No abstract

Rheumatoid arthritis (RA) and osteoarthritis (OA), two common types of arthritis, affect the joints mainly by targeting the synovium and cartilage. Increasing evidence indicates that a significant network connects synovitis and cartilage destruction during the progression of arthritis. We recently demonstrated that hypoxia-inducible factor (HIF)-2α causes RA and OA by regulating the expression of catabolic factors in fibroblast-like synoviocytes (FLS) or chondrocytes. To address the reciprocal influences of HIF-2α on FLS and chondrocytes, we applied an in vitro co-culture system using a transwell apparatus. When co-cultured with HIF-2α-overexpressing chondrocytes, FLS exhibited increased expression of matrix metalloproteinases and inflammatory mediators, similar to the effects induced by tumor-necrosis factor (TNF)-α treatment of FLS. Moreover, chondrocytes co-cultured with HIF-2α-overexpressing FLS exhibited upregulation of Mmp3 and Mmp13, which is similar to the effects induced by interleukin (IL)-6 treatment of chondrocytes. We confirmed these differential HIF-2α-induced effects via distinct secretory mediators using Il6-knockout cells and a TNF-α-blocking antibody. The FLS-co-culture-induced gene expression changes in chondrocytes were significantly abrogated by IL-6 deficiency, whereas TNF-α neutralization blocked the alterations in gene expression associated with co-culture of FLS with chondrocytes. Our results further suggested that the observed changes might reflect the HIF-2α-induced upregulation of specific receptors for TNF-α (in FLS) and IL-6 (in chondrocytes). This study broadens our understanding of the possible regulatory mechanisms underlying the crosstalk between the synovium and cartilage in the presence of HIF-2α, and may suggest potential new anti-arthritis therapies.

We attempted to identify significant pathway cross-talk in rheumatoid arthritis (RA) by the Monte Carlo cross-validation (MCCV) method. We therefore obtained and preprocessed the gene expression profile of RA. MCCV involves identifying differentially expressed genes (DEGs), identifying differential pathways (DPs), calculating the discriminating score (DS) of the pathway cross-talk, and random forest (RF) classification. We carried out 50 bootstrap iterations of MCCV to identify the key instances of pathway cross-talk involved in RA. We identified a total of 17 significant DEGs and 15 significant DPs by comparing RA samples and normal controls. We found the most significant difference between RA and the normal controls in the eIF4 and p70S6K signaling regulation pathway. Furthermore, we identified 10 instances of pathway cross-talk with the best classification performance for RA and normal controls, using the RF classification model. All of the top 10 pathway pairs involved cross-talk with eIF4 and p70S6K signaling regulation, and the other 10 pathways were immune-related. By MCCV, we identified one critical DP and 10 significant instances of pathway cross-talk in RA. We propose that the eIF4 and p70S6K signaling regulation pathway and the other significant instances of pathway cross-talk play key roles in the occurrence and development of RA, and are potential predictive and prognostic markers for RA.