Gene-Specific Variant Classifier (DPYD-Varifier) to Identify Deleterious Alleles of Dihydropyrimidine Dehydrogenase

Machine learning models for pharmacogenomic variant effect predictions - recent developments and future frontiers

Pharmacogenomic variations in genes involved in drug disposition and in drug targets is a major determinant of inter-individual differences in drug response and toxicity. While the effects of common variants are well established, millions of rare variations remain functionally uncharacterized, posing a challenge for the implementation of precision medicine. Recent advances in machine learning (ML) have significantly enhanced the prediction of variant effects by considering DNA as well as protein sequences, as well as their evolutionary conservation and haplotype structures. Emerging deep learning models utilize techniques to capture evolutionary conservation and biophysical properties, and ensemble approaches that integrate multiple predictive models exhibit increased accuracy, robustness, and interpretability. This review explores the current landscape of ML-based variant effect predictors. We discuss key methodological differences and highlight their strengths and limitations for pharmacogenomic applications. We furthermore discuss emerging methodologies for the prediction of substrate-specificity and for consideration of variant epistasis. Combined, these tools improve the functional effect prediction of drug-related variants and offer a viable strategy that could in the foreseeable future translate comprehensive genomic information into pharmacogenetic recommendations.

Translating pharmacogenomic sequencing data into drug response predictions-How to interpret variants of unknown significance

The rapid development of sequencing technologies during the past 20 years has provided a variety of methods and tools to interrogate human genomic variations at the population level. Pharmacogenes are well known to be highly polymorphic and a plethora of pharmacogenomic variants has been identified in population sequencing data. However, so far only a small number of these variants have been functionally characterized regarding their impact on drug efficacy and toxicity and the significance of the vast majority remains unknown. It is therefore of high importance to develop tools and frameworks to accurately infer the effects of pharmacogenomic variants and, eventually, aggregate the effect of individual variations into personalized drug response predictions. To address this challenge, we here first describe the technological advances, including sequencing methods and accompanying bioinformatic processing pipelines that have enabled reliable variant identification. Subsequently, we highlight advances in computational algorithms for pharmacogenomic variant interpretation and discuss the added value of emerging strategies, such as machine learning and the integrative use of omics techniques that have the potential to further contribute to the refinement of personalized pharmacological response predictions. Lastly, we provide an overview of experimental and clinical approaches to validate in silico predictions. We conclude that the iterative feedback between computational predictions and experimental validations is likely to rapidly improve the accuracy of pharmacogenomic prediction models, which might soon allow for an incorporation of the entire pharmacogenetic profile into personalized response predictions.

DPYD Genotyping Recommendations: A Joint Consensus Recommendation of the Association for Molecular Pathology, American College of Medical Genetics and Genomics, Clinical Pharmacogenetics Implementation Consortium, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, European Society for Pharmacogenomics and Personalized Therapy, Pharmacogenomics Knowledgebase, and Pharmacogene Variation Consortium

The goals of the Association for Molecular Pathology Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations for a minimum set of variant alleles (tier 1) and an extended list of variant alleles (tier 2) that will aid clinical laboratories when designing assays for PGx testing. The Association for Molecular Pathology PGx Working Group considered the functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. The goal of this Working Group is to promote standardization of PGx testing across clinical laboratories. This document will focus on clinical DPYD PGx testing that may be applied to all dihydropyrimidine dehydrogenase-related medications. These recommendations are not to be interpreted as prescriptive but to provide a reference guide.

Dihydropyrimidine Dehydrogenase Polymorphism c.2194G>A Screening Is a Useful Tool for Decreasing Gastrointestinal and Hematological Adverse Drug Reaction Risk in Fluoropyrimidine-Treated Patients

Although the risk of fluoropyrimidine toxicity may be decreased by identifying poor metabolizers with a preemptive dihydropyrimidine dehydrogenase (DPYD) test, following international standards, many patients with wild-type (WT) genotypes for classic variations may still exhibit adverse drug reactions (ADRs). Therefore, the safety of fluoropyrimidine therapy could be improved by identifying new DPYD polymorphisms associated with ADRs. This study was carried out to assess whether testing for the underestimated c.2194G>A (DPYD*6 polymorphism, rs1801160) is useful, in addition to other well-known variants, in reducing the risk of ADRs in patients undergoing chemotherapy treatment. This retrospective study included 132 patients treated with fluoropyrimidine-containing regimens who experienced ADRs such as gastrointestinal, dermatological, hematological, and neurological. All subjects were screened for DPYD variants DPYD2A (IVS14+1G>A, c.1905+1G>A, rs3918290), DPYD13 (c.1679T>G, rs55886062), c.2846A>T (rs67376798), c.1236G>A (rs56038477), and c.2194G>A by real-time polymerase chain reaction (RT-PCR). In this cohort, the heterozygous c.2194G>A variant was present in 26 patients, while 106 individuals were WT; both subgroups were compared for the incidence of ADRs. This assessment revealed a high incidence of gastrointestinal and hematological ADRs in DPYD6 carriers compared to WT. Moreover, we have shown a higher prevalence of ADRs in females compared to males when stratifying c.2194G>A carrier individuals. Considering that c.2194G>A was linked to clinically relevant ADRs, we suggest that this variant should also be assessed preventively to reduce the risk of fluoropyrimidine-related ADRs.

Discovering novel germline genetic variants linked to severe fluoropyrimidine-related toxicity in- and outside DPYD

BACKGROUND

The Alpe-DPD study (NCT02324452) demonstrated that prospective genotyping and dose-individualization using four alleles in DPYD (DPYD*2A/rs3918290, c.1236G > A/rs75017182, c.2846A > T/rs67376798 and c.1679 T > G/rs56038477) can mitigate the risk of severe fluoropyrimidine toxicity. However, this could not prevent all toxicities. The goal of this study was to identify additional genetic variants, both inside and outside DPYD, that may contribute to fluoropyrimidine toxicity.

METHODS

Biospecimens and data from the Alpe-DPD study were used. Exon sequencing was performed to identify risk variants inside DPYD. In silico and in vitro analyses were used to classify DPYD variants. A genome-wide association study (GWAS) with severe fluoropyrimidine-related toxicity was performed to identify variants outside DPYD. Association with severe toxicity was assessed using matched-pair analyses for the exon sequencing and logistic, Cox, and ordinal regression analyses for GWAS.

RESULTS

Twenty-four non-synonymous, frameshift, and splice site DPYD variants were detected in ten of 986 patients. Seven of these variants (c.1670C > T, c.1913 T > C, c.1925 T > C, c.506delC, c.731A > C, c.1740 + 1G > T, c.763 - 2A > G) were predicted to be deleterious. The carriers of either of these variants showed a trend towards a 2.14-fold (95% CI, 0.41-11.3, P = 0.388) increased risk of severe toxicity compared to matched controls (N = 30). After GWAS of 942 patients, no individual single nucleotide polymorphisms achieved genome-wide significance (P ≤ 5 × 10-8), however, five variants were suggestive of association (P < 5 × 10-6) with severe toxicity.

CONCLUSIONS

Results from DPYD exon sequencing and GWAS analysis did not identify additional genetic variants associated with severe toxicity, which suggests that testing for single markers at a population level currently has limited clinical value. Identifying additional variants on an individual level is still promising to explain fluoropyrimidine-related severe toxicity. In addition, studies with larger samples sizes, in more diverse cohorts are needed to identify potential clinically relevant genetic variants related to severe fluoropyrimidine toxicity.

DPYD genetic polymorphisms in non-European patients with severe fluoropyrimidine-related toxicity: a systematic review

BACKGROUND

Pre-treatment DPYD screening is mandated in the UK and EU to reduce the risk of severe and potentially fatal fluoropyrimidine-related toxicity. Four DPYD gene variants which are more prominently found in Europeans are tested.

METHODS

Our systematic review in patients of non-European ancestry followed PRISMA guidelines to identify relevant articles up to April 2023. Published in silico functional predictions and in vitro functional data were also extracted. We also undertook in silico prediction for all DPYD variants identified.

