Omics and drug response

Applications of chromatographic methods in metabolomics: A review

Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.

Trifloxystrobin induced developmental toxicity by disturbing the ABC transporters, carbohydrate and lipid metabolism in adult zebrafish

The environmental risks of trifloxystrobin (TR) have drawn attention because of its multiplex toxicity on aquatic organisms, but few studies have paid close attention to its chronic toxicity at environmental concentrations. In present study, histopathology, metabolomics and transcriptomics were comprehensively performed to investigate the toxic effects and biological responses on adult zebrafish after exposure to 0.1, 1 and 10 μg/L TR for 21 d. Results demonstrated long-term exposure of TR affected zebrafish liver, ovary and heart development. Metabolomics revealed 0.1, 1 and 10 μg/L TR simultaneously decreased the carbohydrates enriched in glucose metabolism and ABC transporters pathways, such as glycogen, lactose, lactulose, maltose, maltotriose, d-trehalose, while 1 μg/L and 10 μg/L TR significantly increased many metabolites related to glycerophospholipid and sphingolipid metabolism in zebrafish liver. Transcriptomics showed TR activated the transcription of the Abcb4, Abcb5 and Abcb11 involved in ABC transporters, Pck1, Pfk, Hk, Gyg1a and Pygma related to glucose metabolism, as well as the Lpcat1, Lpcat4, Gpat2, Cers and Sgms in glycerophospholipid and sphingolipid metabolism. Results further demonstrated high concentration of TR strongly affected the DNA repair system, while low dose of TR caused pronounced effects on cardiomyocytes and oocyte regulation pathways at transcriptional levels. The results indicated the abnormal liver, gonad and heart development caused by TR might be ascribed to the disturbance of carbohydrates and lipid metabolism mediating by the Abcb4, Abcb5 and Abcb11 ABC transporters, and long-term exposure of environmental concentration of TR was sufficient to affect zebrafish normal metabolism and development.

Systems pharmacodynamic model of combined gemcitabine and trabectedin in pancreatic cancer cells. Part I.Çô Effects on signal transduction pathways related to tumor growth

Pancreatic ductal adenocarcinoma (PDAC) is often chemotherapy-resistant, and novel drug combinations would fill an unmet clinical need. Previously we reported synergistic cytotoxic effects of gemcitabine and trabectedin on pancreatic cancer cells, but underlying protein-level interaction mechanisms remained unclear. We employed a reliable, sensitive, comprehensive, quantitative, high-throughput IonStar proteomic workflow to investigate the time course of gemcitabine and trabectedin effects, alone and combined, upon pancreatic cancer cells. MiaPaCa-2 cells were incubated with vehicle (controls), gemcitabine, trabectedin, and their combinations over 72 hours. Samples were collected at intervals and analyzed using the label-free IonStar liquid chromatography-mass spectrometry (LC-MS/MS) workflow to provide temporal quantification of protein expression for 4,829 proteins in four experimental groups. To characterize diverse signal transduction pathways, a comprehensive systems pharmacodynamic (SPD) model was developed. The analysis is presented in two parts. Here, Part I describes drug responses in cancer cell growth and migration pathways included in the full model: receptor tyrosine kinase- (RTK), integrin-, G-protein coupled receptor- (GPCR), and calcium-signaling pathways. The developed model revealed multiple underlying mechanisms of drug actions, provides insight into the basis of drug interaction synergism, and offers a scientific rationale for potential drug combination strategies.

Modeling Clinical Phenotype Variability: Consideration of Genomic Variations, Computational Methods, and Quantitative Proteomics

Advances in biomedical and computer technologies have presented the modeling community the opportunity for mechanistically modeling and simulating the variability in a disease phenotype or in a drug response. The capability to quantify response variability can inform a drug development program. Quantitative systems pharmacology scientists have published various computational approaches for creating virtual patient populations (VPops) to model and simulate drug response variability. Genomic variations can impact disease characteristics and drug exposure and response. Quantitative proteomics technologies are increasingly used to facilitate drug discovery and development and inform patient care. Incorporating variations in genomics and quantitative proteomics may potentially inform creation of VPops to model and simulate virtual patient trials, and may help account for, in a predictive manner, phenotypic variations observed clinically.

Histology and metabonomics reveal the toxic effects of kresoxim-methyl on adult zebrafish

Studies have shown that kresoxim-methyl (KM) and other strobilurin fungicides have toxic effects on aquatic organisms. However, the potential deleterious effects of kresoxim-methyl (KM) on adult zebrafish regarding the ecological risk of environmental concentration remain unclear. Here, the histology and untargeted metabonomics was used to investigate the adverse effect on female zebrafish after exposure to KM at environmental concentration, aquatic life benchmark and one-half LC₅₀ of adult zebrafish. Results demonstrated KM affected zebrafish liver, ovary and intestine development, blurred the boundary between hepatocytes or caused hepatic vacuoles, increased the percentage of perinucleolar oocyte and cortical alveolus oocyte, decreased intestinal goblet cells and disturbed villus and wall integrity after 21 d exposure. Metabonomics showed different concentrations of KM simultaneously influenced the metabolites annotated to vitamin digestion and absorption, serotonergic synapse, retinol metabolism, ovarian steroidogenesis and arachidonic acid (AA) metabolism in zebrafish liver. Results showed the decreased triglyceride and cholesterol levels, as well as the metabolic alterations in amino acid, lipid, vitamin and retinol metabolism caused by KM, might disturb the energy supply for normal liver development and oocyte maturation. In addition, KM altered the transcription of Tdo2a, Tdo2b, Ido1, Cxcl8b, Cyp7a, Cyp11a, Cyp11b, Cyp17a, Cyp19a, Hsd3β, Hsd17β, Pla2, Ptgs2a and Ptgs2b, the level of TG, TC, MDA, IFN, IL6 and Ca²⁺, and the activity of CAT, SOD Ca²⁺-ATPase in zebrafish liver. Moreover, cytoscape analysis suggested the disturbed AA metabolism caused by KM, might interconnect multiple metabolic pathways to share implicated function in the regulation of oocyte maturation and immune response. Current study brought us closer to an incremental understanding of the toxic mechanism of KM on adult zebrafish, indicated there was crosstalk among different regulatory pathways to regulate the metabolic disorders and biologically hazardous effects induced by KM.

