UGT1A1 genotype-dependent dose adjustment of belinostat in patients with advanced cancers using population pharmacokinetic modeling and simulation

Quantitative analysis of the UDP-glucuronosyltransferase transcriptome in human tissues

UDP-glucuronosyltransferases (UGTs) are phase II drug metabolizing enzymes that play important roles in the detoxification of endogenous and exogenous substrates. The 22 human UGTs belong to four families (UGT1, UGT2, UGT3, and UGT8) and differ in their expression, substrate specificity, UDP-sugar preference, and physiological functions. Differential expression/activity of the UGTs contributes to interperson variability in drug responses and toxicity, hormone homeostasis, and disease/cancer risks. However, in normal tissues, the tissue-specific expression profiles and transcriptional regulation of the UGTs are still not fully understood. In this study, we comprehensively analyzed the transcriptome of 22 UGTs in 54 human tissues/regions using RNAseq data from GTEx. We then validated the findings in the liver and small intestine samples using real-time PCR. Our results showed large interindividual variability across tissues in the expression of each UGT and the overall composition of UGT pools, consisting of different UGTs and their splice isoforms. Our results also revealed coexpression of the UGTs, Cytochrome P450s, and many transcription factors in the liver, suggesting potential coregulation or functional coordination. Our results provide the groundwork for future studies to detail further the regulation of the expression and activity of the UGTs.

PAnno: A pharmacogenomics annotation tool for clinical genomic testing

Introduction: Next-generation sequencing (NGS) technologies have been widely used in clinical genomic testing for drug response phenotypes. However, the inherent limitations of short reads make accurate inference of diplotypes still challenging, which may reduce the effectiveness of genotype-guided drug therapy. Methods: An automated Pharmacogenomics Annotation tool (PAnno) was implemented, which reports prescribing recommendations and phenotypes by parsing the germline variant call format (VCF) file from NGS and the population to which the individual belongs. Results: A ranking model dedicated to inferring diplotypes, developed based on the allele (haplotype) definition and population allele frequency, was introduced in PAnno. The predictive performance was validated in comparison with four similar tools using the consensus diplotype data of the Genetic Testing Reference Materials Coordination Program (GeT-RM) as ground truth. An annotation method was proposed to summarize prescribing recommendations and classify drugs into avoid use, use with caution, and routine use, following the recommendations of the Clinical Pharmacogenetics Implementation Consortium (CPIC), etc. It further predicts phenotypes of specific drugs in terms of toxicity, dosage, efficacy, and metabolism by integrating the high-confidence clinical annotations in the Pharmacogenomics Knowledgebase (PharmGKB). PAnno is available at https://github.com/PreMedKB/PAnno. Discussion: PAnno provides an end-to-end clinical pharmacogenomics decision support solution by resolving, annotating, and reporting germline variants.

Chemotherapy-related hyperbilirubinemia in pediatric acute lymphoblastic leukemia: a genome-wide association study from the AIEOP-BFM ALL study group

BACKGROUND

Characterization of clinical phenotypes in context with tumor and host genomic information can aid in the development of more effective and less toxic risk-adapted and targeted treatment strategies. To analyze the impact of therapy-related hyperbilirubinemia on treatment outcome and to identify contributing genetic risk factors of this well-recognized adverse effect we evaluated serum bilirubin levels in 1547 pediatric patients with acute lymphoblastic leukemia (ALL) and conducted a genome-wide association study (GWAS).

PATIENTS AND METHODS

Patients were treated in multicenter trial AIEOP-BFM ALL 2000 for pediatric ALL. Bilirubin toxicity was graded 0 to 4 according to the Common Toxicity Criteria (CTC) of the National Cancer Institute. In the GWAS discovery cohort, including 650 of the 1547 individuals, genotype frequencies of 745,895 single nucleotide variants were compared between 435 patients with hyperbilirubinemia (CTC grades 1-4) during induction/consolidation treatment and 215 patients without it (grade 0). Replication analyses included 224 patients from the same trial.