RESULTS

In 32 studies, published between 1998 and 2022, 53 DPYD variants were evaluated in patients from 12 countries encompassing 5 ethnic groups: African American, East Asian, Latin American, Middle Eastern, and South Asian. One of the 4 common European DPYD variants, c.1905+1G>A, is also present in South Asian, East Asian and Middle Eastern patients with severe fluoropyrimidine-related toxicity. There seems to be relatively strong evidence for the c.557A>G variant, which is found in individuals of African ancestry, but is not currently included in the UK genotyping panel.

CONCLUSION

Extending UK pre-treatment DPYD screening to include variants that are present in some non-European ancestry groups will improve patient safety and reduce race and health inequalities in ethnically diverse societies.

Clinical Implementation of Rare and Novel DPYD Variants for Personalizing Fluoropyrimidine Treatment: Challenges and Opportunities

Fluoropyrimidines (FLs) [5-Fluorouracil, Capecitabine] are used in the treatment of several solid tumors. Dihydropyrimidine dehydrogenase (DPD) is the rate-limiting enzyme for FL detoxification, and its deficiency could lead to severe, life-threatening or fatal toxicity after FL administration. Testing with a pharmacogenetic panel of four deleterious variants in the dihydropyrimidine dehydrogenase gene (DPYD) (DPYD*2A, DPYD*13, c.2846A > T, c.1129-5923C > G) prior to FL treatment, is recommended by scientific consortia (e.g., CPIC, DPWG) and drug regulatory agencies (e.g., EMA). However, this panel identifies < 20% of patients at risk of severe FL-related toxicity. Cumulative recent evidence highlights the potential clinical value of rare (minor allele frequency < 1%) and novel DPYD genetic variants for identifying an additional fraction of DPD-deficient patients at increased risk of severe FL-related toxicity. In this review, we aimed to comprehensively describe the available evidence regarding the potential clinical predictive role of novel and rare DPYD variants as toxicity markers in FL-treated patients, and to discuss the challenges and opportunities in tailoring FL treatment based upon clinical application of such markers. Although we must overcome existing barriers to the clinical implementation, the available data support that comprehensive assessment of the DPYD sequence, including rare and novel genetic variants, may significantly enhance the pre-emptive identification of at-risk patients, compared to the current targeted approach.

APF2: an improved ensemble method for pharmacogenomic variant effect prediction

Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20-30% of this variability in drug response stems from variations in genes encoding drug targets or factors involved in drug disposition. Leveraging such pharmacogenomic information for the preemptive identification of patients who would benefit from dose adjustments or alternative medications thus constitutes an important frontier of precision medicine. Computational methods can be used to predict the functional effects of variant of unknown significance. However, their performance on pharmacogenomic variant data has been lackluster. To overcome this limitation, we previously developed an ensemble classifier, termed APF, specifically designed for pharmacogenomic variant prediction. Here, we aimed to further improve predictions by leveraging recent key advances in the prediction of protein folding based on deep neural networks. Benchmarking of 28 variant effect predictors on 530 pharmacogenetic missense variants revealed that structural predictions using AlphaMissense were most specific, whereas APF exhibited the most balanced performance. We then developed a new tool, APF2, by optimizing algorithm parametrization of the top performing algorithms for pharmacogenomic variations and aggregating their predictions into a unified ensemble score. Importantly, APF2 provides quantitative variant effect estimates that correlate well with experimental results (R2 = 0.91, p = 0.003) and predicts the functional impact of pharmacogenomic variants with higher accuracy than previous methods, particularly for clinically relevant variations with actionable pharmacogenomic guidelines. We furthermore demonstrate better performance (92% accuracy) on an independent test set of 146 variants across 61 pharmacogenes not used for model training or validation. Application of APF2 to population-scale sequencing data from over 800,000 individuals revealed drastic ethnogeographic differences with important implications for pharmacotherapy. We thus think that APF2 holds the potential to improve the translation of genetic information into pharmacogenetic recommendations, thereby facilitating the use of Next-Generation Sequencing data for stratified medicine.

Individualized Pharmacotherapy Utilizing Genetic Biomarkers and Novel In Vitro Systems As Predictive Tools for Optimal Drug Development and Treatment

In the area of drug development and clinical pharmacotherapy, a profound understanding of the pharmacokinetics and potential adverse reactions associated with the drug under investigation is paramount. Essential to this endeavor is a comprehensive understanding about interindividual variations in absorption, distribution, metabolism, and excretion (ADME) genetics and the predictive capabilities of in vitro systems, shedding light on metabolite formation and the risk of adverse drug reactions (ADRs). Both the domains of pharmacogenomics and the advancement of in vitro systems are experiencing rapid expansion. Here we present an update on these burgeoning fields, providing an overview of their current status and illuminating potential future directions. SIGNIFICANCE STATEMENT: There is very rapid development in the area of pharmacogenomics and in vitro systems for predicting drug pharmacokinetics and risk for adverse drug reactions. We provide an update of the current status of pharmacogenomics and developed in vitro systems on these aspects aimed to achieve a better personalized pharmacotherapy.

Population-specific variations in KCNH2 predispose patients to delayed ventricular repolarization upon dihydroartemisinin-piperaquine therapy

Dihydroartemisinin-piperaquine is efficacious for the treatment of uncomplicated malaria and its use is increasing globally. Despite the positive results in fighting malaria, inhibition of the Kv11.1 channel (hERG; encoded by the KCNH2 gene) by piperaquine has raised concerns about cardiac safety. Whether genetic factors could modulate the risk of piperaquine-mediated QT prolongations remained unclear. Here, we first profiled the genetic landscape of KCNH2 variability using data from 141,614 individuals. Overall, we found 1,007 exonic variants distributed over the entire gene body, 555 of which were missense. By optimizing the gene-specific parametrization of 16 partly orthogonal computational algorithms, we developed a KCNH2-specific ensemble classifier that identified a total of 116 putatively deleterious missense variations. To evaluate the clinical relevance of KCNH2 variability, we then sequenced 293 Malian patients with uncomplicated malaria and identified 13 variations within the voltage sensing and pore domains of Kv11.1 that directly interact with channel blockers. Cross-referencing of genetic and electrocardiographic data before and after piperaquine exposure revealed that carriers of two common variants, rs1805121 and rs41314375, experienced significantly higher QT prolongations (ΔQTc of 41.8 ms and 61 ms, respectively, vs 14.4 ms in controls) with more than 50% of carriers having increases in QTc >30 ms. Furthermore, we identified three carriers of rare population-specific variations who experienced clinically relevant delayed ventricular repolarization. Combined, our results map population-scale genetic variability of KCNH2 and identify genetic biomarkers for piperaquine-induced QT prolongation that could help to flag at-risk patients and optimize efficacy and adherence to antimalarial therapy.

Germline cis variant determines epigenetic regulation of the anti-cancer drug metabolism gene dihydropyrimidine dehydrogenase (DPYD)

Enhancers are critical for regulating tissue-specific gene expression, and genetic variants within enhancer regions have been suggested to contribute to various cancer-related processes, including therapeutic resistance. However, the precise mechanisms remain elusive. Using a well-defined drug-gene pair, we identified an enhancer region for dihydropyrimidine dehydrogenase (DPD, DPYD gene) expression that is relevant to the metabolism of the anti-cancer drug 5-fluorouracil (5-FU). Using reporter systems, CRISPR genome-edited cell models, and human liver specimens, we demonstrated in vitro and vivo that genotype status for the common germline variant (rs4294451; 27% global minor allele frequency) located within this novel enhancer controls DPYD transcription and alters resistance to 5-FU. The variant genotype increases recruitment of the transcription factor CEBPB to the enhancer and alters the level of direct interactions between the enhancer and DPYD promoter. Our data provide insight into the regulatory mechanisms controlling sensitivity and resistance to 5-FU.

