Clinical Pharmacogenetics

Division Of Basic Sciences - Nci

Investigators

Linked publications, trials & patents

Abstract

Our laboratory has a strong interest in clinical pharmacogenetics. We have integrated pharmacogenetics/pharmacogenomics (PG) research in our drug development efforts to evaluate the impact of genetic variants on drug metabolism, pharmacokinetics (PK), response and toxicity as well as to understand the contribution of inter-individual variation in clinical outcomes in therapies with an already narrow therapeutic window. Given the importance of pharmacogenomics in precision medicine, we are actively involved with implementing the pharmacogenomics program at the NIH Clinical Center. We have established a molecular link between these polymorphisms and their phenotype as it relates to drug treatment. Most of our work has been focused on genetic variations in drug metabolism and transporting candidate genes such as ABCB1 (P-glycoprotein, MDR1), ABCG2 (BCRP), SLCO1B3 (OATP1B3, OATP8), CYP3A4, CYP3A5, CYP1B1, CYP2C19, CYP2D6, UGT1A1, UGT1A9 and several others. Drug transporters mediate the movement of endobiotics and xenobiotics across biological membranes in multiple organs and in most tissues. As such, they are involved in physiology, development of disease, drug PK, and ultimately the clinical response to a myriad of medications. Genetic variants in transporters cause population-specific differences in drug transport and are responsible for considerable interindividual variation in physiology and pharmacotherapy. Thus, we are interested in studying how inherited variants in transporters are associated with disease etiology, disease state, and the pharmacological treatment of diseases. We are also interested in non-candidate gene approaches where large numbers of polymorphisms are explored to establish a relationship with clinical outcome, and experiments are conducted to validate potential causative alleles resulting from exploratory scanning. While many studies have been conducted in order to explain some of the genetic influence on pharmacokinetic variability, we also have a strong interest in clarifying genetic markers of pharmacodynamics and therapeutic outcome of several major anticancer agents since this field has been rather poorly studied. The PharmacoScan pharmacogenomics platform screens for variation in genes that affect drug absorption, distribution, metabolism, elimination (ADME), immune adverse reactions and targets. The platform interrogates 4627 variants in 1191 ADME genes. It also detects 4389 ancestry informative markers, 239 gender markers, 7116 human leukocyte antigen markers, and 1484 killer cell immunoglobulin-like receptor markers. Using such PGx platforms like Pharmacoscan, we have studied the PG assessments of many anticancer agents using including recently mithramycin, belinostat, docetaxel/lenalidomide/bevacizumab combination, olaparib/carboplatin combination, carfilzomib, azathioprine, abiraterone, paclitaxel, cabozantinib, and zotiraciclib. Pharmacogenetic testing is central to precision medicine, enhancing drug efficacy and reducing adverse events. While PGx testing has traditionally relied on array-based genotyping platforms such as Pharmacoscan, these methods are limited by incomplete variant coverage and inability to detect novel alleles. Here, we present a comprehensive validation and clinical implementation study comparing the performance of whole-genome (GS) and whole-exome sequencing (ES) with Pharmacoscan genotyping across eight clinically significant pharmacogenes in a cohort of 300 individuals. GS demonstrated superior accuracy, resolving unknown or ambiguous array-based allele calls in 5% of cases, ultimately achieving 99% baseline accuracy. Moreover, we confirmed the remaining substantial discordances between array-based calls and GS in favor of GS through validation by orthogonal sequencing methods such as long-read PacBio sequencing. We highlight clinically significant inaccuracies that include critical variants missed by arrays. From a cost perspective, GS proved comparable or superior to array-based methods, with significantly greater clinical applicability and flexibility. Our findings underscore the feasibility and superiority of integrating GS-based PGx testing into clinical settings, demonstrating robust analytical performance, improved patient management potential, and a pathway toward broader, lifetime utility of pharmacogenomic data. Underrepresented populations' participation in clinical trials remains limited, and the potential impact of genomic variants on drug metabolism remains elusive. There may be differences in ribociclib metabolism and ribociclib exposure based on CYP3A5 genotype, which could lead to altered clinical outcomes. This study aimed to assess the PK and PGx of ribociclib in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2) advanced breast cancer. PK and PGx were evaluated using tandem mass spectrometry and PharmacoScan (including CYP3A5*3, *6, and *7). CYP3A5 phenotypes varied among participants: 7 poor metabolizers (PM), 6 intermediate metabolizers (IM), and one normal metabolizer (NM). The area under the curve did not significantly differ between PMs and IM/NMs. We found no association between CYP3A5 genotype and ribociclib exposure or adverse effects. Continued efforts are needed to include varied populations in clinical trials to ensure we can continue to improve outcomes of all patients.