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

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.

Spatio-temporal analysis of toxigenic genes expression in the growing Bufo gargarizans based on RNA sequencing data

BACKGROUND

Bufo gargarizans Cantor, a widely distributed amphibian species in Asia, produces and releases toxins through its retroauricular and granular glands. Although various tissues have been sequenced, the molecular mechanisms underlying the toxin production remain unclear. To elucidate these mechanisms, abdominal skin (non-toxic secretory glands) and retroauricular gland (toxic secreting glands) samples were collected at different time points (3, 6, 12, 24, and 36 months) for RNA sequencing (RNA-seq) and analysis.

RESULTS

In comparison to the S group during the same period, a total of 3053, 3026, 1516, 1028, and 2061 differentially expressed genes (DEGs) were identified across five developmental stages. Gene Ontology (GO) analysis revealed that DEGs were primarily enriched in biological processes including cellular processes, single-organism processes, metabolic processes, and biological regulation. In terms of cellular components, the DEGs were predominantly localized in the cell and cell parts, whereas molecular function indicated significant enrichment in binding and catalytic activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the metabolism and synthesis of various substances, such as lipid metabolism, cofactor and vitamin metabolism, tryptophan metabolism, steroid biosynthesis, and primary bile acid biosynthesis, were accompanied by the development of toads. Additionally, using trend analysis, we discovered candidate genes that were upregulated in the retroauricular glands during development, and the abundance of these genes in the abdominal skin was extremely low. Finally, we identified 26 genes that are likely to be involved in toxin production and that are likely to be involved in toxin anabolism.

CONCLUSION

Overall, these results provide new insights into the genes involved in toxin production in B. gargarizans, which will improve our understanding of the molecular mechanisms underlying toxigenic gene expression.

Rare variants in pharmacogenes influence clozapine metabolism in individuals with schizophrenia

Clozapine is the only licensed medication for treatment-resistant schizophrenia (TRS). Few predictors for variation in response to clozapine have been identified, but clozapine metabolism is known to influence therapeutic response and adverse side effects. Here, we expand on genome-wide studies of clozapine metabolism, previously focused on common genetic variation, by analysing whole-exome sequencing data from 2062 individuals with schizophrenia taking clozapine in the UK. We investigated whether rare genomic variation in genes and gene sets involved in the clozapine metabolism pathway influences plasma concentrations of clozapine metabolites, assessed through the longitudinal analysis of 6585 pharmacokinetic assays. We observed a statistically significant association between the burden of rare damaging coding variants (MAF ≤ 1 %) in gene sets broadly related to drug pharmacokinetics and lower clozapine (β = -0.054, SE = 0.019, P-value = 0.005) concentrations in plasma. We estimate that the effects in clozapine plasma concentrations of a single damaging allele in this gene set are akin to reducing the clozapine dose by about 35 mg/day. The gene-based analysis identified rare variants in CYP1A2, which encodes the enzyme responsible for converting clozapine to norclozapine, as having the strongest effects of any gene on clozapine metabolism (β = 0.324, SE = 0.124, P = 0.009). Our findings support the hypothesis that rare genetic variants in known drug-metabolising enzymes and transporters can markedly influence clozapine plasma concentrations; these results suggest that pharmacogenomic efforts trying to predict clozapine metabolism and personalise drug therapy could benefit from the inclusion of rare damaging variants in pharmacogenes beyond those already identified and catalogued as PGx star alleles.

Dihydropyrimidine dehydrogenase gene variants for predicting grade 4-5 fluoropyrimidine-induced toxicity: FUSAFE individual patient data meta-analysis

BACKGROUND

Dihydropyrimidine dehydrogenase (DPD) deficiency is the main known cause of life-threatening fluoropyrimidine (FP)-induced toxicities. We conducted a meta-analysis on individual patient data to assess the contribution of deleterious DPYD variants *2A/D949V/*13/HapB3 (recommended by EMA) and clinical factors, for predicting G4-5 toxicity.

