Omics and drug response

Epigenomics alternations and dynamic transcriptional changes in responses to 5-fluorouracil stimulation reveal mechanisms of acquired drug resistance of colorectal cancer cells

A drug-induced resistant cancer cell is different from its parent cell in transcriptional response to drug treatment. The distinct transcriptional response pattern of a drug-induced resistant cancer cell to drug treatment might be introduced by acquired DNA methylation aberration in the cell exposing to sustained drug stimulation. In this study, we performed both transcriptional and DNA methylation profiles of the HCT-8 wild-type cells (HCT-8/WT) for human colorectal cancer (CRC) and the 5-fluorouracil (5-FU)-induced resistant cells (HCT-8/5-FU) after treatment with 5-FU for 0, 24 and 48 h. Integrated analysis of transcriptional and DNA methylation profiles showed that genes with promoter hypermethylation and concordant expression silencing in the HCT-8/5-FU cells are mainly involved in pathways of pyrimidine metabolism and drug metabolism-cytochrome P450. Transcriptional analysis confirmed that genes with transcriptional differences between a drug-induced resistant cell and its parent cell after drug treatment for a certain time, rather than their primary transcriptional differences, are more likely to be involved in drug resistance. Specifically, transcriptional differences between the drug-induced resistant cells and parental cells after drug treatment for 24 h were significantly consistent with the differentially expressed genes (termed as CRG_5-FU) between the tissues of nonresponders and responders of CRCs to 5-FU-based therapy and the consistence increased after drug treatment for 48 h (binomial test, P-value=1.88E−06). This study reveals a major epigenetic mechanism inducing the HCT-8/WT cells to acquire resistance to 5-FU and suggests an appropriate time interval (24–48 h) of 5-FU exposure for identifying clinically relevant drug resistance signatures from drug-induced resistant cell models.

P450 Oxidoreductase deficiency: Analysis of mutations and polymorphisms

Cytochrome P450 oxidoreductase (POR) is required for metabolic reactions of steroid and drug metabolizing cytochrome P450 proteins located in endoplasmic reticulum. Mutations in POR cause a complex set of disorders resembling combined deficiencies of multiple steroid metabolizing enzymes. The P450 oxidoreductase deficiency (PORD) was first reported in patients with symptoms of defects in steroidogenic cytochrome P450 enzymes and ambiguous genitalia, and bone malformation features resembling Antley-Bixler syndrome. POR is now classified as a separate and rare form of congenital adrenal hyperplasia (CAH), which may cause disorder of sexual development (DSD). Since the initial description of PORD in 2004, a large number of POR mutations and polymorphisms have been described. In this report we have performed computational analysis of mutations and polymorphisms in POR linked to metabolism of steroids and xenobiotics and pathology of PORD from the reported cases. The mutations in POR that were identified in patients with disruption of steroidogenesis also have severe effects on cytochrome P450 proteins involved in metabolism of drugs. Different variations in POR show a range of diverse effects on different partner proteins that are often linked to the location of the particular variants. The variations in POR that cause defective binding of co-factors always have damaging effects on all partner proteins, while the mutations causing subtle structural changes may lead to altered interaction with partner proteins and the overall effect may be different for each individual partner. Computational analysis of available sequencing data and mutation analysis shows that Japanese (R457H), Caucasian (A287P) and Turkish (399-401) populations can be linked to unique founder mutations. Other mutations identified so far were identified as rare alleles or in single isolated reports. The common polymorphism of POR is the variant A503V which can be found in about 27% of alleles in general population but there are remarkable differences among different sub populations.

European healthcare systems readiness to shift from ‘one-size fits all’ to personalized medicine

Personalized medicine (PM) is no longer an abstract healthcare approach. It has become a reality over the last years and is already successfully applied in the various medical fields. Although there are success stories of implementing PM, there are still many more opportunities to further implement and make full use of the potential of PM. We assessed the system readiness of healthcare systems in Europe to shift from the predominant ‘one size fits all’ healthcare approach to PM. We conclude that European healthcare systems are only partially ready for PM. Key challenges such as integration of big data, health literacy, reimbursement and regulatory issues need to be overcome in order to strengthen the implementation and uptake of PM.

Development of Human Membrane Transporters: Drug Disposition and Pharmacogenetics

Membrane transporters play an essential role in the transport of endogenous and exogenous compounds, and consequently they mediate the uptake, distribution, and excretion of many drugs. The clinical relevance of transporters in drug disposition and their effect in adults have been shown in drug–drug interaction and pharmacogenomic studies. Little is known, however, about the ontogeny of human membrane transporters and their roles in pediatric pharmacotherapy. As they are involved in the transport of endogenous substrates, growth and development may be important determinants of their expression and activity. This review presents an overview of our current knowledge on human membrane transporters in pediatric drug disposition and effect. Existing pharmacokinetic and pharmacogenetic data on membrane substrate drugs frequently used in children are presented and related, where possible, to existing ex vivo data, providing a basis for developmental patterns for individual human membrane transporters. As data for individual transporters are currently still scarce, there is a striking information gap regarding the role of human membrane transporters in drug therapy in children.

‘Omics’: an emerging field in pain research and management

Precision medicine is an emerging approach for prevention and treatment of diseases considering individuals’ uniqueness. Omics provide one step forward toward advanced precision medicine and include technologies such as genomics, proteomics and metabolomics generating valuable data through characterization of entire biological systems. With the aid of omics, a major shift has been started to occur in understanding of diseases followed by potential fundamental changes in medical care strategies. This short review aims at providing some examples of current omics that are applied in the field of pain in terms of new biomarkers for diagnosis of different pain types, stratification of patients and new therapeutic targets. Implementation of omics would most likely offer breakthrough in the future of pain management.

