Anti-emetic drugs in oncology: pharmacology and individualization by pharmacogenetics

Objective Nausea and vomiting are the most distressful side effects of cytotoxic drugs in cancer patients. Antiemetics are commonly used to reduce these side effects. However, the current antiemetic efficacy is about 70–80% in patients treated with highly-emetogenic cytotoxic drugs. One of the potential factors explaining this suboptimal response is variability in genes encoding enzymes and proteins which play a role in metabolism, transport and receptors related to antiemetic drugs. Aim of this review was to describe the pharmacology and pharmacogenetic concepts of of antiemetics in oncology. Method Pharmacogenetic and pharmacology studies of antiemetics in oncology published between January 1997 and February 2010 were searched in PubMed. Furthermore, related textbooks were also used for exploring the pharmacology of antiemetic drugs. The antiemetic drugs which were searched were the 5-hydroxytryptamine 3 receptor antagonists (5-HT3RAs), dopamine antagonists, corticosteroids, benzodiazepines, cannabinoids, antihistamines and neurokinin-1 antagonists. Result The 5-HT3RAs are widely used in highly emetogenic chemotherapy in combination with dexamethasone and a neurokinin-1 antagonist, especially in acute phase. However, the dopamine antagonists and benzodiazepines were found more appropriate for use in breakthrough and anticipatory symptoms or in preventing the delayed phase of chemotherapy induced nausea and vomiting. The use of cannabinoids and antihistamines need further investigation. Only six articles on pharmacogenetics of the 5-HT3RAs in highly emetogenic chemotherapy are published. Specifically, these studies investigated the association of the efficacy of 5-HT3RAs and variants in the multi drug resistance 1 (MDR1) gene, 5-HT3A,B and C receptor genes and CYP2D6 gene. The pharmacogenetic studies of the other antiemetics were not found in this review. Conclusion It is concluded that pharmacogenetic studies with antiemetics are sparse. It is too early to implement results of pharmacogenetic association studies of antiemetic drugs in clinical practice: confirmation of early findings is required

Patients with Schizophrenia

Introduction: Genetic polymorphisms of cytochrome P450 (CYP) may predict the treatment response or occurrence of side effects of antipsychotic drugs.Aim: We studied the association of response to clozapine treatment in schizophrenic patients in relation to polymorphisms in the CYP1A2 gene.Methods: The degree of psychosis of the patients (n=55) was assessed using the Brief Psychiatric Rating Scale (BPRS), the Scale for the Assessment of Positive Symptoms (SAPS), the Scale for the Assessment of Negative Symptoms (SANS) and routine biochemistry. The patients were monitored for 18 weeks and the scales were applied before starting the treatment and at the end of the follow up period. Clozapine was used at doses of 200 to 600 mg/day. A positive response was defined as a 20% decrease in pre- and post-treatment scores of one of the BPRS, SANS, or SAPS scores. In addition, 45 patients, who were already on clozapine treatment, were assessed retrospectively.Results: As assessed at the 18(th) week after start of therapy, lack of response to clozapine treatment was 2.4 fold higher in the patients carrying the CYP1A2*1F*1F genotype (p=0.02) compared to patients carrying at least one wild type allele (i.e. *1/*1 or *1/*1F). Smoking decreased the response rate by about 15% (p=0.014).Conclusion: The results of our study suggest that the CYP1A2*1F/*1F genotype may be a risk factor for lack of response to clozapine treatment in psychotic patients, especially in cigarette smokers

A small-Molecule inhibitor of hepatitis C virus infectivity

One of the most challenging goals of hepatitis C virus (HCV) research is to develop well-tolerated regimens with high cure rates across a variety of patient populations. Such a regimen will likely require a combination of at least two distinct direct-acting antivirals (DAAs). Combining two or more DAAs with different resistance profiles increases the number of mutations required for viral breakthrough. Currently, most DAAs inhibit HCV replication. We recently reported that the combination of two distinct classes of HCV inhibitors, entry inhibitors and replication inhibitors, prolonged reductions in extracellular HCV in persistently infected cells. We therefore sought to identify new inhibitors targeting aspects of the HCV replication cycle other than RNA replication. We report here the discovery of the first small-molecule HCV infectivity inhibitor, GS-563253, also called HCV infectivity inhibitor 1 (HCV II-1). HCV II-1 is a substituted tetrahydroquinoline that selectively inhibits genotype 1 and 2 HCVs withlow-nanomolar 50% effective concentrations. It was identified through a high-throughput screen and subsequent chemical optimization. HCV II-1 only permits the production and release of noninfectious HCV particles from cells. Moreover, infectious HCV is rapidly inactivated in its presence. HCV II-1 resistance mutations map to HCV E2. In addition, HCV-II prevents HCV endosomal fusion, suggesting that it either locks the viral envelope in its prefusion state or promotes a viral envelope conformation change incapable of fusion. Importantly, the discovery of HCV II-1 opens up a new class of HCV inhibitors that prolong viral suppression by HCV replication inhibitors in persistently infected cell cultures. 2014, American Society for Microbiology. All Rights Reserve

Formalization, Annotation and Analysis of Diverse Drug and Probe Screening Assay Datasets Using the BioAssay Ontology (BAO)

Huge amounts of high-throughput screening (HTS) data for probe and drug development projects are being generated in the pharmaceutical industry and more recently in the public sector. The resulting experimental datasets are increasingly being disseminated via publically accessible repositories. However, existing repositories lack sufficient metadata to describe the experiments and are often difficult to navigate by non-experts. The lack of standardized descriptions and semantics of biological assays and screening results hinder targeted data retrieval, integration, aggregation, and analyses across different HTS datasets, for example to infer mechanisms of action of small molecule perturbagens. To address these limitations, we created the BioAssay Ontology (BAO). BAO has been developed with a focus on data integration and analysis enabling the classification of assays and screening results by concepts that relate to format, assay design, technology, target, and endpoint. Previously, we reported on the higher-level design of BAO and on the semantic querying capabilities offered by the ontology-indexed triple store of HTS data. Here, we report on our detailed design, annotation pipeline, substantially enlarged annotation knowledgebase, and analysis results. We used BAO to annotate assays from the largest public HTS data repository, PubChem, and demonstrate its utility to categorize and analyze diverse HTS results from numerous experiments. BAO is publically available from the NCBO BioPortal at http://bioportal.bioontology.org/ontologies/1533. BAO provides controlled terminology and uniform scope to report probe and drug discovery screening assays and results. BAO leverages description logic to formalize the domain knowledge and facilitate the semantic integration with diverse other resources. As a consequence, BAO offers the potential to infer new knowledge from a corpus of assay results, for example molecular mechanisms of action of perturbagens