METHODS

Study eligibility criteria included recruitment of Caucasian patients without DPD-based FP-dose adjustment. Main endpoint was 12-week haematological or digestive G4-5 toxicity. The value of DPYD variants *2A/p.D949V/*13 merged, HapB3, and MIR27A rs895819 was evaluated using multivariable logistic models (AUC).

RESULTS

Among 25 eligible studies, complete clinical variables and primary endpoint were available in 15 studies (8733 patients). Twelve-week G4-5 toxicity prevalence was 7.3% (641 events). The clinical model included age, sex, body mass index, schedule of FP-administration, concomitant anticancer drugs. Adding *2A/p.D949V/*13 variants (at least one allele, prevalence 2.2%, OR 9.5 [95%CI 6.7-13.5]) significantly improved the model (p < 0.0001). The addition of HapB3 (prevalence 4.0%, 98.6% heterozygous), in spite of significant association with toxicity (OR 1.8 [95%CI 1.2-2.7]), did not improve the model. MIR27A rs895819 was not associated with toxicity, irrespective of DPYD variants.

CONCLUSIONS

FUSAFE meta-analysis highlights the major relevance of DPYD *2A/p.D949V/*13 combined with clinical variables to identify patients at risk of very severe FP-related toxicity.

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.

Pharmacogenomics Beyond Single Common Genetic Variants: The Way Forward

Interindividual variability in genes encoding drug-metabolizing enzymes, transporters, receptors, and human leukocyte antigens has a major impact on a patient's response to drugs with regard to efficacy and safety. Enabled by both technological and conceptual advances, the field of pharmacogenomics is developing rapidly. Major progress in omics profiling methods has enabled novel genotypic and phenotypic characterization of patients and biobanks. These developments are paralleled by advances in machine learning, which have allowed us to parse the immense wealth of data and establish novel genetic markers and polygenic models for drug selection and dosing. Pharmacogenomics has recently become more widespread in clinical practice to personalize treatment and to develop new drugs tailored to specific patient populations. In this review, we provide an overview of the latest developments in the field and discuss the way forward, including how to address the missing heritability, develop novel polygenic models, and further improve the clinical implementation of pharmacogenomics.

Integrating rare genetic variants into DPYD pharmacogenetic testing may help preventing fluoropyrimidine-induced toxicity

Variability in genes involved in drug pharmacokinetics or drug response can be responsible for suboptimal treatment efficacy or predispose to adverse drug reactions. In addition to common genetic variations, large-scale sequencing studies have uncovered multiple rare genetic variants predicted to cause functional alterations in genes encoding proteins implicated in drug metabolism, transport and response. To understand the functional importance of rare genetic variants in DPYD, a pharmacogene whose alterations can cause severe toxicity in patients exposed to fluoropyrimidine-based regimens, massively parallel sequencing of the exonic regions and flanking splice junctions of the DPYD gene was performed in a series of nearly 3000 patients categorized according to pre-emptive DPD enzyme activity using the dihydrouracil/uracil ([UH2]/[U]) plasma ratio as a surrogate marker of DPD activity. Our results underscore the importance of integrating next-generation sequencing-based pharmacogenomic interpretation into clinical decision making to minimize fluoropyrimidine-based chemotherapy toxicity without altering treatment efficacy.