Pharmacogenomics of Drug Metabolizing Enzymes and Transporters: Relevance to Precision Medicine

The interindividual genetic variations in drug metabolizing enzymes and transporters influence the efficacy and toxicity of numerous drugs. As a fundamental element in precision medicine, pharmacogenomics, the study of responses of individuals to medication based on their genomic information, enables the evaluation of some specific genetic variants responsible for an individual’s particular drug response. In this article, we review the contributions of genetic polymorphisms to major individual variations in drug pharmacotherapy, focusing specifically on the pharmacogenomics of phase-I drug metabolizing enzymes and transporters. Substantial frequency differences in key variants of drug metabolizing enzymes and transporters, as well as their possible functional consequences, have also been discussed across geographic regions. The current effort illustrates the common presence of variability in drug responses among individuals and across all geographic regions. This information will aid health-care professionals in prescribing the most appropriate treatment aimed at achieving the best possible beneficial outcomes while avoiding unwanted effects for a particular patient.

Impact of Membrane Drug Transporters on Resistance to Small-Molecule Tyrosine Kinase Inhibitors

Small-molecule inhibitors of tyrosine kinases (TKIs) are the mainstay of treatment for many malignancies and represent novel treatment options for other diseases such as idiopathic pulmonary fibrosis. Twenty-five TKIs are currently FDA-approved and >130 are being evaluated in clinical trials. Increasing evidence suggests that drug exposure of TKIs may significantly contribute to drug resistance, independently from somatic variation of TKI target genes. Membrane transport proteins may limit the amount of TKI reaching the target cells. This review highlights current knowledge on the basic and clinical pharmacology of membrane transporters involved in TKI disposition and their contribution to drug efficacy and adverse drug effects. In addition to non-genetic and epigenetic factors, genetic variants, particularly rare ones, in transporter genes are promising novel factors to explain interindividual variability in the response to TKI therapy.

Intestinal and Hepatocellular Transporters: Therapeutic Effects and Drug Interactions of Herbal Supplements

Herbal supplements are generally considered safe; however, drug disposition is influenced by the interactions of herbal supplements and food constituents with transport and metabolic processes. Although the interference of herbal supplements with drug metabolism has been studied extensively, knowledge of how they interact with the drug transport processes is less advanced. Therefore, we describe here specific examples of experimental and human interaction studies of herbal supplement components with drug transporters addressing, for example, organic anion transporting polypeptides or P-glycoprotein, as such interactions may lead to severe side effects and altered drug efficacy. Hence, it is clearly necessary to increase the awareness of the clinical relevance of the interference of herbal supplements with the drug transport processes.

Next-generation personalised medicine for high-risk paediatric cancer patients - The INFORM pilot study

The 'Individualized Therapy for Relapsed Malignancies in Childhood' (INFORM) precision medicine study is a nationwide German program for children with high-risk relapsed/refractory malignancies, which aims to identify therapeutic targets on an individualised basis. In a pilot phase, reported here, we developed the logistical and analytical pipelines necessary for rapid and comprehensive molecular profiling in a clinical setting. Fifty-seven patients from 20 centers were prospectively recruited. Malignancies investigated included sarcomas (n = 25), brain tumours (n = 23), and others (n = 9). Whole-exome, low-coverage whole-genome, and RNA sequencing were complemented with methylation and expression microarray analyses. Alterations were assessed for potential targetability according to a customised prioritisation algorithm and subsequently discussed in an interdisciplinary molecular tumour board. Next-generation sequencing data were generated for 52 patients, with the full analysis possible in 46 of 52. Turnaround time from sample receipt until first report averaged 28 d. Twenty-six patients (50%) harbored a potentially druggable alteration with a prioritisation score of 'intermediate' or higher (level 4 of 7). Common targets included receptor tyrosine kinases, phosphoinositide 3-kinase-mammalian target of rapamycin pathway, mitogen-activated protein kinase pathway, and cell cycle control. Ten patients received a targeted therapy based on these findings, with responses observed in some previously treatment-refractory tumours. Comparative primary relapse analysis revealed substantial tumour evolution as well as one case of unsuspected secondary malignancy, highlighting the importance of re-biopsy at relapse. This study demonstrates the feasibility of comprehensive, real-time molecular profiling for high-risk paediatric cancer patients. This extended proof-of-concept, with examples of treatment consequences, expands upon previous personalised oncology endeavors, and presents a model with considerable interest and practical relevance in the burgeoning era of personalised medicine.

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

Impact of Genetic Polymorphisms of ABCB1 (MDR1, P-Glycoprotein) on Drug Disposition and Potential Clinical Implications: Update of the Literature

ATP-binding cassette transporter B1 (ABCB1; P-glycoprotein; multidrug resistance protein 1) is an adenosine triphosphate (ATP)-dependent efflux transporter located in the plasma membrane of many different cell types. Numerous structurally unrelated compounds, including drugs and environmental toxins, have been identified as substrates. ABCB1 limits the absorption of xenobiotics from the gut lumen, protects sensitive tissues (e.g. the brain, fetus and testes) from xenobiotics and is involved in biliary and renal secretion of its substrates. In recent years, a large number of polymorphisms of the ABCB1 [ATP-binding cassette, sub-family B (MDR/TAP), member 1] gene have been described. The variants 1236C>T (rs1128503, p.G412G), 2677G>T/A (rs2032582, p.A893S/T) and 3435C>T (rs1045642, p.I1145I) occur at high allele frequencies and create a common haplotype; therefore, they have been most widely studied. This review provides an overview of clinical studies published between 2002 and March 2015. In summary, the effect of ABCB1 variation on P-glycoprotein expression (messenger RNA and protein expression) and/or activity in various tissues (e.g. the liver, gut and heart) appears to be small. Although polymorphisms and haplotypes of ABCB1 have been associated with alterations in drug disposition and drug response, including adverse events with various ABCB1 substrates in different ethnic populations, the results have been majorly conflicting, with limited clinical relevance. Future research activities are warranted, considering a deep-sequencing approach, as well as well-designed clinical studies with appropriate sample sizes to elucidate the impact of rare ABCB1 variants and their potential consequences for effect sizes.

