Gene Activity Predicts Progression of Systemic Sclerosis

Ricki Lewis, PhD

December 23, 2016

Gene expression profiling (transcriptomics) to distinguish the skin of patients with systemic sclerosis (SSc) from healthy skin may aid diagnosis, monitor disease progression, and predict response to treatment, according to findings published December 22 in JCI Insight.

Systemic sclerosis is also known as "scleroderma," which reflects the skin hardening that patients with severe cases have called "the body turning to stone." SSc is rare and has the highest case fatality rate of the connective tissue diseases. The US Food and Drug Administration has not approved any treatments specifically for SSc, but immunosuppressants are sometimes prescribed off-label.

Healthcare providers identify SSc and assess response to treatment using the modified Rodnan skin score (mRSS). This test measures skin thickening by pinching 17 areas of the body and assigning a value of 0 to 3 to each, with a maximum possible combined score of 51.

Shane Lofgren, a research associate at the Stanford University School of Medicine, California, and colleagues hypothesized that patients with SSc might similarly express a specific set of genes, and that this pattern, if not seen in skin from individuals who do not have SSc, might provide a more objective clinical assessment tool. Past studies have demonstrated that transcriptomic profiles (the collection of messenger RNA molecules in a cell) are very similar for skin cells sampled from different parts of an individual's body.

The researchers derived a 415-gene expression signature from 158 patient skin samples from two datasets and distinguished the signature from 357 skin biopsies from five healthy independent cohorts. The signature persists irrespective of extent of disease, type of drug treatment, whether or not serum autoantibodies are present, and mRSS score.

The team developed the SSc Skin Severity Score (4S), which is the difference between the mean of overexpressed genes and the mean of underexpressed genes in the 415-gene set (211 genes are overexpressed and 204 are underexpressed). Heat maps are used to quantify and compare gene expression. The 4S positively correlates with the mRSS in patients undergoing any treatment and is not confounded by clinical factors such as edema, obesity, and provider-to-provider "pinching" differences. The 4S findings also predict mRSS score. The 4S test enabled the investigators to identify patients from a Northwestern University cohort taking a specific drug who were responding at 12 months. Assessing response using the mRSS is not possible until 24 months.

"Collectively, our results show that despite the repeatedly observed clinical and molecular heterogeneity in SSc patient populations, 4S robustly and reproducibly distinguishes healthy and diseased biopsies and correlates with SSc disease severity as measured by mRSS. It may also be prognostic of future changes in disease severity," the researchers write.

The new test may also be valuable in drug discovery because the specific genes that are differentially expressed in SSc skin provide clues to underlying mechanisms. One such candidate gene encodes the epidermal growth factor receptor (EGFR). EGF is implicated in extracellular matrix deposition and regulation of division of dermal fibroblasts, functions that affect fibrosis, and patients with SSc have autoantibodies to EGFR.

Perhaps EGFR inhibitors approved to treat cancer may be repurposed to treat SSc, senior author Purvesh Khatri, PhD, assistant professor of medicine at Stanford, told Medscape Medical News.

A limitation of the study is the need for prospective evaluation of the prognostic capability of the 4S.

The researchers have disclosed no relevant financial relationships.

JCI Insight. Published online December 22, 2016. Abstract

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