Profiling of drug-metabolizing enzymes/transporters in CD33+ acute myeloid leukemia patients treated with Gemtuzumab-Ozogamicin and Fludarabine, Cytarabine and Idarubicin

Effect of NAT2, GSTM1 and CYP2E1 genetic polymorphisms on plasma concentration of isoniazid and its metabolites in patients with tuberculosis, and the assessment of exposure-response relationships

Objectives: Isoniazid is a key drug in the chemotherapy of tuberculosis (TB), however, interindividual variability in pharmacokinetic parameters and drug plasma levels may affect drug responses including drug induced hepatotoxicity. The current study investigated the relationships between isoniazid exposure and isoniazid metabolism-related genetic factors in the context of occurrence of drug induced hepatotoxicity and TB treatment outcomes. Methods: Demographic characteristics and clinical information were collected in a prospective TB cohort study in Latvia (N = 34). Time to sputum culture conversion (tSCC) was used as a treatment response marker. Blood plasma concentrations of isoniazid (INH) and its metabolites acetylisoniazid (AcINH) and isonicotinic acid (INA) were determined at three time points (pre-dose (0 h), 2 h and 6 h after drug intake) using liquid chromatography-tandem mass spectrometry. Genetic variations of three key INH-metabolizing enzymes (NAT2, CYP2E1, and GSTM1) were investigated by application PCR- and Next-generation sequencing-based methods. Depending on variables, group comparisons were performed by Student's t-test, one-way ANOVA, Mann-Whitney-Wilcoxon, and Kruskal-Wallis tests. Pearson correlation coefficient was calculated for the pairs of normally distributed variables; model with rank transformations were used for non-normally distributed variables. Time-to-event analysis was performed to analyze the tSCC data. The cumulative probability of tSCC was obtained using Kaplan-Meier estimators. Cox proportional hazards models were fitted to estimate hazard rate ratios of successful tSCC. Results: High TB treatment success rate (94.1%) was achieved despite the variability in INH exposure. Clinical and demographic factors were not associated with either tSCC, hepatotoxicity, or INH pharmacokinetics parameters. Correlations between plasma concentrations of INH and its metabolites were NAT2 phenotype-dependent, while GSTM1 genetic variants did not showed any effects. CYP2E1*6 (T > A) allelic variant was associated with INH pharmacokinetic parameters. Decreased level of AcINH was associated with hepatotoxicity, while decreased values of INA/INH and AcINH/INH were associated with month two sputum culture positivity. Conclusion: Our findings suggest that CYP2E1, but not GSTM1, significantly affects the INH pharmacokinetics along with NAT2. AcINH plasma level could serve as a biomarker for INH-related hepatotoxicity, and the inclusion of INH metabolite screening in TB therapeutic drug monitoring could be beneficial in clinical studies for determination of optimal dosing strategies.

Role of Drug Transporters in Elucidating Inter-Individual Variability in Pediatric Chemotherapy-Related Toxicities and Response

Pediatric cancer treatment has evolved significantly in recent decades. The implementation of risk stratification strategies and the selection of evidence-based chemotherapy combinations have improved survival outcomes. However, there is large interindividual variability in terms of chemotherapy-related toxicities and, sometimes, the response among this population. This variability is partly attributed to the functional variability of drug-metabolizing enzymes (DME) and drug transporters (DTS) involved in the process of absorption, distribution, metabolism and excretion (ADME). The DTS, being ubiquitous, affects drug disposition across membranes and has relevance in determining chemotherapy response in pediatric cancer patients. Among the factors affecting DTS function, ontogeny or maturation is important in the pediatric population. In this narrative review, we describe the role of drug uptake/efflux transporters in defining pediatric chemotherapy-treatment-related toxicities and responses. Developmental differences in DTS and the consequent implications are also briefly discussed for the most commonly used chemotherapeutic drugs in the pediatric population.