DNA Methylation of ADME Genes

The epigenetic regulation of expression of genes involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs contributes to interindividual variability in drug response. Epigenetic mechanisms include DNA methylation, histone modifications, and miRNAs. This review systematically outlines the influence of DNA methylation on ADME gene expression and highlights the consequences for interindividual variability in drug response or drug-induced toxicity and the implications for personalized medicine.

Pharmacogenetics: Implications for Modern Type 2 Diabetes Therapy

Many clinical treatment studies have reported remarkable interindividual variability in the response to pharmaceutical drugs, and uncovered the existence of inadequate treatment response, non-response, and even adverse drug reactions. Pharmacogenetics addresses the impact of genetic variants on treatment outcome including side-effects. In recent years, it has also entered the field of clinical diabetes research. In modern type 2 diabetes therapy, metformin is established as first-line drug. The latest pharmaceutical developments, including incretin mimetics, dipeptidyl peptidase 4 inhibitors (gliptins), and sodium/glucose cotransporter 2 inhibitors (gliflozins), are currently experiencing a marked increase in clinical use, while the prescriptions of α-glucosidase inhibitors, sulfonylureas, meglitinides (glinides), and thiazolidinediones (glitazones) are declining, predominantly because of reported side-effects. This review summarizes the current knowledge about gene-drug interactions observed in therapy studies with the above drugs. We report drug interactions with candidate genes involved in the pharmacokinetics (e.g., drug transporters) and pharmacodynamics (drug targets and downstream signaling steps) of the drugs, with known type 2 diabetes risk genes and previously unknown genes derived from hypothesis-free approaches such as genome-wide association studies. Moreover, some new and promising candidate genes for future pharmacogenetic assessment are highlighted. Finally, we critically appraise the current state of type 2 diabetes pharmacogenetics in the light of its impact on therapeutic decisions, and we refer to major problems, and make suggestions for future efforts in this field to help improve the clinical relevance of the results, and to establish genetically determined treatment failure.

Achieving the World Health Organization's vision for clinical pharmacology

Clinical pharmacology is a medical specialty whose practitioners teach, undertake research, frame policy, give information and advice about the actions and proper uses of medicines in humans and implement that knowledge in clinical practice. It involves a combination of several activities: drug discovery and development, training safe prescribers, providing objective and evidence-based therapeutic information to ethics, regulatory and pricing bodies, supporting patient care in an increasingly subspecialized arena where co-morbidities, polypharmacy, altered pharmacokinetics and drug interactions are common and developing and contributing to medicines policies for Governments. Clinical pharmacologists must advocate drug quality and they must also advocate for sustainability of the Discipline. However for this they need appropriate clinical service and training support. This Commentary discusses strategies to ensure the Discipline is supported by teaching, training and policy organizations, to communicate the full benefits of clinical pharmacology services, put a monetary value on clinical pharmacology services and to grow the clinical pharmacology workforce to support a growing clinical, academic and regulatory need.

Biomarker-based drug safety assessment in the age of systems pharmacology: from foundational to regulatory science

Improved biomarker-based assessment of drug safety is needed in drug discovery and development as well as regulatory evaluation. However, identifying drug safety-related biomarkers such as genes, proteins, miRNA and single-nucleotide polymorphisms remains a big challenge. The advances of 'omics' and computational technologies such as genomics, transcriptomics, metabolomics, proteomics, systems biology, network biology and systems pharmacology enable us to explore drug actions at the organ and organismal levels. Computational and experimental systems pharmacology approaches could be utilized to facilitate biomarker-based drug safety assessment for drug discovery and development and to inform better regulatory decisions. In this article, we review the current status and advances of systems pharmacology approaches for the development of predictive models to identify biomarkers for drug safety assessment.

A glutamatergic network mediates lithium response in bipolar disorder as defined by epigenome pathway analysis

AIM

A regulatory network in the human brain mediating lithium response in bipolar patients was revealed by analysis of functional SNPs from genome-wide association studies (GWAS) and published gene association studies, followed by epigenome mapping.

METHODS

An initial set of 23,312 SNPs in linkage disequilibrium with lead SNPs, and sub-threshold GWAS SNPs rescued by pathway analysis, were studied in the same populations. These were assessed using our workflow and annotation by the epigenome roadmap consortium.

RESULTS

Twenty-seven percent of 802 SNPs that were associated with lithium response (13 published studies gene association studies and two GWAS) were shared in common with 1281 SNPs from 18 GWAS examining psychiatric disorders and adverse events associated with lithium treatment. Nineteen SNPs were annotated as active regulatory elements such as enhancers and promoters in a tissue-specific manner. They were located within noncoding regions of ten genes: ANK3, ARNTL, CACNA1C, CACNG2, CDKN1A, CREB1, GRIA2, GSK3B, NR1D1 and SLC1A2. Following gene set enrichment and pathway analysis, these genes were found to be significantly associated (p = 10(-27); Fisher exact test) with an AMPA2 glutamate receptor network in human brain. Our workflow results showed concordance with annotation of regulatory elements from the epigenome roadmap. Analysis of cognate mRNA and enhancer RNA exhibited patterns consistent with an integrated pathway in human brain.

