The use of the 13C-dextromethorphan breath test for phenotyping CYP2D6 in breast cancer patients using tamoxifen: association with CYP2D6 genotype and serum endoxifen levels

EpiHNet: Detecting epistasis by heterogeneous molecule network

Epistasis between single nucleotide polymorphisms (SNPs) plays an important role in elucidating the missing heritability of complex diseases. Diverse approaches have been invented for detecting SNP interactions, but they canonically neglect the important and useful connections between SNPs and other bio-molecules (i.e., miRNAs and lncRNAs). To comprehensively model these disease related molecules, a heterogeneous bio-molecular network based solution EpiHNet is introduced for high-order SNP interactions detection. EpiHNet firstly uses case/control data to construct an SNP statistical network, and meta-path based similarity on the heterogeneous network composed with SNPs, genes, lncRNAs, miRNAs and diseases to define another SNP relational network. The SNP relational network can explore and exploit different associations between molecules and diseases to complement the SNP statistical network and search the significantly associated SNPs. Next, EpiHNet integrates these two networks into a composite network, applies the modularity based clustering with fast search strategy to divide SNP nodes into different clusters. After that, it detects SNP interactions based on SNP combinations derived from each cluster. Synthetic experiments on diverse two-locus and three-locus disease models manifest that EpiHNet outperforms competitive baselines, even without the heterogeneous network. For real WTCCC breast cancer data, EpiHNet also demonstrates expressive results on detecting high-order SNP interactions.

European guideline on indications, performance and clinical impact of 13 C-breath tests in adult and pediatric patients: An EAGEN, ESNM, and ESPGHAN consensus, supported by EPC

Introduction

¹³C‐breath tests are valuable, noninvasive diagnostic tests that can be widely applied for the assessment of gastroenterological symptoms and diseases. Currently, the potential of these tests is compromised by a lack of standardization regarding performance and interpretation among expert centers.

Methods

This consensus‐based clinical practice guideline defines the clinical indications, performance, and interpretation of ¹³C‐breath tests in adult and pediatric patients. A balance between scientific evidence and clinical experience was achieved by a Delphi consensus that involved 43 experts from 18 European countries. Consensus on individual statements and recommendations was established if ≥ 80% of reviewers agreed and <10% disagreed.

Results

The guideline gives an overview over general methodology of ¹³C‐breath testing and provides recommendations for the use of ¹³C‐breath tests to diagnose Helicobacter pylori infection, measure gastric emptying time, and monitor pancreatic exocrine and liver function in adult and pediatric patients. Other potential applications of ¹³C‐breath testing are summarized briefly. The recommendations specifically detail when and how individual ¹³C‐breath tests should be performed including examples for well‐established test protocols, patient preparation, and reporting of test results.

Conclusion

This clinical practice guideline should improve pan‐European harmonization of diagnostic approaches to symptoms and disorders, which are very common in specialist and primary care gastroenterology practice, both in adult and pediatric patients. In addition, this guideline identifies areas of future clinical research involving the use of ¹³C‐breath tests.

Predicting steady-state endoxifen plasma concentrations in breast cancer patients by CYP2D6 genotyping or phenotyping. Which approach is more reliable?