RESULTS

Compared to patients with no (grade 0) or moderate hyperbilirubinemia (grades 1-2) during induction/consolidation, patients with grades 3-4 had a poorer 5-year event free survival (76.6 ± 3% versus 87.7 ± 1% for grades 1-2, P = 0.003; 85.2 ± 2% for grade 0, P < 0.001) and a higher cumulative incidence of relapse (15.6 ± 3% versus 9.0 ± 1% for grades 1-2, P = 0.08; 11.1 ± 1% for grade 0, P = 0.007). GWAS identified a strong association of the rs6744284 variant T allele in the UGT1A gene cluster with risk of hyperbilirubinemia (allelic odds ratio (OR) = 2.1, P = 7 × 10^- 8). TT-homozygotes had a 6.5-fold increased risk of hyperbilirubinemia (grades 1-4; 95% confidence interval (CI) = 2.9-14.6, P = 7 × 10^- 6) and a 16.4-fold higher risk of grade 3-4 hyperbilirubinemia (95% CI 6.1-43.8, P = 2 × 10^- 8). Replication analyses confirmed these associations with joint analysis yielding genome-wide significance (allelic OR = 2.1, P = 6 × 10^- 11; 95% CI 1.7-2.7). Moreover, rs6744284 genotypes were strongly linked to the Gilbert's syndrome-associated UGT1A1*28/*37 allele (r² = 0.70), providing functional support for study findings. Of clinical importance, the rs6744284 TT genotype counterbalanced the adverse prognostic impact of high hyperbilirubinemia on therapy outcome.

CONCLUSIONS

Chemotherapy-related hyperbilirubinemia is a prognostic factor for treatment outcome in pediatric ALL and genetic variation in UGT1A aids in predicting the clinical impact of hyperbilirubinemia.

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Modern developments in germline pharmacogenomics for oncology prescribing

The integration of genomic data into personalized treatment planning has revolutionized oncology care. Despite this, patients with cancer remain vulnerable to high rates of adverse drug events and medication inefficacy, affecting prognosis and quality of life. Pharmacogenomics is a field seeking to identify germline genetic variants that contribute to an individual's unique drug response. Although there is widespread integration of genomic information in oncology, somatic platforms, rather than germline biomarkers, have dominated the attention of cancer providers. Patients with cancer potentially stand to benefit from improved integration of both somatic and germline genomic information, especially because the latter may complement treatment planning by informing toxicity risk for drugs with treatment-limiting tolerabilities and narrow therapeutic indices. Although certain germline pharmacogenes, such as TPMT, UGT1A1, and DPYD, have been recognized for decades, recent attention has illuminated modern potential dosing implications for a whole new set of anticancer agents, including targeted therapies and antibody-drug conjugates, as well as the discovery of additional genetic variants and newly relevant pharmacogenes. Some of this information has risen to the level of directing clinical action, with US Food and Drug Administration label guidance and recommendations by international societies and governing bodies. This review is focused on key new pharmacogenomic evidence and oncology-specific dosing recommendations. Personalized oncology care through integrated pharmacogenomics represents a unique multidisciplinary collaboration between oncologists, laboratory science, bioinformatics, pharmacists, clinical pharmacologists, and genetic counselors, among others. The authors posit that expanded consideration of germline genetic information can further transform the safe and effective practice of oncology in 2022 and beyond.

UGT1A1 Guided Cancer Therapy: Review of the Evidence and Considerations for Clinical Implementation

Simple Summary

The use of multi-gene testing platforms to individualize treatment is rapidly expanding into routine oncology practice. UGT1A1, which encodes for the uridine diphosphate glucuronosyltransferase (UGT) 1A1 enzyme, is commonly included on multi-gene molecular testing assays. UGT1A1 polymorphisms may influence drug-induced toxicities of numerous medications used in oncology. However, guidance for incorporating UGT1A1 results into therapeutic decision-making is sparse and can differ depending on the referenced resource. We summarize the literature describing associations between UGT1A1 polymorphisms and toxicity risk with irinotecan, belinostat, pazopanib, and nilotinib. Resources that provide recommendations for UGT1A1-guided drug prescribing are reviewed, and considerations for implementation into patient care are provided.