Effects of SLCO1B1 Genetic Variant on Metabolite Profile in Participants on Simvastatin Treatment

Organic-anion-transporting polypeptide 1B1 (OATP1B1), encoded by the solute carrier organic anion transporter family member 1B1 gene (SLCO1B1), is highly expressed in the liver and transports several endogenous metabolites into the liver, including statins. Previous studies have not investigated the association of SLCO1B1 rs4149056 variant with the risk of type 2 diabetes (T2D) or determined the metabolite signature of the C allele of SLCO1B1 rs4149056 (SLCO1B1 rs4149056-C allele) in a large randomly selected population. SLCO1B1 rs4149056-C inhibits OATP1B1 transporter and is associated with increased levels of blood simvastatin concentrations. Our study is to first to show that SLCO1B1 rs4149056 variant is not significantly associated with the risk of T2D, suggesting that simvastatin has a direct effect on the risk of T2D. Additionally, we investigated the effects of SLCO1B1 rs4149056-C on plasma metabolite concentrations in 1373 participants on simvastatin treatment and in 1368 age- and body-mass index (BMI)-matched participants without any statin treatment. We found 31 novel metabolites significantly associated with SLCO1B1 rs4149056-C in the participants on simvastatin treatment and in the participants without statin treatment. Simvastatin decreased concentrations of dicarboxylic acids, such as docosadioate and dodecanedioate, that may increase beta- and peroxisomal oxidation and increased the turnover of cholesterol into bile acids, resulting in a decrease in steroidogenesis due to limited availability of cholesterol for steroid synthesis. Our findings suggest that simvastatin exerts its effects on the lowering of low-density lipoprotein (LDL) cholesterol concentrations through several distinct pathways in the carriers of SLCO1B1 rs4149056-C, including dicarboxylic acids, bile acids, steroids, and glycerophospholipids.

Pharmacogenetics of Drugs Used in the Treatment of Cancers

Pharmacogenomics is based on the understanding of the individual differences in drug use, the response to drug therapy (efficacy and toxicity), and the mechanisms underlying variable drug responses. The identification of DNA variants which markedly contribute to inter-individual variations in drug responses would improve the efficacy of treatments and decrease the rate of the adverse side effects of drugs. This review focuses only on the impact of polymorphisms within drug-metabolizing enzymes on drug responses. Anticancer drugs usually have a very narrow therapeutic index; therefore, it is very important to use appropriate doses in order to achieve the maximum benefits without putting the patient at risk of life-threatening toxicities. However, the adjustment of the appropriate dose is not so easy, due to the inheritance of specific polymorphisms in the genes encoding the target proteins and drug-metabolizing enzymes. This review presents just a few examples of such polymorphisms and their impact on the response to therapy.

Establishing Serum Reference Ranges for Antihypertensive Drugs

BACKGROUND

Therapeutic drug monitoring (TDM) involves the measurement of serum drug concentrations to optimize pharmacotherapy. Traditionally, blood pressure measurements alone, and not TDM, have been used to evaluate the antihypertensive drug response. However, approximately 50% of hypertensive patients treated with lifestyle changes and antihypertensive drugs fail to achieve blood pressure control. Serum drug concentration measurements could be useful to select the optimal drugs in adjusted doses and to identify nonadherence. Implementation of TDM in clinical routine for antihypertensive drugs depends on established serum reference ranges.

METHODS

Commonly used antihypertensive drugs were identified based on prescription data. The authors performed a review of authoritative literature on reported serum drug concentrations and calculated expected concentrations from previously reported pharmacokinetic parameters with commonly prescribed daily doses. Finally, serum drug concentrations in samples from patients undergoing antihypertensive treatment were measured.

RESULTS

Serum reference ranges for 24 frequently used antihypertensive drugs were established based on results from 3 approaches.

CONCLUSIONS

Serum drug concentration measurements, interpreted in light of the established reference ranges, together with blood pressure measurements and other clinical data, may help identify nonadherent patients and tailor individual antihypertensive treatment when deviant drug responses appear in line with the concept of personalized medicine.

Decoding variants in drug-metabolizing enzymes and transporters in solid tumor patients by whole-exome sequencing

Background

Pharmacogenetics is involved in customizing therapy according to the genetic makeup of an individual, and is applicable for chemotherapy, radiotherapy as well as targeted therapy. Drug metabolizing enzymes (DMEs) involving both phase I, and phase II reactions are widely studied. Our study was involved in whole exome sequencing (WES) of cancer patients, followed by analysis for identifying key variations in DMEs, and associated transporters that have a potential impact on treatment outcome.

Methodology

A total of 181 solid tumor patients at stage >/= III were subjected to WES by the SureSelect^XT Human All Exon V6 + UTR library preparation kit, and sequencing in the Illumina NextSeq 550 system. Bioinformatics analysis involved use of GATK pipeline, and the variants were further assessed for population frequency, functional impact with annovar insilico algorithms. Further variant information from significant DMEs, and transporters were extracted and analyzed with PharmGKB to assess level of evidence and infer their impact on the pathways involved in drug response.

Results

The total study cohort of 181 solid tumor patients included 60 males, and 121 females respectively. Among DMEs, deleterious mutation in dihydropyrimidine dehydrogenase (DPYD; rs67376798), solute carrier organic anion transporter family member 1B1 (SLCO1B1*5), and cytochrome P450 2D6 (CYP2D6*10) associated with metabolism of anticancer drugs was detected to be in high frequency of 26%, 21% and 25% respectively.

Conclusion

Our analysis detected variations in both phase I and phase II DMEs, as well as associated transporter genes which has been documented to reduce drug efficacy, as well as cause grade 3 and 4 toxicity. Our study reiterates the significance of pharmacogenomics in stratifying patients for appropriate therapy regimen focused at better treatment outcome and quality of life.

COVID19 Drug Repository: text-mining the literature in search of putative COVID19 therapeutics

The recent outbreak of COVID-19 has generated an enormous amount of Big Data. To date, the COVID-19 Open Research Dataset (CORD-19), lists ∼130,000 articles from the WHO COVID-19 database, PubMed Central, medRxiv, and bioRxiv, as collected by Semantic Scholar. According to LitCovid (11 August 2020), ∼40,300 COVID19-related articles are currently listed in PubMed. It has been shown in clinical settings that the analysis of past research results and the mining of available data can provide novel opportunities for the successful application of currently approved therapeutics and their combinations for the treatment of conditions caused by a novel SARS-CoV-2 infection. As such, effective responses to the pandemic require the development of efficient applications, methods and algorithms for data navigation, text-mining, clustering, classification, analysis, and reasoning. Thus, our COVID19 Drug Repository represents a modular platform for drug data navigation and analysis, with an emphasis on COVID-19-related information currently being reported. The COVID19 Drug Repository enables users to focus on different levels of complexity, starting from general information about (FDA-) approved drugs, PubMed references, clinical trials, recipes as well as the descriptions of molecular mechanisms of drugs' action. Our COVID19 drug repository provide a most updated world-wide collection of drugs that has been repurposed for COVID19 treatments around the world.