In previous studies, steady-state Z-endoxifen plasma concentrations (ENDOss) correlated with relapse-free survival in women on tamoxifen (TAM) treatment for breast cancer. ENDOss also correlated significantly with CYP2D6 genotype (activity score) and CYP2D6 phenotype (dextromethorphan test). Our aim was to ascertain which method for assessing CYP2D6 activity is more reliable in predicting ENDOss. The study concerned 203 Caucasian women on tamoxifen-adjuvant therapy (20 mg q.d.). Before starting treatment, CYP2D6 was genotyped (and activity scores computed), and the urinary log(dextromethorphan/dextrorphan) ratio [log(DM/DX)] was calculated after 15 mg of oral dextromethorphan. Plasma concentrations of TAM, N-desmethyl-tamoxifen (ND-TAM), Z-4OH-tamoxifen (4OH-TAM) and ENDO were assayed 1, 4, and 8 months after first administering TAM. Multivariable regression analysis was used to identify the clinical and laboratory variables predicting log-transformed ENDOss (log-ENDOss). Genotype-derived CYP2D6 phenotypes (PM, IM, NM, EM) and log(DM/DX) correlated independently with log-ENDOss. Genotype-phenotype concordance was almost complete only for poor metabolizers, whereas it emerged that 34% of intermediate, normal, and ultrarapid metabolizers were classified differently based on log(DM/DX). Multivariable regression analysis selected log(DM/DX) as the best predictor, with patients' age, weak inhibitor use, and CYP2D6 phenotype decreasingly important: log-ENDOss = 0.162 - log(DM/DX) × 0.170 + age × 0.0063 - weak inhibitor use × 0.250 + IM × 0.105 + (NM + UM) × 0.210; (R2  = 0.51). In conclusion, log(DM/DX) seems superior to genotype-derived CYP2D6 phenotype in predicting ENDOss.

Point-of-care companion diagnostic tests for personalizing psychiatric medications: fulfilling an unmet clinical need

Over the last decade stable isotope-labeled substrates have been used as probes for rapid, point-of-care, non-invasive and user-friendly phenotype breath tests to evaluate activity of drug metabolizing enzymes. These diagnostic breath tests can potentially be used as companion diagnostics by physicians to personalize medications, especially psychiatric drugs with narrow therapeutic windows, to monitor the progress of disease severity, medication efficacy and to study in vivo the pharmacokinetics of xenobiotics. Several genotype tests have been approved by the FDA over the last 15 years for both cytochrome P450 2D6 and 2C19 enzymes, however they have not been cleared for use in personalizing medications since they fall woefully short in identifying all non-responders to drugs, especially for the CYP450 enzymes. CYP2D6 and CYP2C19 are among the most extensively studied drug metabolizing enzymes, involved in the metabolism of approximately 30% of FDA-approved drugs in clinical use, associated with large individual differences in medication efficacy or tolerability essentially due to phenoconversion. The development and commercialization via FDA approval of the non-invasive, rapid (<60 min), in vivo, phenotype diagnostic breath tests to evaluate polymorphic CYP2D6 and CYP2C19 enzyme activity by measuring exhaled ¹³CO₂ as a biomarker in breath will effectively resolve the currently unmet clinical need for individualized psychiatric drug therapy. Clinicians could personalize treatment options for patients based on the CYP2D6 and CYP2C19 phenotype by selecting the optimal medication at the right initial and subsequent maintenance dose for the desired clinical outcome (i.e. greatest efficacy and minimal side effects).

CYP450 genotype and pharmacogenetic association studies: a critical appraisal

Despite strong pharmacological support, association studies using genotype-predicted phenotype as a variable have yielded conflicting or inconclusive evidence to promote personalized pharmacotherapy. Unless the patient is a genotypic poor metabolizer, imputation of patient's metabolic capacity (or metabolic phenotype), a major factor in drug exposure-related clinical response, is a complex and highly challenging task because of limited number of alleles interrogated, population-specific differences in allele frequencies, allele-specific substrate-selectivity and importantly, phenoconversion mediated by co-medications and inflammatory co-morbidities that modulate the functional activity of drug metabolizing enzymes. Furthermore, metabolic phenotype and clinical outcomes are not binary functions; there is large intragenotypic and intraindividual variability. Therefore, the ability of association studies to identify relationships between genotype and clinical outcomes can be greatly enhanced by determining phenotype measures of study participants and/or by therapeutic drug monitoring to correlate drug concentrations with genotype and actual metabolic phenotype. To facilitate improved analysis and reporting of association studies, we propose acronyms with the prefixes ‘g’ (genotype-predicted phenotype) and ‘m’ (measured metabolic phenotype) to better describe this important variable of the study subjects. Inclusion of actually measured metabolic phenotype, and when appropriate therapeutic drug monitoring, promises to reveal relationships that may not be detected by using genotype alone as the variable.