Abstract

Multi-gene assays often include UGT1A1 and, in certain instances, may report associated toxicity risks for irinotecan, belinostat, pazopanib, and nilotinib. However, guidance for incorporating UGT1A1 results into therapeutic decision-making is mostly lacking for these anticancer drugs. We summarized meta-analyses, genome-wide association studies, clinical trials, drug labels, and guidelines relating to the impact of UGT1A1 polymorphisms on irinotecan, belinostat, pazopanib, or nilotinib toxicities. For irinotecan, UGT1A1*28 was significantly associated with neutropenia and diarrhea, particularly with doses ≥ 180 mg/m², supporting the use of UGT1A1 to guide irinotecan prescribing. The drug label for belinostat recommends a reduced starting dose of 750 mg/m² for UGT1A1*28 homozygotes, though published studies supporting this recommendation are sparse. There was a correlation between UGT1A1 polymorphisms and pazopanib-induced hepatotoxicity, though further studies are needed to elucidate the role of UGT1A1-guided pazopanib dose adjustments. Limited studies have investigated the association between UGT1A1 polymorphisms and nilotinib-induced hepatotoxicity, with data currently insufficient for UGT1A1-guided nilotinib dose adjustments.

Phase I trial of belinostat with cisplatin and etoposide in advanced solid tumors, with a focus on neuroendocrine and small cell cancers of the lung

The standard-of-care for advanced small cell lung cancer (SCLC) is chemotherapy with cisplatin+etoposide (C+E). Most patients have chemosensitive disease at the outset, but disease frequently relapses and limits survival. Efforts to improve therapeutic outcomes in SCLC and other neuroendocrine cancers have focused on epigenetic agents, including the histone deacetylase inhibitor belinostat. The primary objective was to determine the maximum tolerated dose of the combination of belinostat (B) with C+E. Belinostat was administered as a 48-h continuous intravenous infusion on days 1-2; cisplatin was administered as a 1-h intravenous infusion on day 2; and etoposide was administered as a 1-h intravenous infusion on days 2, 3, and 4. Twenty-eight patients were recruited in this single-center study. The maximum tolerated dose was belinostat 500 mg/m/24 h, cisplatin 60 mg/m, and etoposide 80 mg/m. The combination was safe, although some patients were more susceptible to adverse events. Hematologic toxicities were most commonly observed. Objective responses were observed in 11 (39%) of 28 patients and seven (47%) of 15 patients with neuroendocrine tumors (including SCLC). Patients carrying more than three copies of variant UGT1A1 (*28 and *60) had higher serum levels of belinostat because of slower clearance. DNA damage peaked at 36 h after the initiation of belinostat, as did global lysine acetylation, but returned to baseline 12 h after the end of infusion. The combination of B+C+E is safe and active in SCLC and other neuroendocrine cancers. Future phase II studies should consider genotyping patients for UGT1A1*28 and UGT1A1*60 and to identify patients at an increased risk of adverse events.

The UDP-Glycosyltransferase (UGT) Superfamily: New Members, New Functions, and Novel Paradigms

UDP-glycosyltransferases (UGTs) catalyze the covalent addition of sugars to a broad range of lipophilic molecules. This biotransformation plays a critical role in elimination of a broad range of exogenous chemicals and by-products of endogenous metabolism, and also controls the levels and distribution of many endogenous signaling molecules. In mammals, the superfamily comprises four families: UGT1, UGT2, UGT3, and UGT8. UGT1 and UGT2 enzymes have important roles in pharmacology and toxicology including contributing to interindividual differences in drug disposition as well as to cancer risk. These UGTs are highly expressed in organs of detoxification (e.g., liver, kidney, intestine) and can be induced by pathways that sense demand for detoxification and for modulation of endobiotic signaling molecules. The functions of the UGT3 and UGT8 family enzymes have only been characterized relatively recently; these enzymes show different UDP-sugar preferences to that of UGT1 and UGT2 enzymes, and to date, their contributions to drug metabolism appear to be relatively minor. This review summarizes and provides critical analysis of the current state of research into all four families of UGT enzymes. Key areas discussed include the roles of UGTs in drug metabolism, cancer risk, and regulation of signaling, as well as the transcriptional and posttranscriptional control of UGT expression and function. The latter part of this review provides an in-depth analysis of the known and predicted functions of UGT3 and UGT8 enzymes, focused on their likely roles in modulation of levels of endogenous signaling pathways.

Applying dynamic contrast enhanced MSOT imaging to intratumoral pharmacokinetic modeling

Examining the dynamics of an agent in the tumor microenvironment can offer critical insights to the influx rate and accumulation of the agent. Intratumoral kinetic characterization in the in vivo setting can further elicudate distribution patterns and tumor microenvironment. Dynamic contrast-enhanced Multispectral Optoacoustic Tomographic imaging (DCE-MSOT) acquires serial MSOT images with the administration of an exogenous contrast agent over time. We tracked the dynamics of a tumor-targeted contrast agent, HypoxiSense 680 (HS680), in breast xenograft mouse models using MSOT. Arterial input function (AIF) approach with MSOT imaging allowed for tracking HS680 dynamics within the mouse. The optoacoustic signal for HS680 was quantified using the ROI function in the ViewMSOT software. A two-compartment pharmacokinetics (PK) model constructed in MATLAB to fit rate parameters. The contrast influx (k_in) and outflux (k_out) rate constants predicted are k_in = 1.96 × 10^-2 s^-1 and k_out = 9.5 × 10^-3 s^-1 (R = 0.9945).

