magna graecia university catanzaro italy

Further technologic tools, like germline SNP panel, can represent the ideal compromise between above mentioned genotyping methods. The approach based on tSNPs allowed to shift from a candidate-gene based approach to the genome-wide association study (GWAS). Consequently, 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.

SNPs in strong LD can be used as markers of a specific haplotype. SNPs are inherited in haplotype blocks spanning within two high hyper-recombination sites (Hot Spot) and in strong LD with specific polymorphic variants in genes located in the same block. In the human genome, SNPs are common inherited variations (>1%) among people in which the DNA sequence may show variants at a single nucleotide level and which can have functional relevance when occurs in coding sequences or in regulatory regions. The most common germline variations studied in PGx are SNPs, insertions, deletions, and copy number variations (CNVs). The effects in PK changes become relevant in patients where genetic polymorphisms can alter the effect on the body and on drug metabolism. Specifically, the activity of polymorphic variants in PK relevant ADME genes, coding for enzymes, transporters, cell membrane, and/or intracellular receptors or components of ion channels, can affect patient’s drug exposure and the efficacy and toxicity for many drugs, especially anti-tumor agents. The germline genome can impact treatment outcome in terms of pharmacokinetics (PK) and pharmacodynamics (PD). The somatic non-inherited mutations in tumor tissue can define disease subtypes and predict drug efficacy and clinical outcome of different tumors. The interindividual variability in drug efficacy and toxicity can be solved by knowledge of somatic (tumor) or germline (patients) variations. 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. Hence, the identification of PGx biomarkers has the potentiality of optimizing treatment for individuals toward the precision medicine paradigm. Polymorphic variants in genes related to drug absorption, distribution, metabolism and excretion (ADME) contribute to interindividual variability in drug efficacy and adverse effects. The study of genetically influenced variations in drug response and ADRs risk is known as PGx which, in particular, focuses on gene-drug relationships highlighting the role of genetic, biological, and molecular mechanisms. 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. Although pharmacogenomic studies were performed in adult cohorts, pharmacogenetic pediatric research has yielded promising results. 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. 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. 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. In the past decades, many efforts have been made to individualize medical treatments, taking into account molecular profiles and the individual genetic background.

Magna graecia university catanzaro italy