Pharmacogenetic screening for drug therapy: From single gene markers to decision making in the next generation sequencing era

MicroRNAs serve as prediction and treatment-response biomarkers of attention-deficit/hyperactivity disorder and promote the differentiation of neuronal cells by repressing the apoptosis pathway

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder. This study aimed to examine whether miRNA expression abundance in total white blood cells (WBCs) facilitated the identification of ADHD and reflected its response to treatment. Furthermore, whether miRNA markers facilitated the growth of the human cortical neuronal (HCN-2) cells was also investigated. Total WBC samples were collected from 145 patients and 83 controls, followed by RNA extraction and qPCR assays. Subsequently, WBC samples were also collected at the endpoint from ADHD patients who had undergone 12 months of methylphenidate treatment. The determined ΔCt values of 12 miRNAs were applied to develop an ADHD prediction model and to estimate the correlation with treatment response. The prediction model applying the ΔCt values of 12 examined miRNAs (using machine learning algorithm) demonstrated good validity in discriminating ADHD patients from controls (sensitivity: 96%; specificity: 94.2%). Among the 92 ADHD patients completing the 12-month follow-up, miR-140-3p, miR-27a-3p, miR-486-5p, and miR-151-5p showed differential trends of ΔCt values between treatment responders and non-responders. In addition, the in vitro cell model revealed that miR-140-3p and miR-126-5p promoted the differentiation of HCN-2 cells by enhancing the length of neurons and the number of junctions. Microarray and flow cytometry assays confirmed that this promotion was achieved by repressing apoptosis and/or necrosis. The findings of this study suggest that the expression levels of miRNAs have the potential to serve as both diagnostic and therapeutic biomarkers for ADHD. The possible biological mechanisms of these biomarker miRNAs in ADHD pathophysiology were also clarified.

Pharmacogenomic Testing: Clinical Evidence and Implementation Challenges

Pharmacogenomics can enhance patient care by enabling treatments tailored to genetic make-up and lowering risk of serious adverse events. As of June 2019, there are 132 pharmacogenomic dosing guidelines for 99 drugs and pharmacogenomic information is included in 309 medication labels. Recently, the technology for identifying individual-specific genetic variants (genotyping) has become more accessible. Next generation sequencing (NGS) is a cost-effective option for genotyping patients at many pharmacogenomic loci simultaneously, and guidelines for implementation of these data are available from organizations such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG). NGS and related technologies are increasing knowledge in the research sphere, yet rates of genomic literacy remain low, resulting in a widening gap in knowledge translation to the patient. Multidisciplinary teams—including physicians, nurses, genetic counsellors, and pharmacists—will need to combine their expertise to deliver optimal pharmacogenomically-informed care.

Cost-minimization analysis of GSTP1c.313A>G genotyping for the prevention of cisplatin-induced nausea and vomiting: A Bayesian inference approach

Background

Chemotherapy-induced nausea and vomiting are concerning adverse events resulting from cancer treatment, and current guidelines recommend the use of neurokinin-1-selective antagonists, such as fosaprepitant, in highly emetogenic schemes. However, the implementation of this strategy may be limited by the cost of treatment. GSTP1 c.313A>G genotype was recently described as a predictor of vomiting related to high-dose cisplatin. We hypothesized that the inclusion of routine GSTP1 c.313A>G screening may be promising in financial terms, in contrast to the wide-spread use of fosaprepitant.

Methods

A cost-minimization analysis was planned to compare GSTP1 c.313A>G genotyping versus overall fosaprepitant implementation for patients with head and neck cancer under chemoradiation therapy with high-dose cisplatin. A decision analytic tree was designed, and conditional probabilities were calculated under Markov chain Monte Carlo simulations using the Metropolis-Hastings algorithm. The observed data included patients under treatment without fosaprepitant, while priors were derived from published studies.

Results

To introduce screening with real-time polymerase chain reaction, an initial investment of U$ 39,379.97 would be required, with an amortization cost of U$ 7,272.97 per year. The mean cost of standard therapy with fosaprepitant is U$ 243.24 per patient, and although the initial cost of routine genotyping is higher, there is a tendency of progressive minimization at a threshold of 155 patients (Credible interval–CI: 119 to 216), provided more than one sample is incorporated for simultaneous analysis. A resulting reduction of 35.83% (CI: 30.31 to 41.74%) in fosaprepitant expenditures is then expected with the implementation of GSTP1 c.313A>G genotyping.

Conclusion

GSTP1 c.313A>G genotyping may reduce the use of preventive support for chemotherapy induced nausea and lower the overall cost of treatment. Despite the results of this simulation, randomized, interventional studies are required to control for known and unknown confounders as well as unexpected expenses.

