The Making of a CYP3A Biomarker Panel for Guiding Drug Therapy.
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ABSTRACT:
SUBMITTER: Wang D
PROVIDER: S-EPMC3901424 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The purpose of this study was to determine the impact of CYP3A5 expression on inhibitory potency (Ki or IC50 values) of CYP3A inhibitors, using recombinant CYP3A4 and CYP3A5 (rCYP3A4 and rCYP3A5) and CYP3A5 genotyped human liver microsomes (HLMs). IC50 ratios between rCYP3A4 and rCYP3A5 (rCYP3A5/rCYP3A4) of ketoconazole (KTZ) and itraconazole (ITZ) were 8.5 and 8.8 for midazolam (MDZ), 4.7 and 9.1 for testosterone (TST), 1.3 and 2.8 for terfenadine, and 0.6 and 1.7 for vincristine, respectively, suggesting substrate- and inhibitor-dependent selectivity of the two azoles. Due to the difference in the IC50 values for CYP3A4 and CYP3A5, nonconcordant expression of CYP3A4 and CYP3A5 protein can significantly affect the observed magnitude of CYP3A-mediated drug-drug interactions in humans. Indeed, the IC50 values of KTZ and ITZ for CYP3A-catalyzed MDZ and TST metabolism were significantly higher in HLMs with CYP3A5*1/*1 and CYP3A5*1/*3 genotypes than in HLMs with the CYP3A5*3/*3 genotype, showing CYP3A5 expression-dependent IC50 values. Moreover, when IC50 values of KTZ and ITZ for different HLMs were kinetically simulated based on CYP3A5 expression level and enzyme-specific IC50 values, a good correlation between the simulated and the experimentally measured IC50 values was observed. Further simulation analysis revealed that both the Ki ratio (for inhibitors) and Vmax/Km ratio (for substrates) between CYP3A4 and CYP3A5 were major factors for CYP3A5 expression-dependent IC50 values. In conclusion, the present study demonstrates that CYP3A5 genotype and expression level have a significant impact on inhibitory potency for CYP3A-catalyzed drug metabolism, but that the magnitude of its effect is inhibitor-substrate pair specific.
| S-EPMC3716306 | biostudies-literature
Project description:Identifying and understanding potential drug-drug interactions (DDIs) are vital for the treatment of human immunodeficiency virus type 1 (HIV-1) infection. This article discusses DDIs between doravirine, a nonnucleoside reverse transcriptase inhibitor (NNRTI), and cytochrome P450 3A (CYP3A) substrates and drugs that modulate CYP3A activity. Consistent with previously published in vitro data and DDI trials with the CYP3A substrates midazolam and atorvastatin, doravirine did not have any meaningful impact on the pharmacokinetics of the CYP3A substrates ethinyl estradiol and levonorgestrel. Coadministration of doravirine with CYP3A inhibitors (ritonavir or ketoconazole) increased doravirine exposure approximately 3-fold. However, these increases were not considered clinically meaningful. Conversely, previously published trials showed that coadministered CYP3A inducers (rifampin and rifabutin) decreased doravirine exposure by 88% and 50%, respectively (K. L. Yee, S. G. Khalilieh, R. I. Sanchez, R. Liu, et al., Clin Drug Investig 37:659-667, 2017 [https://doi.org/10.1007/s40261-017-0513-4]; S. G. Khalilieh, K. L. Yee, R. I. Sanchez, R. Liu, et al., J Clin Pharmacol 58:1044-1052, 2018 [https://doi.org/10.1002/jcph.1103]), while doravirine exposure following prior efavirenz administration led to an initial reduction in doravirine exposure of 62%, but the reduction became less pronounced with time (K. L. Yee, R. I. Sanchez, P. Auger, R. Liu, et al., Antimicrob Agents Chemother 61:e01757-16, 2017 [https://doi.org/10.1128/AAC.01757-16]). Overall, the coadministration of doravirine with CYP3A inhibitors and substrates is, therefore, supported by these data together with efficacy and safety data from clinical trials, while coadministration with strong CYP3A inducers, such as rifampin, cannot be recommended. Concomitant dosing with rifabutin (a CYP3A inducer less potent than rifampin) is acceptable if doravirine dosing is adjusted from once to twice daily; however, the effect of other moderate inducers on doravirine pharmacokinetics is unknown.