Effect of short-chain chlorinated paraffins on metabolic profiling of male SD rats

The toxic effect of high-dose of short-chain chlorinated paraffins (SCCPs) has been extensively studied, however the possible health risks induced by SCCPs at low-dose remain largely unknown. In this study, a comprehensive toxicology analysis of SCCPs was conducted with the exposure levels from the environmental dose to the Lowest Observed Adverse Effect Level (LOAEL) of 100 mg/kg/day. General toxicology analysis revealed inconspicuous toxicity of the environmental dose of SCCPs, high dose SCCP exposure inhibited the growth rate and increased the liver weight of rat. Metabolomics analysis indicated that SCCP-induced toxicity was triggered at environmentally relevant doses. First, inhibition of energy metabolism was observed with the decrease in blood glucose and the dysfunction of TCA cycle, which may have contributed to lower body weight gain in rats exposed to a high dose of SCCPs. Second, the increase of free fatty acids indicated the acceleration of lipid metabolism to compensate for the energy deficiency caused by hypoglycemia. Lipid oxidative metabolism inevitably leads to oxidative stress and stimulates the up-regulation of antioxidant metabolites such as GSH and GSSH. The up-regulation of polyunsaturated fatty acids (PUFAs) and phospholipids composed of arachidonic acid indicates the occurrence of inflammation. Dysfunction of lipid metabolism can be an indicator of SCCP-induced liver injury.

Genetic and Epigenetic Regulation of Organic Cation Transporters

Organic cation transporters (OCTs) of the solute carrier family (SLC) 22 are the subject of intensive research because they mediate the transport of many clinically-relevant drugs such as the antidiabetic agent metformin, the opioid tramadol, and the antimigraine agent sumatriptan. OCT1 (SLC22A1) and OCT2 (SLC22A2) are highly expressed in human liver and kidney, respectively, while OCT3 (SLC22A3) shows a broader tissue distribution. As suggested from studies using knockout mice, particularly OCT2 and OCT3 appear to be of relevance for brain physiological function and drug response. The knowledge of genetic factors and epigenetic modifications affecting function and expression of OCTs is important for a better understanding of disease mechanisms and for personalized treatment of patients. This review briefly summarizes the impact of genetic variants and epigenetic regulation of OCTs in general. A comprehensive overview is given on the consequences of OCT2 and OCT3 knockout in mice and the implications of genetic OCT2 and OCT3 variants on central nervous system function in humans.

Nursing Personnel in the Era of Personalized Healthcare in Clinical Practice

Personalized, stratified, or precision medicine (PM) introduces a new era in healthcare that tries to identify and predict optimum treatment outcomes for a patient or a cohort. It also introduces new scientific terminologies regarding therapeutic approaches and the need of their adoption from healthcare providers. Till today, evidence-based practice (EBP) was focusing on population averages and their variances among cohorts for clinical values that are essential for optimizing healthcare outcome. It can be stated that EBP and PM are complementary approaches for a modern healthcare system. Healthcare providers through EBP often see the forest (population averages) but miss the trees (individual patients), whereas utilization of PM may not see the forest for the trees. Nursing personnel (NP) play an important role in modern healthcare since they are consulting, educating, and providing care to patients whose needs often needs to be individualized (personalized nursing care, PNC). Based on the clinical issues earlier addressed from clinical pharmacology, EBP, and now encompassed in PM, this review tries to describe the challenges that NP have to face in order to meet the requisites of the new era in healthcare. It presents the demands that should be met for upgrading the provided education and expertise of NP toward an updated role in a modern healthcare system.

Molecular Basis of CYP19A1 Deficiency in a 46,XX Patient With R550W Mutation in POR: Expanding the PORD Phenotype

CONTEXT

Mutations in cytochrome P450 oxidoreductase (POR) cause a form of congenital adrenal hyperplasia (CAH). We report a novel R550W mutation in POR identified in a 46,XX patient with signs of aromatase deficiency.

OBJECTIVE

Analysis of aromatase deficiency from the R550W mutation in POR.

DESIGN, SETTING, AND PATIENT

Both the child and the mother had signs of virilization. Ultrasound revealed the presence of uterus and ovaries. No defects in CYP19A1 were found, but further analysis with a targeted Disorders of Sexual Development NGS panel (DSDSeq.V1, 111 genes) on a NextSeq (Illumina) platform in Madrid and Barcelona, Spain, revealed compound heterozygous mutations c.73_74delCT/p.L25FfsTer93 and c.1648C > T/p.R550W in POR. Wild-type and R550W POR were produced as recombinant proteins and tested with multiple cytochrome P450 enzymes at University Children's Hospital, Bern, Switzerland.

MAIN OUTCOME MEASURE AND RESULTS

POR-R550W showed 41% of the WT activity in cytochrome c and 7.7% activity for reduction of MTT. Assays of CYP19A1 showed a severe loss of activity, and CYP17A1 as well as CYP21A2 activities were also lost by more than 95%. Loss of CYP2C9, CYP2C19, and CYP3A4 activities was observed for the R550W-POR. Predicted adverse effect on aromatase activity as well as a reduction in binding of NADPH was confirmed.

CONCLUSIONS

Pathological effects due to POR-R550W were identified, expanding the knowledge of molecular pathways associated with aromatase deficiency. Screening of the POR gene may provide a diagnosis in CAH without defects in genes for steroid metabolizing enzymes.

The Importance of Precision Medicine in Type 2 Diabetes Mellitus (T2DM): From Pharmacogenetic and Pharmacoepigenetic Aspects

BACKGROUND

Type 2 Diabetes Mellitus (T2DM) is a worldwide disorder as the most important challenges of health-care systems. Controlling the normal glycaemia greatly profit long-term prognosis and gives explanation for early, effective, constant, and safe intervention.

