Genetic determinants of drug responsiveness and drug interactions

Analyzing Tumor Heterogeneity by Incorporating Long-Range Mutational Influences and Multiple Sample Data into Heterogeneity Factorial Hidden Markov Model

Cancer arises from successive rounds of mutations, resulting in tumor cells with different somatic mutations known as clones. Drug responsiveness and therapeutics of cancer depend on the accurate detection of the clones in a tumor sample. Recent research has considered inferring clonal composition of a tumor sample using computational models based on the short read data of the sample generated using the next-generation sequencing (NGS) technology. Short reads (segmented DNA parts of different tumor cells) are noisy; therefore, inferring the clones and their mutations from the data is a difficult and complex problem. Existing methods to infer clones from noisy NGS data do not consider the presence of long-range mutational influences. Therefore, we develop a new model, called extended multiple sample tumor heterogeneity prediction by factorial Hidden Markov model (emHetFHMM), based on factorial hidden Markov models to infer clones and their proportions by capturing the long-range mutational influences. In our model, each hidden chain represents the genomic signature of a clone, and a mixture of chains results in the observed data. We make use of Gibbs sampling and exponentiated gradient algorithms to infer the hidden variables and mixing proportions. We compare our model with strong models from the previous work (PyClone, PhyloSub, and HetFHMM) based on both synthetic data and real cancer data from acute myeloid leukemia. Empirical results confirm that emHetFHMM infers clonal composition of a tumor sample more accurately than previous studies.

HetFHMM: A Novel Approach to Infer Tumor Heterogeneity Using Factorial Hidden Markov Models

Cancer arises from successive rounds of mutations, resulting in tumor cells with different somatic mutations known as clones. Drug responsiveness and therapeutics of cancer depend on the accurate detection of clones in a tumor sample. Recent research has considered inferring clonal composition of a tumor sample using computational models based on short read data of the sample generated using next-generation sequencing (NGS) technology. Short reads (segmented DNA parts of different tumor cells) are noisy; therefore, inferring the clones and their mutations from the data is a difficult and complex problem. We develop a new model called HetFHMM, based on factorial hidden Markov models, to infer clones and their proportions from noisy NGS data. In our model, each hidden chain represents the genomic signature of a clone, and a mixture of chains results in the observed data. We make use of Gibbs sampling and exponentiated gradient algorithms to infer the hidden variables and mixing proportions. We compare our model with strong models from previous work (PyClone and PhyloSub) based on both synthetic data and real cancer data on acute myeloid leukemia. Empirical results confirm that HetFHMM infers clonal composition of a tumor sample more accurately than previous work.

Pharmacogenetics of oral anticoagulants

The use of oral anticoagulants (OA) is problematic due to its association with hemorrhagic complications. OA metabolism relies on the CYP2C9 complex. Genetic variations compromising metabolic competence of this complex may explain the risk of excessive and hazardous anticoagulation. A pharmacogenetics-based approach to this issue could be beneficial for choosing adequate dose and duration of treatment, in addition to having a better understanding of pharmacological interactions to which OA are susceptible. However, evidence from several basic and clinical studies indicates that both a complicated system of regulation of expression of multiple genes and the influence of a wide variety of epigenetic factors could be responsible for adverse drug reactions associated with the use of OA. Emphasis on understanding the gene-environment interactions could attain new paths to facilitate the use of these important drugs in the quotidian clinical practice.

Study of urinary 6β-hydroxycortisol/cortisol ratio in spot urine sample as a biomarker of 3A4 enzyme activity in healthy and epileptic subjects of Egyptian population

The ratio of urinary 6 beta-hydroxycortisol/cortisol (6 beta-OHC/FC) in morning spot urine samples collected from 8:00 a.m. to 12:00 p.m. was studied using ELIZA kits (Stabiligen) in a group of healthy adult Egyptians (control group) of both sex (n=65, age range: 16-48 years). The frequency distribution of urinary 6 beta-OHC/FC ratio was widely distributed among subjects with higher values in males in comparison to females. No bimodality in either sex was observed. Another group of adult epileptic patients (n=16) was studied for the influence of chronic carbamazepine antiepileptic drug administration on urinary 6 beta-OHC/FC ratio in spot urine samples. The induction property of carbamazepine on CYP3A4 was observed through significant increase (p=0.01) in 6 beta-OHC/FC ratio among epileptic patients in comparison with control subjects. In conclusion, the frequency distribution of urinary 6 beta-OHC/FC ratio among Egyptians shows sexual dimorphism. Also, measurement of urinary 6 beta-OHC/FC ratio provides a simple non-invasive method to monitor CYP3A4 enzyme induction during administration of carbamazepine antiepileptic drug.