MIR27A rs895819 TC genotype increases risk of fluoropyrimidine-induced severe toxicity independently of DPYD variations

Aim: MicroRNA 27a (miR-27a) regulates post-transcriptionally DPD activity. We have analyzed the association of MIR27A rs895819T>C variation, that modulates miR-27a expression, with fluropyrimidine-induced toxicity. Materials & methods: MIR27A rs895819T>C genotyping was conducted by TaqMan® allelic discrimination assay in 313 FP-treated cancer patients. Results: In overdominance (TC vs TT + CC), TC genotype was associated with grade 3-4 toxicity (p = 0.002), any grade toxicity (p = 0.052), and delayed drug administration or therapy discontinuation (p = 0.038). Odds of grade 3-4 toxicity were increased by both DPYD deficiency (OR: 8.923; p = 0.006) and MIR27A rs895819 TC genotype (OR: 3.865; p = 0.002). Conclusion: MIR27A rs895819 TC genotype is an independent risk factor for fluoropyrimidine-associated toxicity in the Greek population. Thus, MIR27A rs895819TC patients can be closely monitored for fluoropyrimidine-induced severe toxicity.

The burden of rare variants in DPYS gene is a novel predictor of the risk of developing severe fluoropyrimidine-related toxicity

BACKGROUND

Despite a growing number of publications highlighting the potential impact on the therapy outcome, rare genetic variants (minor allele frequency < 1%) in genes associated to drug adsorption, distribution, metabolism, and elimination are poorly studied. Previously, rare germline DPYD missense variants were shown to identify a subset of fluoropyrimidine-treated patients at high risk for severe toxicity. Here, we investigate the impact of rare genetic variants in a panel of 54 other fluoropyrimidine-related genes on the risk of severe toxicity.

METHODS

The coding sequence and untranslated regions of 54 genes related to fluoropyrimidine pharmacokinetics/pharmacodynamics were analyzed by next-generation sequencing in 120 patients developing grade 3-5 toxicity (NCI-CTC vs3.0) and 104 matched controls. Sequence Kernel Association Test (SKAT) analysis was used to select genes with a burden of genetic variants significantly associated with risk of severe toxicity. The statistical association of common and rare genetic variants in selected genes was further investigated. The functional impact of genetic variants was assessed using two different in silico prediction tools (Predict2SNP; ADME Prediction Framework).

RESULTS

SKAT analysis highlighted DPYS and PPARD as genes with a genetic mutational burden significantly associated with risk of severe fluoropyrimidine-related toxicity (Bonferroni adjusted P = 0.024 and P = 0.039, respectively). Looking more closely at allele frequency, the burden of rare DPYS variants was significantly higher in patients with toxicity compared with controls (P = 0.047, Mann-Whitney test). Carrying at least one rare DPYS variant was associated with an approximately fourfold higher risk of severe cumulative (OR = 4.08, P = 0.030) and acute (OR = 4.21, P = 0.082) toxicity. The burden of PPARD rare genetic variants was not significantly related to toxicity. Some common variants with predictive value in DPYS and PPARD were also identified: DPYS rs143004875-T and PPARD rs2016520-T variants predicted an increased risk of severe cumulative (P = 0.002 and P = 0.001, respectively) and acute (P = 0.005 and P = 0.0001, respectively) toxicity.

CONCLUSION

This work demonstrated that the rare mutational burden of DPYS, a gene strictly cooperating with DPYD in the catabolic pathway of fluoropyrimidines, is a promising pharmacogenetic marker for precision dosing of fluoropyrimidines. Additionally, some common genetic polymorphisms in DPYS and PPARD were identified as promising predictive markers that warrant further investigation.

Implementation of pre-emptive testing of a pharmacogenomic panel in clinical practice: Where do we stand?

