Abstract

Dermatomyositis (DM) is a systemic idiopathic inflammatory disease affecting skeletal muscle and skin, clinically characterized by symmetrical proximal muscle weakness and typical skin lesions. Recently, myositis‐specific autoantibodies (MSA) became of utmost importance because they strongly correlate with distinct clinical manifestations and prognosis. Antibodies against transcription intermediary factor 1γ (TIF‐1γ) are frequently associated with increased risk of malignancy, a specific cutaneous phenotype and limited response to therapy in adult DM patients. Anti‐Mi‐2 autoantibodies, in contrast, are typically associated with classic DM rashes, prominent skeletal muscle weakness, better therapeutic response and prognosis, and less frequently with cancer. Nevertheless, the sensitivity of autoantibody testing is only moderate, and alternative reliable methods for DM patient stratification and prediction of cancer risk are needed. To further investigate these clinically distinct DM subgroups, we herein analyzed 30 DM patients (n = 15 Mi‐2+ and n = 15 TIF‐1 γ+) and n = 8 non‐disease controls (NDC). We demonstrate that the NanoString technology can be used as a very sensitive method to clearly differentiate these two clinically distinct DM subgroups. Using the nCounter PanCancer Immune Profiling Panel™, we identified a set of significantly dysregulated genes in anti‐TIF‐1γ+ patient muscle biopsies including VEGFA, DDX58, IFNB1, CCL5, IL12RB2, and CD84. Investigation of type I IFN‐regulated transcripts revealed a striking type I interferon signature in anti‐Mi‐2+ patient biopsies. Our results help to stratify both subgroups and predict, which DM patients require an intensified diagnostic procedure and might have a poorer outcome. Potentially, this could also have implications for the therapeutic approach.

Highlights

  • Using the nCounter PanCancer Immune Profiling PanelTM, we identified a set of significantly dysregulated genes in anti-­transcription intermediary factor 1γ (TIF-­1γ)+ patient muscle biopsies including VEGFA, DDX58, IFNB1, CCL5, IL12RB2, and CD84

  • Dermatomyositis-­specific autoantibodies such as anti-­ TIF-­1γ have been shown to tightly correlate with organ involvement and malignancy in cancer-a­ssociated myositis [2, 4, 5, 10]. These autoantibodies are recognized as useful biomarkers to stratify DM patients into clinical subgroups, and assessing the correct TIF-­1γ antibody status is of high importance to determine diagnostic procedures and prognosis

  • Cancer-­associated myositis (CAM) was detected in 60% of anti-­TIF-­1γ-­ and 20% of anti-­Mi-­2-­associated DM patients, which (i) basically reflects results from other larger patient series [43, 44] and (ii) emphasized the need for personalized risk-­stratified cancer follow-­up for both DM subgroups

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Summary

| METHODS

The study cohort and sample size as well as the experimental design, analysis workflow, diagnosis, and autoantibody status are displayed in Figure 1A and Table S1. Cancer-­associated myositis (CAM) was present in n = 9 (60%) anti-­TIF-­1γ+ and n = 3 (20%) anti-­ Mi-­2+ patients. Patients that suffered from cancer more than 2 years before or more than 3 years after DM diagnosis were defined as CAM-­. Histological stains were performed on 7-­μm cryostat muscle sections according to standard procedures. We performed quantitative real-­time PCR (qPCR) measuring the gene expression profile of VEGF, DDX58, and MSTR1 using the following TaqMan probes (ThermoFisher Scientific): Hs00900055_m1 (VEGFA), Hs00204833_m1 (RIG1/DDX58), Hs00899920_m1 (MST1R), and Hs99999905_m1 (GAPDH). Quality control, and normalization were performed using the nSolverTM 4.0 analysis software. Gene expression measurements from anti-­Mi-­2+ patient muscle biopsies (n = 6) and anti-­TIF-­1γ+ patients’ muscle biopsies (n = 6) were normalized to healthy non-­ diseased control samples (NDC, n = 2) before being compared to each other.

| Evaluation of NanoString results
| RESULTS
| DISCUSSION
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