of cell cycle-regulated genes periodically expressed in U2OS cells and their regulation by FOXM1 and E2F transcription factors

Characterization of the cell cycle–regulated transcripts in U2OS cells yielded 1871 unique genes. FOXM1 targets were identified via ChIP-seq, and novel targets in G2/M and S phases were verified using a real-time luciferase assay. ChIP-seq data were used to map cell cycle transcriptional regulators of cell cycle–regulated gene expression in U2OS cells.

We identify the cell cycle–regulated mRNA transcripts genome-wide in the osteosarcoma-derived U2OS cell line. This results in 2140 transcripts mapping to 1871 unique cell cycle–regulated genes that show periodic oscillations across multiple synchronous cell cycles. We identify genomic loci bound by the G2/M transcription factor FOXM1 by chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) and associate these with cell cycle–regulated genes. FOXM1 is bound to cell cycle–regulated genes with peak expression in both S phase and G2/M phases. We show that ChIP-seq genomic loci are responsive to FOXM1 using a real-time luciferase assay in live cells, showing that FOXM1 strongly activates promoters of G2/M phase genes and weakly activates those induced in S phase. Analysis of ChIP-seq data from a panel of cell cycle transcription factors (E2F1, E2F4, E2F6, and GABPA) from the Encyclopedia of DNA Elements and ChIP-seq data for the DREAM complex finds that a set of core cell cycle genes regulated in both U2OS and HeLa cells are bound by multiple cell cycle transcription factors. These data identify the cell cycle–regulated genes in a second cancer-derived cell line and provide a comprehensive picture of the transcriptional regulatory systems controlling periodic gene expression in the human cell division cycle.

Increased expression of endoplasmic reticulum stress and unfolded protein response genes in peripheral blood mononuclear cells from patients with limited cutaneous systemic sclerosis and pulmonary arterial hypertension

OBJECTIVE

Pulmonary arterial hypertension (PAH), a common complication of limited cutaneous systemic sclerosis (lcSSc), is associated with alterations of markers of inflammation and vascular damage in peripheral blood mononuclear cells (PBMCs). Endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) have been implicated in autoimmune and inflammatory diseases. The goal of this study was to assess whether markers of ER stress and the UPR are present in PBMCs from lcSSc patients with PAH.

METHODS

PBMCs were purified from 36 healthy controls, 32 lcSSc patients with PAH, and 34 lcSSc patients without PAH. Gene expression in healthy control PBMCs stimulated with thapsigargin was analyzed by DNA microarray. Genes were validated by quantitative real-time reverse transcription-polymerase chain reaction in PBMCs from healthy controls and lcSSc patients.

RESULTS

Several ER stress/UPR genes, including BiP, activating transcription factor 4 (ATF-4), ATF-6, and a spliced form of X-box binding protein 1, were up-regulated in PBMCs from lcSSc patients, with the highest levels in patients with PAH. Thapsigargin up-regulated heat-shock proteins (HSPs) and interferon (IFN)-regulated genes in PBMCs from healthy controls. Selected HSP genes (particularly DnaJB1) and IFN-related genes were also found at significantly elevated levels in PBMCs from lcSSc patients, while IFN regulatory factor 4 expression was significantly decreased. There was a positive correlation between DnaJB1 and severity of PAH (measured by pulmonary artery pressure) (r = 0.56, P < 0.05) and between ER stress markers and interleukin-6 levels (r = 0.53, P < 0.0001) in PBMCs from lcSSc patients.

CONCLUSION

This study demonstrates an association between select ER stress/UPR markers and lcSSc with PAH, suggesting that ER stress and the UPR may contribute to the altered function of circulating immune cells in lcSSc.

Computational discovery of transcriptional regulatory modules in fungal ribosome biogenesis genes reveals novel sequence and function patterns

Genes involved in ribosome biogenesis and assembly (RBA) are responsible for ribosome formation. In Saccharomyces cerevisiae, their transcription is regulated by two dissimilar DNA motifs. We were interested in analyzing conservation and divergence of RBA transcription regulation machinery throughout fungal evolution. We have identified orthologs of S. cerevisiae RBA genes in 39 species across fungal phylogeny and searched upstream regions of these gene sets for DNA sequences significantly similar to S. cerevisiae RBA regulatory motifs. In addition to confirming known motif arrangements comprising two different motifs in a set of S. cerevisiae close relatives or two instances of the same motif (that we refer to as modules), we have also discovered novel modules in a group of fungi closely related to Neurospora crassa. Despite a single nucleotide difference between consensus sequences of RBA motifs, modules associated with S, cerevisiae group and N. crassa group displayed consistently different characteristics with respect to preferred module organization and several other module properties. For a given species, we have found a correlation between the configuration of the RBA module and significant enrichment in a set of specific Gene Ontology biological processes. We have identified several likely new candidates for a role in ribosome biogenesis in S. cerevisiae based on the combined evidence of RBA module presence in the upstream regions, functional annotation information and microarray expression profiles. We believe that this approach will be useful in terms of generating hypotheses about functional roles of genes for which only fragmentary data from a single source are available.