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Project description:Worldwide, oesophageal cancer is the sixth leading cause of deaths related to cancer and represents a major health concern. Sub-Saharan Africa is one of the regions of the world with the highest incidence and mortality rates for oesophageal cancer and most of the cases of oesophageal cancer in this region are oesophageal squamous cell carcinoma (OSCC). The development and progression of OSCC is characterized by genomic changes which can be utilized as diagnostic or prognostic markers. These include changes in the expression of various genes involved in signaling pathways that regulate pathways that regulate processes that are related to the hallmarks of cancer, changes in the tumor mutational burden, changes in alternate splicing and changes in the expression of non-coding RNAs such as miRNA. These genomic changes give rise to characteristic profiles of altered proteins, transcriptomes, spliceosomes and genomes which can be used in clinical applications to monitor specific disease related parameters. Some of these profiles are characteristic of more aggressive forms of cancer or are indicative of treatment resistance or tumors that will be difficult to treat or require more specialized specific treatments. In Sub-Saharan region of Africa there is a high incidence of viral infections such as HPV and HIV, which are both risk factors for OSCC. The genomic changes that occur due to these infections can serve as diagnostic markers for OSCC related to viral infection. Clinically this is an important distinction as it influences treatment as well as disease progression and treatment monitoring practices. This underlines the importance of the characterization of the molecular landscape of OSCC in order to provide the best treatment, care, diagnosis and screening options for the management of OSCC.
| S-EPMC9598679 | biostudies-literature
Project description:Lemborexant is approved for treating insomnia and is under investigation for treating irregular sleep-wake rhythm disorder. Based on in vitro drug-drug interaction (DDI) characteristics, phase 1, open-label DDI studies were conducted to evaluate lemborexant's cytochrome P450 3A (CYP3A) and CYP2B6 interaction potential. Interactions between lemborexant 10 mg and strong and moderate CYP3A inhibitors (itraconazole and fluconazole), a strong CYP3A inducer (rifampin), and CYP3A (midazolam) and CYP2B6 substrates (bupropion) were evaluated. Coadministration of lemborexant with itraconazole or fluconazole resulted in 1.4- to 1.6-fold and 3.7- to 4-fold increases in lemborexant maximum observed concentration (Cmax ) and area under the concentration-time curve from zero time extrapolated to infinity (AUC0-inf ), respectively. Coadministration of lemborexant with rifampin resulted in >90% decreases in lemborexant Cmax and AUC0-inf . Midazolam exposure was not affected. Coadministration of lemborexant with bupropion resulted in 49.9% and 45.5% decreases in S-bupropion Cmax and AUC0-inf , respectively.Comparison of estimated exposures for patients in phase 3 trials who were/were not receiving concomitant weak CYP3A inhibitors substantiated the DDI pharmacokinetic findings. Lemborexant was generally well tolerated in the phase 1 studies. In summary, lemborexant does not affect the pharmacokinetics of CYP3A substrates and has potential to induce CYP2B6. Consistent with in vitro findings, moderate and strong CYP3A inhibitors and inducers affected the pharmacokinetics of lemborexant; hence, patients taking lemborexant 5 or 10 mg should avoid coadministration with moderate and strong CYP3A inhibitors and inducers.
| S-EPMC8248323 | biostudies-literature
Project description:Milademetan is a small-molecule inhibitor of murine double minute 2 (MDM2) that is in clinical development for advanced solid tumors and hematological cancers, including liposarcoma and acute myeloid leukemia. Milademetan is a CYP3A and P-glycoprotein substrate and moderate CYP3A inhibitor. The current study aims to understand the drug-drug interaction (DDI) risk of milademetan as a CYP3A substrate during its early clinical development. A clinical DDI study of milademetan (NCT03614455) showed that concomitant administration of single-dose milademetan with the strong CYP3A inhibitor itraconazole or posaconazole increased milademetan mean area under the curve from zero to infinity (AUCinf ) by 2.15-fold (90% confidence interval [CI], 1.98-2.34) and 2.49-fold (90% CI, 2.26-2.74), respectively, supporting that the milademetan dose should be reduced by 50% when concomitantly administered with strong CYP3A inhibitors. A physiologically-based pharmacokinetic (PBPK) model of milademetan was subsequently developed to predict the magnitude of CYP3A-mediated DDI potential of milademetan with moderate CYP3A inhibitors. The PBPK model predicted an increase in milademetan exposure of 1.72-fold (90% CI, 1.69-1.76) with fluconazole, 1.91-fold (90% CI, 1.83-1.99) with erythromycin, and 2.02-fold (90% CI, 1.93-2.11) with verapamil. In addition, it estimated that milademetan's original dose (160 mg once daily) could be resumed from its half-reduced dose 3 days after discontinuation of concomitant strong CYP3A inhibitors. The established PBPK model of milademetan was qualified and considered to be robust enough to support continued development of milademetan.
