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Review
. 2016 Aug 16;7(33):54028-54050.
doi: 10.18632/oncotarget.9927.

DMET™ (Drug Metabolism Enzymes and Transporters): a pharmacogenomic platform for precision medicine

Mariamena Arbitrio  1 , Maria Teresa Di Martino  2 , Francesca Scionti  2 , Giuseppe Agapito  3 , Pietro Hiram Guzzi  3 , Mario Cannataro  3   4 , Pierfrancesco Tassone  2 , Pierosandro Tagliaferri  2
Affiliations
Review

DMET™ (Drug Metabolism Enzymes and Transporters): a pharmacogenomic platform for precision medicine

Mariamena Arbitrio et al. Oncotarget. .

Abstract

In the era of personalized medicine, high-throughput technologies have allowed the investigation of genetic variations underlying the inter-individual variability in drug pharmacokinetics/pharmacodynamics. Several studies have recently moved from a candidate gene-based pharmacogenetic approach to genome-wide pharmacogenomic analyses to identify biomarkers for selection of patient-tailored therapies. In this aim, the identification of genetic variants affecting the individual drug metabolism is relevant for the definition of more active and less toxic treatments. This review focuses on the potentiality, reliability and limitations of the DMET™ (Drug Metabolism Enzymes and Transporters) Plus as pharmacogenomic drug metabolism multi-gene panel platform for selecting biomarkers in the final aim to optimize drugs use and characterize the individual genetic background.

Keywords: ADME genes; DMET™; biomarkers; pharmacogenomics; single nucleotide polymorphism.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1. TagSNPs and recombination hotspots
Single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) are coheredited in haplotype blocks. TagSNPs are used to identify gene variants potentially correlated to phenotypes, withouth the need to genotpype all SNPs included in each haplotype block.
Figure 2
Figure 2. DMET gene list
Genes included in DMET™ plus platform (231 total genes) are: 76 phase I enzymes, 62 phase II enzymes, 51 transporters and 41 other genes. * = translated to predicted phenotype/metabolizer status.
Figure 3
Figure 3. DMET data analysis workflow
Figure 4
Figure 4. Statistical analysis and interpretation
The picture describes necessary steps to convert intensity value in actionable knowledge. Each column represents the flow of information when using respectively DMET® Console, apt-DMET-genotype and DMET-Analyzer.
Figure 5
Figure 5. Biomarkers validation workflow
Figure 6
Figure 6. Genotyping platform for personalized therapy: genetic variants in pharmacodynamics and pharmacokinetics related genes determine inter-individual variability and therapeutical outcome
Patients predicted as non responder should undergo treatment with alternative drugs; patients predicted at risk of drug toxicity should undergo dose reduction.
See this image and copyright information in PMC

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