Adverse drug reactions (ADRs) account for a large proportion of hospitalizations among adults and are more common in multimorbid patients, worsening clinical outcomes and burdening healthcare resources. Over the past decade, pharmacogenomics has been developed as a practical tool for optimizing treatment outcomes by mitigating the risk of ADRs. Some single-gene reactive tests are already used in clinical practice, including the DPYD test for fluoropyrimidines, which demonstrates how integrating pharmacogenomic data into routine care can improve patient safety in a cost-effective manner. The evolution from reactive single-gene testing to comprehensive pre-emptive genotyping panels holds great potential for refining drug prescribing practices. Several implementation projects have been conducted to test the feasibility of applying different genetic panels in clinical practice. Recently, the results of a large prospective randomized trial in Europe (the PREPARE study by Ubiquitous Pharmacogenomics consortium) have provided the first evidence that prospective application of a pre-emptive pharmacogenomic test panel in clinical practice, in seven European healthcare systems, is feasible and yielded a 30% reduction in the risk of developing clinically relevant toxicities. Nevertheless, some important questions remain unanswered and will hopefully be addressed by future dedicated studies. These issues include the cost-effectiveness of applying a pre-emptive genotyping panel, the role of multiple co-medications, the transferability of currently tested pharmacogenetic guidelines among patients of non-European origin and the impact of rare pharmacogenetic variants that are not detected by currently used genotyping approaches.

Implementation of upfront DPYD genotyping with a low-cost and high-throughput assay to guide fluoropyrimidine treatment in cancer patients

OBJECTIVES

Genetic variants in the dihydropyrimidine dehydrogenase (DPYD ) gene are associated with reduced dihydropyrimidine dehydrogenase enzyme activity and can cause severe fluoropyrimidine-related toxicity. We assessed the frequency of the four most common and well-established DPYD variants associated with fluoropyrimidine toxicity and implemented a relatively low-cost and high-throughput genotyping assay for their detection.

METHODS

This study includes 457 patients that were genotyped for the DPYD c.1129-5923C>G, c.1679T>G, c.1905 + 1G>A and c.2846A>T variants, either by Sanger sequencing or kompetitive allele specific PCR (KASP) technology. Of these, 172 patients presented toxicity during treatment with fluoropyrimidines (post-treatment group), and 285 were tested before treatment (pretreatment group).

RESULTS

Heterozygous DPYD variants were identified in 7.4% of the entire series of 457 patients, being the c.2846A>T the most frequent variant. In the post-treatment group, 15.7% of the patients presented DPYD variants, whereas only 2.5% of the patients in the pretreatment group presented a variant. The KASP assays designed in this study presented 100% genotype concordance with the results obtained by Sanger sequencing.

CONCLUSIONS

The combined assessment of the four DPYD variants in our population increases the identification of patients at high risk for developing fluoropyrimidine toxicity, supporting the upfront routine implementation of DPYD variant genotyping. Furthermore, the KASP genotyping assay described in this study presents a rapid turnaround time and relatively low cost, making upfront DPYD screening feasible in clinical practice.

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.

Machine Learning Application Identifies Germline Markers of Hypertension in Patients With Ovarian Cancer Treated With Carboplatin, Taxane, and Bevacizumab

Pharmacogenomics studies how genes influence a person's response to treatment. When complex phenotypes are influenced by multiple genetic variations with little effect, a single piece of genetic information is often insufficient to explain this variability. The application of machine learning (ML) in pharmacogenomics holds great potential - namely, it can be used to unravel complicated genetic relationships that could explain response to therapy. In this study, ML techniques were used to investigate the relationship between genetic variations affecting more than 60 candidate genes and carboplatin-induced, taxane-induced, and bevacizumab-induced toxicities in 171 patients with ovarian cancer enrolled in the MITO-16A/MaNGO-OV2A trial. Single-nucleotide variation (SNV, formerly SNP) profiles were examined using ML to find and prioritize those associated with drug-induced toxicities, specifically hypertension, hematological toxicity, nonhematological toxicity, and proteinuria. The Boruta algorithm was used in cross-validation to determine the significance of SNVs in predicting toxicities. Important SNVs were then used to train eXtreme gradient boosting models. During cross-validation, the models achieved reliable performance with a Matthews correlation coefficient ranging from 0.375 to 0.410. A total of 43 SNVs critical for predicting toxicity were identified. For each toxicity, key SNVs were used to create a polygenic toxicity risk score that effectively divided individuals into high-risk and low-risk categories. In particular, compared with low-risk individuals, high-risk patients were 28-fold more likely to develop hypertension. The proposed method provided insightful data to improve precision medicine for patients with ovarian cancer, which may be useful for reducing toxicities and improving toxicity management.