MATERIAL AND METHODS

Finding the main genetic and epigenetic profile of T2DM and the exact molecular targets of T2DM medications can shed light on its personalized management. The comprehensive information of T2DM was earned through the genome-wide association study (GWAS) studies. In the current review, we represent the most important candidate genes of T2DM like CAPN10, TCF7L2, PPAR-γ, IRSs, KCNJ11, WFS1, and HNF homeoboxes. Different genetic variations of a candidate gene can predict the efficacy of T2DM personalized strategy medication.

RESULTS

SLCs and AMPK variations are considered for metformin, CYP2C9, KATP channel, CDKAL1, CDKN2A/2B and KCNQ1 for sulphonylureas, OATP1B, and KCNQ1 for repaglinide and the last but not the least ADIPOQ, PPAR-γ, SLC, CYP2C8, and SLCO1B1 for thiazolidinediones response prediction.

CONCLUSION

Taken everything into consideration, there is an extreme need to determine the genetic status of T2DM patients in some known genetic region before planning the medication strategies.

Deep learning for drug response prediction in cancer

Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of paramount importance for precision medicine. Machine learning(ML) algorithms can be trained on high-throughput screening data to develop models that are able to predict the response of cancer cell lines and patients to novel drugs or drug combinations. Deep learning (DL) refers to a distinct class of ML algorithms that have achieved top-level performance in a variety of fields, including drug discovery. These types of models have unique characteristics that may make them more suitable for the complex task of modeling drug response based on both biological and chemical data, but the application of DL to drug response prediction has been unexplored until very recently. The few studies that have been published have shown promising results, and the use of DL for drug response prediction is beginning to attract greater interest from researchers in the field. In this article, we critically review recently published studies that have employed DL methods to predict drug response in cancer cell lines. We also provide a brief description of DL and the main types of architectures that have been used in these studies. Additionally, we present a selection of publicly available drug screening data resources that can be used to develop drug response prediction models. Finally, we also address the limitations of these approaches and provide a discussion on possible paths for further improvement. Contact:  mrocha@di.uminho.pt.

Copy number variation profiling in pharmacogenes using panel-based exome resequencing and correlation to human liver expression

Structural variants including copy number variations (CNV) have gained widespread attention, especially in pharmacogenomics but for several genes functional relevance and clinical evidence are still lacking. Detection of CNVs in next-generation sequencing data is challenging but offers widespread applications. We developed a cohort-based CNV detection workflow to extract CNVs from read counts of targeted NGS of 340 genes involved in absorption, distribution, metabolism and excretion (ADME) of drugs. We applied our method to 150 human liver tissue samples and correlated identified CNVs to mRNA expression levels. In total, we identified 445 deletions (73%) and 167 duplications (27%) in 36 pharmacogenes including all well-known CNVs of CYPs, GSTs, SULTs, UGTs, numerous described rare CNVs of CYP2E1, SLC16A3 or UGT2B15 as well as novel observations, e.g., for SLC22A12, SLC22A17 and GPS2 (G Protein Pathway Suppressor 2). We were able to fine-map complex CNVs of CYP2A6 and CYP2D6 with exon resolution. Correlation analysis confirmed known expression patterns for common CNVs and suggested an influence on expression variability for some rare CNVs. Our straightforward CNV detection workflow can be easily applied to any NGS coverage data and helped to analyze CNVs in an ADME-NGS panel of 340 pharmacogenes to improve genotype-phenotype correlations.

Beyond drugs: the evolution of genes involved in human response to medications

The genetic variation of our species reflects human demographic history and adaptation to diverse local environments. Part of this genetic variation affects individual responses to exogenous substances, such as food, pollutants and drugs, and plays an important role in drug efficacy and safety. This review provides a synthesis of the evolution of loci implicated in human pharmacological response and metabolism, interpreted within the theoretical framework of population genetics and molecular evolution. In particular, I review and discuss key evolutionary aspects of different pharmacogenes in humans and other species, such as the relationship between the type of substrates and rate of evolution; the selective pressure exerted by landscape variables or dietary habits; expected and observed patterns of rare genetic variation. Finally, I discuss how this knowledge can be translated directly or after the implementation of specific studies, into practical guidelines.

Variability in Loss of Multiple Enzyme Activities Due to the Human Genetic Variation P284T Located in the Flexible Hinge Region of NADPH Cytochrome P450 Oxidoreductase

Cytochromes P450 located in the endoplasmic reticulum require NADPH cytochrome P450 oxidoreductase (POR) for their catalytic activities. Mutations in POR cause multiple disorders in humans related to the biosynthesis of steroid hormones and also affect drug-metabolizing cytochrome P450 activities. Electron transfer in POR occurs from NADH to FAD to FMN, and the flexible hinge region in POR is essential for domain movements to bring the FAD and FMN close together for electron transfer. We tested the effect of variations in the hinge region of POR to check if the effects would be similar across all redox partners or there will be differences in activities. Here we are reporting the effects of a POR genetic variant P284T located in the hinge region of POR that is necessary for the domain movements and internal electron transfer between co-factors. Human wild-type and P284T mutant of POR and cytochrome P450 proteins were expressed in bacteria, purified, and reconstituted for enzyme assays. We found that for the P284T variant of POR, the cytochrome c reduction activity was reduced to 47% of the WT and MTT reduction was reduced to only 15% of the WT. No impact on ferricyanide reduction activity was observed, indicating intact direct electron transfer from FAD to ferricyanide, but a severe loss of CYP19A1 (aromatase) activity was observed (9% of WT). In the assays of drug-metabolizing cytochrome P450 enzymes, the P284T variant of POR showed 26% activity for CYP2C9, 44% activity for CYP2C19, 23% activity for CYP3A4, and 44% activity in CYP3A5 assays compared to the WT POR. These results indicate a severe effect on several cytochrome P450 activities due to the P284T variation in POR, which suggests a negative impact on both the steroid as well as drug metabolism in the individuals carrying this variation. The negative impact of P284T mutation in the hinge region of POR seems to be due to disruption of FAD to FMN electron transfer. These results further emphasize the importance of hinge region in POR for protein flexibility and electron transfer within POR as well as the interaction of POR with different redox partners.

