Confirmation practice in pharmacogenetic testing; how good is good enough?

Personalised Therapeutic

Feasibility of pharmacy-initiated pharmacogenetic screening for CYP2D6 and CYP2C19

PURPOSE: Our purpose was to investigate the feasibility of pharmacy-initiated pharmacogenetic (PGt) screening in primary care with respect to patient willingness to participate, quality of DNA collection with saliva kits, genotyping, and dispensing data retrieved from the pharmacy. METHODS: Polypharmacy patients aged >60 years who used at least one drug with Anatomical Therapeutic Chemical (ATC) code N06AA01-N06AX19 (antidepressants), A02BC01-A02BC05 (proton-pump inhibitors), N05AA01-N05AH04 (antipsychotics), or C07AB02 (metoprolol) in the preceding 2 years were randomly selected. DNA was collected with saliva kits and genotyped for CYP2D6 and CYP2C19 with the AmpliChip. Pharmacy dispensing records were retrieved and screened for drugs interacting with the patient's CYP2D6 and CYP2C19 genotype by using the evidence-based PGt guidelines from the Dutch Pharmacogenetics Working Group. RESULTS: Out of the 93 invited patients, 54 (58.1%) provided informed consent. Nine saliva samples (16.7%) contained too little DNA. Call rates for CYP2D6 and CYP2C19 were 93.3% and 100%, respectively. Frequencies of genotype-predicted phenotype were 2.4%, 38.1%, 54.8%, and 4.8% for CYP2D6 poor metabolizers (PM), intermediate metabolizers (IM), extensive metabolizers (EM), and ultrarapid metabolizers (UM) respectively. For CYP2C19 genotype-predicted phenotype, frequencies were 2.2%, 15.6%, and 82.2% for PM, IM, and EM, respectively. CONCLUSIONS: This study shows that pharmacy-initiated PGt screening is feasible for a primary care setting

Pharmacogenetics of telatinib, a VEGFR-2 and VEGFR-3 tyrosine kinase inhibitor, used in patients with solid tumors

Purpose Telatinib is an orally active small-molecule tyrosine kinase inhibitor of kinase insert domain receptor (KDR; VEGFR-2) and fms-related tyrosine kinase 4 (FLT4; VEGFR-3). This study aims at the identification of relationships between single nucleotide polymorphisms (SNPs) in genes encoding for transporter proteins and pharmacokinetic parameters in order to clarify the significant interpatient variability in drug exposure. In addition, the potential relationship between target receptor polymorphisms and toxicity of telatinib is explored. Methods Blood samples from 33 patients enrolled in a phase I dose-escalation study of telatinib were analyzed. For correlation with dose normalized AUC(0–12), ATP-binding cassette (ABC) B1 (ABCB1), ABCC1, and ABCG2 were the genes selected. For correlation with telatinib toxicity, selected genes were the drug target genes KDR and FLT4. Results No association between dose normalized AUC(0–12) and drug transporter protein polymorphisms was observed. In addition, no association between toxicity and KDR or FLT4 genotype or haplotype was seen. Conclusions Our pharmacogenetic analysis could not reveal a correlation between relevant gene polymorphisms and clinical and pharmacokinetic observations of telatinib

Influence of pharmacogenetic variability on the pharmacokinetics and toxicity of the aurora kinase inhibitor danusertib

Objectives Danusertib is a serine/threonine kinase inhibitor of multiple kinases, including aurora-A, B, and C. This explorative study aims to identify possible relationships between single nucleotide polymorphisms in genes coding for drug metabolizing enzymes and transporter proteins and clearance of danusertib, to clarify the interpatient variability in exposure. In addition, this study explores the relationship between target receptor polymorphisms and toxicity of danusertib. Methods For associations with clearance, 48 cancer patients treated in a phase I study were analyzed for ABCB1, ABCG2 and FMO3 polymorphisms. Association analyses between neutropenia and drug target receptors, including KDR, RET, FLT3, FLT4, AURKB and AURKA, were performed in 30 patients treated at recommended phase II dose-levels in three danusertib phase I or phase II trials. Results No relationships between danusertib clearance and drug metabolizing enzymes and transporter protein polymorphisms were found. Only, for the one patient with FMO3 18281AA polymorphism, a significantly higher clearance was noticed, compared to patients carrying at least 1 wild type allele. No effect of target receptor genotypes or haplotypes on neutropenia was observed. Conclusions As we did not find any major correlations between pharmacogenetic variability in the studied enzymes and transporters and pharmacokinetics nor toxicity, it is unlikely that danusertib is highly susceptible for pharmacogenetic variation. Therefore, no dosing alterations of danusertib are expected in the future, based on the polymorphisms studied. However, the relationship between FMO3 polymorphisms and clearance of danusertib warrants further research, as we could study only a small group of patients