CONCLUSION

This pharmacoepigenomic regulatory pathway is located in the same brain regions that exhibit tissue volume loss in bipolar disorder. Although in silico analysis requires biological validation, the approach provides value for identification of candidate variants that may be used in pharmacogenomic testing to identify bipolar patients likely to respond to lithium.

Epigenomic mapping and effect sizes of noncoding variants associated with psychotropic drug response

AIM

To provide insight into potential regulatory mechanisms of gene expression underlying addiction, analgesia, psychotropic drug response and adverse drug events, genome-wide association studies searching for variants associated with these phenotypes has been undertaken with limited success. We undertook analysis of these results with the aim of applying epigenetic knowledge to aid variant discovery and interpretation.

METHODS

We applied conditional imputation to results from 26 genome-wide association studies and three candidate gene-association studies. The analysis workflow included data from chromatin conformation capture, chromatin state annotation, DNase I hypersensitivity, hypomethylation, anatomical localization and biochronicity. We also made use of chromatin state data from the epigenome roadmap, transcription factor-binding data, spatial maps from published Hi-C datasets and 'guilt by association' methods.

RESULTS

We identified 31 pharmacoepigenomic SNPs from a total of 2024 variants in linkage disequilibrium with lead SNPs, of which only 6% were coding variants. Interrogation of chromatin state using our workflow and the epigenome roadmap showed agreement on 34 of 35 tissue assignments to regulatory elements including enhancers and promoters. Loop boundary domains were inferred by association with CTCF (CCCTC-binding factor) and cohesin, suggesting proximity to topologically associating domain boundaries and enhancer clusters. Spatial interactions between enhancer-promoter pairs detected both known and previously unknown mechanisms. Addiction and analgesia SNPs were common in relevant populations and exhibited large effect sizes, whereas a SNP located in the promoter of the SLC1A2 gene exhibited a moderate effect size for lithium response in bipolar disorder in patients of European ancestry. SNPs associated with drug-induced organ injury were rare but exhibited the largest effect sizes, consistent with the published literature.

CONCLUSION

This work demonstrates that an in silico bioinformatics-based approach using integrative analysis of a diversity of molecular and morphological data types can discover pharmacoepigenomic variants that are suitable candidates for further validation in cell lines, animal models and human clinical trials.

NMR-Based Metabolomics Separates the Distinct Stages of Disease in a Chronic Relapsing Model of Multiple Sclerosis

Relapsing experimental allergic encephalomyelitis (Cr-EAE) is commonly used to explore the pathogenesis and efficacy of new therapies for MS, but it is unclear whether the metabolome of Cr-EAE is comparable to human multiple sclerosis (MS). For MS, the diagnosis and staging can be achieved by metabolomics on blood using a combination of magnetic resonance spectroscopy and partial least squares discriminant analysis (PLS-DA). Here, we sought to discover whether this approach could be used to differentiate between sequential disease states in Cr-EAE and whether the same metabolites would be discriminatory. Urine and plasma samples were obtained at different time-points from a clinically relevant model of MS. Using PLS-DA modelling for the urine samples furnished some predictive models, but could not discriminate between all disease states. However, PLS-DA modelling of the plasma samples was able to distinguish between animals with clinically silent disease (day 10, 28) and animals with active disease (day 14, 38). We were also able to distinguish Cr-EAE mice from naive mice at all-time points and control mice, treated with complete Freund's adjuvant alone, at day 14 and 38. Key metabolites that underpin these models included fatty acids, glucose and taurine. Two of these metabolites, fatty acids and glucose, were also key metabolites in separating relapsing-remitting MS from secondary-progressive MS in the human study. These results demonstrate the sensitivity of this metabolomics approach for distinguishing between different disease states. Furthermore, some, but not all, of the changes in metabolites were conserved in humans and the mouse model, which could be useful for future drug development.

Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine

Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL).

Functional characterization of common protein variants in the efflux transporter ABCC11 and identification of T546M as functionally damaging variant

Multidrug resistance protein 8 (ABCC11) is an efflux transporter for anionic lipophilic compounds, conferring resistance to antiviral and anticancer agents like 5-fluorouracil (5-FU). ABCC11 missense variants may contribute to variability in drug response but functional consequences, except for the 'earwax variant' c.538G>A, are unknown. Using the 'Screen and Insert' technology, we generated human embryonic kidney 293 cells stably expressing ABCC11 missense variants frequently occurring in different ethnic populations: c.57G>A, c.538G>A, c.950C>A, c.1637C>T, c.1942G>A, c.4032A>G. A series of in silico prediction analyses and in vitro plasma membrane vesicle uptake, immunoblotting and immunolocalization experiments were undertaken to investigate functional consequences. We identified c.1637C>T (T546M), previously associated with 5-FU-related toxicity, as a novel functionally damaging ABCC11 variant exhibiting markedly reduced transport function of 5-FdUMP, the active cytotoxic metabolite of 5-FU. Detailed analysis of 14 subpopulations revealed highest allele frequencies of c.1637C>T in Europeans and Americans (up to 11%) compared with Africans and Asians (up to 3%).

Personalized biochemistry and biophysics

Whole human genome sequencing of individuals is becoming rapid and inexpensive, enabling new strategies for using personal genome information to help diagnose, treat, and even prevent human disorders for which genetic variations are causative or are known to be risk factors. Many of the exploding number of newly discovered genetic variations alter the structure, function, dynamics, stability, and/or interactions of specific proteins and RNA molecules. Accordingly, there are a host of opportunities for biochemists and biophysicists to participate in (1) developing tools to allow accurate and sometimes medically actionable assessment of the potential pathogenicity of individual variations and (2) establishing the mechanistic linkage between pathogenic variations and their physiological consequences, providing a rational basis for treatment or preventive care. In this review, we provide an overview of these opportunities and their associated challenges in light of the current status of genomic science and personalized medicine, the latter often termed precision medicine.