CYP2D6 Metabolism in Frail Elderly Compared to Non-Frail Elderly: A Pilot Feasibility Study

BACKGROUND

Frailty is a clinical phenotype that is associated with adverse health outcomes. Since frail patients may be more prone for adverse drug events and about 15-20 % of commonly prescribed drugs are metabolized by CYP2D6, we hypothesized that CYP2D6 metabolism is decreased in frail patients compared with healthy subjects.

METHODS

The (13)C-dextromethorphan breath test (DM-BT) was used to determine CYP2D6 phenotype using (13)C-dextromethorphan ((13)C-DM) as a probe. Eleven frail and 22 non-frail (according to the Fried criteria) subjects aged 70-85 years were phenotyped for CYP2D6.

RESULTS

Despite inequalities in CYP2D6 genotype between frail and non-frail subjects, the CYP2D6 gene activity score was equally distributed between the two groups (1.33 ± 0.50 vs. 1.28 ± 0.752). In male patients, no difference in total and free serum testosterone levels was observed between frail and non-frail men. Serum dehydroepiandrostenedione sulfate (DHEAS) levels were lower in frail subjects (1.56 μmol/L) compared with non-frail subjects (2.36 μmol/L), but the difference was not significant (p = 0.15). Body mass index was significantly correlated to CYP2D6 phenotype, whereas frailty score and individual parameters of frailty, Karnofsky score, and activities of daily living score were not significantly correlated to CYP2D6 phenotype. Although there was no difference in CYP2D6 phenotype observed between frail mean ± standard deviation (mean ± SD) area under the curve for delta over baseline values (0-2 h) (AUCDOB2h) 319 ± 169 ‰ min] and non-frail subjects (mean ± SD AUCDOB2h 298 ± 159 ‰ min), the present sample size is considered too small to draw any firm conclusions regarding a potential phenoconversion of CYP2D6 in frail elderly as compared with healthy subjects.

CONCLUSION

Frail and non-frail subjects did not differ in CYP2D6 phenotype, taking into account that the precalculated sample size was not achieved. Further studies with more patients are needed in order to adequately understand a possible correlation.

Evaluation of CYP2D6 enzyme activity using a 13C-dextromethorphan breath test in women receiving adjuvant tamoxifen

BACKGROUND

In tamoxifen-treated patients, breast cancer recurrence differs according to CYP2D6 genotype and endoxifen steady-state concentrations (Endx Css). The ¹³C-dextromethorphan breath test (DM-BT), labeled with ¹³C at the O-CH3 moiety, measures CYP2D6 enzyme activity. We sought to examine the ability of the DM-BT to identify known CYP2D6 genotypic poor metabolizers and examine the correlation between DM-BT and Endx Css.

METHODS

DM-BT and tamoxifen pharmacokinetics were obtained at baseline, 3, and 6 months following tamoxifen initiation. Potent CYP2D6 inhibitors were prohibited. The correlation between baseline DM-BT with CYP2D6 genotype and Endx Css was determined. The association between baseline DM-BT (where values ≤0.9 is an indicator of poor in vivo CYP2D6 metabolism) and Endx Css (using values≤11.2 known to be associated with poorer recurrence free survival) was explored.

RESULTS

A total of 91 patients were enrolled and 77 were eligible. CYP2D6 genotype was positively correlated with baseline, 3, and 6 months DM-BT (r ranging from 0.457-0. 60; P<0.001). Both CYP2D6 genotype (r=0.47, 0.56, P<0.0001), and baseline DM-BT (r=0.60, 0.54, P<0.001) were associated with 3 and 6 months Endx Css, respectively. Seven (78%) of nine patients with low (≤11.2 nmol/l) 3 month Endx Css also had low DM-BT (≤0.9) including 2/2 CYP2D6 PM/PM and 5/5 IM/PM. In contrast, one (2%) of 48 patients with a low DM-BT had Endx Css more than 11.2 nmol/l.

