Scleroderma is a heterogeneous disease of unknown etiology that results in cutaneous fibrosis, autoimmunity, internal organ dysfunction, and microvascular obliteration. Despite over 15,000 Pubmed citations on the disease, there is limited understanding of the molecular mechanisms at play in scleroderma. This indicates that a new approach is needed. In this core, our preliminary data establish that high- throughput genomic approaches can generate insights into the pathological processes driving skin fibrosis in patients with systemic sclerosis with diffuse scleroderma. Analysis of the spectrum of gene expression in skin biopsies demonstrates our ability to quantitatively separate patients into distinct groups based on their gene expression patterns alone. These groupings are independent of disease duration, but instead reflect different fundamental biology, similar to what has been found in the molecular subtypes of breast and lung tumors. We show that the distinct groups identified by gene expression can be mapped to definable clinical covariates. The Pi's experience and the optimized sample processing protocols, and data analysis methods will be utilized for this core. The goals are to (1) hybridize skin biopsies and PBMC samples from patients with scleroderma and normal controls as they arrive at Dartmouth, (2) to analyze the resulting data for biomarkers the predict disease activity and (3) to generate hypotheses regarding the molecular mechanisms underlying scleroderma that could ultimately be tested by more cell biological methods. The core will also employ pilot RNAseq experiments using ultra-high throughput sequencing methods.
(See Instructions): Scleroderma is a major health concern. High throughput gene expression has identified subsets in scleroderma that are driven by fundamentally different pathways. The core will provide the ability to subset patients as a component of this CORT proposal and each subset will likely respond differently to therapy. It will also allow us to test if specific pathways investigated in each project are deregulated in patients.
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