Overcoming Barriers to Discovery and Implementation of Equitable Pharmacogenomic Testing in Oncology

Pharmacogenomics (PGx), the study of inherited genomic variation and drug response or safety, is a vital tool in precision medicine. In oncology, testing to identify PGx variants offers patients the opportunity for customized treatments that can minimize adverse effects and maximize the therapeutic benefits of drugs used for cancer treatment and supportive care. Because individuals of shared ancestry share specific genetic variants, PGx factors may contribute to outcome disparities across racial and ethnic categories when genetic ancestry is not taken into account or mischaracterized in PGx research, discovery, and application. Here, we examine how the current scientific understanding of the role of PGx in differential oncology safety and outcomes may be biased toward a greater understanding and more complete clinical implementation of PGx for individuals of European descent compared with other genetic ancestry groups. We discuss the implications of this bias for PGx discovery, access to care, drug labeling, and patient and provider understanding and use of PGx approaches. Testing for somatic genetic variants is now the standard of care in treatment of many solid tumors, but the integration of PGx into oncology care is still lacking despite demonstrated actionable findings from PGx testing, reduction in avoidable toxicity and death, and return on investment from testing. As the field of oncology is poised to expand and integrate germline genetic variant testing, it is vital that PGx discovery and application are equitable for all populations. Recommendations are introduced to address barriers to facilitate effective and equitable PGx application in cancer care.

Germline cis variant determines epigenetic regulation of the anti-cancer drug metabolism gene dihydropyrimidine dehydrogenase (DPYD)

Enhancers are critical for regulating tissue-specific gene expression, and genetic variants within enhancer regions have been suggested to contribute to various cancer-related processes, including therapeutic resistance. However, the precise mechanisms remain elusive. Using a well-defined drug-gene pair, we identified an enhancer region for dihydropyrimidine dehydrogenase (DPD, DPYD gene) expression that is relevant to the metabolism of the anti-cancer drug 5-fluorouracil (5-FU). Using reporter systems, CRISPR genome edited cell models, and human liver specimens, we demonstrated in vitro and vivo that genotype status for the common germline variant (rs4294451; 27% global minor allele frequency) located within this novel enhancer controls DPYD transcription and alters resistance to 5-FU. The variant genotype increases recruitment of the transcription factor CEBPB to the enhancer and alters the level of direct interactions between the enhancer and DPYD promoter. Our data provide insight into the regulatory mechanisms controlling sensitivity and resistance to 5-FU.

Complete DPYD genotyping combined with dihydropyrimidine dehydrogenase phenotyping to prevent fluoropyrimidine toxicity: A retrospective study

INTRODUCTION

In April 2019, French authorities mandated dihydropyrimidine dehydrogenase (DPD) screening, specifically testing uracilemia, to mitigate the risk of toxicity associated with fluoropyrimidine-based chemotherapy. However, this subject is still of debate as there is no consensus on a standardized DPD deficiency screening test. We conducted a real-life retrospective study with the aim of assessing the impact of DPD screening on the occurrence of severe toxicity and exploring the potential benefits of complete genotyping using next-generation sequencing.

METHODS

All adult patients consecutively treated with 5-fluorouracil (5-FU) or its oral prodrug at six cancer centers between March 2018 and February 2019 were considered for inclusion. Dihydropyrimidine dehydrogenase deficiency screening included gene encoding DPD (DPYD) genotyping using complete genome sequencing and DPD phenotyping (uracilemia or dihydrouracilemia/uracilemia ratio) or both tests. Associations between each DPD screening method and (i) severe (grade ≥3) early toxicity and (ii) fluoropyrimidine dose reduction in the second chemotherapy cycle were evaluated using multivariable logistic regression analysis. Furthermore, we assessed the concordance between DPD genotype and phenotype using Cohen's kappa.

RESULTS

A total of 551 patients were included. Most patients were tested for DPD deficiency (86%) including DPYD genotyping only (6%), DPD phenotyping only (8%), or both (72%). Complete DPD deficiency was not detected in the study population. Severe early toxicity events were observed in 73 patients (13%), with two patients (0.30%) presenting grade 5 toxicity. Despite the numerically higher toxicity rate in untested patients, the occurrence of severe toxicity was not significantly associated with the DPD screening method (p = 0.69). Concordance between the DPD genotype and phenotype was weak (Cohen's kappa of 0.14).

CONCLUSION

Due to insufficient numbers, our study was not able to demonstrate any added value of DPYD genotyping using complete genome sequencing to prevent 5-FU toxicity. The optimal strategy for DPD screening before fluoropyrimidine-based chemotherapy requires further clinical evaluation.

Next-generation sequencing in pharmacogenomics - fit for clinical decision support?

INTRODUCTION

The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial.

AREAS COVERED

We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing.

EXPERT OPINION

While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.

Implementing pharmacogenetic testing in fluoropyrimidine-treated cancer patients: DPYD genotyping to guide chemotherapy dosing in Greece

Introduction: Dihydropyrimidine dehydrogenase (DPD), encoded by DPYD gene, is the rate-limiting enzyme responsible for fluoropyrimidine (FP) catabolism. DPYD gene variants seriously affect DPD activity and are well validated predictors of FP-associated toxicity. DPYD variants rs3918290, rs55886062, rs67376798, and rs75017182 are currently included in FP genetic-based dosing guidelines and are recommended for genotyping by the European Medicines Agency (EMA) before treatment initiation. In Greece, however, no data exist on DPYD genotyping. The aim of the present study was to analyze prevalence of DPYD rs3918290, rs55886062, rs67376798, rs75017182, and, additionally, rs1801160 variants, and assess their association with FP-induced toxicity in Greek cancer patients. Methods: Study group consisted of 313 FP-treated cancer patients. DPYD genotyping was conducted on QuantStudio ™ 12K Flex Real-Time PCR System (ThermoFisher Scientific) using the TaqMan® assays C__30633851_20 (rs3918290), C__11985548_10 (rs55886062), C__27530948_10 (rs67376798), C_104846637_10 (rs75017182) and C__11372171_10 (rs1801160). Results: Any grade toxicity (1-4) was recorded in 208 patients (66.5%). Out of them, 25 patients (12%) experienced grade 3-4 toxicity. DPYD EMA recommended variants were detected in 9 patients (2.9%), all experiencing toxicity (p = 0.031, 100% specificity). This frequency was found increased in grade 3-4 toxicity cases (12%, p = 0.004, 97.9% specificity). DPYD deficiency increased the odds of grade 3-4 toxicity (OR: 6.493, p = 0.014) and of grade 1-4 gastrointestinal (OR: 13.990, p = 0.014), neurological (OR: 4.134, p = 0.040) and nutrition/metabolism (OR: 4.821, p = 0.035) toxicities. FP dose intensity was significantly reduced in DPYD deficient patients (β = -0.060, p <0.001). DPYD rs1801160 variant was not associated with FP-induced toxicity or dose intensity. Triple interaction of DPYD*TYMS*MTHFR was associated with grade 3-4 toxicity (OR: 3.725, p = 0.007). Conclusion: Our findings confirm the clinical validity of DPYD reduced function alleles as risk factors for development of FP-associated toxicity in the Greek population. Pre-treatment DPYD genotyping should be implemented in clinical practice and guide FP dosing. DPYD*gene interactions merit further investigation as to their potential to increase the prognostic value of DPYD genotyping and improve safety of FP-based chemotherapy.

Pharmacogenomic-guided dosing of fluoropyrimidines beyond DPYD: time for a polygenic algorithm?

Fluoropyrimidines are chemotherapeutic agents widely used for the treatment of various solid tumors. Commonly prescribed FPs include 5-fluorouracil (5-FU) and its oral prodrugs capecitabine (CAP) and tegafur. Bioconversion of 5-FU prodrugs to 5-FU and subsequent metabolic activation of 5-FU are required for the formation of fluorodeoxyuridine triphosphate (FdUTP) and fluorouridine triphosphate, the active nucleotides through which 5-FU exerts its antimetabolite actions. A significant proportion of FP-treated patients develop severe or life-threatening, even fatal, toxicity. It is well known that FP-induced toxicity is governed by genetic factors, with dihydropyrimidine dehydrogenase (DPYD), the rate limiting enzyme in 5-FU catabolism, being currently the cornerstone of FP pharmacogenomics. DPYD-based dosing guidelines exist to guide FP chemotherapy suggesting significant dose reductions in DPYD defective patients. Accumulated evidence shows that additional variations in other genes implicated in FP pharmacokinetics and pharmacodynamics increase risk for FP toxicity, therefore taking into account more gene variations in FP dosing guidelines holds promise to improve FP pharmacotherapy. In this review we describe the current knowledge on pharmacogenomics of FP-related genes, beyond DPYD, focusing on FP toxicity risk and genetic effects on FP dose reductions. We propose that in the future, FP dosing guidelines may be expanded to include a broader ethnicity-based genetic panel as well as gene*gene and gender*gene interactions towards safer FP prescription.