[Antihypertensive drug-drug interactions]

A drug interaction is the quantitative or qualitative modification of the effect of a drug by the simultaneous or successive administration of a different one. Hypertensive patients, mainly the more elderly ones, frequently present concomitant diseases that require the administration of several medicines which facilitates the appearance of interactions. The lack of effectiveness of the antihypertensive treatment is a relatively frequent fact that sometimes is due to interactions of antihypertensive drugs with other treatments. It is difficult to determine the incidence of interactions, but it is related to the number of drugs administered simultaneously. Between 37 and 60% of hospital-admissions are treated with potentially dangerous drug associations and up to a 6% of fatal events are due to this circumstance. Among antihypertensive drugs, diuretics and angiotensin converting enzyme inhibitors are less affected by drug-interactions. Lipophilic beta-blockers agents may present some clinical relevant interactions, whereas calcium channel blockers, especially the non-dihydropiridinic ones, are implied in clinically relevant pharmacokinetic interactions. Among the angiotensin receptor blockers there are differences that would have to be considered when they are used in patients who receive other drugs. Although it is impossible for the doctor to remember all the clinical relevant interactions, it is important to bear in mind their existence and the possible mechanisms of production which can help to identify them and to contribute to their prevention. The most frequent interactions related with clinical problems are the pharmacokinetic ones, mainly those related to the metabolism through the cytochrome P450 system or the presystemic clearance by means of the P-glycoprotein. Enzymes of the cytochrome P450 system may present polymorphisms that can explain the individual differences in the response to drugs or the appearance of drug-interactions.

Psychotropic drug interactions with valproate

Valproate is a well-established anticonvulsant that is increasingly being employed, often in combination with other psychotropics, for its mood-stabilizing properties. This compound is metabolized by conjugation, beta-oxidation, and cytochrome P450 oxidation (CYP2C9, CYP2C19, and CYP2A6) and also acts as a broad-spectrum inhibitor of a variety of hepatic enzymes including glucoronyltransferase, epoxide hydrolase, and the CYP2C enzymes. In addition, it exhibits saturable protein binding and competes with many drugs for protein binding sites. It is therefore not surprising that valproate has been noted to interact with psychotropic medications of all classes. This article provides an overview of the noted pharmacokinetic psychotropic interactions with valproate, with a particular focus on the mechanisms of these interactions and potential clinical consequences.

Oral antifungal drug interactions: a mechanistic approach to understanding their cause

Oral antifungal drugs are generally regarded as effective and safe when used according to their manufacturer's recommendation. However, when an oral antifungal agent is administered with certain interacting agents or classes of drugs, rare severe iatrogenic adverse experiences including death may occur. This article alerts and demystifies some of the clinically significant oral antifungal drug interactions by exploring their underlying pharmacological basis.

What is next in pharmacogenomics? Translating it to clinical practice

Pharmacogenomics (PG) holds promise for transforming medical therapeutics but the details of how the promise will become reality are still vague. In this article, we focus on the role that laboratory medicine, as a discipline, might play in transitioning the application of pharmacogenomics into the healthcare system and begin to frame a perspective on how PG may be viewed in this context. Development of clinical diagnostic tests usually evolves as a continuum of information starting with the discovery of a potential biological marker through to its routine use in clinical practice. This process has traditionally been rooted in the practice of laboratory medicine and, importantly, includes the development of testing strategies to optimize the predictive value of single or a combination of biological markers. In this context, we also discuss a perspective on some future strategies that may prove useful in advancing the application of PG, including the need for an evidenced-based approach and the potential role of proteomics as a means to drive more comprehensive strategies.