Systematic Review of Pharmacogenetics of ABC and SLC Transporter Genes in Acute Myeloid Leukemia

Antineoplastic uptake by blast cells in acute myeloid leukemia (AML) could be influenced by influx and efflux transporters, especially solute carriers (SLCs) and ATP-binding cassette family (ABC) pumps. Genetic variability in SLC and ABC could produce interindividual differences in clinical outcomes. A systematic review was performed to evaluate the influence of SLC and ABC polymorphisms and their combinations on efficacy and safety in AML cohorts. Anthracycline intake was especially influenced by SLCO1B1 polymorphisms, associated with lower hepatic uptake, showing higher survival rates and toxicity in AML studies. The variant alleles of ABCB1 were related to anthracycline intracellular accumulation, increasing complete remission, survival and toxicity. Similar findings have been suggested with ABCC1 and ABCG2 polymorphisms. Polymorphisms of SLC29A1, responsible for cytarabine uptake, demonstrated significant associations with survival and response in Asian populations. Promising results were observed with SLC and ABC combinations regarding anthracycline toxicities. Knowledge of the role of transporter pharmacogenetics could explain the differences observed in drug disposition in the blast. Further studies including novel targeted therapies should be performed to determine the influence of genetic variability to individualize chemotherapy schemes.

Role of Pharmacogenetics in the Treatment of Acute Myeloid Leukemia: Systematic Review and Future Perspectives

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by remarkable toxicity and great variability in response to treatment. Plenteous pharmacogenetic studies have already been published for classical therapies, such as cytarabine or anthracyclines, but such studies remain scarce for newer drugs. There is evidence of the relevance of polymorphisms in response to treatment, although most studies have limitations in terms of cohort size or standardization of results. The different responses associated with genetic variability include both increased drug efficacy and toxicity and decreased response or resistance to treatment. A broad pharmacogenetic understanding may be useful in the design of dosing strategies and treatment guidelines. The aim of this study is to perform a review of the available publications and evidence related to the pharmacogenetics of AML, compiling those studies that may be useful in optimizing drug administration.

Impact of combinations of single-nucleotide polymorphisms of anthracycline transporter genes upon the efficacy and toxicity of induction chemotherapy in acute myeloid leukemia

Anthracycline uptake could be affected by influx and efflux transporters in acute myeloid leukemia (AML). Combinations of single-nucleotide polymorphisms (SNPs) of wild-type genotype of influx transporters (SLC22A16, SLCO1B1) and homozygous variant genotypes of ABC polymorphisms (ABCB1, ABCC1, ABCC2, ABCG2) were evaluated in 225 adult de novo AML patients. No differences in complete remission were reported, but higher induction death was observed with combinations of SLCO1B1 rs4149056 and ABCB1 (triple variant haplotype, rs1128503), previously associated with ABCB1 and SLCO1B1 SNPs. Several combinations of SLCO1B1 and SLC22A16 with ABCB1 SNPs were associated with higher toxicities, including nephrotoxicity and hepatotoxicity, neutropenia, previously related to ABCB1, and a novel correlation with mucositis. Combination of SLC22A16 rs714368 and ABCG2 rs2231142 was related to cardiac toxicity, reproducing previous correlations with ABCG2. This study shows the impact of transporter polymorphisms in AML chemotherapy safety. Further prospective studies with larger populations are needed to validate these associations.

Precision medicine in acute myeloid leukemia: where are we now and what does the future hold?

INTRODUCTION

Precision medicine has revolutionized the diagnostic and therapeutic management of acute myeloid leukemia (AML), from standardized schemes based on chemotherapy to tailored approaches according to molecular and genetic profile and targeted therapy.

AREAS COVERED

The main topics of precision medicine in AML were reviewed in MEDLINE, EMBASE, and Cochrane Central Register databases, and future directions in this therapeutic area were addressed. This review included targeted therapies, drug-sensitivity tests and predictive biomarkers, and genetic studies employing pharmacogenetic and deep sequencing strategies.

EXPERT OPINION

Precision medicine has opened the door to personalized therapy for specific AML patient populations with promising results. Several targeted therapies have been approved or are being tested for specific mutations (i.e. FLT3, IDH, BCL-2, TP53), obtaining improvements in clinical outcomes and less toxicity as compared with intensive treatment, allowing potential combination therapy. Ongoing trials and real data will establish the role of these molecules in monotherapy or combined in different AML settings (front-line, relapsed/refractory, or post-transplant). Experience in drug-sensitivity predictors and pharmacogenetic biomarkers is encouraging and could be useful tools in the next years, but we need a better understanding of AML biology and pathogenesis as well as confirmatory studies to demonstrate the utility in clinical practice.