Analytical methods in untargeted metabolomics: state of the art in 2015

Metabolomics comprises the methods and techniques that are used to measure the small molecule composition of biofluids and tissues, and is actually one of the most rapidly evolving research fields. The determination of the metabolomic profile - the metabolome - has multiple applications in many biological sciences, including the developing of new diagnostic tools in medicine. Recent technological advances in nuclear magnetic resonance and mass spectrometry are significantly improving our capacity to obtain more data from each biological sample. Consequently, there is a need for fast and accurate statistical and bioinformatic tools that can deal with the complexity and volume of the data generated in metabolomic studies. In this review, we provide an update of the most commonly used analytical methods in metabolomics, starting from raw data processing and ending with pathway analysis and biomarker identification. Finally, the integration of metabolomic profiles with molecular data from other high-throughput biotechnologies is also reviewed.

Stratified medicine for the use of antidiabetic medication in treatment of type II diabetes and cancer: where do we go from here?

At present, the global diabetes epidemic is affecting 347 million individuals, 90% of whom are diagnosed with type II diabetes mellitus (T2DM). T2DM is commonly treated with more than one type of therapy, including oral antidiabetic drugs (OADs) and agents used in the treatment of diabetic complications. Several pharmacological classes of OADs are currently available for the treatment of T2DM, of which insulin secretagogues (i.e. sulphonylureas and meglitinides), insulin sensitizers [thiazolidinediones (TZDs)] and biguanides are the most commonly prescribed. Although many of these OADs have been used for more than half a century in the treatment of T2DM, the pharmacogenomic characteristics of these compounds have only recently been investigated, primarily in retrospective studies. Recent advances in pharmacogenomics have led to the identification of polymorphisms that affect the expression and function of drug-metabolizing enzymes and drug transporters, as well as drug targets and receptors. These polymorphisms have been shown to affect the therapeutic response to and side effects associated with OADs. The aim of this review was to provide an up-to-date summary of some of the pharmacogenomic data obtained from studies of T2DM treatment, with a focus on polymorphisms in genes affecting pharmacokinetics, pharmacodynamics and treatment outcome of the most commonly prescribed OADs. In addition, the implications of pharmacogenomics in the use of the OAD metformin in cancer will be briefly discussed. Finally, we will focus on recent advances in novel 'omics' technologies and discuss how these might aid in the personalized management of T2DM.

Evolutionary Diagnosis of non-synonymous variants involved in differential drug response

Background

Many pharmaceutical drugs are known to be ineffective or have negative side effects in a substantial proportion of patients. Genomic advances are revealing that some non-synonymous single nucleotide variants (nsSNVs) may cause differences in drug efficacy and side effects. Therefore, it is desirable to evaluate nsSNVs of interest in their ability to modulate the drug response.

Results

We found that the available data on the link between drug response and nsSNV is rather modest. There were only 31 distinct drug response-altering (DR-altering) and 43 distinct drug response-neutral (DR-neutral) nsSNVs in the whole Pharmacogenomics Knowledge Base (PharmGKB). However, even with this modest dataset, it was clear that existing bioinformatics tools have difficulties in correctly predicting the known DR-altering and DR-neutral nsSNVs. They exhibited an overall accuracy of less than 50%, which was not better than random diagnosis. We found that the underlying problem is the markedly different evolutionary properties between positions harboring nsSNVs linked to drug responses and those observed for inherited diseases. To solve this problem, we developed a new diagnosis method, Drug-EvoD, which was trained on the evolutionary properties of nsSNVs associated with drug responses in a sparse learning framework. Drug-EvoD achieves a TPR of 84% and a TNR of 53%, with a balanced accuracy of 69%, which improves upon other methods significantly.

Conclusions

The new tool will enable researchers to computationally identify nsSNVs that may affect drug responses. However, much larger training and testing datasets are needed to develop more reliable and accurate tools.

Biotransformation in vitro: An essential consideration in the quantitative in vitro-to-in vivo extrapolation (QIVIVE) of toxicity data

Early consideration of the multiplicity of factors that govern the biological fate of foreign compounds in living systems is a necessary prerequisite for the quantitative in vitro-in vivo extrapolation (QIVIVE) of toxicity data. Substantial technological advances in in vitro methodologies have facilitated the study of in vitro metabolism and the further use of such data for in vivo prediction. However, extrapolation to in vivo with a comfortable degree of confidence, requires continuous progress in the field to address challenges such as e.g., in vitro evaluation of chemical-chemical interactions, accounting for individual variability but also analytical challenges for ensuring sensitive measurement technologies. This paper discusses the current status of in vitro metabolism studies for QIVIVE extrapolation, serving today's hazard and risk assessment needs. A short overview of the methodologies for in vitro metabolism studies is given. Furthermore, recommendations for priority research and other activities are provided to ensure further widespread uptake of in vitro metabolism methods in 21st century toxicology. The need for more streamlined and explicitly described integrated approaches to reflect the physiology and the related dynamic and kinetic processes of the human body is highlighted i.e., using in vitro data in combination with in silico approaches.

Personalized medicine in oncology: ethical implications for the delivery of healthcare

While personalized medicine brings benefits for the treatment of cancer, there are still key ethical issues at stake in developing personalized medicine in oncology. We propose an ethical analysis of personalized medicine in oncology that highlights the particularities of cancer care, critically assesses the scientific advances behind personalized medicine in oncology and emphasizes fairness in resource allocation in the delivery of personalized healthcare. This allows for a broader understanding of the real impacts on both recipients and the healthcare system.

