Mitsubishi Tanabe Pharma Corporation Yokohama, Japan
Disclosure information not submitted.
Yuuichi Ono1, Akira Mogami1, Ryuta Saito2, Noriyasu Seki1, Sho Ishigaki3, Hiroshi Takei3, Keiko Yoshimoto3, Kenji Chiba1, Tsutomu Takeuchi4 and Yuko Kaneko5, 1Mitsubishi Tanabe Pharma Corporation, Yokohama, Japan, 2Mitsubishi Tanabe Pharma Corporaion, Yokohama, Japan, 3Keio University School of Medicine, Tokyo, Japan, 4Keio University School of Medicine and Saitama Medical University, Tokyo, Japan, 5Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan
Background/Purpose: SSc-related pulmonary arterial hypertension (SSc-PAH) is the one of the leading causes of death in SSc. Early diagnosis and effective therapy for SSc-PAH may lead to improved outcomes. We have been developing MT-6194, a bispecific FynomAb targeting both human IL-17A and IL-6 receptor. To ensure that MT-6194 is used in appropriate patients, we attempted to stratify the patients using serum parameters.
Methods: SSc patients who met the 2013 ACR/EULAR classification criteria were eligible for study participation. We analyzed serum samples from 17 patients with diffuse cutaneous systemic sclerosis, 58 patients with limited cutaneous systemic sclerosis, and 38 healthy controls. PAH was defined as a mean pulmonary artery pressure of ≥25 mm Hg with pulmonary capillary wedge pressure of < 15 mm Hg by right-sided heart catheterization, and an absence of significant interstitial lung disease. The abundance ofserum proteins were analyzed using Proximity Extension Assay (PEA) technology (Olink).
Results: SSc patients were divided into 4 clusters according to their blood levels of IL-6 and IL-17A. SSc patients with high blood levels of both IL-6 and IL-17A had a high prevalence of PAH. We also identified 34 proteins that are upregulated in patients with high blood levels of both IL-6 and IL-17A, and that were significantly correlated with PAH prevalence. Unsupervised hierarchical clustering using the 34 proteins divided SSc patients into three clusters ("PAH cluster 1", "PAH cluster 2", and "PAH cluster 3" were defined). Almost all patients in "PAH cluster 3", where the identified proteins were highly elevated, had PAH. On the other hand, 4 of 30 patients in "PAH cluster 1", where the identified proteins were moderate elevated, had PAH, and there were no patients with PAH in "PAH cluster 2", which has low levels of identified proteins. A %FVC/%DLCO ratio > 1.6 is considered a risk factor for developing SSc-PAH. The %FVC/%DLCO ratio exceeded 1.6 not only in patients in "PAH cluster 3" but also in most patients in "PAH cluster 1". From these results, the 34 proteins can detect not only patients already suffering from PAH, but also patients at high risk of developing PAH. To identify predictive biomarkers of drug response, we evaluated the effects of MT-6194 on in vitro neutralization experiment using fibroblasts. As a result, eight molecules (IL-6, GDF15, LTBP2, CCL7, CHI3L1, EFEFMP1, PLAUR, and SPON1) were found to be upregulated in patients with high blood levels of both IL-6 and IL-17A, upregulated in fibroblast activation, and suppressed by MT-6194. The classification model using these biomarkers could classify not only "PAH cluster 3" but also "PAH cluster 1" with good performance.
Conclusion: Our study investigated the IL-6 and IL-17A-related classification of systemic sclerosis based on serum proteomics. Identified biomarkers stratified patients at increased risk of PAH. The 8-molecule signature identified in this study allowed us to select the appropriate patient population for MT-6194 treatment. Appropriately stratified clinical trials may yield additional treatment options for patients with systemic sclerosis.