DPYD genotyping and predicting fluoropyrimidine toxicity: where do we stand?

Fluoropyrimidines (FPs) are antineoplastic drugs widely used in the treatment of various solid tumors. Nearly 30% of patients treated with FP chemotherapy experience severe FP-related toxicity, and in some cases, toxicity can be fatal. Patients with reduced activity of DPD, the main enzyme responsible for the breakdown of FP, are at an increased risk of experiencing severe FP-related toxicity. While European regulatory agencies and clinical societies recommend pre-treatment DPD deficiency screening for patients starting treatment with FPs, this is not the case with American ones. Pharmacogenomic guidelines issued by several pharmacogenetic organizations worldwide recommend testing four DPD gene (DPYD) risk variants, but these can predict only a proportion of toxicity cases. New evidence on additional common DPYD polymorphisms, as well as identification and functional characterization of rare DPYD variants, could partially address the missing heritability of DPD deficiency and FP-related toxicity.

Challenges Related to the Use of Next-Generation Sequencing for the Optimization of Drug Therapy

Over the last decade, next-generation sequencing (NGS) methods have become increasingly used in various areas of human genomics. In routine clinical care, their use is already implemented in oncology to profile the mutational landscape of a tumor, as well as in rare disease diagnostics. However, its utilization in pharmacogenomics is largely lacking behind. Recent population-scale genome data has revealed that human pharmacogenes carry a plethora of rare genetic variations that are not interrogated by conventional array-based profiling methods and it is estimated that these variants could explain around 30% of the genetically encoded functional pharmacogenetic variability.To interpret the impact of such variants on drug response a multitude of computational tools have been developed, but, while there have been major advancements, it remains to be shown whether their accuracy is sufficient to improve personalized pharmacogenetic recommendations in robust trials. In addition, conventional short-read sequencing methods face difficulties in the interrogation of complex pharmacogenes and high NGS test costs require stringent evaluations of cost-effectiveness to decide about reimbursement by national healthcare programs. Here, we illustrate current challenges and discuss future directions toward the clinical implementation of NGS to inform genotype-guided decision-making.

A paradigm shift in pharmacogenomics: From candidate polymorphisms to comprehensive sequencing

Genetic factors have long been recognized as important determinants of interindividual variability in drug efficacy and toxicity. However, despite the increasing number of established gene-drug associations, candidate polymorphisms can only explain a fraction of the genetically encoded functional variability in drug disposition. Advancements in genetic profiling methods now allow to analyse the landscape of human pharmacogenetic variations comprehensively, which opens new opportunities to identify novel factors that could explain the "missing heritability." Here, we provide an updated overview of the landscape of pharmacogenomic variability based on recent analyses of population-scale sequencing projects. We then summarize the current state-of-the-art how the functional consequences of variants with unknown effects can be quantitatively estimated while discussing challenges and peculiarities that are specific to pharmacogenes. In the last sections, we discuss the importance of considering ethnogeographic diversity to provide equitable benefits of pharmacogenomics and summarize current roadblocks for the implementation of sequencing-based guidance of clinical decision-making. Based on the current state of the field, we conclude that testing is likely to gradually shift from the interrogation of selected candidate polymorphisms to comprehensive sequencing, which allows to consider the full spectrum of pharmacogenomic variations for a true personalization of genomic prescribing.

Assessment of the Clinical Utility of Pretreatment DPYD Testing for Patients Receiving Fluoropyrimidine Chemotherapy

PURPOSE

Patients who carry pathogenic variants in DPYD have higher systemic fluoropyrimidine (FP) concentrations and greater risk of severe and fatal FP toxicity. Pretreatment DPYD testing and DPYD-guided FP dosing to reduce toxicity and health care costs is recommended by European clinical oncology guidelines and has been adopted across Europe, but has not been recommended or adopted in the United States. The cochairs of the National Comprehensive Cancer Network Guidelines for colon cancer treatment explained their concerns with recommending pretreatment DPYD testing, particularly the risk that reduced FP doses in DPYD carriers may reduce treatment efficacy.

METHODS

This special article uses previously published frameworks for assessing the clinical utility of cancer biomarker tests, including for germline indicators of toxicity risk, to assess the clinical utility of pretreatment DPYD testing, with a particular focus on the risk of reducing treatment efficacy.

RESULTS

There is no direct evidence of efficacy reduction, and the available indirect evidence demonstrates that DPYD-guided FP dosing results in similar systemic FP exposure and toxicity compared with standard dosing in noncarriers, and is well calibrated to the maximum tolerated dose, strongly suggesting there is minimal risk of efficacy reduction.

CONCLUSION

This article should serve as a call to action for clinicians and clinical guidelines committees in the United States to re-evaluate the clinical utility of pretreatment DPYD testing. If clinical utility has not been demonstrated, further dialogue is needed to clarify what additional evidence is needed and which of the available study designs, also described within this article, would be appropriate. Clinical guideline recommendations for pretreatment DPYD testing would increase clinical adoption and ensure that all patients receive maximally safe and effective FP treatment.

Rare genetic variant burden in DPYD predicts severe fluoropyrimidine-related toxicity risk

Preemptive targeted pharmacogenetic testing of candidate variations in DPYD is currently being used to limit toxicity associated with fluoropyrimidines. The use of innovative next generation sequencing (NGS) approaches could unveil additional rare (minor allele frequency <1%) genetic risk variants. However, their predictive value and management in clinical practice are still controversial, at least partly due to the challenges associated with functional analyses of rare variants. The aim of this study was to define the predictive power of rare DPYD variants burden on the risk of severe fluoropyrimidine-related toxicity.

The DPYD coding sequence and untranslated regions were analyzed by NGS in 120 patients developing grade 3–5 (NCI-CTC vs3.0) fluoropyrimidine-related toxicity and 104 matched controls (no-toxicity). The functional impact of rare variants was assessed using two different in silico predictive tools (i.e., Predict2SNP and ADME Prediction Framework) and structural modeling. Plasma concentrations of uracil (U) and dihydrouracil (UH2) were quantified in carriers of the novel variants.

Here, we demonstrate that the burden of rare variants was significantly higher in patients with toxicity compared to controls (p = 0.007, Mann-Whitney test). Carriers of at least one rare missense DPYD variant had a 16-fold increased risk in the first cycle and an 11-fold increased risk during the entire course of chemotherapy of developing a severe adverse event compared to controls (p = 0.013 and p = 0.0250, respectively by multinomial regression model). Quantification of plasmatic U/UH2 metabolites and in silico visualization of the encoded protein were consistent with the predicted functional effect for the novel variations.

Analysis and consideration of rare variants by DPYD-sequencing could improve prevention of severe toxicity of fluoropyrimidines and improve patients’ quality of life.

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DPYD genotype-guided dosing reduces fluoropyrimidine (FP) toxicity risk.

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Rare DPYD variants associate with severe FP toxicities.

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Carriers of rare DPYD variants have 11-fold increased risk of toxicity.

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DPYD sequencing and in silico functional prediction could prevent FP toxicity events.

Challenges and opportunities associated with rare-variant pharmacogenomics

Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.

Testing for Dihydropyrimidine Dehydrogenase Deficiency to Individualize 5-Fluorouracil Therapy

Severe adverse events (toxicity) related to the use of the commonly used chemotherapeutic drug 5-fluorouracil (5-FU) affect one in three patients and are the primary reason cited for premature discontinuation of therapy. Deficiency of the 5-FU catabolic enzyme dihydropyrimidine dehydrogenase (DPD, encoded by DPYD) has been recognized for the past 3 decades as a pharmacogenetic syndrome associated with high risk of 5-FU toxicity. An appreciable fraction of patients with DPD deficiency that receive 5-FU-based chemotherapy die as a result of toxicity. In this manuscript, we review recent progress in identifying actionable markers of DPD deficiency and the current status of integrating those markers into the clinical decision-making process. The limitations of currently available tests, as well as the regulatory status of pre-therapeutic DPYD testing, are also discussed.