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.

Characterization of pharmacogenomic variants in a Brazilian admixed cohort of elderly individuals based on whole-genome sequencing data

Introduction: Research in the field of pharmacogenomics (PGx) aims to identify genetic variants that modulate response to drugs, through alterations in their pharmacokinetics (PK) or pharmacodynamics (PD). The distribution of PGx variants differs considerably among populations, and whole-genome sequencing (WGS) plays a major role as a comprehensive approach to detect both common and rare variants. This study evaluated the frequency of PGx markers in the context of the Brazilian population, using data from a population-based admixed cohort from Sao Paulo, Brazil, which includes variants from WGS of 1,171 unrelated, elderly individuals. Methods: The Stargazer tool was used to call star alleles and structural variants (SVs) from 38 pharmacogenes. Clinically relevant variants were investigated, and the predicted drug response phenotype was analyzed in combination with the medication record to assess individuals potentially at high-risk of gene-drug interaction. Results: In total, 352 unique star alleles or haplotypes were observed, of which 255 and 199 had a frequency < 0.05 and < 0.01, respectively. For star alleles with frequency > 5% (n = 97), decreased, loss-of-function and unknown function accounted for 13.4%, 8.2% and 27.8% of alleles or haplotypes, respectively. Structural variants (SVs) were identified in 35 genes for at least one individual, and occurred with frequencies >5% for CYP2D6, CYP2A6, GSTM1, and UGT2B17. Overall 98.0% of the individuals carried at least one high risk genotype-predicted phenotype in pharmacogenes with PharmGKB level of evidence 1A for drug interaction. The Electronic Health Record (EHR) Priority Result Notation and the cohort medication registry were combined to assess high-risk gene-drug interactions. In general, 42.0% of the cohort used at least one PharmGKB evidence level 1A drug, and 18.9% of individuals who used PharmGKB evidence level 1A drugs had a genotype-predicted phenotype of high-risk gene-drug interaction. Conclusion: This study described the applicability of next-generation sequencing (NGS) techniques for translating PGx variants into clinically relevant phenotypes on a large scale in the Brazilian population and explores the feasibility of systematic adoption of PGx testing in Brazil.

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.

Predicting Dihydropyrimidine Dehydrogenase Deficiency and Related 5-Fluorouracil Toxicity: Opportunities and Challenges of DPYD Exon Sequencing and the Role of Phenotyping Assays

Deficiency of dihydropyrimidine dehydrogenase (DPD), encoded by the DPYD gene, is associated with severe toxicity induced by the anti-cancer drug 5-Fluorouracil (5-FU). DPYD genotyping of four recommended polymorphisms is widely used to predict toxicity, yet their prediction power is limited. Increasing availability of next generation sequencing (NGS) will allow us to screen rare variants, predicting a larger fraction of DPD deficiencies. Genotype−phenotype correlations were investigated by performing DPYD exon sequencing in 94 patients assessed for DPD deficiency by the 5-FU degradation rate (5-FUDR) assay. Association of common variants with 5-FUDR was analyzed with the SNPStats software. Functional interpretation of rare variants was performed by in-silico analysis (using the HSF system and PredictSNP) and literature review. A total of 23 rare variants and 8 common variants were detected. Among common variants, a significant association was found between homozygosity for the rs72728438 (c.1974+75A>G) and decreased 5-FUDR. Haplotype analysis did not detect significant associations with 5-FUDR. Overall, in our sample cohort, NGS exon sequencing allowed us to explain 42.5% of the total DPD deficiencies. NGS sharply improves prediction of DPD deficiencies, yet a broader collection of genotype−phenotype association data is needed to enable the clinical use of sequencing data.