Principles of precision medicine and its application in toxicology

Precision medicine is an approach to developing drugs that focuses on employing biomarkers to stratify patients in clinical trials with the goal of improving efficacy and/or safety outcomes, ultimately increasing the odds of clinical success and drug approval. Precision medicine is an important tool for toxicologists to utilize, because its principles can be used to decide whether to pursue a drug target, to understand interindividual differences in response to drugs in both nonclinical and clinical settings, to aid in selecting doses that optimize efficacy or reduce adverse events, and to facilitate understanding of a drug's mode-of-action. Nonclinical models such as the mouse and non-human primate can be used to understand genetic variation and its potential translation to humans, and are available for toxicologists to employ in advance of drugs moving into clinical development. Understanding interindividual differences in response to drugs and how these differences can influence the drug's risk-benefit profile and lead to the identification of biomarkers that enhance patient efficacy and safety is of critical importance for toxicologists today, and in the future, as the fields of pharmacogenomics and genetics continue to advance.

Blood-Bourne MicroRNA Biomarker Evaluation in Attention-Deficit/Hyperactivity Disorder of Han Chinese Individuals: An Exploratory Study

Background: Attention-deficit/hyperactivity disorder (ADHD) is a highly genetic neurodevelopmental disorder, and its dysregulation of gene expression involves microRNAs (miRNAs). The purpose of this study was to identify potential miRNAs biomarkers and then use these biomarkers to establish a diagnostic panel for ADHD. Design and methods: RNA samples from white blood cells (WBCs) of five ADHD patients and five healthy controls were combined to create one pooled patient library and one control library. We identified 20 candidate miRNAs with the next-generation sequencing (NGS) technique (Illumina). Blood samples were then collected from a Training Set (68 patients and 54 controls) and a Testing Set (20 patients and 20 controls) to identify the expression profiles of these miRNAs with real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate both the specificity and sensitivity of the probability score yielded by the support vector machine (SVM) model. Results: We identified 13 miRNAs as potential ADHD biomarkers. The ΔCt values of these miRNAs in the Training Set were integrated to create a biomarker model using the SVM algorithm, which demonstrated good validity in differentiating ADHD patients from control subjects (sensitivity: 86.8%, specificity: 88.9%, AUC: 0.94, p < 0.001). The results of the blind testing showed that 85% of the subjects in the Testing Set were correctly classified using the SVM model alignment (AUC: 0.91, p < 0.001). The discriminative validity is not influenced by patients' age or gender, indicating both the robustness and the reliability of the SVM classification model. Conclusion: As measured in peripheral blood, miRNA-based biomarkers can aid in the differentiation of ADHD in clinical settings. Additional studies are needed in the future to clarify the ADHD-associated gene functions and biological mechanisms modulated by miRNAs.

Hybridization-Induced Aggregation Technology for Practical Clinical Testing: KRAS Mutation Detection in Lung and Colorectal Tumors

KRAS mutations have emerged as powerful predictors of response to targeted therapies in the treatment of lung and colorectal cancers; thus, prospective KRAS genotyping is essential for appropriate treatment stratification. Conventional mutation testing technologies are not ideal for routine clinical screening, as they often involve complex, time-consuming processes and/or costly instrumentation. In response, we recently introduced a unique analytical strategy for revealing KRAS mutations, based on the allele-specific hybridization-induced aggregation (HIA) of oligonucleotide probe-conjugated microbeads. Using simple, inexpensive instrumentation, this approach allows for the detection of any common KRAS mutation in <10 minutes after PCR. Here, we evaluate the clinical utility of the HIA method for mutation detection (HIAMD). In the analysis of 20 lung and colon tumor pathology specimens, we observed a 100% correlation between the KRAS mutation statuses determined by HIAMD and sequencing. In addition, we were able to detect KRAS mutations in a background of 75% wild-type DNA-a finding consistent with that reported for sequencing. With this, we show that HIAMD allows for the rapid and cost-effective detection of KRAS mutations, without compromising analytical performance. These results indicate the validity of HIAMD as a mutation-testing technology suitable for practical clinical testing. Further expansion of this platform may involve the detection of mutations in other key oncogenic pathways.

Effects of UGT1A1 genotype on the pharmacokinetics, pharmacodynamics, and toxicities of belinostat administered by 48-hour continuous infusion in patients with cancer