Personalized laboratory medicine: a patient-centered future approach

In contrast to population-based medical decision making, which emphasizes the use of evidence-based treatment strategies for groups of patients, personalized medicine is based on optimizing treatment at the level of the individual patient. The creation of molecular profiles of individual patients was made possible by the advent of "omics" technologies, based on high throughput instrumental techniques in combination with biostatistics tools and artificial intelligence. The goal of personalized laboratory medicine is to use advanced technologies in the process of preventive, curative or palliative patient management. Personalized medicine does not rely on changes in concentration of a single molecular marker to make a therapeutic decision, but rather on changes of a profile of markers characterizing an individual patient's status, taking into account not only the expected response to treatment of the disease but also the expected response of the patient. Such medical approach promises a more effective diagnostics with more effective and safer treatment, as well as faster recovery and restoration of health and improved cost effectiveness. The laboratory medicine profession is aware of its key role in personalized medicine, but to empower the laboratories, at least an enhancement in cooperation between disciplines within laboratory medicine will be necessary.

Applications of omics and nanotechnology to improve pig embryo production in vitro

An appropriate environment to optimize porcine preimplantation embryo production in vitro is required as genetically modified pigs have become indispensable for biomedical research and agriculture. To provide suitable culture conditions, omics technologies have been applied to elucidate which metabolic substrates and pathways are involved during early developmental processes. Metabolomic profiling and transcriptional analysis comparing in vivo- and in vitro-derived embryos have demonstrated the important role of amino acids during preimplantation development. Transcriptional profiling studies have been helpful in assessing epigenetic reprogramming agents to allow for the correction of gene expression during the cloning process. Along with this, nanotechnology, which is a highly promising field, has allowed for the use of engineered nanoplatforms in reproductive biology. A growing number of studies have explored the use of nanoengineered materials for sorting, labeling, and targeting purposes; which demonstrates their potential to become one of the solutions for precise delivery of molecules into gametes and embryos. Considering the contributions of omics and the recent progress in nanoscience, in this review, we focused on their emerging applications for current in vitro pig embryo production systems to optimize the generation of genetically modified animals.

Building a Hybrid Physical-Statistical Classifier for Predicting the Effect of Variants Related to Protein-Drug Interactions

A key issue in drug design is how population variation affects drug efficacy by altering binding affinity (BA) in different individuals, an essential consideration for government regulators. Ideally, we would like to evaluate the BA perturbations of millions of single-nucleotide variants (SNVs). However, only hundreds of protein-drug complexes with SNVs have experimentally characterized BAs, constituting too small a gold standard for straightforward statistical model training. Thus, we take a hybrid approach: using physically based calculations to bootstrap the parameterization of a full model. In particular, we do 3D structure-based docking on ∼10,000 SNVs modifying known protein-drug complexes to construct a pseudo gold standard. Then we use this augmented set of BAs to train a statistical model combining structure, ligand and sequence features and illustrate how it can be applied to millions of SNVs. Finally, we show that our model has good cross-validated performance (97% AUROC) and can also be validated by orthogonal ligand-binding data.

Investigating the intracellular effects of hyperbranched polycation-DNA complexes on lung cancer cells using LC-MS-based metabolite profiling

Cationic polymers have emerged as a promising alternative to viral vectors in gene therapy. They are cheap to scale up, easy to functionalise and are potentially safer than viral vectors, however many are cytotoxic. The large number of polycations, designed to address the toxicity problem, raises a practical need to develop a fast and reliable method for assessing the safety of these materials. In this regard, metabolomics provides a detailed and comprehensive method that can assess the potential toxicity at the cellular and molecular level. Here, we applied metabolomics to investigate the impact of hyperbranched polylysine, hyperbranched polylysine-co-histidine and branched polyethyleneimine polyplexes at sub-toxic concentrations on the metabolic pathways of A459 and H1299 lung carcinoma cell lines. The study revealed that the polyplexes downregulated metabolites associated with glycolysis and the TCA cycle, and induced oxidative stress in both cell lines. The relative changes of the metabolites indicated that the polyplexes of polyethyleneimine and hyperbranched polylysine affected the metabolism much more than the polyplexes of hyperbranched polylysine-co-histidine. This was in line with transfection results, suggesting a correlation between the toxicity and transfection efficiency of these polyplexes. Our work highlights the importance of the metabolomics approach not just to assess the potential toxicity of polyplexes but also to understand the molecular mechanisms underlying any adverse effects, which could help in designing more efficient vectors.

Clinical Trial: CYP2D6 Related Dose Escalation of Tamoxifen in Breast Cancer Patients With Iranian Ethnic Background Resulted in Increased Concentrations of Tamoxifen and Its Metabolites

Introduction: The polymorphic enzyme cytochrome P450 2D6 (CYP2D6) catalyzes a major step in the bioactivation of tamoxifen. Genotyping of clinically relevant CYP2D6 alleles and subsequent dose adjustment is a promising approach to individualize breast cancer therapy. The aim of this study was to investigate the relationship between the plasma levels of tamoxifen and its metabolites and different CYP2D6 genotypes under standard (20 mg/day) and dose-adjusted therapy (Registration ID in Iranian Registry of Clinical Trials: IRCT2015082323734N1). Materials and Methods: Using TaqMan^® assays common alleles of CYP2D6 (^∗1, ^∗2, ^∗4, ^∗5, ^∗6, ^∗10, ^∗17, and ^∗41) and gene duplication were identified in 134 breast cancer patients. Based on CYP2D6 genotypes patients with an activity score 1 (n = 15) and 0-0.5 (n = 2) were treated with tamoxifen adjusted dosage of 30 and 40 mg/day, respectively. The concentration of tamoxifen and its metabolites before and after 4 and 8 months of dose adjustment were measured using LC-MS/MS technology. Results: At baseline, (Z)-endoxifen plasma concentrations (33 ± 15.5, 28.1 ± 14, 26.6 ± 23.4, 14.3 ± 8.6, and 10.7 ± 5.5 nmol/l for EM/EM, EM/IM, EM/PM, IM/IM and PM/PM, respectively) and the metabolic ratio (Z)-Endoxifen/N-desmethyltamoxifen (0.0558 ± 0.02, 0.0396 ± 0.0111, 0.0332 ± 0.0222, 0.0149 ± 0.0026, and 0.0169 ± 0.0177 for EM/EM, EM/IM, EM/PM, IM/IM, and PM/PM, respectively) correlated with CYP2D6 genotype (Kruskal-Wallis p = 0.013 and p < 0.0001, respectively). Dose escalation to 30 and 40 mg/day in patients with a CYP2D6 activity score of 1 (n = 15) and 0-0.5 (n = 2) resulted in a significant increase in (Z)-endoxifen plasma levels (22.17 ± 24.42, 34.43 ± 26.54, and 35.77 ± 28.89 nmol/l at baseline, after 4 and 8 months, respectively, Friedman p = 0.0388) along with the plasma concentrations of tamoxifen and its other metabolites. No severe side effects were recorded during dose escalation. Conclusion: For the first time, we show the feasibility of dose escalation of tamoxifen in breast cancer patients with compromised CYP2D6 activity and Iranian ethnic background to increase the plasma concentrations of (Z)-endoxifen.