DPYD polymorphisms c.496A>G, c.2194G>A and c.85T>C and risk of severe adverse drug reactions in patients treated with fluoropyrimidine-based protocols

AIMS

Cancer patients with reduced dihydropyrimidine dehydrogenase (DPD) activity are at increased risk of severe fluoropyrimidine (FP)-related adverse events (AE). Guidelines recommend FP dosing adjusted to genotype-predicted DPD activity based on four DPYD variants (rs3918290, rs55886062, rs67376798 and rs56038477). We evaluated the relationship between three further DPYD polymorphisms: c.496A>G (rs2297595), *6 c.2194G>A (rs1801160) and *9A c.85T>C (rs1801265) and the risk of severe AEs.

METHODS

Consecutive FP-treated adult patients were genotyped for "standard" and tested DPYD variants, and for UGT1A1*28 if irinotecan was included, and were monitored for the occurrence of grade ≥3 (National Cancer Institute Common Terminology Criteria) vs. grade 0-2 AEs. For each of the tested polymorphisms, variant allele carriers were matched to respective wild type controls (optimal full matching combined with exact matching, in respect to: age, sex, type of cancer, type of FP, DPYD activity score, use of irinotecan/UGT1A1, adjuvant therapy, radiotherapy, biological therapy and genotype on the remaining two tested polymorphisms).

RESULTS

Of the 503 included patients (82.3% colorectal cancer), 283 (56.3%) developed grade ≥3 AEs, mostly diarrhoea and neutropenia. Odds of grade ≥3 AEs were higher in c.496A>G variant carriers (n = 127) than in controls (n = 376) [OR = 5.20 (95% CI 1.88-14.3), Bayesian OR = 5.24 (95% CrI 3.06-9.12)]. Odds tended to be higher in c.2194G>A variant carriers (n = 58) than in controls (n = 432) [OR = 1.88 (0.95-3.73), Bayesian OR = 1.90 (1.03-3.56)]. c.85T>C did not appear associated with grade ≥3 AEs (206 variant carriers vs. 284 controls).

CONCLUSION

DPYD c.496A>G and possibly c.2194G>A variants might need to be considered for inclusion in the DPYD genotyping panel.

SWAAT Bioinformatics Workflow for Protein Structure-Based Annotation of ADME Gene Variants

Recent genomic studies have revealed the critical impact of genetic diversity within small population groups in determining the way individuals respond to drugs. One of the biggest challenges is to accurately predict the effect of single nucleotide variants and to get the relevant information that allows for a better functional interpretation of genetic data. Different conformational scenarios upon the changing in amino acid sequences of pharmacologically important proteins might impact their stability and plasticity, which in turn might alter the interaction with the drug. Current sequence-based annotation methods have limited power to access this type of information. Motivated by these calls, we have developed the Structural Workflow for Annotating ADME Targets (SWAAT) that allows for the prediction of the variant effect based on structural properties. SWAAT annotates a panel of 36 ADME genes including 22 out of the 23 clinically important members identified by the PharmVar consortium. The workflow consists of a set of Python codes of which the execution is managed within Nextflow to annotate coding variants based on 37 criteria. SWAAT also includes an auxiliary workflow allowing a versatile use for genes other than ADME members. Our tool also includes a machine learning random forest binary classifier that showed an accuracy of 73%. Moreover, SWAAT outperformed six commonly used sequence-based variant prediction tools (PROVEAN, SIFT, PolyPhen-2, CADD, MetaSVM, and FATHMM) in terms of sensitivity and has comparable specificity. SWAAT is available as an open-source tool.

Clinical Relevance of Novel Polymorphisms in the Dihydropyrimidine Dehydrogenase (DPYD) Gene in Patients with Severe Fluoropyrimidine Toxicity: A Spanish Case-Control Study

Among cancer patients treated with fluoropyrimidines, 10-40% develop severe toxicity. Polymorphism of the dihydropyrimidine dehydrogenase (DPYD) gene may reduce DPD function, the main enzyme responsible for the metabolism of fluoropyrimidines. This leads to drug accumulation and to an increased risk of toxicity. Routine genotyping of this gene, which usually includes DPYD *HapB3, *2A, *13 and c.2846A > T (D949V) variants, helps predict approximately 20-30% of toxicity cases. For DPD intermediate (IM) or poor (PM) metabolizers, a dose adjustment or drug switch is warranted to avoid toxicity, respectively. Societies such as the Spanish Society of Pharmacogenetics and Pharmacogenomics (SEFF), the Dutch Pharmacogenetics Working Group (DPWG) or the Clinical Pharmacogenetics Implementation Consortium (CPIC) and regulatory agencies (e.g., the Spanish Medicines Agency, AEMPS) already recommend DPYD routine genotyping. However, the predictive capacity of genotyping is currently still limited. This can be explained by the presence of unknown polymorphisms affecting the function of the enzyme. In this case-control work, 11 cases of severe fluoropyrimidine toxicity in patients who did not carry any of the four variants mentioned above were matched with 22 controls, who did not develop toxicity and did not carry any variant. The DPYD exome was sequenced (Sanger) in search of potentially pathogenic mutations. DPYD rs367619008 (c.187 A > G, p.Lys63Glu), rs200643089 (c.2324 T > G, p.Leu775Trp) and rs76387818 (c.1084G > A, p.Val362Ile) increased the percentage of explained toxicities to 38-48%. Moreover, there was an intronic variant considered potentially pathogenic: rs944174134 (c.322-63G > A). Further studies are needed to confirm its clinical relevance. The remaining variants were considered non-pathogenic.

Abnormal Dihydropyrimidine Dehydrogenase Activity as an Indicator of Potential 5-Fluorouracil Linked Cardiotoxicity in Colorectal Cancer Patients: Are Toxic Events Inevitable?

Colorectal cancer (CRC) treatment can be limited to surgical resection for low stages of the disease while subsequent chemotherapy is the preferred treatment for the higher-stage disease. This chemotherapy relies heavily on fluoropyrimidine: 5-fluorouracil (5-FU) and capecitabine, a role played for decades. Fluoropyrimidine-linked treatment can present important and even lethal toxic events at the cardiac level like acute coronary syndrome, arrhythmias, and death.

The production of these toxic events depends on the capacity of a subject to metabolize the fluoropyrimidines adequately, and this depends on the activity of the enzyme dihydropyrimidine dehydrogenase (DPD). Any change that affects the quantity or quality of this enzyme will compromise its capacity to metabolize the fluoropyrimidines. The resultant abnormal enzyme activity exposes the patient to continuously high levels of the chemotherapeutic agent or its catabolites. Consequently, the patient becomes more susceptible to pyrimidine-linked toxic adverse events.

Genetic testing of patients for potential decreased DPD activity before subjecting them to fluoropyrimidine-based chemotherapy will help identify subjects at greater risk of increased cardiotoxicities, the possibility of prompt intervention, should these appear, and a multidisciplinary strategy aimed at managing these cases. Potential cases of cardiotoxicity in CRC patients, candidates to fluoropyrimidine toxicities, can be anticipated by pretreatment screening of DPD activity. Pretreatment screening will reduce many hospitalizations with a consequent decrease in costs both to the patients and the healthcare system.

This review article will examine the 5-FU linked cardiotoxicity, known correlated risk factors, clinical manifestations, management strategy, and the role of genetic testing in identifying high-risk patients.