Determinants of Functional Coupling between Astrocytes and Respiratory Neurons in the Pre-Bötzinger Complex

Respiratory neuronal network activity is thought to require efficient functioning of astrocytes. Here, we analyzed neuron-astrocyte communication in the pre-Bötzinger Complex (preBötC) of rhythmic slice preparations from neonatal mice. In astrocytes that exhibited rhythmic potassium fluxes and glutamate transporter currents, we did not find a translation of respiratory neuronal activity into phase-locked astroglial calcium signals. In up to 20% of astrocytes, 2-photon calcium imaging revealed spontaneous calcium fluctuations, although with no correlation to neuronal activity. Calcium signals could be elicited in preBötC astrocytes by metabotropic glutamate receptor activation or after inhibition of glial glutamate uptake. In the latter case, astrocyte calcium elevation preceded a surge of respiratory neuron discharge activity followed by network failure. We conclude that astrocytes do not exhibit respiratory-rhythmic calcium fluctuations when they are able to prevent synaptic glutamate accumulation. Calcium signaling is, however, observed when glutamate transport processes in astrocytes are suppressed or neuronal discharge activity is excessive

Using Expression and Genotype to Predict Drug Response in Yeast

Personalized, or genomic, medicine entails tailoring pharmacological therapies according to individual genetic variation at genomic loci encoding proteins in drug-response pathways. It has been previously shown that steady-state mRNA expression can be used to predict the drug response (i.e., sensitivity or resistance) of non-genotyped mammalian cancer cell lines to chemotherapeutic agents. In a real-world setting, clinicians would have access to both steady-state expression levels of patient tissue(s) and a patient's genotypic profile, and yet the predictive power of transcripts versus markers is not well understood. We have previously shown that a collection of genotyped and expression-profiled yeast strains can provide a model for personalized medicine. Here we compare the predictive power of 6,229 steady-state mRNA transcript levels and 2,894 genotyped markers using a pattern recognition algorithm. We were able to predict with over 70% accuracy the drug sensitivity of 104 individual genotyped yeast strains derived from a cross between a laboratory strain and a wild isolate. We observe that, independently of drug mechanism of action, both transcripts and markers can accurately predict drug response. Marker-based prediction is usually more accurate than transcript-based prediction, likely reflecting the genetic determination of gene expression in this cross

Gene expression biomarkers of response to citalopram treatment in major depressive disorder

There is significant variability in antidepressant treatment outcome, with ∼30–40% of patients with major depressive disorder (MDD) not presenting with adequate response even following several trials. To identify potential biomarkers of response, we investigated peripheral gene expression patterns of response to antidepressant treatment in MDD. We did this using Affymetrix HG-U133 Plus2 microarrays in blood samples, from untreated individuals with MDD (N=63) ascertained at a community outpatient clinic, pre and post 8-week treatment with citalopram, and used a regression model to assess the impact of gene expression differences on antidepressant response. We carried out technical validation of significant probesets by quantitative reverse transcriptase PCR and conducted central nervous system follow-up of the most significant result in post-mortem brain samples from 15 subjects who died during a current MDD episode and 11 sudden-death controls. A total of 32 probesets were differentially expressed according to response to citalopram treatment following false discovery rate correction. Interferon regulatory factor 7 (IRF7) was the most significant differentially expressed gene and its expression was upregulated by citalopram treatment in individuals who responded to treatment. We found these results to be concordant with our observation of decreased expression of IRF7 in the prefrontal cortex of MDDs with negative toxicological evidence for antidepressant treatment at the time of death. These findings point to IRF7 as a gene of interest in studies investigating genomic factors associated with antidepressant response