Systemic Sclerosis Clinical Trial
Official title:
Genomic and Histological Analysis of Skin Biopsy Specimens as Biomarkers of Systemic Sclerosis and Response to Mycophenolate Mofetil
The purpose of this study is to assess whether skin biopsy specimens from patients with diffuse cutaneous systemic sclerosis (dcSSc) can be used as biomarkers (measures of activity and type) of disease to predict response to various experimental treatments. There are various experimental treatments being used in the treatment of slceroderma, but there is no way to predict response to any given therapy. The investigators will use DNA microarray to analyze the changes in gene expression in skin biopsies in response to various treatments. Our hypothesis is that the investigators will see changes in gene expression in response to various treatments that will give us insight into the cause of scleroderma. The investigators predict that they will be able to use this information to predict which experimental treatments will be beneficial to individual patients
Systemic sclerosis (SSc) is an autoimmune connective tissue disease primarily affecting
young to middle-aged women. The pathogenesis of SSc is complex involving interplay of three
seemingly diverse processes: autoimmunity, vasculopathy, and fibrosis. Patients experience
varying degrees of disabling skin thickening and potentially life-threatening internal organ
fibrosis and vasculopathy, but there is no way to accurately predict disease subtype and
risk for severity and progression. Current experimental treatments for SSc include oral and
intravenous cyclophosphamide and mycophenolate mofetil that blunt the immune response,
autologous stem cell transplant that may reset the immune system, and imatinib mesylate that
may reduce fibrosis.
Recent exciting genomics research from our lab and our collaborator suggests that skin
biopsy samples obtained from patients with SSc have robust alterations in gene expression
profiles compared to controls. Changes in expression of genes known to be involved in
profibrotic pathways were prominent. The present proposal describes novel experiments to
evaluate genomic approaches coupled with clinical data to identify patient subsets, predict
response to treatment, and to better understand the molecular basis for disease
pathogenesis, and treatment response.
The Northwestern Scleroderma Program (NSP) is a novel multidisciplinary program to
accelerate SSc research and provide comprehensive care to >400 SSc patients. Standardized
clinical information including demographic, laboratory, and diagnostic data
(echocardiography, high resolution chest computerized tomography, and pulmonary function
testing) as well as DNA is currently collected on all patients and entered into a clinical
database. NSP patients will be offered the option to donate dermal tissue for genomic
analysis using a previously established, optimized approach to extract RNA from tissue
samples.
We hypothesize that our DNA microarray technique will permit analysis of changes in gene
expression from the skin of patients undergoing dermal biopsies before and after treatment
and will identify unrecognized profibrotic pathways in addition to providing new, important
information regarding known fibrotic pathways. The knowledge gained will not only deepen our
understanding of the molecular pathways involved in fibrosis, but also provide a means to
reliably predict which patients are likely to respond to various treatments.
Relevance:
SSc is a devastating orphan connective tissue disease with no known cure. There are no
disease biomarkers that can accurately predict disease subtype or risk for internal organ
involvement and progression at present. Using well-established genomic techniques, the
current proposal will investigate if changes in gene expression of profibrotic pathways in
dermal biopsies before and after various treatments correlates with clinical response. If
so, genonic analysis of dermal tissue may be useful to better understand the molecular
pathogenesis of SSc and as a disease biomarker.
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Observational Model: Case Control, Time Perspective: Prospective
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