Structural Basis for How Biologic Medicines Bind their Targets in Psoriasis Therapy.
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ABSTRACT:
SUBMITTER: Eldirany SA
PROVIDER: S-EPMC7087057 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
Publications
Structural Basis for How Biologic Medicines Bind their Targets in Psoriasis Therapy.
Eldirany Sherif A SA Ho Minh M Bunick Christopher G CG
The Yale journal of biology and medicine 20200327 1
As biologic therapies become first line treatments for many inflammatory disorders, it becomes increasingly important for the practicing physician to be familiar with how these drugs function at the molecular level. This information is useful in making therapeutic decisions and helping patients understand their treatment options. It is critical to patient safety and clinical response that the molecular differences between these drugs inform prescribing practices. To this end, we present and anal ...[more]
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Project description:Background and objectives: Psoriasis is a chronic immune-mediated skin disease caused by several complex factors, both environmental and genetic, many of which are still not fully understood. Nowadays, several groups of biological drugs are being used for psoriasis treatment. Although these therapies are very effective, they show significant variability in efficacy among individuals. Therefore, there is a need for biomarkers to predict treatment outcomes in order to guide personalized therapeutic decisions. Pharmacogenetics is the study of variations in DNA sequences related to drug response. Materials and Methods: In this article, we review pharmacogenetics studies on the treatment of moderate-to-severe psoriasis focusing on anti-interleukin (IL) 12/23 (ustekinumab) and anti-IL17 drugs (secukinumab and ixekizumab), as well as recent studies concerning anti-TNF drugs. Results: Several polymorphisms have been studied over the years in reference to anti-TNF drugs; some of the most recent studies included the performance of a genome-wide association study (GWAS) and pharmacogenetics studies focused on the optimization of a treatment regimen. Various polymorphisms in different genes have been related to ustekinumab response; among them, the most commonly studied is the HLA-C*06:02 allele. Conclusions: Although not confirmed in some studies, most studies have shown that patients carrying this allele present a significantly higher response rate to ustekinumab. Some polymorphisms have been studied in patients treated with anti-IL17 drugs, mostly related to secukinumab; however, up to now, no association has been found between any of these polymorphisms and response. Nevertheless, further studies involving larger cohorts are needed in order to confirm these results before the implementation of this biomarker in clinical practice.
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Project description:Biologic therapies have shown high efficacy in psoriasis, but individual response varies and is poorly understood. To inform biomarker discovery in the Psoriasis Stratification to Optimise Relevant Therapy (i.e., PSORT) study, we evaluated a comprehensive array of omics platforms across three time points and multiple tissues in a pilot investigation of 10 patients with severe psoriasis, treated with the tumor necrosis factor (TNF) inhibitor, etanercept. We used RNA sequencing to analyze mRNA and small RNA transcriptome in blood, lesional and nonlesional skin, and the SOMAscan platform to investigate the serum proteome. Using an integrative systems biology approach, we identified signals of treatment response in genes and pathways associated with TNF signaling, psoriasis pathology, and the major histocompatibility complex region. We found association between clinical response and TNF-regulated genes in blood and skin. Using a combination of differential expression testing, upstream regulator analysis, clustering techniques, and predictive modeling, we show that baseline samples are indicative of patient response to biologic therapies, including signals in blood, which have traditionally been considered unreliable for inference in dermatology. In conclusion, our pilot study provides both an analytical framework and empirical basis to estimate power for larger studies, specifically the ongoing PSORT study, which we show as powered for biomarker discovery and patient stratification.
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