The dihydropyrimidine dehydrogenase gene contributes to heritable differences in sleep in mice

Many aspects of sleep are heritable, but only a few sleep-regulating genes have been reported. Here, we leverage mouse models to identify and confirm a previously unreported gene affecting sleep duration-dihydropyrimidine dehydrogenase (Dpyd). Using activity patterns to quantify sleep in 325 Diversity Outbred (DO) mice-a population with high genetic and phenotypic heterogeneity-a linkage peak for total sleep in the active lights off period was identified on chromosome 3 (LOD score = 7.14). Mice with the PWK/PhJ ancestral haplotype at this location demonstrated markedly reduced sleep. Among the genes within the linkage region, available RNA sequencing data in an independent sample of DO mice supported a highly significant expression quantitative trait locus for Dpyd, wherein reduced expression was associated with the PWK/PhJ allele. Validation studies were performed using activity monitoring and EEG/EMG recording in Collaborative Cross mouse strains with and without the PWK/PhJ haplotype at this location, as well as EEG and EMG recording of sleep and wake in Dpyd knockout mice and wild-type littermate controls. Mice lacking Dpyd had 78.4 min less sleep during the lights-off period than wild-type mice (p = 0.007; Cohen's d = -0.94). There was no difference in other measured behaviors in knockout mice, including assays evaluating cognitive-, social-, and affective-disorder-related behaviors. Dpyd encodes the rate-limiting enzyme in the metabolic pathway that catabolizes uracil and thymidine to β-alanine, an inhibitory neurotransmitter. Thus, data support β-alanine as a neurotransmitter that promotes sleep in mice.

Applying Next-Generation Sequencing Platforms for Pharmacogenomic Testing in Clinical Practice

Pharmacogenomics (PGx) studies the use of genetic data to optimize drug therapy. Numerous clinical centers have commenced implementing pharmacogenetic tests in clinical routines. Next-generation sequencing (NGS) technologies are emerging as a more comprehensive and time- and cost-effective approach in PGx. This review presents the main considerations for applying NGS in guiding drug treatment in clinical practice. It discusses both the advantages and the challenges of implementing NGS-based tests in PGx. Moreover, the limitations of each NGS platform are revealed, and the solutions for setting up and management of these technologies in clinical practice are addressed.

DPYD Exome, mRNA Expression and Uracil Levels in Early Severe Toxicity to Fluoropyrimidines: An Extreme Phenotype Approach

Dihydropyrimidine dehydrogenase deficiency is a major cause of severe fluoropyrimidine-induced toxicity and could lead to interruption of chemotherapy or life-threatening adverse reactions. This study aimed to characterize the DPYD exon sequence, mRNA expression and in vivo DPD activity by plasma uracil concentration. It was carried out in two groups of patients with extreme phenotypes (toxicity versus control) newly treated with a fluoropyrimidine, during the first three cycles of treatment. A novel nonsense gene variant (c.2197insA) was most likely responsible for fluoropyrimidine-induced toxicity in one patient, while neither DPYD mRNA expression nor plasma uracil concentration was globally associated with early toxicity. Our present work may help improve pharmacogenetic testing to avoid severe and undesirable adverse reactions to fluoropyrimidine treatment and it also supports the idea of looking beyond DPYD.

Pharmacogenomic-Guided Therapy in Colorectal Cancer

Approximately 20 drugs have been shown to be effective for the treatment of colorectal cancer (CRC). These drugs are from several classes of agents and include cytotoxic drugs, therapeutics that target cell signaling pathways at the extracellular and/or intracellular levels, and combination therapies that contain multiple targeted agents and/or cytotoxic compounds. Targeted therapeutics can include monoclonal antibodies, fusion proteins, and small molecule drugs. The first introduced into clinical use was 5-fluorouracil in the early 1960s and remains the foundation for most CRC treatments in both adjuvant therapy and in advanced (metastatic) treatment regimens. As with other cancers, the consideration of biomarkers has the potential to improve CRC therapy through patient stratification. The biomarkers can include germline genetic markers, tumor-specific genetic markers, immune markers, and other biomarkers that can predict antitumor efficacy or the likelihood of toxicity prior to administration of a specific drug. Consistent with the benefit of considering biomarkers in treatment, many newer targeted therapies are developed and approved simultaneously with a companion diagnostic test to determine efficacy. This review will focus on biomarkers that have demonstrated clinical utility in CRC treatment; however, it is noted that many additional biomarkers have been theorized to contribute to drug response and/or toxicity based on known biological pathways but thus far have not attained widespread use in the clinic. The importance of pretreatment biomarker testing is expected to increase as future drug development will likely continue to focus on the concurrent development of companion diagnostics.

Computational Tools to Assess the Functional Consequences of Rare and Noncoding Pharmacogenetic Variability

Interindividual differences in drug response are a common concern in both drug development and across layers of care. While genetics clearly influences drug response and toxicity of many drugs, a substantial fraction of the heritable pharmacological and toxicological variability remains unexplained by known genetic polymorphisms. In recent years, population-scale sequencing projects have unveiled tens of thousands of coding and noncoding pharmacogenetic variants with unclear functional effects that might explain at least part of this missing heritability. However, translating these personalized variant signatures into drug response predictions and actionable advice remains challenging and constitutes one of the most important frontiers of contemporary pharmacogenomics. Conventional prediction methods are primarily based on evolutionary conservation, which drastically reduces their predictive accuracy when applied to poorly conserved pharmacogenes. Here, we review the current state-of-the-art of computational variant effect predictors across variant classes and critically discuss their utility for pharmacogenomics. Besides missense variants, we discuss recent progress in the evaluation of synonymous, splice, and noncoding variations. Furthermore, we discuss emerging possibilities to assess haplotypes and structural variations. We advocate for the development of algorithms trained on pharmacogenomic instead of pathogenic data sets to improve the predictive accuracy in order to facilitate the utilization of next-generation sequencing data for personalized clinical decision support and precision pharmacogenomics.

An Evaluation of the Diagnostic Accuracy of a Panel of Variants in DPYD and a Single Variant in ENOSF1 for Predicting Common Capecitabine Related Toxicities

Simple Summary

5-Fluorouracil (5-FU) is a chemotherapy drug that can cause severe toxicity in some patients. A protein, an action molecule in our cells, called dihydropyrimidine dehydrogenase, or DPD for short, is important in clearing 5-FU from the body. Some people have versions of DPD that do not clear 5-FU very well. This causes active drug to stay in the body too long, causing toxicities such as diarrhoea or low levels of blood cells important for fighting infections. Current guidelines identify four sequence changes in the gene that encodes DPD with high level evidence of an impact on protein activity. Our study aims to calculate the frequency of a set of variants identified in patients with DPD deficiency in patients that were part of a clinical trial called QUASAR 2. We go on to test how well the DPD deficiency variants and a set of common variants previously shown to be associated with 5-FU toxicity can predict a person’s risk of 5-Fluorouracil induced toxicity. Our research is important for working out the best way to identify patients at risk of toxicity so high risk patients can be given lower doses of 5-Fluorouracil or be treated with a different drug all together.

Abstract

Efficacy of 5-Fluorouracil (5-FU)-based chemotherapy is limited by significant toxicity. Tests based upon variants in the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines with high level evidence of a link to dihydropyrimidine dehydrogenase (DPD) phenotype and 5-FU toxicity are available to identify patients at high risk of severe adverse events (AEs). We previously reported associations between rs1213215, rs2612091, and NM_000110.3:c.1906-14763G>A (rs12022243) and capecitabine induced toxicity in clinical trial QUASAR 2. We also identified patients with DPD deficiency alleles NM_000110.3: c.1905+1G>A, NM_000110.3: c.2846C>T, NM_000110.3:c.1679T>G and NM_000110.3:c.1651G>A. We have now assessed the frequency of thirteen additional DPYD deficiency variants in 888 patients from the QUASAR 2 clinical trial. We also compared the area under the curve (AUC)—a measure of diagnostic accuracy—of the high-level evidence variants from the CPIC guidelines plus and minus additional DPYD deficiency variants and or common variants associated with 5-FU toxicity. Including additional DPYD deficiency variants retained good diagnostic accuracy for serious adverse events (AEs) and improved sensitivity for predicting grade 4 haematological toxicities (sensitivity 0.75, specificity 0.94) but the improvement in AUC for this toxicity was not significant. Larger datasets will be required to determine the benefit of including additional DPYD deficiency variants not observed here. Genotyping two common alleles statistically significantly improves AUC for prediction of risk of HFS and may be clinically useful (AUC difference 0.177, sensitivity 0.84, specificity 0.31).

