Pharmacogenomic Profiling of ADME Gene Variants: Current Challenges and Validation Perspectives

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.

[1]  Mario Cannataro,et al.  Single nucleotide polymorphisms of ABCC5 and ABCG1 transporter genes correlate to irinotecan-associated gastrointestinal toxicity in colorectal cancer patients: A DMET microarray profiling study , 2011, Cancer biology & therapy.

[2]  Jill P. Mesirov,et al.  Criteria for the use of omics-based predictors in clinical trials , 2013, Nature.

[3]  Ronald W. Davis,et al.  Multiplexed genotyping with sequence-tagged molecular inversion probes , 2003, Nature Biotechnology.

[4]  Peter Kraft,et al.  Drinking from the fire hose--statistical issues in genomewide association studies. , 2007, The New England journal of medicine.

[5]  Kenneth Offit,et al.  Genome-wide association studies of cancer. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[6]  Robert Brian Jenkins,et al.  Molecular Testing Guideline for Selection of Lung Cancer Patients for EGFR and ALK Tyrosine Kinase Inhibitors: Guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology , 2013, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[7]  I. Ellis,et al.  The updated ASCO/CAP guideline recommendations for HER2 testing in the management of invasive breast cancer: a critical review of their implications for routine practice , 2014, Histopathology.

[8]  Mario Cannataro,et al.  DMET-Analyzer: automatic analysis of Affymetrix DMET Data , 2012, BMC Bioinformatics.

[9]  J. Jukema,et al.  Genetics: Genetic risk scores—new promises for drug evaluation , 2015, Nature Reviews Cardiology.

[10]  M. Kennedy,et al.  Impact of New Genomic Technologies on Understanding Adverse Drug Reactions , 2015, Clinical Pharmacokinetics.

[11]  Mario Cannataro,et al.  Identification of polymorphic variants associated with erlotinib-related skin toxicity in advanced non-small cell lung cancer patients by DMET microarray analysis , 2015, Cancer Chemotherapy and Pharmacology.

[12]  M. Shapero,et al.  DMET microarray technology for pharmacogenomics-based personalized medicine. , 2010, Methods in molecular biology.

[13]  D. Meyers,et al.  Pharmacogenetics: implications of race and ethnicity on defining genetic profiles for personalized medicine. , 2014, The Journal of allergy and clinical immunology.

[14]  Andrew Wallace,et al.  A standardized framework for the validation and verification of clinical molecular genetic tests , 2010, European Journal of Human Genetics.

[15]  Ahmed Kamel,et al.  Colon Cancer, Version 1.2017, NCCN Clinical Practice Guidelines in Oncology. , 2017, Journal of the National Comprehensive Cancer Network : JNCCN.

[16]  Christine M. Micheel,et al.  COMMITTEE ON THE REVIEW OF OMICS-BASED TESTS FOR PREDICTING PATIENT OUTCOMES IN CLINICAL TRIALS , 2012 .

[17]  Micheline Piquette-Miller,et al.  User considerations in assessing pharmacogenomic tests and their clinical support tools , 2018, npj Genomic Medicine.

[18]  M. Gulley,et al.  Recommended principles and practices for validating clinical molecular pathology tests. , 2009, Archives of pathology & laboratory medicine.

[19]  R. Myers,et al.  Candidate-gene approaches for studying complex genetic traits: practical considerations , 2002, Nature Reviews Genetics.

[20]  M. Pirmohamed Acceptance of Biomarker‐Based Tests for Application in Clinical Practice: Criteria and Obstacles , 2010, Clinical pharmacology and therapeutics.

[21]  Giuseppe Agapito,et al.  Genetic variants associated with gastrointestinal symptoms in Fabry disease , 2016, Oncotarget.

[22]  Sharon R Grossman,et al.  Integrating common and rare genetic variation in diverse human populations , 2010, Nature.

[23]  Lei Li,et al.  The role of ADME pharmacogenomics in early clinical trials: perspective of the Industry Pharmacogenomics Working Group (I-PWG). , 2015, Pharmacogenomics.

[24]  M. Schwab,et al.  Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation. , 2013, Pharmacology & therapeutics.

[25]  Magali Olivier,et al.  Somatic mutations in cancer prognosis and prediction: lessons from TP53 and EGFR genes , 2011, Current opinion in oncology.

[26]  Giuseppe Agapito,et al.  Genetic variants associated with Fabry disease progression despite enzyme replacement therapy , 2017, Oncotarget.

[27]  Mario Cannataro,et al.  DMET™ (Drug Metabolism Enzymes and Transporters): a pharmacogenomic platform for precision medicine , 2016, Oncotarget.

[28]  Mario Cannataro,et al.  A peroxisome proliferator-activated receptor gamma (PPARG) polymorphism is associated with zoledronic acid-related osteonecrosis of the jaw in multiple myeloma patients: analysis by DMET microarray profiling , 2011, British journal of haematology.

[29]  Fumihiko Takeuchi,et al.  Linkage Disequilibrium Grouping of Single Nucleotide Polymorphisms (SNPs) Reflecting Haplotype Phylogeny for Efficient Selection of Tag SNPs , 2005, Genetics.

[30]  L. Lind,et al.  A genetic risk score is significantly associated with statin therapy response in the elderly population , 2017, Clinical genetics.

[31]  A. Bode,et al.  Recent advances in precision oncology research , 2018, npj Precision Oncology.

[32]  M Ingelman-Sundberg,et al.  Genetic polymorphisms of cytochrome P450 2D6 (CYP2D6): clinical consequences, evolutionary aspects and functional diversity , 2005, The Pharmacogenomics Journal.

[33]  P. Munroe,et al.  A genetic risk score is associated with statin-induced low-density lipoprotein cholesterol lowering. , 2016, Pharmacogenomics.

[34]  M. Cornel,et al.  Ethical and social issues in pharmacogenomics testing. , 2010, Current pharmaceutical design.

[35]  E. Clayton,et al.  Operational Implementation of Prospective Genotyping for Personalized Medicine: The Design of the Vanderbilt PREDICT Project , 2012, Clinical pharmacology and therapeutics.

[36]  Fuli Yu,et al.  Highly multiplexed molecular inversion probe genotyping: over 10,000 targeted SNPs genotyped in a single tube assay. , 2005, Genome research.

[37]  Xiaodong Wang,et al.  Discovering Genome-Wide Tag SNPs Based on the Mutual Information of the Variants , 2016, PloS one.

[38]  Wei Huang,et al.  Linkage disequilibrium sharing and haplotype-tagged SNP portability between populations , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[39]  Richard Shen,et al.  Medium- to high-throughput SNP genotyping using VeraCode microbeads. , 2009, Methods in molecular biology.

[40]  Russell A. Wilke,et al.  Pharmacogenomics: The Genetics of Variable Drug Responses , 2011, Circulation.

[41]  Ching-Hon Pui,et al.  PG4KDS: A model for the clinical implementation of pre‐emptive pharmacogenetics , 2014, American journal of medical genetics. Part C, Seminars in medical genetics.

[42]  B. Malone,et al.  Warfarin pharmacogenomics. , 2009, P & T : a peer-reviewed journal for formulary management.