Identification of novel sarcoma risk genes using a two-stage genome wide DNA sequencing strategy in cancer cluster families and population case and control cohorts

Background

Although familial clustering of cancers is relatively common, only a small proportion of familial cancer risk can be explained by known cancer predisposition genes.

Methods

In this study we employed a two-stage approach to identify candidate sarcoma risk genes. First, we conducted whole exome sequencing in three multigenerational cancer families ascertained through a sarcoma proband (n = 19) in order to prioritize candidate genes for validation in an independent case-control cohort of sarcoma patients using family-based association and segregation analysis. The second stage employed a burden analysis of rare variants within prioritized candidate genes identified from stage one in 560 sarcoma cases and 1144 healthy ageing controls, for which whole genome sequence was available.

Results

Variants from eight genes were identified in stage one. Following gene-based burden testing and after correction for multiple testing, two of these genes, ABCB5 and C16orf96, were determined to show statistically significant association with cancer. The ABCB5 gene was found to have a higher burden of putative regulatory variants (OR = 4.9, p-value = 0.007, q-value = 0.04) based on allele counts in sarcoma cases compared to controls. C16orf96, was found to have a significantly lower burden (OR = 0.58, p-value = 0.0004, q-value = 0.003) of regulatory variants in controls compared to sarcoma cases.

Conclusions

Based on these genetic association data we propose that ABCB5 and C16orf96 are novel candidate risk genes for sarcoma. Although neither of these two genes have been previously associated with sarcoma, ABCB5 has been shown to share clinical drug resistance associations with melanoma and leukaemia and C16orf96 shares regulatory elements with genes that are involved with TNF-alpha mediated apoptosis in a p53/TP53-dependent manner. Future genetic studies in other family and population cohorts will be required for further validation of these novel findings.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0808-9) contains supplementary material, which is available to authorized users.

Genome-wide sequence analyses of ethnic populations across Russia

The Russian Federation is the largest and one of the most ethnically diverse countries in the world, however no centralized reference database of genetic variation exists to date. Such data are crucial for medical genetics and essential for studying population history. The Genome Russia Project aims at filling this gap by performing whole genome sequencing and analysis of peoples of the Russian Federation. Here we report the characterization of genome-wide variation of 264 healthy adults, including 60 newly sequenced samples. People of Russia carry known and novel genetic variants of adaptive, clinical and functional consequence that in many cases show allele frequency divergence from neighboring populations. Population genetics analyses revealed six phylogeographic partitions among indigenous ethnicities corresponding to their geographic locales. This study presents a characterization of population-specific genomic variation in Russia with results important for medical genetics and for understanding the dynamic population history of the world's largest country.

Pharmacometrics and systems pharmacology for metabolic bone diseases

Mathematical modelling and simulation (M&S) of drug concentrations, pharmacologic effects and the (patho)physiologic systems within which they interact can be powerful tools for the preclinical, translational and clinical development of drugs. Indeed, the Prescription Drug User Fee Act (PDUFA VI), incorporated as part of the FDA Reauthorization Act of 2017 (FDARA), highlights the goal of advancing model-informed drug development (MIDD). MIDD can benefit development across many drug classes, including for metabolic bone diseases such as osteoporosis, cancer-related and numerous rare metabolic bone diseases; conditions characterized by significant morbidity and mortality. A drought looms in terms of the availability of new drugs to better treat these devastating diseases. This review provides an overview of several M&S approaches ranging from simple pharmacokinetic to integrated pharmacometric and systems pharmacology modelling. Examples are included to illustrate the use of these approaches during the development of several drugs for metabolic bone diseases such as bisphosphonates, denosumab, teriparatide and sclerostin inhibitors (romosozumab and blosozumab).

Accelerating Biologics Manufacturing by Modeling or: Is Approval under the QbD and PAT Approaches Demanded by Authorities Acceptable Without a Digital-Twin?

Innovative biologics, including cell therapeutics, virus-like particles, exosomes,recombinant proteins, and peptides, seem likely to substitute monoclonal antibodies as the maintherapeutic entities in manufacturing over the next decades. This molecular variety causes agrowing need for a general change of methods as well as mindset in the process development stage,as there are no platform processes available such as those for monoclonal antibodies. Moreover,market competitiveness demands hyper-intensified processes, including accelerated decisionstoward batch or continuous operation of dedicated modular plant concepts. This indicates gaps inprocess comprehension, when operation windows need to be run at the edges of optimization. Inthis editorial, the authors review and assess potential methods and begin discussing possiblesolutions throughout the workflow, from process development through piloting to manufacturingoperation from their point of view and experience. Especially, the state-of-the-art for modeling inred biotechnology is assessed, clarifying differences and applications of statistical, rigorousphysical-chemical based models as well as cost modeling. “Digital-twins” are described and effortsvs. benefits for new applications exemplified, including the regulation-demanded QbD (quality bydesign) and PAT (process analytical technology) approaches towards digitalization or industry 4.0based on advanced process control strategies. Finally, an analysis of the obstacles and possiblesolutions for any successful and efficient industrialization of innovative methods from processdevelopment, through piloting to manufacturing, results in some recommendations. A centralquestion therefore requires attention: Considering that QbD and PAT have been required byauthorities since 2004, can any biologic manufacturing process be approved by the regulatoryagencies without being modeled by a “digital-twin” as part of the filing documentation?