Whole genome sequencing identifies high-impact variants in well-known pharmacogenomic genes

More than 1100 genetic loci have been correlated with drug response outcomes but disproportionately few have been translated into clinical practice. One explanation for the low rate of clinical implementation is that the majority of associated variants may be in linkage disequilibrium (LD) with the causal variants, which are often elusive. This study aims to identify and characterize likely causal variants within well-established pharmacogenomic genes using next-generation sequencing data from the 1000 Genomes Project. We identified 69,319 genetic variations within 160 pharmacogenomic genes, of which 8207 variants are in strong LD (r2>0.8) with known pharmacogenomic variants. Of the latter, eight are coding or structural variants predicted to have high impact, with 19 additional missense variants that are predicted to have moderate impact. In conclusion, we identified putatively functional variants within known pharmacogenomics loci that could account for the association signals and represent the missing causative variants underlying drug response phenotypes.

DMET™ (Drug Metabolism Enzymes and Transporters): a pharmacogenomic platform for precision medicine

In the era of personalized medicine, high-throughput technologies have allowed the investigation of genetic variations underlying the inter-individual variability in drug pharmacokinetics/pharmacodynamics. Several studies have recently moved from a candidate gene-based pharmacogenetic approach to genome-wide pharmacogenomic analyses to identify biomarkers for selection of patient-tailored therapies. In this aim, the identification of genetic variants affecting the individual drug metabolism is relevant for the definition of more active and less toxic treatments. This review focuses on the potentiality, reliability and limitations of the DMET™ (Drug Metabolism Enzymes and Transporters) Plus as pharmacogenomic drug metabolism multi-gene panel platform for selecting biomarkers in the final aim to optimize drugs use and characterize the individual genetic background.

A 29-gene and cytogenetic score for the prediction of resistance to induction treatment in acute myeloid leukemia

Primary therapy resistance is a major problem in acute myeloid leukemia treatment. We set out to develop a powerful and robust predictor for therapy resistance for intensively treated adult patients. We used two large gene expression data sets (n=856) to develop a predictor of therapy resistance, which was validated in an independent cohort analyzed by RNA sequencing (n=250). In addition to gene expression markers, standard clinical and laboratory variables as well as the mutation status of 68 genes were considered during construction of the model. The final predictor (PS29MRC) consisted of 29 gene expression markers and a cytogenetic risk classification. A continuous predictor is calculated as a weighted linear sum of the individual variables. In addition, a cut off was defined to divide patients into a high-risk and a low-risk group for resistant disease. PS29MRC was highly significant in the validation set, both as a continuous score (OR=2.39, P=8.63·10⁻⁹, AUC=0.76) and as a dichotomous classifier (OR=8.03, P=4.29·10⁻⁹); accuracy was 77%. In multivariable models, only TP53 mutation, age and PS29MRC (continuous: OR=1.75, P=0.0011; dichotomous: OR=4.44, P=0.00021) were left as significant variables. PS29MRC dominated all models when compared with currently used predictors, and also predicted overall survival independently of established markers. When integrated into the European LeukemiaNet (ELN) 2017 genetic risk stratification, four groups (median survival of 8, 18, 41 months, and not reached) could be defined (P=4.01·10⁻¹⁰). PS29MRC will make it possible to design trials which stratify induction treatment according to the probability of response, and refines the ELN 2017 classification.

