Overview

The aim of this research center is to establish a new network model which can explain the evolution mechanisms of acute to chronic and pre-cancerous changes in arthritic synoviums, focusing on synovial fibroblasts. We investigate the time and spatial dynamics of the interaction between synovial cells and surrounding immune cells. We also determine the primary signal pathway and genetic regulatory mechanism involving this process. We expect that the final results will enable the development of new drugs selectively targeting rheumatoid synovial fibroblasts with an aggressive and destructive phenotype.

By James Heilman, MD - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=11110471

Previous knowledge on the role of FLS

in the pathogenesis of rheumatoid arthritis (RA)

FIGURE 1. ROLE OF FLS IN RA

Bottini, N. & Firestein, G. S. (2012) Nat. Rev. Rheumatol. 

Rheumatoid arthritis (RA) is a common autoimmune disorder that afflicts approximately 1% of the population. Despite the advent of anti-cytokine therapies that ameliorate the inflammatory manifestations of the disease, there is no cure and the pathogenesis of RA remains unknown. In RA joints, various inflammatory cells, including innate immune cells (e.g. mast cells, macrophages, dendritic cells, and natural killer cells), adaptive immune cells (T- and B-cells), endothelial cells, and fibroblast-like synoviocytes (FLS), are activated (1). Identification of the major roles of the participating cells has been a key issue in understanding RA pathogenesis. Evidence is emerging that rheumatoid synoviocytes, consisting of macrophage-like and FLS, play a central role in the pathogenesis of RA (2). These cells are the major constituents of the synovial lining layer, and pro-actively participate in inflammatory cascades and cartilage/bone destruction (2).

FLS of RA patients (RA-FLS), in particular, represent a major effector in the invasive pannus, directly participating in chronic inflammation and joint destruction (2,3). They produce high levels of matrix-metalloproteinases (MMPs), pro-inflammatory cytokines, such as interleukin (IL)-1 and IL-6 (2), and angiogenic factors, including vascular endothelial growth (VEGF) (2,3). (Fig. 1) Moreover, although RA-FLS are primary cells, they proliferate abnormally and exhibit characteristics of metastatic cancer cells, represented by somatic mutations of H-Ras and p53 genes (2,3). Besides abnormal proliferation, RA-FLS also show invasiveness and excessive migratory capacity (2,3), and even spread disease to unaffected sites when they are implanted into immuno-deficient mice (4). Despite the importance of FLS in RA pathogenesis, how RA-FLS exhibit aggressive and invasive phenotype remains unresolved. In addition, molecular signatures and biological networks defining the distinct features of RA-FLS have not been systematically explored. Therefore, there have been no drugs or trials to specifically suppress FLS proliferation and invasiveness, which may explain why RA cannot be cured by any medication currently used.

Despite distinct features in vitro, RA-FLS are exposed persistently to pro-inflammatory cytokines, growth factors, and hypoxia in vivo (in the RA joints). A number of innate and adaptive immune cells interact via an array of cytokines and/or cell-to-cell contacts, which also can similarly activate FLS, leading to the secretion of different and common cyto-chemokines, growth factors, and other inflammatory mediators (1-3). This complexity presents challenges in determining the specific roles of RA-FLS and their interplay during the progression of RA. Comparative and unbiased analyses of gene expression profiles in different cell types (5), as well as a computational framework for removing the effects of sample heterogeneity (6), may help to identify distinct and shared molecular signatures involving RA pathogenesis.

Systems analysis for

intercellular communication network

in RA synoviums

Until recently, RA pathogenesis studies have focused on traditional reductionism in the investigation and understanding of biology and medicine. In the past, “a particular gene” or bio-molecule was extracted from the systems in order to validate its functions. For instance, the growth and division as well as inflammatory reactions in a particular cell (e.g. lymphocytes or FLS) and tissue were investigated to analyze their innate properties and functions in a system (e.g. joints). However, bio-molecules in the living organism closely cooperate with other molecules as a composite body rather than acting individually. For example, most cell components interact with each other at the inter- and intra-cellular level and in organs and tissues. Furthermore, abnormal interactions between molecules and cells in a complex disorder, like RA, tend to grow in degree and range with progression of disease and as tissues or organs are deformed. Therefore, complex interactions within inter-cellular and intra-cellular communication networks (e.g. interactions between synovial fibroblasts and surrounding immune cells or between ligands and receptors in RA synovia), cannot be clearly identified by conducting fragmentary and reductive research at a single cell level.

In this regard, integration of inter- and intra-cellular communication networks is essential to identify the relations between acute and chronic inflammation and cell to cell interaction in RA. However, the existing research has focused on a limited stage of inflammatory responses or on a certain cell type to simply analyze research results involving partial pathology phenomena (e.g. macrophage activation and FLS or lymphocyte proliferation in culture system), which makes comprehensive understanding and analysis unfeasible. This limitation has been a significant hindrance to the explanation of inter- and intra-cellular communication networks in RA synovia where multiple cell types interact with each other and makes it difficult to identify novel diagnostic markers or therapeutic targets.

Summary of our hypothesis and experimental design to achieve the final goal.

Timeline for the 9 years CiRaD research