Clinical translation in the virtual liver network

The liver is the central detoxifying organ, continuously removing xenobiotics from the vascular system. Given its role in drug metabolism, a functional understanding of liver physiology is crucial to optimizing drug efficacy and patient safety. The Virtual Liver Network (VLN), a German national flagship research program, focuses on producing validated computer models of human liver physiology. These models are used to analyze patient-derived data and thereby gain mechanistic insights in the processes underlying drug pharmacokinetics (PK).

Personalized pharmacogenomics: predicting efficacy and adverse drug reactions

Drug response varies between individuals owing to disease heterogeneity, environmental factors, and genetic factors. Genetic factors can affect both the pharmacokinetics and pharmacodynamics of a drug, leading to changes in local and systemic drug exposure and/or changes in the function of the drug target, altering drug response. Several pharmacogenetic biomarkers are already utilized in clinical practice and have been shown to improve clinical outcomes. However, a large number of other biomarkers have never made it beyond the discovery stage. Concerted effort is needed to improve the translation of pharmacogenetic biomarkers into clinical practice, and this will involve the use of standardized phenotyping and genotyping strategies, collaborative work, multidisciplinary approaches to identifying and replicating associations, and cooperation with industry to facilitate translation and commercialization. Acceptance of these approaches by clinicians, regulators, patients, and the public will be important in determining future success.

Personalized medicine, availability, and group disparity: an inquiry into how physicians perceive and rate the elements and barriers of personalized medicine

BACKGROUND

The success of personalized medicine depends on factors influencing the availability and implementation of its new tools to individualize clinical care. However, little is known about physicians' views of the availability of personalized medicine across racial/ethnic groups and the relationship between perceived availability and clinical implementation. This study examines physicians' perceptions of key elements/tools and potential barriers to personalized medicine in connection with their perceptions of the availability of the latter across subpopulations.

METHODS

Study subjects consisted of physicians recruited from Cincinnati Children's Hospital Medical Center and UC Health. An electronic survey conducted from September 2012 to November 2012 recruited 104 physicians. Wilcoxon rank sum analysis compared groups.

RESULTS

Physicians were divided about whether personalized medicine contributes to health equality, as 37.4% of them believe that personalized medicine is currently available only for some subpopulations. They also rated the importance of racial/ethnic background almost as high as the importance of genetic information in the delivery of personalized medicine. Actual elements of personalized medicine rated highest include family history, drug-drug interaction alerts in medical records, and biomarker measurements to guide therapy. Costs of gene-based therapies and genetic testing were rated the most significant barriers. The ratings of several elements and barriers were associated with perceived availability of personalized medicine across subpopulations.

CONCLUSION

While physicians hold differing views about the availability and implementation of personalized medicine, they likewise establish complex relationships between race/ethnicity and personalized medicine that may carry serious implications for its clinical success.

Impact of point-of-care testing for CYP2C19 on platelet inhibition in patients with acute coronary syndrome and early dual antiplatelet therapy in the emergency setting

AIMS

Only limited data exist about the role of point of care CYP2C19 testing in the acute setting in the early phase of acute coronary syndromes (ACS). Therefore, the present study was designed to investigate the impact of CYP2C19 loss-of-function point-of-care (POC) genotyping in patients presenting with acute coronary syndromes (ACS) and treated with dual antiplatelet therapy in the emergency setting.

METHODS AND RESULTS

137 subjects with ACS scheduled for percutaneous coronary intervention were consecutively enrolled. Pre- and on-treatment platelet aggregation was assessed by multiple electrode aggregometry (MEA) after stimulation with adenosine diphosphate (ADP). Patients were loaded according to current guideline adherent indications and contraindications for use of P2Y12 inhibitors in ACS. POC genotyping for CYP2C19*2 was performed in the emergency room after obtaining a buccal swab using the Spartan RX CYP2C19 system and obtaining patient's informed consent. Prasugrel and ticagrelor treated patients had significantly lower PR compared to clopidogrel-treated patients. The benefits of prasugrel and ticagrelor compared to clopidogrel treated patients in terms of platelet inhibition were more pronounced in CYP2C19*2 carriers. Non-carriers showed similar inhibition regardless of particular P2Y12 inhibitor treatment. Statistical analyses adjusting for factors associated with response (e.g. smoking) revealed that CYP2C19*2 allele carrier status and loading with different type of P2Y12 receptor blockers were significant predictors of on-treatment platelet reactivity in the early phase of ACS.

CONCLUSION

The results of this pilot study of treatment of patients in the early phase of ACS indicate that CYP2C19*2 POC genotyping might help to identify patients at risk with poor response to clopidogrel treatment, thereby benefiting from reloading and switching to alternative P2Y12 receptor inhibition.

Pharmacogenomics of human P450 oxidoreductase

Cytochrome P450 oxidoreductase (POR) supports reactions of microsomal cytochrome P450 which metabolize drugs and steroid hormones. Mutations in POR cause disorders of sexual development. P450 oxidoreductase deficiency (PORD) was initially identified in patients with Antley–Bixler syndrome (ABS) but now it has been established as a separate disorder of sexual development (DSD). Here we are summarizing the work on variations in POR related to metabolism of drugs and xenobiotics. We have compiled mutation data on reported cases of PORD from clinical studies. Mutations found in patients with defective steroid profiles impact metabolism of steroid hormones as well as drugs. Some trends are emerging that establish certain founder mutations in distinct populations, with Japanese (R457H), Caucasian (A287P), and Turkish (399–401) populations showing repeated findings of similar mutations. Most other mutations are found as single occurrences. A large number of different variants in POR gene with more than 130 amino acid changes are now listed in databases. Among the polymorphisms, the A503V is found in about 30% of all alleles but there are some differences across different population groups.