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Project description:Drug repositioning aims to discover novel clinical benefits of existing drugs, is an effective way to develop drugs for complex diseases such as cancer and may facilitate the process of traditional drug development. Meanwhile, network-based computational biology approaches, which allow the integration of information from different aspects to understand the relationships between biomolecules, has been successfully applied to drug repurposing. In this work, we developed a new strategy for network-based drug repositioning against cancer. Combining the mechanism of action and clinical efficacy of the drugs, a cancer-related drug similarity network was constructed, and the correlation score of each drug with a specific cancer was quantified. The top 5% of scoring drugs were reviewed for stability and druggable potential to identify potential repositionable drugs. Of the 11 potentially repurposable drugs for non-small cell lung cancer (NSCLC), 10 were confirmed by clinical trial articles and databases. The targets of these drugs were significantly enriched in cancer-related pathways and significantly associated with the prognosis of NSCLC. In light of the successful application of our approach to colorectal cancer as well, it provides an effective clue and valuable perspective for drug repurposing in cancer.
| S-EPMC9917231 | biostudies-literature
Project description:Time-dependent inactivation (TDI) of cytochrome P450s (CYPs) is a leading cause of clinical drug-drug interactions (DDIs). Current methods tend to overpredict DDIs. In this study, a numerical approach was used to model complex CYP3A TDI in human-liver microsomes. The inhibitors evaluated included troleandomycin (TAO), erythromycin (ERY), verapamil (VER), and diltiazem (DTZ) along with the primary metabolites N-demethyl erythromycin (NDE), norverapamil (NV), and N-desmethyl diltiazem (NDD). The complexities incorporated into the models included multiple-binding kinetics, quasi-irreversible inactivation, sequential metabolism, inhibitor depletion, and membrane partitioning. The resulting inactivation parameters were incorporated into static in vitro-in vivo correlation (IVIVC) models to predict clinical DDIs. For 77 clinically observed DDIs, with a hepatic-CYP3A-synthesis-rate constant of 0.000?146 min-1, the average fold difference between the observed and predicted DDIs was 3.17 for the standard replot method and 1.45 for the numerical method. Similar results were obtained using a synthesis-rate constant of 0.000?32 min-1. These results suggest that numerical methods can successfully model complex in vitro TDI kinetics and that the resulting DDI predictions are more accurate than those obtained with the standard replot approach.
| S-EPMC5938745 | biostudies-literature
Project description:ObjectivesThe GUIDE-IT (Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure) study is designed to determine the safety, efficacy, and cost-effectiveness of a strategy of adjusting therapy with the goal of achieving and maintaining a target N-terminal pro-B-type natriuretic peptide (NT-proBNP) level of <1,000 pg/ml compared with usual care in high-risk patients with systolic heart failure (HF).BackgroundElevations in natriuretic peptide (NP) levels provide key prognostic information in patients with HF. Therapies proven to improve outcomes in patients with HF are generally associated with decreasing levels of NPs, and observational data show that decreases in NP levels over time are associated with favorable outcomes. Results from smaller prospective, randomized studies of this strategy thus far have been mixed, and current guidelines do not recommend serial measurement of NP levels to guide therapy in patients with HF.MethodsGUIDE-IT is a prospective, randomized, controlled, unblinded, multicenter clinical trial designed to randomize approximately 1,100 high-risk subjects with systolic HF (left ventricular ejection fraction ≤40%) to either usual care (optimized guideline-recommended therapy) or a strategy of adjusting therapy with the goal of achieving and maintaining a target NT-proBNP level of <1,000 pg/ml. Patients in either arm of the study are followed up at regular intervals and after treatment adjustments for a minimum of 12 months. The primary endpoint of the study is time to cardiovascular death or first hospitalization for HF. Secondary endpoints include time to cardiovascular death and all-cause mortality, cumulative mortality, health-related quality of life, resource use, cost-effectiveness, and safety.ConclusionsThe GUIDE-IT study is designed to definitively assess the effects of an NP-guided strategy in high-risk patients with systolic HF on clinically relevant endpoints of mortality, hospitalization, quality of life, and medical resource use. (Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure [GUIDE-IT]; NCT01685840).
