Predict Methotrexate Response Research Articles

The implication of adenosine receptor expression in prediction of methotrexate clinical response in Egyptian rheumatoid arthritis patients

BackgroundAdenosine signaling is now an accepted explanation for the therapeutic mechanism of Methotrexate (MTX) in rheumatoid arthritis (RA). Adenosine receptors categorized into four subclasses: adenosine A1 receptor (ADORA1), adenosine 2a receptor (ADORA2a), adenosine 2b receptor (ADORA2B), and adenosine 3 receptor (ADORA3). Our aim is to check the mRNA expression of two adenosine receptors; ADORA2a and ADORA3 in whole blood cell of RA patients and its relation in prediction of MTX clinical response in Egyptian patients.ResultsThere was significant correlation between both ADORA2a and ADORA3 gene expression in RA patients as compared with healthy controls. The expression of ADORA2a and ADORA3 was increased in good and moderate response groups compared to no response group. There was significant correlation between both genes in mRNA expression before and after MTX treatment. Matrix metalloproteinase-3 (MMP3) concentration was significantly decreased after treatment in good and moderate response groups in comparison to non-responder group.ConclusionThe inflammatory and clinical responses in RA patients which is demonstrated by DAS28 and suppression of MMP3 were regulated by ADORA2a and ADORA3. Their level of expression can predict MTX response and their agonists may offer a novel and effective therapeutic option for RA patients.

The Macrophage Reprogramming Ability of Antifolates Reveals Soluble CD14 as a Potential Biomarker for Methotrexate Response in Rheumatoid Arthritis

The identification of “trained immunity/tolerance” in myeloid cells has changed our perception of the performance of monocytes and macrophages during inflammatory and immune responses. Pemetrexed (PMX) and methotrexate (MTX) are blockers of the one-carbon metabolism (OCM) and commonly used therapeutic agents in cancer and rheumatoid arthritis (RA). We have previously showed that MTX promotes trained immunity in human macrophages. In the present manuscript, we have assessed the anti-inflammatory effects of PMX and MTX and found that OCM blockers alter the functional and gene expression profile of human macrophages and that OCM blockade reprograms macrophages towards a state of lipopolysaccharide (LPS) tolerance at the signaling and functional levels. Moreover, OCM blockade reduced macrophage LPS responsiveness by impairing the expression of membrane-bound and soluble CD14 (sCD14). The therapeutic relevance of these results was later confirmed in early RA patients, as MTX-responder RA patients exhibit lower sCD14 serum levels, with baseline sCD14 levels predicting MTX response. As a whole, our results demonstrate that OCM is a metabolic circuit that critically mediates the acquisition of innate immune tolerance and positions sCD14 as a valuable tool to predict MTX response in RA patients.

Role of Serum MRP8/14 in Predicting Response to Methotrexate in Children With Juvenile Idiopathic Arthritis.

Nearly 40% of children with juvenile idiopathic arthritis (JIA) might not respond to first-line disease-modifying antirheumatic drugs (DMARDs) including methotrexate (MTX). Hence, there is a need for a biomarker that can predict MTX response and help in tailoring initial therapy. Our objective was to study the role of serum myeloid-related protein (MRP) 8/14, and other inflammatory cytokines, as predictors of response to MTX among children with JIA. We did a longitudinal follow-up study among children diagnosed with JIA at our institute. All MTX-naive children with JIA requiring DMARDs were eligible for this study; those who either took corticosteroids or DMARDs for more than 6 weeks at time of presentation were excluded. The demographic and clinical information was collected using a pretested semistructured questionnaire, and selected biomarkers were collected at baseline and again at 3 months. Response at 3 months was assessed using the American College of Rheumatology (ACR) criteria; responders were children who achieved ACR50, whereas those failing to achieve ACR30 were classified as nonresponders. Multivariate binary logistic regression was done to assess determinants of being a responder. We enrolled 69 children (36 boys) with JIA, of which 48 (69.5%) were responders. The baseline value of serum MRP8/14 was significantly higher in responders (median, 144.34 [interquartile range, 88.54-188.34] ng/mL) compared with the nonresponders (median, 95.34 [interquartile range, 76.54-130.28] ng/mL), p = 0.047. Being a responder was significantly associated with baseline serum MRP8/14 with adjusted odds ratio of 1.01 (95% confidence interval, 1.00-1.02). The baseline levels of MRP8/14 were significantly raised in children meeting ACR50 at follow-up and suggest a prognostic value in predicting response to MTX.

