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Determination of the Relative Potency of an Anti-TNF Monoclonal Antibody (mAb) by Neutralizing TNF Using an In Vitro Bioanalytical Method
Published on: September 16, 2017
Pharmacogenomics of tumor necrosis factor antagonists in rheumatoid arthritis
1Washington University School of Medicine, Division of Rheumatology, 660 S. Euclid Avenue, Campus Box 8045, St. Louis, Missouri 63110, USA. prangana@ im.wustl.edu
Abstract:
Tumor necrosis factor (TNF)-alpha plays a central role in the pathogenesis of rheumatoid arthritis (RA) and is instrumental in causing joint destruction, the clinical hallmark of the disease. Recognizing this, in recent years biological therapies have been developed that work by blocking the damaging effects of TNF-alpha on synovium and cartilage. Three such agents are currently approved for treatment in RA - etanercept, infliximab and adalimumab. Although these agents are very effective in slowing the clinical and structural progression in RA, they are expensive, totaling several thousand dollars in yearly costs. Furthermore, only about 60% of patients respond effectively to these agents. As RA is a chronic disease, with most patients expected to remain on these therapies for life, ways to prospectively identify patients most likely to benefit from these agents are being explored. Pharmacogenomic approaches form the basis of most such screening methods. Polymorphisms in genes encoding TNF-alpha, TNF-alpha receptors, other cytokines, and the major histocompatibility complex region, and their ability to predict response to anti-TNF therapies, have been the focus of many recent studies. The results from such studies are mixed, with some suggesting that single nucleotide polymorphisms (SNPs) in these genes are significant, while others conclude that such SNPs are irrelevant in predicting response. Such conflicting results are likely to be due to a variety of factors, as discussed in this article. Whether pharmacogenomics will allow prediction of anti-TNF therapy efficacy in RA remains a question with no clear answers to date. Large, prospective, multicenter studies with the examination of not just individual SNPs, but also multi-SNP haplotypes, are needed to address this question in the future.
Insights
Identifying patients who will benefit from anti-tumor necrosis factor (TNF)-alpha therapies for rheumatoid arthritis (RA) is crucial. Pharmacogenomic studies exploring gene variations to predict treatment response have yielded mixed results, requiring further investigation.
Area of Science:
- Rheumatology
- Pharmacogenomics
- Immunology
Background:
- Rheumatoid arthritis (RA) pathogenesis involves tumor necrosis factor (TNF)-alpha, leading to joint destruction.
- Biological therapies targeting TNF-alpha (etanercept, infliximab, adalimumab) are effective but costly and not universally responsive.
- Identifying patients likely to benefit from anti-TNF therapy is essential for chronic RA management.
Purpose of the Study:
- To explore the utility of pharmacogenomic approaches in predicting patient response to anti-TNF therapies in rheumatoid arthritis.
- To review the current evidence and challenges in using genetic polymorphisms to guide treatment decisions for RA.
Main Methods:
- Review of recent studies investigating gene polymorphisms (e.g., SNPs) in TNF-alpha pathway genes and their association with anti-TNF therapy response.
- Analysis of factors contributing to conflicting results in existing pharmacogenomic research.
Main Results:
- Studies on gene polymorphisms (SNPs) in TNF-alpha, its receptors, and other immune-related genes have shown inconsistent results in predicting response to anti-TNF drugs.
- Some studies suggest SNP significance, while others find them irrelevant, indicating complex interactions and potential confounding factors.
Conclusions:
- Pharmacogenomic prediction of anti-TNF therapy efficacy in RA remains uncertain due to conflicting study outcomes.
- Future research requires large, prospective, multicenter studies examining individual SNPs and multi-SNP haplotypes for accurate prediction.
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