Association between prolonged neutropenia and reduced relapse risk in pediatric AML: A report from the children's oncology group

Objective was to describe the relationship between the number of sterile site infections and duration of neutropenia during the first four cycles of chemotherapy and the risk of recurrence and overall survival in children with newly diagnosed acute myeloid leukemia (AML). AAML0531 was a Children's Oncology Group randomized phase 3 clinical trial that included 1022 children with de novo AML. For this analysis, we focused on non-Down syndrome favorable and standard risk patients who completed at least 4 cycles of chemotherapy without recurrence or withdrawal during protocol therapy. Those receiving hematopoietic stem cell transplantation in first remission were excluded. Five hundred and sixty-nine patients were included; 274 (48.2%) were favorable risk. The median cumulative time with neutropenia between Induction II to completion of Intensification II was 96 (range 54-204) days. Number of sterile site infections did not influence the risk of relapse or overall survival. However, longer duration of neutropenia was associated with a lower risk of relapse (hazard ratio 0.81 per 20 days neutropenia, p = 0.007). Longer duration of neutropenia was associated with a reduced risk of relapse for children with favorable and standard risk AML. Toxicity may be influenced by pharmacogenomics suggesting that individualized chemotherapy dosing may be an effective strategy.

Pharmacogenomics and the treatment of acute myeloid leukemia

Acute myeloid leukemia (AML) is a clinically and biologically heterogeneous malignancy that is primarily treated with combinations of cytarabine and anthracyclines. Although this scheme remains effective in most of the patients, variability of outcomes in patients has been partly related with their genetic variability. Several pharmacogenetic studies have analyzed the impact of polymorphisms in genes encoding transporters, metabolizers or molecular targets of chemotherapy agents. A systematic review on all eligible studies was carried out in order to estimate the effect of polymorphisms of anthracyclines and cytarabine pathways on efficacy and toxicity of AML treatment. Other emerging genes recently studied in AML, such as DNA repair genes, genes potentially related to chemotherapy response or AML prognosis, have also been included.

Single Nucleotide Polymorphisms as Genomic Markers for High-Throughput Pharmacogenomic Studies

Genetic variations in patients have strong impact on their drug therapies and responses because the variations may contribute to the efficacy and/or produce undesirable side effects for any given drug. The Drug Metabolizing Enzymes and Transporters (DMET) assay is a high-throughput technology by Affymetrix that is able to simultaneously genotype variants in multiple genes involved in absorption, distribution, metabolism, and excretion of drugs for subsequent clinical applications, i.e., the assay allows for a precise genetic map that can guide therapeutic interventions and avoid side effects.

The organic anion transporter (OAT) family: a systems biology perspective

The organic anion transporter (OAT) subfamily, which constitutes roughly half of the SLC22 (solute carrier 22) transporter family, has received a great deal of attention because of its role in handling of common drugs (antibiotics, antivirals, diuretics, nonsteroidal anti-inflammatory drugs), toxins (mercury, aristolochic acid), and nutrients (vitamins, flavonoids). Oats are expressed in many tissues, including kidney, liver, choroid plexus, olfactory mucosa, brain, retina, and placenta. Recent metabolomics and microarray data from Oat1 [Slc22a6, originally identified as NKT (novel kidney transporter)] and Oat3 (Slc22a8) knockouts, as well as systems biology studies, indicate that this pathway plays a central role in the metabolism and handling of gut microbiome metabolites as well as putative uremic toxins of kidney disease. Nuclear receptors and other transcription factors, such as Hnf4α and Hnf1α, appear to regulate the expression of certain Oats in conjunction with phase I and phase II drug metabolizing enzymes. Some Oats have a strong selectivity for particular signaling molecules, including cyclic nucleotides, conjugated sex steroids, odorants, uric acid, and prostaglandins and/or their metabolites. According to the "Remote Sensing and Signaling Hypothesis," which is elaborated in detail here, Oats may function in remote interorgan communication by regulating levels of signaling molecules and key metabolites in tissues and body fluids. Oats may also play a major role in interorganismal communication (via movement of small molecules across the intestine, placental barrier, into breast milk, and volatile odorants into the urine). The role of various Oat isoforms in systems physiology appears quite complex, and their ramifications are discussed in the context of remote sensing and signaling.

