title: Synovial phenotypes in rheumatoid arthritis correlate with response to biologic therapeutics.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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).
  
  
  CONCLUSIONS
  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.
  
  
  BACKGROUND
  ClinicalTrials.gov NCT01119859
authors.forename: Glynn
authors.initials: G
authors.lastname: Dennis
authors.forename: Cécile T J
authors.initials: CT
authors.lastname: Holweg
authors.forename: Sarah K
authors.initials: SK
authors.lastname: Kummerfeld
authors.forename: David F
authors.initials: DF
authors.lastname: Choy
authors.forename: A Francesca
authors.initials: AF
authors.lastname: Setiadi
authors.forename: Jason A
authors.initials: JA
authors.lastname: Hackney
authors.forename: Peter M
authors.initials: PM
authors.lastname: Haverty
authors.forename: Houston
authors.initials: H
authors.lastname: Gilbert
authors.forename: Wei Yu
authors.initials: WY
authors.lastname: Lin
authors.forename: Lauri
authors.initials: L
authors.lastname: Diehl
authors.forename: S
authors.initials: S
authors.lastname: Fischer
authors.forename: An
authors.initials: A
authors.lastname: Song
authors.forename: David
authors.initials: D
authors.lastname: Musselman
authors.forename: Micki
authors.initials: M
authors.lastname: Klearman
authors.forename: Cem
authors.initials: C
authors.lastname: Gabay
authors.forename: Arthur
authors.initials: A
authors.lastname: Kavanaugh
authors.forename: Judith
authors.initials: J
authors.lastname: Endres
authors.forename: David A
authors.initials: DA
authors.lastname: Fox
authors.forename: Flavius
authors.initials: F
authors.lastname: Martin
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Townsend
mesh_terms: D000068879:Adalimumab; D000328:Adult; D000368:Aged; D061067:Antibodies, Monoclonal, Humanized / Q000627:therapeutic use; D018501:Antirheumatic Agents / Q000627:therapeutic use*; D001172:Arthritis, Rheumatoid / Q000145:classification* / Q000188:drug therapy / Q000235:genetics*; D001688:Biological Products / Q000627:therapeutic use; D015415:Biomarkers / Q000032:analysis*; D005260:Female; D006801:Humans; D007150:Immunohistochemistry; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D010641:Phenotype; D013583:Synovial Membrane; D059467:Transcriptome
chemical_list: D061067:Antibodies, Monoclonal, Humanized; D018501:Antirheumatic Agents; D001688:Biological Products; D015415:Biomarkers; D000068879:Adalimumab; C502936:tocilizumab