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

ABSTRACT: 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.

SUBMITTER: Martyanov V

PROVIDER: S-EPMC5679625 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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

Martyanov Viktor V Kim Grace-Hyun J GJ Hayes Wendy W Du Shuyan S Ganguly Bishu J BJ Sy Oumar O Lee Sun Ku SK Bogatkevich Galina S GS Schieven Gary L GL Schiopu Elena E Marangoni Roberta Gonçalves RG Goldin Jonathan J Whitfield Michael L ML Varga John J

PloS one 20171109 11

<h4>Background</h4>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).<h4>Methods</h4>Primary objectives were safety and pharmacokinetics. Secondary outcomes included clinical assessments, quantitative high-resolution computed to ...[more]

PMID: 29121645

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Project description:ObjectiveWe undertook this hypothesis-generating study to identify skin transcripts correlating with severity of interstitial lung disease (ILD) in systemic sclerosis (SSc).MethodsSkin biopsy samples from 59 patients enrolled in the Genetics versus Environment in Scleroderma Outcome Study (GENISOS) cohort or an open-label imatinib study (baseline visit) were examined by global gene expression analysis using Illumina HT-12 arrays. Skin transcripts correlating with concomitantly obtained forced vital capacity (FVC) values and the modified Rodnan skin thickness score (MRSS) were identified by quantitative trait analysis. Also, immunofluorescence staining for selected transcripts was performed in affected skin and lung tissue. Plasma levels of CCL2, soluble SELP, and soluble P-selectin glycoprotein ligand 1 (sPSGL-1) were examined in all patients enrolled in the GENISOS cohort (n = 266).ResultsEighty-two skin transcripts correlated significantly with FVC. This gene list distinguished patients with more severe ILD (FVC <70% predicted) in unsupervised hierarchical clustering analysis (P < 0.001). These genes included SELP, CCL2, and matrix metalloproteinase 3, which are involved in extravasation and adhesion of inflammatory cells. Among the FVC correlates, 8 genes (CCL2, HAPLN3, GPR4, ADCYAP1, WARS, CDC25B, PLP1, and STXBP6) also correlated with the MRSS. Immunofluorescence staining revealed that SELP and CCL2 were also overexpressed in affected skin and lung tissue from SSc patients compared to those from controls. Plasma levels of CCL2 and sPSGL-1 correlated with concomitantly obtained FVC values (r = -0.22, P = 0.001 and r = 0.17, P = 0.015, respectively). This relationship was independent of potential confounders (age, sex, ethnicity, smoking status, anti-topoisomerase I positivity, treatment with immunosuppressive agents, MRSS, disease type, and disease duration).ConclusionA limited number of skin transcripts including genes involved in extravasation and adhesion of inflammatory cells correlate with severity of ILD.

Project description:Systemic sclerosis is a rare connective tissue disease; and interstitial lung disease (SSc-ILD) is associated with significant morbidity and mortality. There are no clinical, radiologic features, nor biomarkers that identify the specific time when patients are at risk for progression at which the benefits from treatment outweigh the risks. Our study aimed to identify blood protein biomarkers associated with progression of interstitial lung disease in patients with SSc-ILD using an unbiased, high-throughput approach. We classified SSc-ILD as progressive or stable based on change in forced vital capacity over 12 months or less. We profiled serum proteins by quantitative mass spectrometry and analyzed the association between protein levels and progression of SSc-ILD via logistic regression. The proteins associated with at a p value of < 0.1 were queried in the ingenuity pathway analysis (IPA) software to identify interaction networks, signaling, and metabolic pathways. Through principal component analysis, the relationship between the top 10 principal components and progression was evaluated. Unsupervised hierarchical clustering with heatmapping was done to define unique groups. The cohort consisted of 72 patients, 32 with progressive SSc-ILD and 40 with stable disease with similar baseline characteristics. Of a total of 794 proteins, 29 were associated with disease progression. After adjusting for multiple testing, these associations did not remain significant. IPA identified five upstream regulators that targeted proteins associated with progression, as well as a canonical pathway with a higher signal in the progression group. Principal component analysis showed that the ten components with the highest Eigenvalues represented 41% of the variability of the sample. Unsupervised clustering analysis revealed no significant heterogeneity between the subjects. We identified 29 proteins associated with progressive SSc-ILD. While these associations did not remain significant after accounting for multiple testing, some of these proteins are part of pathways relevant to autoimmunity and fibrogenesis. Limitations included a small sample size and a proportion of immunosuppressant use in the cohort, which could have altered the expression of inflammatory and immunologic proteins. Future directions include a targeted evaluation of these proteins in another SSc-ILD cohort or application of this study design to a treatment naïve population.

Dataset Information

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

Publications

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

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