(M0930-10-59) Implementing of Next-Generation Sequencing-Based Approach for Pharmacogenomics Profiling and Exploring Its Potential Clinical Utilities

Purpose: It is essential to systematically investigate genetic variability of metabolic enzymes and transporters associated with the absorption, distribution, metabolism, and elimination (ADME) using widely implemented next-generation sequencing (NGS) for enabling pharmacogenomics and/or pharmacogenetic biomarkers focus precision medicine driven drug development. Majority of the currently available solutions for pharmacogenomic profiling are determined by single-nucleotide polymorphisms (SNPs) in a pre-defined set of genomic regions by using methods such as oligo-based microarray technology. Besides, understanding SNPs related to drug metabolizing enzymes and transporters a comprehensive analysis of the germline genetic profile is of high importance for oncology clinical translational research for two reasons; i) somatic mutations can be called with high confidence, and ii) to understand any existing disease predisposition due to germline variants. Given the fact that whole exome sequencing (WES) is an established technique for detection of germline variants with potential clinical utility, WES is applied for the characterization of pharmacogenomic profile, moreover, with the integrated approach, both detection of germline variants and pharmacogenomic profile can be performed in a single assay.

Methods: An in-depth comparison of variant calling by WES and array-based technologies in 28 core ADME pharmacogenes was performed (Figure 1). A total of 79 human blood samples from oncology clinical trials (NCT03724890, NCT03770689, NCT02516813 and NCT02278250) were profiled using ImmunoID NeXT^TM WES platform. Following variant calling by the third-party analysis pipeline, genetic phenotype annotation was added using PharmGKB. The same set of samples were also analyzed by PharmacoScan™ array-based assay to generate the small nuclide variants (SNVs) call and a phenotypic report. An orthogonal analysis was carried out to assess the concordance between WES and array-based assay in the commonly targeted regions within 28 core ADME genes and identify variants exclusively present in either WES or array-based assay. The analysis was done at sample level, where the variants that are solely found in WES are defined as false positives (FP), while variants not identified by WES but present in array-based assay are defined as false negatives (FN). Variants identified by both methods are defined as true positives (TP). Precision is defined as the number of variants correctly identified by WES out of all variants detected by WES (TP/(TP+FP)) whereas recall referred to the number of variants correctly identified by WES out of all variants detected by array-based assay (TP/(TP+FN)).

Results: The ImmunoID NeXT^TM WES precision and recall rate of SNVs ranged from 0.75-0.92 in the core ADME gene regions. Approximately 200-300 SNVs per sample were exclusively identified by WES within 28 ADME gene regions and not by PharmacoScan^TM_. The 56 unique WES SNV variants were annotated using PharmGKB. Among these unique WES SNVs, six variants mapping to CYP2D6, CYP2C9, CYP2C8, ABCB1 or DPYP were identified as highly significant modifiers for metabolism, dosage, PK or toxicity based on the following factors: maximum number of drug associations, significance of association, phenotypic category (toxicity, metabolism, efficacy, dosage) & evidence level (1A or 2A)¹. There are 40-80 variants per sample were exclusively identified by array-based assay. A total of 12 array-based assay unique variants relating CYP2C9, CYP2D6, UGT1A1 or UGT2B7 genes were identified and prioritized based on gene activity filters (increased or decreased) and phenotype call (PM: poor metabolizer or RM: rapid metabolizer or IM: intermediate metabolizer). We found that ImmunoID NeXT^TM WES detected relevant SNVs with high precision and recall when compared to an industry standard assay for pharmacogenomic profiling, although one inherent limitation of WES is that intronic SNVs cannot be profiled. Differences in the variant calls (recall) are not unexpected and could likely be attributed to the different assay technologies which have varying assay principles and sensitivities. WES could identify more SNVs that the region is not specified by oligo-based microarray technology and also identified additional variants potentially relevant to drug metabolism.

Conclusion: We demonstrated the potential clinical feasibility of using of WES for pharmacogenomic profile detection in a clinical setting for 28 core ADME genes. WES is emerging as an indispensable approach, an ongoing study that is exploring the pharmacogenomics and/or pharmacogenetic biomarkers association with drug treatment will reveal more intriguing evidence, which could be decision-supporting for predicting and improving drug response. Collectively, it is anticipated the WES-data shall eventually provide fundamental holistic overview of PGx profiles to assess polymorphism of ADME genes, which would contribute to precision medicine-driven drug development.

References: [1] Gong L, Whirl-Carrillo M, Klein TE. PharmGKB, an Integrated Resource of Pharmacogenomic Knowledge. Curr Protoc. 2021;1(8):e226. doi:10.1002/cpz1.226

Acknowledgements:

Funding: This research was supported by the healthcare business of Merck KGaA, Darmstadt, Germany (CrossRef Funder ID: 10.13039/100009945).


Figure 1. Analysis Strategy