Genetic heterogeneity beyond CYP2C8*3 does not explain differential sensitivity to paclitaxel-induced neuropathy

The development of paclitaxel-induced peripheral neuropathy (PIPN) is influenced by drug exposure and patient genetics. The purpose of this analysis was to expand on a previous reported association of CYP2C8*3 and PIPN risk by investigating additional polymorphisms in CYP2C8 and in hundreds of other genes potentially relevant to paclitaxel pharmacokinetics. Clinical data was collected prospectively in an observational registry of newly diagnosed breast cancer patients. Patients treated with paclitaxel-containing regimens were genotyped using the Affymetrix DMET™ Plus chip. Patients who carried the CYP2C8*2, *3, or *4 variant were collapsed into a low-metabolizer CYP2C8 phenotype for association with PIPN. Separately, all SNPs that surpassed quality control were assessed individually and as a composite of genetic ancestry for associations with PIPN. 412 paclitaxel-treated patients and 564 genetic markers were included in the analysis. The risk of PIPN was significantly greater in the CYP2C8 low-metabolizer group (HR = 1.722, p = 0.018); however, the influences of the *2 and *4 SNPs were not independently significant (*2: p = 0.847, *4: p = 0.408). One intronic SNP in ABCG1 (rs492338) surpassed the exploratory significance threshold for an association with PIPN in the Caucasian cohort (p = 0.0008) but not in the non-Caucasian replication group (p = 0.54). Substantial genetic variability was observed within self-reported racial groups but this genetic variability was not associated with risk of grade 2+ PIPN. The pharmacogenetic heterogeneity within a cohort of breast cancer patients is dramatic, though we did not find evidence that this heterogeneity directly influences the risk of PIPN beyond the contribution of CYP2C8*3.

Impact of polymorphisms in drug pathway genes on disease-free survival in adults with acute myeloid leukemia

Acute myeloid leukemia (AML) is a clinically heterogeneous disease, with 5-year disease-free survival (DFS) ranging from under 10% to over 70% for distinct groups of patients. At our institution, cytarabine, etoposide and busulfan are used in first or second remission patients treated with a 2-step approach to autologous stem cell transplantation (ASCT). In this study, we tested the hypothesis that polymorphisms in the pharmacokinetic and pharmacodynamic pathway genes of these drugs are associated with DFS in AML patients. A total of 1659 variants in 42 genes were analyzed for their association with DFS using a Cox proportional hazards model. 154 genetically European patients were used for the primary analysis. An intronic SNP in ABCC3 (rs4148405) was associated with a significantly shorter DFS (HR=3.2, p=5.6 x 10(-6)) in our primary cohort. In addition a SNP in the GSTM1-GSTM5 locus, rs3754446, was significantly associated with a shorter DFS in all patients (HR=1.8, p=0.001 for 154 European ancestry; HR=1.7, p=0.028 for 125 non-European patients). Thus for the first time, genetic variants in drug pathway genes are shown to be associated with DFS in AML patients treated with chemotherapy-based autologous ASCT.

Imputation reliability on DNA biallelic markers for drug metabolism studies

BACKGROUND

Imputation is a statistical process used to predict genotypes of loci not directly assayed in a sample of individuals. Our goal is to measure the performance of imputation in predicting the genotype of the best known gene polymorphisms involved in drug metabolism using a common SNP array genotyping platform generally exploited in genome wide association studies.

METHODS

Thirty-nine (39) individuals were genotyped with both Affymetrix Genome Wide Human SNP 6.0 (AFFY) and Affymetrix DMET Plus (DMET) platforms. AFFY and DMET contain nearly 900000 and 1931 markers respectively. We used a 1000 Genomes Pilot + HapMap 3 reference panel. Imputation was performed using the computer program Impute, version 2. SNPs contained in DMET, but not imputed, were analysed studying markers around their chromosome regions. The efficacy of the imputation was measured evaluating the number of successfully imputed SNPs (SSNPs).

RESULTS

The imputation predicted the genotypes of 654 SNPs not present in the AFFY array, but contained in the DMET array. Approximately 1000 SNPs were not annotated in the reference panel and therefore they could not be directly imputed. After testing three different imputed genotype calling threshold (IGCT), we observed that imputation performs at its best for IGCT value equal to 50%, with rate of SSNPs (MAF > 0.05) equal to 85%.

CONCLUSIONS

Most of the genes involved in drug metabolism can be imputed with high efficacy using standard genome-wide genotyping platforms and imputing procedures.