P17 Prediction of response of methotrexate in patients with rheumatoid arthritis using serum lipidomics

Abstract Background For patients with rheumatoid arthritis (RA), introduction of early, effective therapy has consistently been shown to improve long-term outcomes. Low-dose methotrexate (MTX) is commonly prescribed as first-line treatment for RA. However, MTX is not effective for a large minority of patients and there is currently no way to determine ahead of therapy which patients are most likely to benefit. Metabolomics and lipidomics are emerging approaches for studying patient stratification in RA and have the potential to identify disease processes that underpin treatment outcomes. Here we apply state-of-the-art machine learning algorithms to predict MTX treatment response, by testing serum lipid levels measured at two time-points (pre-treatment and following 4 weeks on drug) to predict MTX response by 6 months. Methods This study included patients from the Rheumatoid Arthritis Medication Study (RAMS), a UK multi-centre one-year prospective observational study investigating predictors of response to MTX in patients with RA. Since 2008, patients who are about to start MTX for the first time are asked to provide demographic and clinical data, as well as blood samples to permit DNA, RNA and serum-based biomarker studies. Patients about to commence MTX treatment were followed longitudinally and those categorised as good or non-responders following 6 months on-drug using EULAR response criteria were analysed. Serum lipid levels were measured at pre-treatment and following 4 weeks on drug using ultra-performance liquid chromatography tailored for complex lipid analysis, coupled to mass spectrometry. State-of-the-art supervised machine learning methods were then applied to predict EULAR response at 6 months. Models including lipid levels were compared to models including clinical covariates (including: MTX start dose, steroid use at inclusion, BMI, number of swollen joints, number of tender joints, CRP levels, patients’ assessment of their overall wellbeing, gender, age-at-inclusion, age-at-onset, disease duration, HAQ score and pre-treatment smoking habits). Results Following quality control, 3,366 features (1,060 in negatively-charged mode and 2,306 in positive mode) were available for analysis at pre-treatment and 4 weeks from 100 RA patients categorised as good (GR, n = 50) or poor (NR, n = 50) responders to MTX following 6 months on drug. The best model performance for the classifier including clinical covariates was observed using L1/L2-regularised logistic regression (ROC AUC 0.68 ± 0.02). However, the clinical covariate model outperformed the classifier including lipid levels when either pre- or on-treatment time-points were investigated (ROC AUC 0.61 ± 0.02). Conclusion These data do not support the utility of early treatment lipidomic monitoring in routine clinical practice in patients started on MTX for their RA. Disclosures M. Maciejewski: Shareholder/stock ownership; owns stock or stock options in Pfizer. C. Sands None. N. Nair None. S. Ling None. S. Verstappen None. K. Hyrich None. A. Barton None. D. Ziemek Shareholder/stock ownership; owns stock or stock options in Pfizer. M. Lewis None. D. Plant None.

5-aminoimidazole-4-carboxamide ribonucleotide-transformylase and inosine-triphosphate-pyrophosphatase genes variants predict remission rate during methotrexate therapy in patients with juvenile idiopathic arthritis

For children with Juvenile Idiopathic Arthritis (JIA) who fail to respond to methotrexate, the delay in identifying the optimal treatment at an early stage of disease can lead to long-term joint damage. Recent studies indicate that relevant variants to predict methotrexate response in JIA are those in 5-aminoimidazole-4-carboxamide ribonucleotide-transformylase (ATIC), inosine-triphosphate-pyrophosphatase (ITPA) and solute-liquid-carrier-19A1 (SLC19A1) genes.

PReS-FINAL-2165: Pharmacogenetic determinants of response to methotrexate in juvenile idiopathic arthritis

Juvenile idiopathic arthritis (JIA) is the most common arthritis disease of childhood and is an important cause of disability. Methotrexate (MTX) is the mainstay treatment in JIA. Unfortunately, 30-35% of patients fail to respond MTX, and the delay in identifying the optimal treatment at an early stage of disease can lead to long-term joint damage. Recent studies have evaluated comprehensively the effect of genetic variants in candidate genes involved in MTX pharmacokinetics and pharmacodynamics on the response to the medication in children with JIA. These studies seem to indicate that the most relevant variants to predict MTX response in JIA are those in ATIC, ITPA and SLC19A1 genes.

