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)

The present article summarizes the discussions of the 3rd European Science Foundation-University of Barcelona (ESF-UB) Conference in Biomedicine on Pharmacogenetics and Pharmacogenomics, which was held in June 2010 in Spain. It was focused on practical applications in routine medical practice. We provide practical recommendations for ten different clinical situations, that have either been approved or not approved by regulatory agencies. We propose some comments that might accompany the results of these tests, indicating the best drug and doses to be prescribed. The discussed examples include KRAS, cetuximab, panitumumab, EGFR-gefitinib, CYP2D6-tamoxifen, TPMT-azathioprine-6-mercaptopurine, VKORC1/CYP2C9-warfarin, CYP2C19-clopidogrel, HLA-B*5701-abacavir, HLA-B*5701-flucloxacillin, SLCO1B1-statins and CYP3A5-tacrolimus. We hope that these practical recommendations will help physicians, biologists, scientists and other healthcare professionals to prescribe, perform and interpret these genetic tests.
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PMID:Practical recommendations for pharmacogenomics-based prescription: 2010 ESF-UB Conference on Pharmacogenetics and Pharmacogenomics. 2117 26

Pharmacogenetics has substantially added to our understanding of the variability of drug response. A number of single gene markers have been established and are ready to use in clinical practice. Here we review the validity and utility of markers in a number of genes (CYP2D6, CYP2C19, CYP2C9, VKORC1, TPMT, UGT1A1, OATP1B1, KRAS and HLA locus) for therapy decisions. As drug response is a complex trait in the majority of cases, most of the identified functional variants will only explain a limited part of the variability of drug response. In this sense, a phenotype is the product of many low-penetrance variations. Technical progress has not only improved the cost-effectiveness of screening for single gene markers, but offers the possibility of generating vast amounts of genome-wide single nucleotide polymorphism (SNP) or sequence data for each patient. The latest challenge is to incorporate these amounts of data into pharmacogenetic decision support. We discuss here the challenges associated with choosing the correct therapy for patients who present to their physicians with personal genome data.
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PMID:Pharmacogenetic screening for drug therapy: from single gene markers to decision making in the next generation sequencing era. 2222 55

In light of the increasing need by decision makers for a method of evaluating genomic applications based on the weight of evidence for their efficacy, several agencies have developed systems of classification. Here I review the horizon-scanning method for prioritizing genomics applications as described by Dotson et al. in this issue of CPT. Using the examples of the authors' Tier 1/Green classification for KRAS and Tier 2/Yellow for TPMT, I discuss differences between the guidelines issued by the Clinical Pharmacogenetics Implementation Consortium (CPIC) and those by the National Comprehensive Cancer Network (NCCN). Additionally, I offer suggestions regarding classification of the Tier 3/Red genomics applications and the reproducibility of the data-curating algorithm of the horizon-scanning method.
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PMID:A horizon-prioritizing method can identify gaps among genomic application guidelines. 2439 97