Pharmacogenetics for the individualization of psychiatric treatment

Drug treatment of psychiatric disorders is troubled by severe adverse effects, low compliance and lack of efficacy in about 30% of patients. Pharmacogenetic research in psychiatry aims to elucidate the reasons for treatment failure and adverse reactions. Genetic variations in cytochrome P450 (CYP) enzymes have the potential to directly influence the efficacy and tolerability of commonly used antipsychotic and antidepressant drugs. The activity of psychiatric drugs can also be influenced by genetic alterations affecting the drug target molecule. These include the dopaminergic and serotonergic receptors, neurotransmitter transporters and other receptors and enzymes involved in psychiatric disorders. Association studies investigating the relation between genetic polymorphisms in metabolic enzymes and neurotransmitter receptors on psychiatric treatment outcome provide a step towards the individualization of psychiatric treatment through enabling the selection of the most beneficial drug according to the individual's genetic background.

Genetic polymorphism in exon 4 of cytochrome P450 CYP2C9 may be associated with warfarin sensitivity in Chinese patients

CYP2C9 polymorphisms reported in Caucasians (Arg144Cys in exon 3 and Ile359Leu in exon 7) are extremely uncommon in Chinese persons. The genotype of CYP2C9 in this population was characterized to investigate its relation with the interindividual variation in warfarin dosages. Eighty-nine Chinese patients receiving warfarin were recruited. Target sequences in CYP2C9 in exons 1, 4, and 5 were amplified by polymerase chain reaction, followed by direct sequencing. Polymorphisms at 4 positions were demonstrated in exon 4. Heterozygosities for 608TTG>GTG (Leu208Val), 561CAG>CCG (Gln192Pro), 537CAT>CCT (His184Pro), and 527ATT>CTT (Ile181Leu) existed at frequencies 0.75, 0.20, 0.10, and 0.09, respectively. Seventeen patients (frequency, 0.19) were homozygous for Val208. The common genotypic combinations at these loci are Ile181/His184/Gln192/Leu208Val (n = 50), Ile181/His184/Gln192/Val208 (n = 15), Ile181/His184/Gln192/Leu208 (n = 4), Ile181/His184/Gln192Pro/Leu208Val (n = 6), Ile181/His184Pro/Gln192Pro/Leu208Val (n = 4), and Ile181Leu/His184/Gln192Pro/ Leu208Val (n = 4). At codon 208, heterozygous Leu208Val and homozygous Val208 appeared to have a lower warfarin dose requirement than the homozygous Leu208. Patients who are heterozygous for Ile181Leu had a higher warfarin dose requirement than the homozygous Ile181. Amplified sequences in exons 1 and 5 did not exhibit polymorphism. In conclusion, Chinese patients showed genetic polymorphisms of CYP2C9 in exon 4 and at codon 208; most were heterozygous Leu208Val and homozygous Val208. Homozygous Leu208, a common allele in Caucasians, is uncommon in this cohort. The significance of these CYP2C9 polymorphic alleles remains to be determined.

Herb-drug interactions: focus on pharmacokinetics

Recent literature regarding drug-drug, herb-drug, and food-drug interactions must not be ignored; nor can they always be taken at face value. Studies have shown that St. John's wort (SJW) (Hypericum perforatum) can reduce plasma levels of indinavir, cyclosporin, digoxin, and possibly other drugs as well. Current knowledge regarding the metabolism of these medications suggests that the cytochrome P450 (CYP) drug metabolizing enzyme systems cannot account for all these effects. It has been reported that the P-glycoprotein (Pgp) transmembrane pump is also induced by SJW. Medications that are substrates of both CYP 3A4 and Pgp are of particular concern and may pose special interaction risks when combined with certain foods or botanical products such as SJW.

