Identification and evaluation of novel synovial tissue biomarkers in rheumatoid arthritis by laser scanning cytometry

Introduction

Suitable biomarkers are essential for therapeutic strategies in personalized medicine in terms of diagnosis as well as of prognosis. With highly specific biomarkers, it is possible, for example, to identify patients with poor prognosis, which enables early intervention and intensive treatment. The aim of this study was to identify and validate biomarkers and possible combinations for a prospective use in immunoscintigraphy, which may improve diagnosis of rheumatoid arthritis (RA) patients with consideration of inflammatory activity in the affected joints. Therefore, we tested several monoclonal antibodies (mAbs) directed against cellular-surface molecules on cells likely to be involved in the pathogenesis of RA.

Methods

Synovial tissue from patients with long-standing RA (accompanied by synovitis with varying states of current activity) and patients with acute non-RA arthritis were stained for surface molecules on different cell types by using fluorochrome-labeled antibodies. Tissue analysis was done by laser scanning cytometry (LSC), and statistical evaluation, by discriminant analysis and ROC analysis.

Results

CD11b, HLA-DR, CD90, and CD64 revealed significant differences between tissues from patients with RA and acute non-RA arthritis. Especially with the expression of CD64, both patient cohorts could be discriminated with high sensitivity and specificity. RA classification was improved by simultaneously investigating the expression of two or three different surface proteins, such as HLA-DR, CD90, and CD29 in the tissue. The simultaneous analysis of CD64 together with CD304 or the combination of CD11b and CD38 was suitable for the identification of RA patients with high current activity in synovitis.

Conclusions

In this study, we showed that LSC is a novel reliable method in biomarker prevalidation in RA. Hence, identified mAbs in situ may allow their potential use in in vivo approaches. Moreover, we proved that biomarker-combination analysis resulted in better discrimination than did single-marker analysis. Combinations of these markers make a novel and reliable panel for the discrimination between RA and acute non-RA arthritis. In addition, further expedient combinations may be novel promising biomarker panels to identify current activity in synovitis in RA.