Utilization of data below the analytical limit of quantitation in pharmacokinetic analysis and modeling: promoting interdisciplinary debate

Traditionally, bioanalytical laboratories do not report actual concentrations for samples with results below the LOQ (BLQ) in pharmacokinetic studies. BLQ values are outside the method calibration range established during validation and no data are available to support the reliability of these values. However, ignoring BLQ data can contribute to bias and imprecision in model-based pharmacokinetic analyses. From this perspective, routine use of BLQ data would be advantageous. We would like to initiate an interdisciplinary debate on this important topic by summarizing the current concepts and use of BLQ data by regulators, pharmacometricians and bioanalysts. Through introducing the limit of detection and evaluating its variability, BLQ data could be released and utilized appropriately for pharmacokinetic research.

A population pharmacokinetic/toxicity model for the reduction of platelets during a 48-h continuous intravenous infusion of the histone deacetylase inhibitor belinostat

PURPOSE

Belinostat is a second-generation histone deacetylase inhibitor (HDI) predominantly metabolized by UGT1A1-mediated glucuronidation. Two common polymorphisms (UGT1A1*28 and UGT1A1*60) were previously associated with impaired drug clearance and thrombocytopenia risk, likely from increased drug exposure. This latter phenomenon has been observed with other HDIs such as abexinostat, panobinostat, romidepsin, and vorinostat. It was the intention of this brief report to expand a population pharmacokinetic (PPK) model to include a pharmacodynamic (PD) model describing the change in platelet levels in patients with cancer administered belinostat as a 48-h continuous intravenous infusion, along with cisplatin and etoposide.

METHODS

The PPK/PD model developed here introduced an additional rate constant to a commonly used mechanistic myelosuppression model to better describe the maturation of megakaryocytes into platelets before degradation and a feedback mechanism. The model employed a proportional error model to describe the observed circulating platelet data.

RESULTS

Several covariates were explored, including sex, body weight, UGT1A1 genotype status, liver, and kidney function, but none significantly improved the model. Platelet levels rebounded to baseline within 21 days, before the next cycle of therapy. Simulations predicted that higher belinostat drug exposure does cause lower thrombocyte nadirs compared to lower belinostat levels. However, platelet levels rebound by the start of the next belinostat cycle.

CONCLUSIONS

This model suggests a q3week schedule allows for sufficient platelet recovery before the next belinostat infusion is optimal.

Pharmacogenomics and histone deacetylase inhibitors

The histone deacetylase inhibitor valproic acid (VPA) has been used for many decades in neurology and psychiatry. The more recent introduction of the histone deacetylase inhibitors (HDIs) belinostat, romidepsin and vorinostat for treatment of hematological malignancies indicates the increasing popularity of these agents. Belinostat, romidepsin and vorinostat are metabolized or transported by polymorphic enzymes or drug transporters. Thus, genotype-directed dosing could improve pharmacotherapy by reducing the risk of toxicities or preventing suboptimal treatment. This review provides an overview of clinical studies on the effects of polymorphisms on the pharmacokinetics, efficacy or toxicities of HDIs including belinostat, romidepsin, vorinostat, panobinostat, VPA and a number of novel compounds currently being tested in Phase I and II trials. Although pharmacogenomic studies for HDIs are scarce, available data indicate that therapy with belinostat (UGT1A1), romidepsin (ABCB1), vorinostat (UGT2B17) or VPA (UGT1A6) could be optimized by upfront genotyping.