Pharmacogenovigilance: a pharmacogenomics pharmacovigilance program

In this report, we review the importance of pharmacovigilance in detecting postmarketing adverse drug events and the potential for developing pharmacogenovigilance programs by integrating pharmacogenomics with pharmacovigilance. We propose to start developing such a program in primary healthcare systems that use basic features of electronic medical records and have access to large numbers of patients commonly prescribed drugs. Such programs, if carefully designed, may grow over time and hopefully enhance the collection and interpretation of useful data for the clinical applications of pharmacogenomics testing.

Genetic biomarkers in epilepsy

The identification of valid biomarkers for outcome prediction of diseases and improvement of drug response, as well as avoidance of side effects is an emerging field of interest in medicine. The concept of individualized therapy is becoming increasingly important in the treatment of patients with epilepsy, as predictive markers for disease prognosis and treatment outcome are still limited. Currently, the clinical decision process for selection of an antiepileptic drug (AED) is predominately based on the patient's epileptic syndrome and side effect profiles of the AEDs, but not on effectiveness data. Although standard dosages of AEDs are used, supplemented, in part, by therapeutic monitoring, the response of an individual patient to a specific AED is generally unpredictable, and the standard care of patients in antiepileptic treatment is more or less based on trial and error. Therefore, there is an urgent need for valid predictive biomarkers to guide patient-tailored individualized treatment strategies in epilepsy, a research area that is still in its infancy. This review focuses on genomic factors as part of an individual concept for AED therapy summarizing examples that influence the prognosis of the disease and the response to AEDs, including side effects.

Cytochrome P450 Enzyme Metabolites in Lead Discovery and Development

The cytochrome P450 (CYP) enzymes are a versatile superfamily of heme-containing monooxygenases, perhaps best known for their role in the oxidation of xenobiotic compounds. However, due to their unique oxidative chemistry, CYPs are also important in natural product drug discovery and in the generation of active metabolites with unique therapeutic properties. New tools for the analysis and production of CYP metabolites, including microscale analytical technologies and combinatorial biosynthesis, are providing medicinal chemists with the opportunity to use CYPs as a novel platform for lead discovery and development. In this review, we will highlight some of the recent examples of drug leads identified from CYP metabolites and the exciting possibilities of using CYPs as catalysts for future drug discovery.

Tamoxifen integromics and personalized medicine: dynamic modular transformations underpinning response to tamoxifen in breast cancer treatment

Recent advances in pharmacogenomics technologies allow bold steps to be taken towards personalized medicine, more accurate health planning, and personalized drug development. In this framework, systems pharmacology network-based approaches offer an appealing way for integrating multi-omics data and set the basis for defining systems-level drug response biomarkers. On the road to individualized tamoxifen treatment in estrogen receptor-positive breast cancer patients, we examine the dynamics of the attendant pharmacological response mechanisms. By means of an "integromics" network approach, we assessed the tamoxifen effect through the way the high-order organization of interactome (i.e., the modules) is perturbed. To accomplish that, first we integrated the time series transcriptome data with the human protein interaction data, and second, an efficient module-detecting algorithm was applied onto the composite graphs. Our findings show that tamoxifen induces severe modular transformations on specific areas of the interactome. Our modular biomarkers in response to tamoxifen attest to the immunomodulatory role of tamoxifen, and further reveal that it deregulates cell cycle and apoptosis pathways, while coordinating the proteasome and basal transcription factors. To the best of our knowledge, this is the first report that informs the fields of personalized medicine and clinical pharmacology about the actual dynamic interactome response to tamoxifen administration.

Multiomics medicine in oncology: assessing effectiveness, cost–effectiveness and future research priorities for the molecularly unique individual

The development of genomic technologies has ushered in the era of pharmacogenomics. However, discoveries and clinical use of targeted therapies are still in their infancy. A focus on monogenic pharmacogenetic traits may contribute to this lack of progress. Variation in drug response is likely a complex paradigm involving not only genomic factors but proteomic, metabolomic and epigenomic influences. The incorporation of these omics elements into pharmaceutical development and clinical decision-making will ultimately require the use of methods to determine clinical and economic value. Current methodologies and guidelines for determining clinical effectiveness and cost–effectiveness may have limited applicability to the increasingly personalized nature of omics treatment strategies. Using examples from oncology, this article argues for the adaptation and tailoring of three existing methods for ensuring development and clinical use of multiomics-guided therapies that are effective, safe and offer value for money.

