Methotrexate normalizes up-regulated folate pathway genes in rheumatoid arthritis.

OBJECTIVE: The folate antagonist methotrexate (MTX) is an anchor drug in the treatment of rheumatoid arthritis (RA), but its mechanism of action with regard to the impact on folate metabolism remains elusive. The aim of the present study was to investigate the cellular pharmacologic impact of MTX on peripheral blood cells, by comparing MTX-treated RA patients to MTX-naive RA patients and healthy controls. METHODS: Gene expression microarray data were used to investigate the expression of 17 folate pathway genes by peripheral blood cells from a cohort of 25 RA patients treated with MTX, 10 MTX-naive RA patients starting treatment with MTX, and 15 healthy controls (test cohort). Multiplex real-time polymerase chain reaction was used to validate the results in an independent cohort, consisting of 151 RA patients treated with MTX, 28 MTX-naive RA patients starting treatment with MTX, and 24 healthy controls (validation cohort). RESULTS: Multiple folate metabolism-related genes were consistently and significantly altered between the 3 groups in both cohorts. Concurrent with evidence of an immune-activation gene signature in MTX-naive RA patients, significant up-regulation of the folate-metabolizing enzymes γ-glutamyl hydrolase and dihydrofolate reductase, as well as the MTX/folate efflux transporters ABCC2 and ABCC5, was observed in the MTX-naive RA group compared to healthy controls. Strikingly, MTX treatment of RA patients normalized these differential gene expression levels to the levels observed in healthy controls. CONCLUSION: These results suggest that under inflammatory conditions, basal folate metabolism in the peripheral blood cells of RA patients is markedly up-regulated, and treatment with MTX restores folate metabolism to normal levels. Identification of this novel gene signature provides insight into the mechanism of action of MTX, thus paving the way for development of novel folate metabolism-targeted therapies.

A domino effect in drug action: from metabolic assault towards parasite differentiation.

Awareness is growing that drug target validation should involve systems analysis of cellular networks. There is less appreciation, though, that the composition of networks may change in response to drugs. If the response is homeostatic (e.g. through upregulation of the target protein), this may neutralize the inhibitory effect. In this scenario the effect on cell growth and survival would be less than anticipated based on affinity of the drug for its target. Glycolysis is the sole free-energy source for the deadly parasite Trypanosoma brucei and is therefore a possible target pathway for anti-trypanosomal drugs. Plasma-membrane glucose transport exerts high control over trypanosome glycolysis and hence the transporter is a promising drug target. Here we show that at high inhibitor concentrations, inhibition of trypanosome glucose transport causes cell death. Most interestingly, sublethal concentrations initiate a domino effect in which network adaptations enhance inhibition. This happens via (i) metabolic control exerted by the target protein, (ii) decreases in mRNAs encoding the target protein and other proteins in the same pathway, and (iii) partial differentiation of the cells leading to (low) expression of immunogenic insect-stage coat proteins. We discuss how these 'anti-homeostatic' responses together may facilitate killing of parasites at an acceptable drug dosage.

Type I interferon response gene expression in established rheumatoid arthritis is not associated with clinical parameters.

BACKGROUND: A peripheral blood interferon (IFN) signature (i.e., elevated type I interferon response gene [IRG] expression) has been described in a subset of patients with rheumatoid arthritis (RA). In the present study, we systematically assessed the association between this IRG expression and clinical parameters. METHODS: Expression of 19 IRGs was determined in peripheral blood from 182 consecutive patients with RA and averaged into an IFN score per individual. Correlation and unpaired analyses were performed on the complete patient group. The analyses were internally validated by using an algorithm to randomize the patient group 1000 times into two equally sized sets, and then analyses were performed on both sets. RESULTS: Associations were assessed between IFN score and disease duration, 28-joint Disease Activity Score and its components, the occurrence of erosions and nodules, autoantibody positivity, and immunosuppressive treatment. This analysis revealed lower IFN scores in patients using hydroxychloroquine, prednisone, and/or sulfasalazine, but it did not show significant associations between the other parameters and the IFN score. Selecting patients who were not treated with hydroxychloroquine, prednisone, and/or sulfasalazine (n = 95) did not reveal any significant associations either. CONCLUSIONS: IRG expression in RA is affected by immunosuppressive treatment with prednisone, hydroxychloroquine, and/or sulfasalazine, but it is not evidently associated with other clinical parameters. Hence, the IFN signature appears to describe a subgroup of patients with RA but does not seem to reflect disease activity.

Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab.

INTRODUCTION: Elevated type I interferon (IFN) response gene (IRG) expression has proven clinical relevance in predicting rituximab non-response in rheumatoid arthritis (RA). Interference between glucocorticoids (GCs) and type I IFN signaling has been demonstrated in vitro. Since GC use and dose are highly variable among patients before rituximab treatment, the aim of this study was to determine the effect of GC use on IRG expression in relation to rituximab response prediction in RA. METHODS: In two independent cohorts of 32 and 182 biologic-free RA patients and a third cohort of 40 rituximab-starting RA patients, peripheral blood expression of selected IRGs was determined by microarray or quantitative real-time polymerase chain reaction (qPCR), and an IFN-score was calculated. The baseline IFN-score was tested for its predictive value towards rituximab response in relation to GC use using receiver operating characteristics (ROC) analysis in the rituximab cohort. Patients with a decrease in disease activity score (∆DAS28) >1.2 after 6 months of rituximab were considered responders. RESULTS: We consistently observed suppression of IFN-score in prednisone users (PREDN(+)) compared to non-users (PREDN(-)). In the rituximab cohort, analysis on PREDN(-) patients (n = 13) alone revealed improved prediction of rituximab non-response based on baseline IFN-score, with an area under the curve (AUC) of 0.975 compared to 0.848 in all patients (n = 40). Using a group-specific IFN-score cut-off for all patients and PREDN(-) patients alone, sensitivity increased from 41% to 88%, respectively, combined with 100% specificity. CONCLUSIONS: Because of prednisone-related suppression of IFN-score, higher accuracy of rituximab response prediction was achieved in PREDN(-) patients. These results suggest that the IFN-score-based rituximab response prediction model could be improved upon implementation of prednisone use.