Synovial phenotypes in rheumatoid arthritis correlate with response to biologic therapeutics
- Equal contributors
1 Departments of Immunology Discovery, Genentech, South San Francisco, California, USA
2 ITGR Diagnostics Discovery, Genentech, South San Francisco, California, USA
3 Bioinformatics and Computational Biology, Genentech, South San Francisco, California, USA
4 Non-clinical Biostatistics, Genentech, South San Francisco, California, USA
5 Pathology, Genentech, South San Francisco, California, USA
6 Bioanalytical Sciences, Genentech, South San Francisco, California, USA
7 Product Development, Genentech, South San Francisco, California, USA
8 University Hospital of Geneva, Geneva, Switzerland
9 University of California San Diego, San Diego, California, USA
10 Rheumatic Disease Core Center and Division of Rheumatology, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA
11 Current address: Inflammation Therapeutic Area, Amgen, 1201 Amgen Court West, Seattle, Washington, USA
Arthritis Research & Therapy 2014, 16:R90 doi:10.1186/ar4555Published: 30 April 2014
Rheumatoid arthritis (RA) is a complex and clinically heterogeneous autoimmune disease. Currently, the relationship between pathogenic molecular drivers of disease in RA and therapeutic response is poorly understood.
We analyzed synovial tissue samples from two RA cohorts of 49 and 20 patients using a combination of global gene expression, histologic and cellular analyses, and analysis of gene expression data from two further publicly available RA cohorts. To identify candidate serum biomarkers that correspond to differential synovial biology and clinical response to targeted therapies, we performed pre-treatment biomarker analysis compared with therapeutic outcome at week 24 in serum samples from 198 patients from the ADACTA (ADalimumab ACTemrA) phase 4 trial of tocilizumab (anti-IL-6R) monotherapy versus adalimumab (anti-TNFα) monotherapy.
We documented evidence for four major phenotypes of RA synovium – lymphoid, myeloid, low inflammatory, and fibroid - each with distinct underlying gene expression signatures. We observed that baseline synovial myeloid, but not lymphoid, gene signature expression was higher in patients with good compared with poor European league against rheumatism (EULAR) clinical response to anti-TNFα therapy at week 16 (P =0.011). We observed that high baseline serum soluble intercellular adhesion molecule 1 (sICAM1), associated with the myeloid phenotype, and high serum C-X-C motif chemokine 13 (CXCL13), associated with the lymphoid phenotype, had differential relationships with clinical response to anti-TNFα compared with anti-IL6R treatment. sICAM1-high/CXCL13-low patients showed the highest week 24 American College of Rheumatology (ACR) 50 response rate to anti-TNFα treatment as compared with sICAM1-low/CXCL13-high patients (42% versus 13%, respectively, P =0.05) while anti-IL-6R patients showed the opposite relationship with these biomarker subgroups (ACR50 20% versus 69%, P =0.004).
These data demonstrate that underlying molecular and cellular heterogeneity in RA impacts clinical outcome to therapies targeting different biological pathways, with patients with the myeloid phenotype exhibiting the most robust response to anti-TNFα. These data suggest a path to identify and validate serum biomarkers that predict response to targeted therapies in rheumatoid arthritis and possibly other autoimmune diseases.