Virtual Prototyping and Parametric Design of 3D-Printed Tablets Based on the Solution of Inverse Problem

The problem of designing tablet geometry and its internal structure that results into a specified release profile of the drug during dissolution was considered. A solution method based on parametric programming, inspired by CAD (computer-aided design) approaches currently used in other fields of engineering, was proposed and demonstrated. The solution of the forward problem using a parametric series of structural motifs was first carried out in order to generate a library of drug release profiles associated with each structural motif. The inverse problem was then solved in three steps: first, the combination of basic structural motifs whose superposition provides the closest approximation of the required drug release profile was found by a linear combination of pre-calculated release profiles. In the next step, the final tablet design was constructed and its dissolution curve found computationally. Finally, the proposed design was 3D printed and its dissolution profile was confirmed experimentally. The computational method was based on the numerical solution of drug diffusion in a boundary layer surrounding the tablet, coupled with erosion of the tablet structure encoded by the phase volume function. The tablets were 3D printed by fused deposition modelling (FDM) from filaments produced by hot-melt extrusion. It was found that the drug release profile could be effectively controlled by modifying the tablet porosity. Custom release profiles were obtained by combining multiple porosity regions in the same tablet. The computational method yielded accurate predictions of the drug release rate for both single- and multi-porosity tablets.

Genetic polymorphisms of organic cation transporter 1 (OCT1) and responses to metformin therapy in individuals with type 2 diabetes: A systematic review

BACKGROUND

Metformin is one of the most commonly used drugs for the treatment of type 2 diabetes mellitus (T2DM). Despite its widespread use, there are considerable interindividual variations in metformin response, with about 35% of patients failing to achieve initial glycemic control. These variabilities that reflect phenotypic differences in drug disposition and action may indeed be due to polymorphisms in genes that regulate pharmacokinetics and pharmacodynamics of metformin. Moreover, interethnic differences in drug responses in some cases correspond to substantial differences in the frequencies of the associated pharmacogenomics risk allele.

AIM

This study aims to highlight and summarize the overall effects of organic cation transporter 1(OCT1) polymorphisms on therapeutic responses to metformin and to evaluate the potential role of such polymorphisms in interethnic differences in metformin therapy.

METHODS

We conducted a systematic review according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. We searched for PubMed/MEDLINE, Embase, and CINAHL, relevant studies reporting the effects of OCT1 polymorphisms on metformin therapy in T2DM individuals. Data were extracted on study design, population characteristics, relevant polymorphisms, measure of genetic association, and outcomes. The presence of gastrointestinal side effects, glycated hemoglobin A1 (HbA1c) levels, fasting plasma glucose (FPG), and postprandial plasma glucose (PPG) concentrations after treatment with metformin were chosen as measures of the metformin responses. This systematic review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO).

RESULTS

According to the data extracted, a total of 34 OCT1 polymorphisms were identified in 10 ethnic groups. Significant differences in the frequencies of common alleles were observed among these groups. Met408Val (rs628031) variant was the most extensively explored with metformin responses. Although some genotypes and alleles have been associated with deleterious effects on metformin response, others indeed, exhibited positive effects.

CONCLUSION

Genetic effects of OCT1 polymorphisms on metformin responses were population specific. Further investigations in other populations are required to set ethnicity-specific reference for metformin responses and to obtain a solid basis to design personalized therapeutic approaches for T2DM treatment.

Celecoxib-Induced Self-Assembly of Smart Albumin-Doxorubicin Conjugate for Enhanced Cancer Therapy

Recent years have witnessed the great contributions that drug combination therapy has made for enhanced cancer therapy. However, because of the complicated pharmacokinetics of combined drug formulations, the majority of combination strategies show severe adverse effects at high dosage and poor biodistribution in vivo. To overcome these deficiencies and achieve enhanced cancer therapy, we put forward a method to construct a smart albumin-based nanoplatform, denoted as K237-HSA-DC, for codelivery of cyclooxygenase-2 (COX-2) inhibitor (celecoxib) and chemotherapeutic agent (doxorubicin, DOX). Both in vitro and in vivo studies indicate that K237-HSA-DC exhibits the best therapeutic efficacy on tumor cells compared with all the other formulations. Moreover, K237-HSA-DC shows fewer side effects on normal organs in contrast to other formulations. To understand the reasons behind the improved drug efficacy in depth, we performed a cell metabonomics-based mechanism study and found that celecoxib could enhance the inhibitory effect of DOX on the transport of glucose into cells and then lead to subsequent significant energy metabolism inhibition. Considering the above-mentioned advantages of K237-HSA-DC, we believe the smart albumin-based nanoplatform can serve as a promising drug delivery system for enhanced cancer therapy.

Overcoming multiple myeloma drug resistance in the era of cancer 'omics'

Multiple myeloma (MM) is among the most compelling examples of cancer in which research has markedly improved the length and quality of lives of those afflicted. Research efforts have led to 18 newly approved treatments over the last 12 years, including seven in 2015. However, despite significant improvement in overall survival, MM remains incurable as most patients inevitably, yet unpredictably, develop refractory disease. Recent advances in high-throughput 'omics' techniques afford us an unprecedented opportunity to (1) understand drug resistance at the genomic, transcriptomic, and proteomic level; (2) discover novel diagnostic, prognostic, and therapeutic biomarkers; (3) develop novel therapeutic targets and rational drug combinations; and (4) optimize risk-adapted strategies to circumvent drug resistance, thus bringing us closer to a cure for MM. In this review, we provide an overview of 'omics' technologies in MM biomarker and drug discovery, highlighting recent insights into MM drug resistance gleaned from the use of 'omics' techniques. Moving from the bench to bedside, we also highlight future trends in MM, with a focus on the potential use of 'omics' technologies as diagnostic, prognostic, or response/relapse monitoring tools to guide therapeutic decisions anchored upon highly individualized, targeted, durable, and rationally informed combination therapies with curative potential.

Applying genomics in heart transplantation

While advances in patient care and immunosuppressive pharmacotherapies have increased the lifespan of heart allograft recipients, there are still significant comorbidities post-transplantation and 5-year survival rates are still significant, at approximately 70%. The last decade has seen massive strides in genomics and other omics fields, including transcriptomics, with many of these advances now starting to impact heart transplant clinical care. This review summarizes a number of the key advances in genomics which are relevant for heart transplant outcomes, and we highlight the translational potential that such knowledge may bring to patient care within the next decade.