In vitro characterization of belinostat glucuronidation: demonstration of both UGT1A1 and UGT2B7 as the main contributing isozymes

1. Belinostat is a histone deacetylase inhibitor that has been approved for the treatment of peripheral T-cell lymphoma. This study aimed to identify the UDP-glucuronosyltransferase (UGT) enzymes responsible for belinostat glucuronidation through kinetic determination using recombinant enzymes with determined enzyme concentrations. 2. The rate of glucuronidation was determined by incubation of belinostat with enzyme preparations. Kinetic parameters such as K_m and V_max were derived by fitting an appropriate model to the glucuronidation data. The role of active UGT enzymes to belinostat metabolism was evaluated using inhibition experiments and activity correlation analyses. 3. Human liver microsomes generated a glucuronide metabolite (i.e. belinostat glucuronide) from belinostat. The glucuronide structure was confirmed by high-resolution mass spectrometry as well as the fragmentation pattern. Of 12 test UGT enzymes, only four (UGT1A1, 1A3, 2B4, and 2B7) showed metabolic activities toward belinostat. UGT1A1 was the most active enzyme, followed by UGT2B7, 1A3, and 2B4. Kinetic profiles for UGT1A1, 1A3, 2B4, and 2B7 were well described by Michaelis-Menten, Michaelis-Menten, Hill equation, and substrate inhibition equation, respectively. 4. Glucuronidation of belinostat was markedly inhibited by emodin and apigenin (two potent inhibitors of UGT1A1), and by quinidine and diclofenac sodium (two selective inhibitors of UGT2B7). Belinostat glucuronidation was found to be significantly correlated with β-estradiol 3-O-glucuronidation and zidovudine glucuronidation. 5. It was concluded that in addition to UGT1A1, UGT2B7 was also an important contributor to belinostat glucuronidation.

UGT genotyping in belinostat dosing

Certain genetic polymorphisms of UDP glucuronosyltransferase 1 family, polypeptide A1 (UGT1A1) can reduce gene expression (*28, *60, *93) or activity (*6), thereby altering the pharmacokinetics, pharmacodynamics, and the risk of toxicities of UGT1A1 substrates, of which irinotecan is a widely-described example. This review presents an overview of the clinical effects of UGT1A1 polymorphisms on the pharmacology of UGT1A1 substrates, with a special focus on the novel histone deacetylase inhibitor belinostat. Belinostat, approved for the treatment of peripheral T-cell lymphoma, is primarily glucuronidated by UGT1A1. Recent preclinical and clinical data showed that UGT1A1*28 was associated with reduced glucuronidation in human liver microsomes, while in a retrospective analysis of a Phase I trial with patients receiving belinostat UGT1A1*60 was predominantly associated with increased belinostat plasma concentrations. Furthermore, both UGT1A1*28 and *60 variants were associated with increased incidence of thrombocytopenia and neutropenia. Using population pharmacokinetic analysis a 33% dose reduction has been proposed for patients carrying UGT1A1 variant alleles. Clinical effects of this genotype-based dosing recommendation is currently prospectively being investigated. Overall, the data suggest that UGT1A1 genotyping is useful for improving belinostat therapy.

Effects of UGT1A1 genotype on the pharmacokinetics, pharmacodynamics, and toxicities of belinostat administered by 48-hour continuous infusion in patients with cancer

The histone deacetylase inhibitor belinostat is eliminated through glucuronidation by UGT1A1. Polymorphisms that reduce UGT1A1 function could result in increased belinostat exposure and toxicities. We wanted to determine which single-nucleotide polymorphisms alter belinostat exposure and toxicity. In a phase 1 trial (belinostat over 48 hours in combination with cisplatin and etoposide), belinostat (400, 500, 600, or 800 mg/m(2) /24 h, 48-hour continuous infusion) was administered to patients with cancer in combination with cisplatin and etoposide (n = 25). Patients were genotyped for UGT1A1 variants associated with reduced function: UGT1A1*6, UGT1A1*28, and UGT1A1*60. End points were associations between UGT1A1 genotype and belinostat pharmacokinetics (PK), toxicities, and global protein lysine acetylation (AcK). Belinostat AUC was increased (P = .003), and t1/2 increased (P = .0009) in UGT1A1*28 and UGT1A1*60 carriers who received more than 400 mg/m(2) /24 h. The incidence of grades 3-4 thrombocytopenia (P = .0081) was associated with UGT1A1 polymorphisms. The US Food and Drug Administration-approved package insert recommends dose adjustment of belinostat for UGT1A1*28. However, our data suggest dose adjustment is also necessary for UGT1A1*60. UGT1A1 polymorphisms were associated with increased systemic belinostat exposure, increased AcK, and increased incidence of toxicities, particularly at doses > 400 mg/m(2) /24 h.