CONCLUSION

In patients not taking potent CYP2D6 inhibitors, DM-BT was associated with CYP2D6 genotype and 3 and 6 months Endx Css but did not provide better discrimination of Endx Css compared with CYP2D6 genotype alone. Further studies are needed to identify additional factors which alter Endx Css.

Population pharmacokinetic modelling to assess the impact of CYP2D6 and CYP3A metabolic phenotypes on the pharmacokinetics of tamoxifen and endoxifen

AIMS

Tamoxifen is considered a pro-drug of its active metabolite endoxifen. The major metabolic enzymes involved in endoxifen formation are CYP2D6 and CYP3A. There is considerable evidence that variability in activity of these enzymes influences endoxifen exposure and thereby may influence the clinical outcome of tamoxifen treatment. We aimed to quantify the impact of metabolic phenotype on the pharmacokinetics of tamoxifen and endoxifen.

METHODS

We assessed the CYP2D6 and CYP3A metabolic phenotypes in 40 breast cancer patients on tamoxifen treatment with a single dose of dextromethorphan as a dual phenotypic probe for CYP2D6 and CYP3A. The pharmacokinetics of dextromethorphan, tamoxifen and their relevant metabolites were analyzed using non-linear mixed effects modelling.

RESULTS

Population pharmacokinetic models were developed for dextromethorphan, tamoxifen and their metabolites. In the final model for tamoxifen, the dextromethorphan derived metabolic phenotypes for CYP2D6 as well as CYP3A significantly (P < 0.0001) explained 54% of the observed variability in endoxifen formation (inter-individual variability reduced from 55% to 25%).

CONCLUSIONS

We have shown that not only CYP2D6, but also CYP3A enzyme activity influences the tamoxifen to endoxifen conversion in breast cancer patients. Our developed model may be used to assess separately the impact of CYP2D6 and CYP3A mediated drug-drug interactions with tamoxifen without the necessity of administering this anti-oestrogenic drug and to support Bayesian guided therapeutic drug monitoring of tamoxifen in routine clinical practice.

Tailored Tamoxifen Treatment for Breast Cancer Patients: A Perspective

Tamoxifen, an endocrine agent, is widely used in the treatment of estrogen receptor-positive breast cancer. It has greatly reduced disease recurrence and mortality rates of breast cancer patients, however, not all patients benefit from tamoxifen treatment because in approximately 25% to 30% of the patients the disease recurs. Many researchers have sought to find factors associated with endocrine treatment outcome in the past years, however, this quest has not been finished. In this article, we focus on a factor that might influence outcome of tamoxifen treatment: interpatient variability in tamoxifen pharmacokinetics. In recent years it has become clear that tamoxifen undergoes extensive metabolism and that some of the formed metabolites are much more pharmacologically active than tamoxifen itself. Despite the wide interpatient variability in tamoxifen pharmacokinetics and pharmacodynamics, all patients receive a standard dose of 20 mg tamoxifen per day. Different approaches can be pursued to individualize tamoxifen dosing: genotyping, phenotyping, and therapeutic drug monitoring. Therapeutic drug monitoring seems to be the most direct and promising approach, however, further clinical research is warranted to establish the added value of individual dosing in tamoxifen treatment optimization.