Network-based identification of microRNAs as potential pharmacogenomic biomarkers for anticancer drugs

As the recent development of high-throughput technologies in cancer pharmacogenomics, there is an urgent need to develop new computational approaches for comprehensive identification of new pharmacogenomic biomarkers, such as microRNAs (miRNAs). In this study, a network-based framework, namely the SMiR-NBI model, was developed to prioritize miRNAs as potential biomarkers characterizing treatment responses of anticancer drugs on the basis of a heterogeneous network connecting drugs, miRNAs and genes. A high area under the receiver operating characteristic curve of 0.820 ± 0.013 was yielded during 10-fold cross validation. In addition, high performance was further validated in identifying new anticancer mechanism-of-action for natural products and non-steroidal anti-inflammatory drugs. Finally, the newly predicted miRNAs for tamoxifen and metformin were experimentally validated in MCF-7 and MDA-MB-231 breast cancer cell lines via qRT-PCR assays. High success rates of 60% and 65% were yielded for tamoxifen and metformin, respectively. Specifically, 11 oncomiRNAs (e.g. miR-20a-5p, miR-27a-3p, miR-29a-3p, and miR-146a-5p) from the top 20 predicted miRNAs were experimentally verified as new pharmacogenomic biomarkers for metformin in MCF-7 or MDA-MB-231 cell lines. In summary, the SMiR-NBI model would provide a powerful tool to identify potential pharmacogenomic biomarkers characterized by miRNAs in the emerging field of precision cancer medicine, which is available at http://lmmd.ecust.edu.cn/database/smir-nbi/.

Systems Pharmacology Dissection of Cholesterol Regulation Reveals Determinants of Large Pharmacodynamic Variability between Cell Lines

In individuals, heterogeneous drug-response phenotypes result from a complex interplay of dose, drug specificity, genetic background, and environmental factors, thus challenging our understanding of the underlying processes and optimal use of drugs in the clinical setting. Here, we use mass-spectrometry-based quantification of molecular response phenotypes and logic modeling to explain drug-response differences in a panel of cell lines. We apply this approach to cellular cholesterol regulation, a biological process with high clinical relevance. From the quantified molecular phenotypes elicited by various targeted pharmacologic or genetic treatments, we generated cell-line-specific models that quantified the processes beneath the idiotypic intracellular drug responses. The models revealed that, in addition to drug uptake and metabolism, further cellular processes displayed significant pharmacodynamic response variability between the cell lines, resulting in cell-line-specific drug-response phenotypes. This study demonstrates the importance of integrating different types of quantitative systems-level molecular measurements with modeling to understand the effect of pharmacological perturbations on complex biological processes.

A Rational Approach to Target the Epidermal Growth Factor Receptor in Glioblastoma

Glioblastoma (GBM) is a deadly brain cancer, and all attempts to control it have failed so far. However, the future looks bright, as we now know the molecular landscape of GBM through the work of The Cancer Genome Atlas (TCGA) program. GBMs exhibit significant inter- and intratumoral heterogeneity, and to control this type of tumor, a personalized approach is required. One target, whose gene is amplified and mutated in a large number of GBMs, is the epidermal growth factor receptor (EGFR). But all attempts to target it have been unsuccessful. We attribute the reason for this failure to the molecular heterogeneity of EGFR in GBM, as well as to the poor brain penetration of previously tested EGFR-Tyrosine Kinase Inhibitors (EGFR-TKIs). In this review, we discuss the molecular heterogeneity of EGFR and provide rational preclinical and clinical guidelines for testing AZD9291, a third generation, irreversible EGFR-TKI with both a high affinity for EGFRvIII and excellent brain penetration.

3D inkjet printing of tablets exploiting bespoke complex geometries for controlled and tuneable drug release

A hot melt 3D inkjet printing method with the potential to manufacture formulations in complex and adaptable geometries for the controlled loading and release of medicines is presented. This first use of a precisely controlled solvent free inkjet printing to produce drug loaded solid dosage forms is demonstrated using a naturally derived FDA approved material (beeswax) as the drug carrier and fenofibrate as the drug. Tablets with bespoke geometries (honeycomb architecture) were fabricated. The honeycomb architecture was modified by control of the honeycomb cell size, and hence surface area to enable control of drug release profiles without the need to alter the formulation. Analysis of the formed tablets showed the drug to be evenly distributed within the beeswax at the bulk scale with evidence of some localization at the micron scale. An analytical model utilizing a Fickian description of diffusion was developed to allow the prediction of drug release. A comparison of experimental and predicted drug release data revealed that in addition to surface area, other factors such as the cell diameter in the case of the honeycomb geometry and material wettability must be considered in practical dosage form design. This information when combined with the range of achievable geometries could allow the bespoke production of optimized personalised medicines for a variety of delivery vehicles in addition to tablets, such as medical devices for example.

ABCB1 genetic variants in leukemias: current insights into treatment outcomes

Despite improvements in treatment of different types of leukemia, not all patients respond optimally for a particular treatment. Some treatments will work better for some, while being harmful or ineffective for others. This is due to genetic variation in the form of single-nucleotide polymorphisms (SNPs) that affect gene expression or function and cause inherited interindividual differences in the metabolism and disposition of drugs. Drug transporters are one of the determinants governing the pharmacokinetic profile of chemotherapeutic drugs. The ABCB1 transporter gene transports a wide range of drugs, including drugs used in leukemia treatment. Polymorphisms in the ABCB1 gene do affect intrinsic resistance and pharmacokinetics of several drugs used in leukemia treatment protocols and thereby affect the efficacy of treatment and event-free survival. This review focuses on the impact of three commonly occurring SNPs (1236C>T, 2677G>T/A, and 3435C>T) of ABCB1 on treatment response of various types of leukemia. From the literature available, some of the genotypes and haplotypes of these SNPs have been found to be potential determinants of interindividual variability in drug disposition and pharmacologic response in different types of leukemia. However, due to inconsistencies in the results observed across the studies, additional studies, considering novel genomic methodologies, comprehensive definition of clinical phenotypes, adequate sample size, and uniformity in all the confounding factors, are warranted.

Genetic findings in sport-related concussions: potential for individualized medicine?

Concussion is a traumatic transient disturbance of the brain. In sport, the initial time and severity of concussion is known giving an opportunity for subsequent analysis. Variability in susceptibility and recovery between individual athletes depends, among other parameters, on genetic factors. The genes-encoding polypeptides that determine incidence, severity and prognosis for concussion are the primary candidates for genetic analysis. Genetic polymorphisms in the genes contributing to plasticity and repair (APOE), synaptic connectivity (GRIN2A), calcium influx (CACNA1E), uptake and deposit of glutamate (SLC17A7) are potential biomarkers of concussion incidence and recovery rate. With catalogued genetic variants, prospective genotyping of athletes at the beginning of their career will allow medical professionals to improve concussion management and return-to-play decisions.

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.