Molecular signatures in skin associated with clinical improvement during mycophenolate treatment in systemic sclerosis

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 skin score/MRSS improvement during mycophenolate mofetil (MMF) treatment. Gene expression and intrinsic subset assignment were measured in 12 SSc patients’ biopsies and ten controls at baseline, and from serial biopsies of one cyclophosphamide-treated patient, and nine 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. 321 genes (FDR <5%) were differentially expressed at baseline between patients with and without MRSS improvement during treatment. Expression of 571 genes (FDR <10%) changed between pre- and post-MMF treatment biopsies for patients demonstrating 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.

Live-cell monitoring of periodic gene expression in synchronous human cells identifies Forkhead genes involved in cell cycle control

A periodic luciferase reporter system from cell cycle–regulated promoters in synchronous U2OS cells measures periodic, cell cycle–regulated gene expression in live cells. This assay is used to identify Forkhead transcription factors that control periodic gene expression, and it identifies FOXK1 as an activator of key cell cycle genes.

We developed a system to monitor periodic luciferase activity from cell cycle–regulated promoters in synchronous cells. Reporters were driven by a minimal human E2F1 promoter with peak expression in G1/S or a basal promoter with six Forkhead DNA-binding sites with peak expression at G2/M. After cell cycle synchronization, luciferase activity was measured in live cells at 10-min intervals across three to four synchronous cell cycles, allowing unprecedented resolution of cell cycle–regulated gene expression. We used this assay to screen Forkhead transcription factors for control of periodic gene expression. We confirmed a role for FOXM1 and identified two novel cell cycle regulators, FOXJ3 and FOXK1. Knockdown of FOXJ3 and FOXK1 eliminated cell cycle–dependent oscillations and resulted in decreased cell proliferation rates. Analysis of genes regulated by FOXJ3 and FOXK1 showed that FOXJ3 may regulate a network of zinc finger proteins and that FOXK1 binds to the promoter and regulates DHFR, TYMS, GSDMD, and the E2F binding partner TFDP1. Chromatin immunoprecipitation followed by high-throughput sequencing analysis identified 4329 genomic loci bound by FOXK1, 83% of which contained a FOXK1-binding motif. We verified that a subset of these loci are activated by wild-type FOXK1 but not by a FOXK1 (H355A) DNA-binding mutant.

Using SCOPE to identify potential regulatory motifs in coregulated genes

SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference¹. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data¹. In this article, we utilize a web version of SCOPE² to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs^3,4 and has been used in other studies^5-8.

The three algorithms that comprise SCOPE are BEAM⁹, which finds non-degenerate motifs (ACCGGT), PRISM¹⁰, which finds degenerate motifs (ASCGWT), and SPACER¹¹, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well.

Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor.

Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run.

Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from a file. The output from SCOPE contains a list of all identified motifs with their scores, number of occurrences, fraction of genes containing the motif, and the algorithm used to identify the motif. For each motif, result details include a consensus representation of the motif, a sequence logo, a position weight matrix, and a list of instances for every motif occurrence (with exact positions and "strand" indicated). Results are returned in a browser window and also optionally by email. Previous papers describe the SCOPE algorithms in detail^1,2,9-11.

Identifying functional relationships within sets of co-expressed genes by combining upstream regulatory motif analysis and gene expression information

BACKGROUND

Existing clustering approaches for microarray data do not adequately differentiate between subsets of co-expressed genes. We devised a novel approach that integrates expression and sequence data in order to generate functionally coherent and biologically meaningful subclusters of genes. Specifically, the approach clusters co-expressed genes on the basis of similar content and distributions of predicted statistically significant sequence motifs in their upstream regions.

RESULTS

We applied our method to several sets of co-expressed genes and were able to define subsets with enrichment in particular biological processes and specific upstream regulatory motifs.

CONCLUSIONS

These results show the potential of our technique for functional prediction and regulatory motif identification from microarray data.