| S-EPMC4194159 | biostudies-literature
Project description:The immunosuppressant and narrow therapeutic index drug tacrolimus is metabolized mainly via cytochrome P450 (CYP) 3A4 and CYP3A5. For its pharmacokinetics (PK), high inter- and intra-individual variability can be observed. Underlying causes include the effect of food intake on tacrolimus absorption as well as genetic polymorphism in the CYP3A5 gene. Furthermore, tacrolimus is highly susceptible to drug-drug interactions, acting as a victim drug when coadministered with CYP3A perpetrators. This work describes the development of a whole-body physiologically based pharmacokinetic model for tacrolimus as well as its application for investigation and prediction of (i) the impact of food intake on tacrolimus PK (food-drug interactions [FDIs]) and (ii) drug-drug(-gene) interactions (DD[G]Is) involving the CYP3A perpetrator drugs voriconazole, itraconazole, and rifampicin. The model was built in PK-Sim® Version 10 using a total of 37 whole blood concentration-time profiles of tacrolimus (training and test) compiled from 911 healthy individuals covering the administration of tacrolimus as intravenous infusions as well as immediate-release and extended-release capsules. Metabolism was incorporated via CYP3A4 and CYP3A5, with varying activities implemented for different CYP3A5 genotypes and study populations. The good predictive model performance is demonstrated for the examined food effect studies with 6/6 predicted FDI area under the curve determined between first and last concentration measurements (AUClast ) and 6/6 predicted FDI maximum whole blood concentration (Cmax ) ratios within twofold of the respective observed ratios. In addition, 7/7 predicted DD(G)I AUClast and 6/7 predicted DD(G)I Cmax ratios were within twofold of their observed values. Potential applications of the final model include model-informed drug discovery and development or the support of model-informed precision dosing.
| S-EPMC10196430 | biostudies-literature
Project description:BACKGROUND:Many men develop a rising PSA after initial therapy for prostate cancer. While some of these men will develop a local or metastatic recurrence that warrants further therapy, others will have no evidence of disease progression. We hypothesized that an expression biomarker panel can predict which men with a rising PSA would benefit from further therapy. METHODOLOGY/PRINCIPAL FINDINGS:A case-control design was used to test the association of gene expression with outcome. Systemic (SYS) progression cases were men post-prostatectomy who developed systemic progression within 5 years after PSA recurrence. PSA progression controls were matched men post-prostatectomy with PSA recurrence but no evidence of clinical progression within 5 years. Using expression arrays optimized for paraffin-embedded tissue RNA, 1021 cancer-related genes were evaluated-including 570 genes implicated in prostate cancer progression. Genes from 8 previously reported marker panels were included. A systemic progression model containing 17 genes was developed. This model generated an AUC of 0.88 (95% CI: 0.84-0.92). Similar AUCs were generated using 3 previously reported panels. In secondary analyses, the model predicted the endpoints of prostate cancer death (in SYS cases) and systemic progression beyond 5 years (in PSA controls) with hazard ratios 2.5 and 4.7, respectively (log-rank p-values of 0.0007 and 0.0005). Genes mapped to 8q24 were significantly enriched in the model. CONCLUSIONS/SIGNIFICANCE:Specific gene expression patterns are significantly associated with systemic progression after PSA recurrence. The measurement of gene expression pattern may be useful for determining which men may benefit from additional therapy after PSA recurrence.
| S-EPMC2565588 | biostudies-literature