Molecular modeling approaches to address drug-metabolizing enzymes (DMEs) mediated chemoresistance: a review

Resistance against clinically approved anticancer drugs is the main roadblock in cancer treatment. Drug metabolizing enzymes (DMEs) that are capable of metabolizing a variety of xenobiotic get overexpressed in malignant cells, therefore, catalyzing drug inactivation. As evident from the literature reports, the levels of DMEs increase in cancer cells that ultimately lead to drug inactivation followed by drug resistance. To puzzle out this issue, several strategies inclusive of analog designing, prodrug designing, and inhibitor designing have been forged. On that front, the implementation of computational tools can be considered a fascinating approach to address the problem of chemoresistance. Various research groups have adopted different molecular modeling tools for the investigation of DMEs mediated toxicity problems. However, the utilization of these in-silico tools in maneuvering the DME mediated chemoresistance is least considered and yet to be explored. These tools can be employed in the designing of such chemotherapeutic agents that are devoid of the resistance problem. The current review canvasses various molecular modeling approaches that can be implemented to address this issue. Special focus was laid on the development of specific inhibitors of DMEs. Additionally, the strategies to bypass the DMEs mediated drug metabolism were also contemplated in this report that includes analogs and pro-drugs designing. Different strategies discussed in the review will be beneficial in designing novel chemotherapeutic agents that depreciate the resistance problem.

Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies

For the last couple of decades, there has been a significant growth in sequencing data, leading to an extraordinary increase in the number of gene variants. This places a challenge on the bioinformatics research community to develop and improve computational tools for functional annotation of new variants. Genes coding for epigenetic regulators have important roles in cancer pathogenesis and mutations in these genes show great potential as clinical biomarkers, especially in hematologic malignancies. Therefore, we developed a model that specifically focuses on these genes, with an assumption that it would outperform general models in predicting the functional effects of amino acid substitutions. EpiMut is a standalone software that implements a sequence based alignment-free method. We applied a two-step approach for generating sequence based features, relying on the biophysical and biochemical indices of amino acids and the Fourier Transform as a sequence transformation method. For each gene in the dataset, the machine learning algorithm-Naïve Bayes was used for building a model for prediction of the neutral or disease-related status of variants. EpiMut outperformed state-of-the-art tools used for comparison, PolyPhen-2, SIFT and SNAP2. Additionally, EpiMut showed the highest performance on the subset of variants positioned outside conserved functional domains of analysed proteins, which represents an important group of cancer-related variants. These results imply that EpiMut can be applied as a first choice tool in research of the impact of gene variants in epigenetic regulators, especially in the light of the biomarker role in hematologic malignancies. EpiMut is freely available at https://www.vin.bg.ac.rs/180/tools/epimut.php.

Variation benchmark datasets: update, criteria, quality and applications

Development of new computational methods and testing their performance has to be carried out using experimental data. Only in comparison to existing knowledge can method performance be assessed. For that purpose, benchmark datasets with known and verified outcome are needed. High-quality benchmark datasets are valuable and may be difficult, laborious and time consuming to generate. VariBench and VariSNP are the two existing databases for sharing variation benchmark datasets used mainly for variation interpretation. They have been used for training and benchmarking predictors for various types of variations and their effects. VariBench was updated with 419 new datasets from 109 papers containing altogether 329 014 152 variants; however, there is plenty of redundancy between the datasets. VariBench is freely available at http://structure.bmc.lu.se/VariBench/. The contents of the datasets vary depending on information in the original source. The available datasets have been categorized into 20 groups and subgroups. There are datasets for insertions and deletions, substitutions in coding and non-coding region, structure mapped, synonymous and benign variants. Effect-specific datasets include DNA regulatory elements, RNA splicing, and protein property for aggregation, binding free energy, disorder and stability. Then there are several datasets for molecule-specific and disease-specific applications, as well as one dataset for variation phenotype effects. Variants are often described at three molecular levels (DNA, RNA and protein) and sometimes also at the protein structural level including relevant cross references and variant descriptions. The updated VariBench facilitates development and testing of new methods and comparison of obtained performances to previously published methods. We compared the performance of the pathogenicity/tolerance predictor PON-P2 to several benchmark studies, and show that such comparisons are feasible and useful, however, there may be limitations due to lack of provided details and shared data.

Database URL: http://structure.bmc.lu.se/VariBench

Functional effects of protein variants

Genetic and other variations frequently affect protein functions. Scientific articles can contain confusing descriptions about which function or property is affected, and in many cases the statements are pure speculation without any experimental evidence. To clarify functional effects of protein variations of genetic or non-genetic origin, a systematic conceptualisation and framework are introduced. This framework describes protein functional effects on abundance, activity, specificity and affinity, along with countermeasures, which allow cells, tissues and organisms to tolerate, avoid, repair, attenuate or resist (TARAR) the effects. Effects on abundance discussed include gene dosage, restricted expression, mis-localisation and degradation. Enzymopathies, effects on kinetics, allostery and regulation of protein activity are subtopics for the effects of variants on activity. Variation outcomes on specificity and affinity comprise promiscuity, specificity, affinity and moonlighting. TARAR mechanisms redress variations with active and passive processes including chaperones, redundancy, robustness, canalisation and metabolic and signalling rewiring. A framework for pragmatic protein function analysis and presentation is introduced. All of the mechanisms and effects are described along with representative examples, most often in relation to diseases. In addition, protein function is discussed from evolutionary point of view. Application of the presented framework facilitates unambiguous, detailed and specific description of functional effects and their systematic study.

Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier

BACKGROUND

Inter-individual differences in dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine S-methyltransferase (TPMT) activity are important predictors for fluoropyrimidine and thiopurine toxicity. While several variants in these genes are known to decrease enzyme activities, many additional genetic variations with unclear functional consequences have been identified, complicating informed clinical decision-making in the respective carriers.

METHODS

We used a novel pharmacogenetically trained ensemble classifier to analyse DPYD and TPMT genetic variability based on sequencing data from 138,842 individuals across eight populations.

RESULTS

The algorithm accurately predicted in vivo consequences of DPYD and TPMT variants (accuracy 91.4% compared to 95.3% in vitro). Further analysis showed high genetic complexity of DPD deficiency, advocating for sequencing-based DPYD profiling, whereas genotyping of four variants in TPMT was sufficient to explain >95% of phenotypic TPMT variability. Lastly, we provided population-scale profiles of ethnogeographic variability in DPD and TPMT phenotypes, and revealed striking interethnic differences in frequency and genetic constitution of DPD and TPMT deficiency.

CONCLUSION

These results provide the most comprehensive data set of DPYD and TPMT variability published to date with important implications for population-adjusted genetic profiling strategies of fluoropyrimidine and thiopurine risk factors and precision public health.

In Vitro Assessment of Fluoropyrimidine-Metabolizing Enzymes: Dihydropyrimidine Dehydrogenase, Dihydropyrimidinase, and β-Ureidopropionase

Fluoropyrimidine drugs (FPs), including 5-fluorouracil, tegafur, capecitabine, and doxifluridine, are among the most widely used anticancer agents in the treatment of solid tumors. However, severe toxicity occurs in approximately 30% of patients following FP administration, emphasizing the importance of predicting the risk of acute toxicity before treatment. Three metabolic enzymes, dihydropyrimidine dehydrogenase (DPD), dihydropyrimidinase (DHP), and β-ureidopropionase (β-UP), degrade FPs; hence, deficiencies in these enzymes, arising from genetic polymorphisms, are involved in severe FP-related toxicity, although the effect of these polymorphisms on in vivo enzymatic activity has not been clarified. Furthermore, the clinical usefulness of current methods for predicting in vivo activity, such as pyrimidine concentrations in blood or urine, is unknown. In vitro tests have been established as advantageous for predicting the in vivo activity of enzyme variants. This is due to several studies that evaluated FP activities after enzyme metabolism using transient expression systems in Escherichia coli or mammalian cells; however, there are no comparative reports of these results. Thus, in this review, we summarized the results of in vitro analyses involving DPD, DHP, and β-UP in an attempt to encourage further comparative studies using these drug types and to aid in the elucidation of their underlying mechanisms.

New DPYD variants causing DPD deficiency in patients treated with fluoropyrimidine

PURPOSE

Several clinical guidelines recommend genetic screening of DPYD, including coverage of the variants c.1905 + 1G>A(DPYD*2A), c.1679T>G(DPYD*13), c.2846A>T, and c.1129-5923C>G, before initiating treatment with fluoropyrimidines. However, this screening is often inadequate at predicting the occurrence of severe fluoropyrimidine-induced toxicity in patients.