An immunological biomarker to predict MTX response in early RA

ObjectivesThe therapeutic goal for patients with rheumatoid arthritis (RA) is clinical remission. This is best achieved by early diagnosis and appropriate therapeutic intervention. RA is associated with dysregulation of T-cell...

Translational medicine from bedside to bench and back again: methotrexate revisited

Translational medicine efforts, geared towards the development of new drugs, have brought numerous biologicals from the bedside of rheumatoid and juvenile idiopathic arthritis patients to bench. Biologicals took the attention of the pharmaceutical industry, as well as rheumatologists, away from the first drug that advanced the treatment of rheumatic diseases – methotrexate (MTX). As a consequence, crucial unmet needs surrounding MTX still remain poorly elucidated, even though this anchor drug is taken by many more patients than biologicals and its efficacy has not consistently been surpassed by biologicals in MTX-naive patients. These unmet needs include an incomplete understanding of anti-inflammatory actions of MTX and the inability to predict MTX response. Addressing these needs will result not only in optimization of MTX use, but also of biological use, leading to personalized tailor-made therapy. This review will discuss the place of MTX in juvenile idiopathic arthritis, illustrated by examples from ...

Genetic polymorphisms in key methotrexate pathway genes are associated with response to treatment in rheumatoid arthritis patients

We investigated the effect of Single Nucleotide Polymorphisms (SNPs) spanning 10 methotrexate (MTX) pathway genes, namely AMPD1, ATIC, DHFR, FPGS, GGH, ITPA, MTHFD1, SHMT1, SLC19A1 (RFC) and TYMS on the outcome of MTX treatment in a UK rheumatoid arthritis (RA) patient cohort. Tagging SNPs were selected and genotyping performed in 309 patients with predefined outcomes to MTX treatment. Of the 129 SNPs tested, 11 associations were detected with efficacy (p-trend ≤ 0.05) including four SNPs in the ATIC gene (rs12995526, rs3821353, rs7563206 and rs16853834), 6 SNPs in the SLC19A1 gene region (rs11702425, rs2838956, rs7499, rs2274808, rs9977268, rs7279445) and a single SNP within the GGH gene (rs12681874). Five SNPs were significantly associated with adverse events; three in the DHFR gene (rs12517451, rs10072026, and rs1643657) and two of borderline significance in the FPGS gene. The results suggest that genetic variations in several key MTX pathway genes may influence response to MTX in RA patients. Further studies will be required to validate these findings and if confirmed these results could contribute towards a better understanding of and ability to predict MTX response in RA.

Biomarkers Predict p53 Gene Therapy Efficacy in Recurrent Squamous Cell Carcinoma of the Head and Neck

PURPOSE: Most recurrent squamous cell carcinomas of the head and neck have a dysfunctional p53 tumor suppressor pathway contributing to treatment resistance. We hypothesized that tumor p53 biomarkers may predict the efficacy of normal p53 delivered by gene therapy in these patients. EXPERIMENTAL DESIGN: Tumor p53 biomarkers were evaluated in 116 patients, including 29 treated with methotrexate in a phase III randomized controlled trial. Profiles favorable for p53 gene therapy efficacy were hypothesized to have either normal p53 gene sequences or low-level p53 protein expression, whereas unfavorable p53 inhibitor profiles were predicted to have high-level expression of mutated p53 that can inhibit normal p53 protein function. RESULTS: A statistically significant increase in tumor responses was observed for patients with favorable p53 efficacy profiles compared with those with unfavorable p53 inhibitor profiles [phase I/II trials: favorable (34 of 46, 74%) versus unfavorable (1 of 5, 20%), P = 0.0290; phase III trial: favorable (17 of 24, 71%) versus unfavorable (2 of 11, 18%), P = 0.0088]. In the phase III trial, there was statistically significant increased time to progression (TTP) and survival following p53 gene therapy in patients with favorable p53 profiles compared with unfavorable p53 inhibitor profiles (median TTP, 2.7 months versus 1.4 months, P = 0.0121; median survival, 7.2 months versus 2.7 months, P < 0.0001). In contrast, the biomarker profiles predictive of p53 gene therapy efficacy did not predict methotrexate response, TTP, or survival outcomes. CONCLUSIONS: These results indicate that tumor p53 biomarker profiles may predict p53 gene therapy efficacy in recurrent squamous cell carcinoma of the head and neck. (Clin Cancer Res 2009;15(24):7719-25).