Extreme discordant phenotype methodology: an intuitive approach to clinical pharmacogenetics

Pharmacogenetics represents "the study of variability in drug response due to heredity". Of the more than six dozen pharmacogenetic differences described in the medical literature, the majority of these variations occurs in drug-metabolizing enzyme genes and others in drug receptor and drug transporter genes, whereas many others have not yet been explained on a molecular basis. It is clear that "drug efficacy" or "drug toxicity" represents a multiplex phenotype, i.e. interaction between the drug (or its metabolites) and the gene products (enzymes, receptors, other targets) of two, and usually many more than two, genes. Because there is a gradient in these phenotypes (efficacy or toxicity), it is extremely important to select patients having the most unequivocal phenotype possible-if one wishes to find the gene(s) responsible for the trait. The method of "extreme discordant phenotype" (EDP) is therefore highly recommended. Using EDP methodology, DNA sequence variants (genotype) can be unconditionally correlated with drug efficacy or toxicity (phenotype). EDP methodology is mathematically intuitive and, in essence, has been used in a number of previous clinical pharmacogenetic studies. This EDP approach should be applicable to virtually any pharmaceutical agent in patient populations.

Metabolic basis of drug interactions in the intensive care unit

Drug interactions are a potentially hazardous consequence of drug therapy, particularly in the critically ill. Many drug interactions result from changes in drug metabolism. These interactions can result in either an increase in toxicity or a decrease in effect. The process of normal drug metabolism depends on the activity of individual metabolizing enzymes. The activity of these enzymes can be altered by many factors, and it is alterations in these enzymes that account for most drug interactions. This article reviews normal and abnormal drug metabolism and discusses how this knowledge can be used to predict and prevent potential drug interactions.

Effect of St. John's wort (Hypericum perforatum) on cytochrome P-450 2D6 and 3A4 activity in healthy volunteers

The effects of the herb St. John's wort (Hypericum perforatum), a purported antidepressant, on the activity of cytochrome P-450 (CYP) 2D6 and 3A4 was assessed in seven normal volunteers. Probe substrates dextromethorphan (2D6 activity) and alprazolam (3A4 activity) were administered orally with and without the co-administration of St. John's wort. Urinary concentrations of dextromethorphan and dextrorphan were quantified and dextromethorphan metabolic ratios (DMRs) determined. Plasma samples were collected (0-60 hrs) for alprazolam pharmacokinetic analysis sufficient to estimate tmax, Cmax, t 1/2, and AUC. Validated HPLC methods were used to quantify all compounds of interest. No statistically significant differences were found in any estimated pharmacokinetic parameter for alprazolam or DMRs. These results suggest that St. John's wort, when taken at recommended doses for depression, is unlikely to inhibit CYP 2D6 or CYP 3A4 activity.

Pharmacogenetics and pharmacogenomics: why is this relevant to the clinical geneticist?

Adverse drug reactions, due at least in part to interindividual variability in drug response, rank between the 4th and 6th leading causes of death in the USA. The field of 'pharmacogenetics', which is 'the study of variability in drug response due to heredity', should help in reducing drug-caused morbidity and mortality. The recently coined term 'pharmacogenomics' usually refers to 'the field of new drug development based on our rapidly increasing knowledge of all genes in the human genome'. However, the two terms - pharmacogenetics and pharmacogenomics - are often used interchangeably. A classification of more than five dozen pharmacogenetic differences is presented here. Most of these variations occur in drug-metabolizing enzyme (DME) genes, with some presumed to exist in the DME receptor and drug transporter genes, and others have not yet been explained on a molecular basis. A method for unequivocally defining a quantitative phenotype (drug efficacy, toxicity, etc.) is proposed; this is where help from the clinical geneticist can be especially important. Our current appreciation of the degree of variability (including single-nucleotide polymorphisms, SNPs) in the human genome is described, with emphasis on the need to prove that a particular genotype is indeed the cause of a specific phenotype; this topic has been termed 'functional genomics'. Furthermore, the current amount of admixture amongst almost all ethnic groups will obviously make studies of gene-drug interactions more complicated, as will the withholding of ethnic information about DNA samples during any molecular epidemiologic study. DME genes and DME receptor and drug transporter genes can be regarded as 'modifier genes', because they influence disorders as diverse as risk of cancer, bone marrow toxicity resulting from occupational exposure, and Parkinson's disease; for this reason, the clinical geneticist, as well as the medical genetics counselor, should be knowledgeable in the rapidly expanding fields of pharmacogenetics and pharmacogenomics.