Oncotarget

Reviews:

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

Mariamena Arbitrio, Maria Teresa Di Martino, Francesca Scionti, Giuseppe Agapito, Pietro Hiram Guzzi, Mario Cannataro, Pierfrancesco Tassone _ and Pierosandro Tagliaferri

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Oncotarget. 2016; 7:54028-54050. https://doi.org/10.18632/oncotarget.9927

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Abstract

Mariamena Arbitrio1, Maria Teresa Di Martino2, Francesca Scionti2, Giuseppe Agapito3, Pietro Hiram Guzzi3, Mario Cannataro3,4, Pierfrancesco Tassone2,* and Pierosandro Tagliaferri2,*

1 ISN-CNR, Roccelletta di Borgia, Catanzaro, Italy

2 Department of Experimental and Clinical Medicine, Medical Oncology Unit, Mater Domini Hospital, Magna Graecia University, Salvatore Venuta University Campus, Catanzaro, Italy

3 Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy

4 ICAR-CNR, Cosenza, Italy

* These authors have contributed equally to this work

Correspondence to:

Pierosandro Tagliaferri, email:

Pierfrancesco Tassone, email:

Keywords: pharmacogenomics, single nucleotide polymorphism, DMETTM, ADME genes, biomarkers

Received: March 14, 2016 Accepted: May 29, 2016 Published: June 09, 2016

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 DMETTM (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.


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PII: 9927