METHODS

Using a complementary approach combining whole DPYD exome sequencing and in silico and structural analysis, as well as phenotyping of DPD by measuring uracilemia (U), dihydrouracilemia (UH₂), and the UH₂/U ratio in plasma, we were able to characterize and interpret DPYD variants in 28 patients with severe fluoropyrimidine-induced toxicity after negative screening.

RESULTS

Twenty-five out of 28 patients (90%) had at least 1 variant in the DPYD coding sequence, and 42% of the variants (6/14) were classified as potentially deleterious by at least 2 of the following algorithms: SIFT, Poly-Phen-2, and DPYD varifier. We identified two very rare deleterious mutations, namely, c.2087G>A (p.R696H) and c.2324T>G (p.L775W). We were able to demonstrate partial DPD deficiency, as measured by the UH₂/U ratio in a patient carrying the variant p.L775W for the first time.

CONCLUSION

Whole exon sequencing of DPYD in patients with suspicion of partial DPD deficiency can help to identify rare or new variants that lead to enzyme inactivation. Combining different techniques can yield abundant information without increasing workload and cost burden, thus making it a useful approach for implementation in patient care.

A Simple and Rapid UPLC-UV Method for Detecting DPD Deficiency in Patients With Cancer

Detecting patients with dihydropyrimidine dehydrogenase (DPD) deficiency is becoming a major concern in clinical oncology. Monitoring physiologic plasma uracil and/or plasma uracil‐to‐dihydrouracil metabolic ratio is a common surrogate frequently used to determine DPD phenotype without direct measurement of the enzymatic activity. With respect to the increasing number of patients rquiring analysis, it is critical to develop simple, rapid, and affordable methods suitable for routine screening. We have developed and validated a simple and robust ultraperformance liquid chromatography‒ultraviolet (UPLC‐UV) method with shortened (i.e., 12 minutes) analytical run‐times, compatible with the requirements of large‐scale upfront screening. The method enables detection of uracil (U) over a range of 5–500 ng/ml (265 nm) and of dihydrouracil (UH2) over a range of 40–500 ng/ml (210 nm) in plasma with no chromatographic interference. When used as part of routine screening for DPD deficiency, this method was fully able to discriminate nondeficient patients (i.e., with U levels < 16 ng/ml) from deficient patients at risk of severe toxicity (i.e., U > 16 ng/ml). Results from 1 month of routine testing are presented and, although no complete deficits were detected, 10.7% of the screened patients presented DPD deficiency and would thus require s decresed dose. Overall, this new method, using a simple preanalytical solid‐phase extraction procedure, and based on use of a standard UPLC apparatus, is both cost‐ and time‐effective and can be easily implemented in any laboratory aiming to begin routine DPD testing.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction of DPYD and fluoropyrimidines

Despite advances in the field of pharmacogenetics (PGx), clinical acceptance has remained limited. The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate PGx implementation by developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy. This guideline describes the starting dose optimization of three anti-cancer drugs (fluoropyrimidines: 5-fluorouracil, capecitabine and tegafur) to decrease the risk of severe, potentially fatal, toxicity (such as diarrhoea, hand-foot syndrome, mucositis or myelosuppression). Dihydropyrimidine dehydrogenase (DPD, encoded by the DPYD gene) enzyme deficiency increases risk of fluoropyrimidine-induced toxicity. The DPYD-gene activity score, determined by four DPYD variants, predicts DPD activity and can be used to optimize an individual’s starting dose. The gene activity score ranges from 0 (no DPD activity) to 2 (normal DPD activity). In case it is not possible to calculate the gene activity score based on DPYD genotype, we recommend to determine the DPD activity and adjust the initial dose based on available data. For patients initiating 5-fluorouracil or capecitabine: subjects with a gene activity score of 0 are recommended to avoid systemic and cutaneous 5-fluorouracil or capecitabine; subjects with a gene activity score of 1 or 1.5 are recommended to initiate therapy with 50% the standard dose of 5-fluorouracil or capecitabine. For subjects initiating tegafur: subjects with a gene activity score of 0, 1 or 1.5 are recommended to avoid tegafur. Subjects with a gene activity score of 2 (reference) should receive a standard dose. Based on the DPWG clinical implication score, DPYD genotyping is considered “essential”, therefore directing DPYD testing prior to initiating fluoropyrimidines.

Rare Dihydropyrimidine Dehydrogenase Variants and Toxicity by Floropyrimidines: A Case Report

Variations in the activity, up to absolute deficiency, of the enzyme dihydropyrimidine dehydrogenase (DPD), result in the occurrence of adverse reactions to chemotherapy, and have been included among the pharmacogenetic factors underlying inter-individual variability in response to fluoropyrimidines. The study of single-nucleotide polymorphisms of the DPYD gene, which encodes the DPD enzyme, is one of the main parameters capable of predicting reduced enzymatic activity and the consequent influence on fluoropyrimidine treatment, in terms of reduction of both adverse reactions and therapeutic efficacy in disease control. In this paper, we describe a patient with metastatic breast cancer showing signs of increased toxicity following capecitabine therapy. The DPD enzyme activity analysis revealed a partial deficiency. The study of the most frequent polymorphisms of the DPYD gene suggested a wild-type genotype but indicated a novel variant c.1903A>G (p.Asn635Asp), not previously described, proximal to the splice donor site of exon 14. After excluding the potential pathogenic feature of the newly-identified variant, we performed cDNA sequencing of the entire DPYD coding sequence. This analysis identified the variants c.85T>C and c.496A>G, which were previously described as pivotal components of the haplotype associated with decreased enzyme activity and suggested that both variant alleles are related to DPD deficiency. The clinical case findings described in this study emphasize the importance of performing complete genetic analysis of the DPYD gene in order to identify rare and low frequency variants potentially responsible for toxic reactions to fluoropyrimidine treatment.

DPYD*6 plays an important role in fluoropyrimidine toxicity in addition to DPYD*2A and c.2846A>T: a comprehensive analysis in 1254 patients

Dihydropyrimidine dehydrogenase (DPYD) is a highly polymorphic gene and classic deficient variants (i.e., c.1236G>A/HapB3, c.1679T>G, c.1905+1G>A and c.2846A>T) are characterized by impaired enzyme activity and risk of severe adverse drug reactions (ADRs) in patients treated with fluoropyrimidines. The identification of poor metabolizers by pre-emptive DPYD screening may reduce the rate of ADRs but many patients with wild-type genotype for classic variants may still display ADRs. Therefore, the search for additional DPYD polymorphisms associated with ADRs may improve the safety of treatment with fluoropyrimidines. This study included 1254 patients treated with fluoropyrimidine-containing regimens and divided into cohort 1, which included 982 subjects suffering from gastrointestinal G≥2 and/or hematological G≥3 ADRs, and cohort 2 (control group), which comprised 272 subjects not requiring dose reduction, delay or discontinuation of treatment. Both groups were screened for DPYD variants c.496A>G, c.1236G>A/HapB3, c.1601G>A (DPYD*4), c.1627A>G (DPYD*5), c.1679T>G (DPYD*13), c.1896T>C, c.1905 + 1G>A (DPYD*2A), c.2194G>A (DPYD*6), and c.2846A>T to assess their association with toxicity. Genetic analysis in the two cohorts were done by Real-Time PCR of DNA extracted from 3 ml of whole blood. DPYD c.496A>G, c.1601G>A, c.1627A>G, c.1896T>C, and c.2194G>A variants were found in both cohort 1 and 2, while c.1905+1G>A and c.2846A>T were present only in cohort 1. DPYD c.1679T>G and c.1236G>A/HapB3 were not found. Univariate analysis allowed the selection of c.1905+1G>A, c.2194G>A and c.2846A>T alleles as significantly associated with gastrointestinal and hematological ADRs (p < 0.05), while the c.496A>G variant showed a positive trend of association with neutropenia (p = 0.06). In conclusion, c.2194G>A is associated with clinically-relevant ADRs in addition to the already known c.1905+1G>A and c.2846A>T variants and should be evaluated pre-emptively to reduce the risk of fluoropyrimidine-associated ADRs.