Addressing phenoconversion: the Achilles' heel of personalized medicine

Phenoconversion is a phenomenon that converts genotypic extensive metabolizers (EMs) into phenotypic poor metabolizers (PMs) of drugs, thereby modifying their clinical response to that of genotypic PMs. Phenoconversion, usually resulting from nongenetic extrinsic factors, has a significant impact on the analysis and interpretation of genotype-focused clinical outcome association studies and personalizing therapy in routine clinical practice. The high phenotypic variability or genotype-phenotype mismatch, frequently observed due to phenoconversion within the genotypic EM population, means that the real number of phenotypic PM subjects may be greater than predicted from their genotype alone, because many genotypic EMs would be phenotypically PMs. If the phenoconverted population with genotype-phenotype mismatch, most extensively studied for CYP2D6, is as large as the evidence suggests, there is a real risk that genotype-focused association studies, typically correlating only the genotype with clinical outcomes, may miss clinically strong pharmacogenetic associations, thus compromising any potential for advancing the prospects of personalized medicine. This review focuses primarily on co-medication-induced phenoconversion and discusses potential approaches to rectify some of the current shortcomings. It advocates routine phenotyping of subjects in genotype-focused association studies and proposes a new nomenclature to categorize study populations. Even with strong and reliable data associating patients' genotypes with clinical outcome(s), there are problems clinically in applying this knowledge into routine pharmacotherapy because of potential genotype-phenotype mismatch. Drug-induced phenoconversion during routine clinical practice remains a major public health issue. Therefore, the principal challenges facing personalized medicine, which need to be addressed, include identification of the following factors: (i) drugs that are susceptible to phenoconversion; (ii) co-medications that can cause phenoconversion; and (iii) dosage amendments that need to be applied during and following phenoconversion.

Precursors for cytochrome P450 profiling breath tests from an in silico screening approach

The family of cytochrome P450 enzymes (CYPs) is a major player in the metabolism of drugs and xenobiotics. Genetic polymorphisms and transcriptional regulation give a complex patient-individual CYP activity profile for each human being. Therefore, personalized medicine demands easy and non-invasive measurement of the CYP phenotype. Breath tests detect volatile organic compounds (VOCs) in the patients' exhaled air after administration of a precursor molecule. CYP breath tests established for individual CYP isoforms are based on the detection of (13)CO2 or (14)CO2 originating from CYP-catalyzed oxidative degradation reactions of isotopically labeled precursors.We present an in silico work-flow aiming at the identification of novel precursor molecules, likely to result in VOCs other than CO2 upon oxidative degradation as we aim at label-free precursor molecules. The ligand-based work-flow comprises five parts: (1) CYP profiling was encoded as a decision tree based on 2D molecular descriptors derived from established models in the literature and validated against publicly available data extracted from the DrugBank. (2) Likely sites of metabolism were identified by reactivity and accessibility estimation for abstractable hydrogen radical. (3) Oxidative degradation reactions (O- and N-dealkylations) were found to be most promising in the release of VOCs. Thus, the CYP-catalyzed oxidative degradation reaction was encoded as SMIRKS (a programming language style to implement reactions based on the SMARTS description) to enumerate possible reaction products. (4) A quantitative structure property relation (QSPR) model aiming to predict the Henry constant H was derived from data for 488 organic compounds and identifies potentially VOCs amongst CYP reaction products. (5) A blacklist of naturally occurring breath components was implemented to identify marker molecules allowing straightforward detection within the exhaled air.Evident oxidative degradation reactions served as test case for the screening approach. Comparisons to metabolism data from literature support the results' plausibility. Thus, a large scale screening for potential novel breath test precursor using the presented five stage work-flow is promising.

Breath tests to phenotype drug disposition in oncology

Breath tests (BTs) have been investigated as diagnostic tools to phenotype drug disposition in cancer patients in the pursuit to individualize drug treatment. The choice of the right phenotype probe is crucial and depends on the metabolic pathway of the anticancer agent of interest. BTs using orally or intravenously administered selective non-radioactive (13)C-labeled probes to non-invasively evaluate dihydropyrimidine dehydrogenase, cytochrome P450 (CYP) 3A4, and CYP2D6 enzyme activity have been published. Clinically, a (13)C-dextromethorphan BT to predict endoxifen levels in breast cancer patients and a (13)C-uracil BT to predict fluoropyrimidine toxicity in colorectal cancer patients are most promising. However, the clinical benefit and cost effectiveness of these phenotype BTs need to be determined in order to make the transition from an experimental setting to clinical practice as companion diagnostic tests.