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)

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

The dose of docetaxel is currently calculated based on body surface area and does not reflect the pharmacokinetic, metabolic potential or genetic background of the patients. The influence of genetic variation on the clearance of docetaxel was analysed in a two-stage analysis. In step one, 583 single-nucleotide polymorphisms (SNPs) in 203 genes were genotyped on samples from 24 patients with locally advanced non-small cell lung cancer. We found that many of the genes harbour several SNPs associated with clearance of docetaxel. Most notably these were four SNPs in EGF, three SNPs in PRDX4 and XPC, and two SNPs in GSTA4, TGFBR2, TNFAIP2, BCL2, DPYD and EGFR. The multiple SNPs per gene suggested the existence of common haplotypes associated with clearance. These were confirmed with detailed haplotype analysis. On the basis of analysis of variance (ANOVA), quantitative mutual information score (QMIS) and Kruskal-Wallis (KW) analysis SNPs significantly associated with clearance of docetaxel were confirmed for GSTA4, PRDX4, TGFBR2 and XPC and additional putative markers were found in CYP2C8, EPHX1, IGF2, IL1R2, MAPK7, NDUFB4, TGFBR3, TPMT (2 SNPs), (P<0.05 or borderline significant for all three methods, 14 SNPs in total). In step two, these 14 SNPs were genotyped in additional 9 samples and the results combined with the genotyping results from the first step. For 7 of the 14 SNPs, the results are still significant/borderline significant by all three methods: ANOVA, QMIS and KW analysis strengthening our hypothesis that they are associated with the clearance of docetaxel.
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PMID:SNPs in genes coding for ROS metabolism and signalling in association with docetaxel clearance. 2015 31

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

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