Abstract
In the past decades, many efforts have been made to individualize medical treatments, taking into account molecular profiles and the individual genetic background. The development of molecularly targeted drugs and immunotherapy have revolutionized medical treatments but the inter-patient variability in the anti-tumor drug pharmacokinetics (PK) and pharmacodynamics can be explained, at least in part, by genetic variations in genes encoding drug metabolizing enzymes and transporters (ADME) or in genes encoding drug receptors. Here, we focus on high-throughput technologies applied for PK screening for the identification of predictive biomarkers of efficacy or toxicity in cancer treatment, whose application in clinical practice could promote personalized treatments tailored on individual’s genetic make-up. Pharmacogenomic tools have been implemented and the clinical utility of pharmacogenetic screening could increase safety in patients for the identification of drug metabolism-related biomarkers for a personalized medicine. Although pharmacogenomic studies were performed in adult cohorts, pharmacogenetic pediatric research has yielded promising results. Additionally, we discuss the current challenges and theoretical bases for the implementation of pharmacogenetic tests for translation in the clinical practice taking into account that pharmacogenomics platforms are discovery oriented and must open the way for the setting of robust tests suitable for daily practice.
Highlights
Over the past few decades, pharmacogenomics (PGx) studies contributed to the understanding of the interindividual variability in response to drug treatment opening a new scenario toward personalized approaches in the modern health care
A modest number of common single nucleotide polymorphisms (SNPs), selected from each block and considered as tag or tagging SNP, would allow to identify the gene variants related to a disease or to interindividual variability in drug response or toxicity [6]
More and more advanced and sophisticated technologies allowed the identification of genomic loci associated to interindividual variability in drug response, the primary objective of these approaches was towards the mapping and discovery of genes that may have a role in disease development or risk [7]
Summary
Over the past few decades, pharmacogenomics (PGx) studies contributed to the understanding of the interindividual variability in response to drug treatment opening a new scenario toward personalized approaches in the modern health care. The HapMap Project brought to identify haplotype blocks of common single nucleotide polymorphisms (SNPs) in different human populations which were co-inherited and in linkage disequilibrium (LD) with specific genetic variants with important functional variability [1]. The identification of PGx biomarkers has the potentiality of optimizing treatment for individuals toward the precision medicine paradigm In this context, the major goal for cancer treatment in a personalized approach is to select the right dose of the right drug for a right tumor in the right patient. A modest number of common SNPs, selected from each block and considered as tag or tagging SNP (tSNP), would allow to identify the gene variants related to a disease or to interindividual variability in drug response or toxicity [6]. The purpose of this review is to critically discuss advantages and weaknesses of different PGx approaches for the discovery of germline predictive biomarkers in ADME genes comparing potentialities and limitations of different PGx tools for pre-treatment testing for translation into common practice for personalized treatment
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