Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:2.1.1.67 (thiopurine methyltransferase)
 551 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Pharmacoeconomics and pharmacogenetics are two fields converging together as it is increasingly recognized that genetic markers predicting efficacy and toxicity to drugs can cost-effectively improve patient care. While pharmacogenetics aims at identifying genetic markers underlying the response to drugs, pharmacoeconomics aims at delivering healthcare cost-effectively. Several studies have investigated the potential cost-effectiveness of pharmacogenetic-based approaches. Recent evidences include screening for thiopurine methyltransferase gene polymorphisms to prevent azathioprine-induced myelosuppression, or screening for human leukocyte antigen (HLA)B5701 to prevent hypersensitivity reactions to abacavir therapy. Furthermore, examples suggesting a cost-effectiveness of markers predicting drug efficacy include screening the angiotensin-converting enzyme gene polymorphisms for statins therapy, the alpha-adducin gene variant for diuretic therapy and the assessment of human epidermal growth factor receptor (HER2) expression for trastuzumab therapy. However, thus far, all these pharmacoeconomic analyses are exploratory and validations in prospective randomized clinical trials are warranted.
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PMID:Overview of the pharmacoeconomics of pharmacogenetics. 1718 5

Current choice of cancer therapy is usually empirical and relies mainly on the statistical prediction of the treatment success. Molecular research provides some opportunities to personalize antitumor treatment. For example, life-threatening toxic reactions can be avoided by the identification of subjects, who carry susceptible genotypes of drug-metabolizing genes (e.g. TPMT, UGT1A1, MTHFR, DPYD). Tumor sensitivity can be predicted by molecular portraying of targets and other molecules associated with drug response. Tailoring of antiestrogen and trastuzumab therapy based on hormone and HER2 receptor status has already become a classical example of customized medicine. Other predictive markers have been identified both for cytotoxic and for targeted therapies, and include, for example, expression of TS, TP, DPD, OPRT, ERCC1, MGMT, TOP2A, class III beta-tubulin molecules as well as genomic alterations of EGFR, KIT, ABL oncogenes.
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PMID:Molecular-based choice of cancer therapy: realities and expectations. 1730 83

Precision medicine in oncology is the result of an increasing awareness of patient-specific clinical features coupled with the development of genomic-based diagnostics and targeted therapeutics. Companion diagnostics designed for specific drug-target pairs were the first to widely utilize clinically applicable tumor biomarkers (eg, HER2, EGFR), directing treatment for patients whose tumors exhibit a mutation susceptible to an FDA-approved targeted therapy (eg, trastuzumab, erlotinib). Clinically relevant germline mutations in drug-metabolizing enzymes and transporters (eg, TPMT, DPYD) have been shown to impact drug response, providing a rationale for individualized dosing to optimize treatment. The use of multigene expression-based assays to analyze an array of prognostic biomarkers has been shown to help direct treatment decisions, especially in breast cancer (eg, Oncotype DX). More recently, the use of next-generation sequencing to detect many potential "actionable" cancer molecular alterations is further shifting the 1 gene-1 drug paradigm toward a more comprehensive, multigene approach. Currently, many clinical trials (eg, NCI-MATCH, NCI-MPACT) are assessing novel diagnostic tools with a combination of different targeted therapeutics while also examining tumor biomarkers that were previously unexplored in a variety of cancer histologies. Results from ongoing trials such as the NCI-MATCH will help determine the clinical utility and future development of the precision-medicine approach.
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PMID:Precision Oncology Medicine: The Clinical Relevance of Patient-Specific Biomarkers Used to Optimize Cancer Treatment. 2719 80