The letrozole phase 1 metabolite carbinol as a novel probe drug for UGT2B7

Carbinol [4,4'-(hydroxymethylene)dibenzonitrile] is the main phase 1 metabolite of letrozole, a nonsteroidal aromatase inhibitor used for endocrine therapy in postmenopausal breast cancer. We elucidated the contribution of UDP-glucuronosyltransferase (UGT) isoforms on the glucuronidation of carbinol. Identification of UGT isoforms was performed using a panel of recombinant human UGT enzymes. Kinetic studies were done in recombinant human UGT2B7 and pooled human liver microsomes (HLMs). A liquid chromatography-tandem mass spectrometry method was used for detection of metabolites. To assess the impact of UGT2B7*2, we determined the carbinol glucuronidation activity using HLM as well as UGT2B7 protein expression in 148 human livers. Moreover, we analyzed the plasma concentrations of 60 letrozole-treated breast cancer patients. We identified UGT2B7 as the predominant UGT isoform involved in carbinol glucuronidation. In HLMs and recombinant UGT2B7, we determined K(m) values (9.99 and 9.56 µM) and V(max) values (3430 and 2399 pmol/min per milligram of protein), respectively. In the set of 148 human livers, carbinol glucuronidation activity significantly correlated with UGT2B7 protein as determined by Western blotting (r(s) = 0.5088, P < 0.0001). Neither carbinol glucuronidation activity (*1/*1: n = 25, 2434 ± 1018; *1/*2: n = 80, 2356 ± 1372; *2/*2: n = 43, 2251 ± 1421 pmol/min per milligram of protein) nor UGT2B7 protein expression was altered by the UGT2B7*2 genotype. No impact of UGT2B7*2 on plasma levels of carbinol and carbinol-gluc [bis(4-cyanophenyl)methyl hexopyranosiduronic acid] in 60 letrozole-treated patients was found. Taken together, these findings suggest carbinol as a novel in vitro probe substrate for UGT2B7. In vitro and in vivo data suggest a lack of influence of the UGT2B7*2 polymorphism on carbinol glucuronidation.

Genomics and transcriptomics in drug discovery

The popularization of genomic high-throughput technologies is causing a revolution in biomedical research and, particularly, is transforming the field of drug discovery. Systems biology offers a framework to understand the extensive human genetic heterogeneity revealed by genomic sequencing in the context of the network of functional, regulatory and physical protein-drug interactions. Thus, approaches to find biomarkers and therapeutic targets will have to take into account the complex system nature of the relationships of the proteins with the disease. Pharmaceutical companies will have to reorient their drug discovery strategies considering the human genetic heterogeneity. Consequently, modeling and computational data analysis will have an increasingly important role in drug discovery.

Genetic variation of platelet function and pharmacology: an update of current knowledge

Platelets are critically involved in atherosclerosis and acute thrombosis. The platelet phenotype shows a wide variability documented by the inherited difference of platelet reactivity, platelet volume and count and function of platelet surface receptors. Several candidate genes have been put into focus and investigated for their functional and prognostic role in healthy individuals and patients with cardiovascular (CV) disease treated with antiplatelet agents. In addition to genetic variation, other clinical, disease-related and demographic factors are important so-called non-genetic factors. Due to the small effect sizes of single nucleotide polymorphisms (SNP) in candidate genes and due to the low allele frequencies of functional relevant candidate SNPs, the identification of genetic risk factors with high predictive values generally depends on the sample size of study cohorts. In the post-genome era new array and bioinformatic technologies facilitate high throughput genome-wide association studies (GWAS) for the identification of novel candidate genes in large cardiovascular cohorts. One of the crucial aspects of platelet genomic studies is the precise definition of a specific clinical phenotype (e.g. stent thrombosis) as this will impact importantly the findings of genomic studies like GWAS. Here, we provide an update on genetic variation of platelet receptors and drug metabolising enzymes under specific consideration of data derived by GWAS. The potential impact of this information and the role in personalised therapeutic concepts will be discussed.

Identifying health effects of exposure to trichloroacetamide using transcriptomics and metabonomics in mice ( Mus musculus )

Microarray-based transcriptomics and one-dimensional proton nuclear magnetic resonance ((1)H NMR) based metabonomics approaches were employed to investigate the health effects of nitrogenous disinfection byproducts (N-DBPs) of trichloroacetamide (TCAcAm) on mice. Mice were exposed to TCAcAm at concentrations of 50, 500, and 5000 μg/L for 90 days, and hepatic transcriptome and serum metabonome and histopathological parameters were detected in comparison with those of control. TCAcAm esposures resulted in liver inflammation, weight loss (in 5000 ug/L TCAcAm group), and alterations in hepatic transcriptome and serum metabonome. Based on the differentially expressed genes and altered metabolites, several significant pathways were identified, which are associated with lipid, xenobiotics, amino acid and energy metabolism, and cell process. Moreover, integrative pathway analyses revealed that TCAcAm exposure in this study induced hepatotoxicity and cytotoxicity. These results also highlight the noninvasive prospect of transcriptomic and metabonomic approaches in evaluating the health risk of emerging N-DBPs.

Systems approaches in risk assessment

Adverse drug events (ADEs) remain a universal problem in drug development, regulatory review, and clinical practice with a substantial financial burden on the global health-care system. Recent advances in molecular and "omics" technologies, along with online databases and bioinformatics, have enabled a more integrative approach to understanding drug-target (protein) interactions, both desirable and undesirable, within a biological system. This has led to the development of systems approaches to risk assessment in an attempt to complement and improve on contemporary observational and predictive strategies for assessing risk. Although still in an evolutionary phase, systems approaches have the potential to markedly advance our understanding of ADEs and ability to predict them. Systems approaches will also move personalized medicine forward by enabling better identification of individual and subgroup risk factors.

Polymorphisms of Phase I and Phase II Enzymes and Breast Cancer Risk

Breast cancer is a complex disease which is provoked by a multitude of exogenous and endogenous factors including genetic variations. Recent genome-wide association studies identified a set of more than 18 novel low penetrant susceptibility loci, however, a limitation of this powerful approach is the hampered analysis of polymorphisms in DNA sequences with a high degree of similarity to other genes or pseudo genes. Since this common feature affects the majority of the highly polymorphic genes encoding phase I and II enzymes the retrieval of specific genotype data requires adapted amplification methods. With regard to breast cancer these genes are of certain interest due to their involvement in the metabolism of carcinogens like exogenous genotoxic compounds or steroid hormones. The present review summarizes the observed effects of functional genetic variants of phase I and II enzymes in well designed case control studies to shed light on their contribution to breast cancer risk.