The histone deacetylase inhibitor belinostat is eliminated through glucuronidation by UGT1A1. Polymorphisms that reduce UGT1A1 function could result in increased belinostat exposure and toxicities. We wanted to determine which single-nucleotide polymorphisms alter belinostat exposure and toxicity. In a phase 1 trial (belinostat over 48 hours in combination with cisplatin and etoposide), belinostat (400, 500, 600, or 800 mg/m(2) /24 h, 48-hour continuous infusion) was administered to patients with cancer in combination with cisplatin and etoposide (n = 25). Patients were genotyped for UGT1A1 variants associated with reduced function: UGT1A1*6, UGT1A1*28, and UGT1A1*60. End points were associations between UGT1A1 genotype and belinostat pharmacokinetics (PK), toxicities, and global protein lysine acetylation (AcK). Belinostat AUC was increased (P = .003), and t1/2 increased (P = .0009) in UGT1A1*28 and UGT1A1*60 carriers who received more than 400 mg/m(2) /24 h. The incidence of grades 3-4 thrombocytopenia (P = .0081) was associated with UGT1A1 polymorphisms. The US Food and Drug Administration-approved package insert recommends dose adjustment of belinostat for UGT1A1*28. However, our data suggest dose adjustment is also necessary for UGT1A1*60. UGT1A1 polymorphisms were associated with increased systemic belinostat exposure, increased AcK, and increased incidence of toxicities, particularly at doses > 400 mg/m(2) /24 h.

From genes to genomes in the clinic

Next-generation sequencing is revolutionizing medical genetics and in the near future will pervade all medical fields. To maximize the potential clinical utility of this approach, global data sharing and phenotyping are needed, and the role of the geneticist in the interpretation of variation is vital.

Pharmacogenetics and pharmacogenomics in rheumatology

Pharmacogenetics and pharmacogenomics deal with possible associations of a single genetic polymorphism or those of multiple gene profiles with responses to drugs. In rheumatology, genes and gene signatures may be associated with altered efficacy and/or safety of anti-inflammatory drugs, disease-modifying antirheumatic drugs (DMARDs) and biologics. In brief, genes of cytochrome P450, other enzymes involved in drug metabolism, transporters and some cytokines have been associated with responses to and toxicity of non-steroidal anti-inflammatory drugs, corticosteroids and DMARDs. The efficacy of biologics may be related to alterations in cytokine, chemokine and FcγR genes. Numerous studies reported multiple genetic signatures in association with responses to biologics; however, data are inconclusive. More, focused studies carried out in larger patient cohorts, using pre-selected genes, may be needed in order to determine the future of pharmacogenetics and pharmacogenomics as tools for personalized medicine in rheumatology.

Pharmacogenomics of high-density lipoprotein-cholesterol-raising therapies

High levels of HDL cholesterol (HDL-C) have traditionally been linked to lower incidence of cardiovascular disease, prompting the search for effective and safe HDL-C raising pharmaceutical agents. Although drugs such as niacin and fibrates represent established therapeutic approaches, HDL-C response to such therapies is variable and heritable, suggesting a role for pharmacogenomic determinants. Multiple genetic polymorphisms, located primarily in genes encoding lipoproteins, cholesteryl ester transfer protein, transporters and CYP450 proteins have been shown to associate with HDL-C drug response in vitro and in epidemiologic studies. However, few of the pharmacogenomic findings have been independently validated, precluding the development of clinical tools that can be used to predict HDL-C response and leaving the goal of personalized medicine to future efforts.

A review of pharmacogenetics of adverse drug reactions in elderly people

Older adults are more susceptible to the prevalence of therapeutic failure and adverse drug reactions (ADRs). Recent advances in genomic research have shed light on the crucial role of genetic variants, mainly involving genes encoding drug-metabolizing enzymes, drug transporters and genes responsible for a compound's mechanism of action, in driving different treatment responses among individuals, in terms of therapeutic efficacy and safety. The interindividual variations of these genes may account for the differences observed in drug efficacy and the appearance of ADRs in elderly people. The advent of whole genome mapping techniques has allowed researchers to begin to characterize the genetic components underlying serious ADRs. The identification and validation of these genetic markers will enable the screening of patients at risk of serious ADRs and to establish personalized treatment regimens.The aim of this review was to provide an update on the recent developments in geriatric pharmacogenetics in clinical practice by reviewing the available evidence in the PubMed database to September 2012. A Pubmed search was performed (years 1999-2012) using the following two search strategies: ('pharmacogenomic' OR 'pharmacogenetic ') AND ('geriatric' or 'elderly ') AND 'adverse drug reactions'; [gene name] AND ('geriatric' or 'elderly ') AND 'adverse drug reactions', in which the gene names were those contained in the Table of Pharmacogenomic Biomarkers in Drug Labels published online by the US Food and Drug Administration ( http://www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/ucm083378.htm ). Reference lists of included original articles and relevant review articles were also screened. The search was limited to studies published in the English language.

Patterns of cancer genetic testing: a randomized survey of Oregon clinicians

Introduction. Appropriate use of genetic tests for population-based cancer screening, diagnosis of inherited cancers, and guidance of cancer treatment can improve health outcomes. We investigated clinicians' use and knowledge of eight breast, ovarian, and colorectal cancer genetic tests. Methods. We conducted a randomized survey of 2,191 Oregon providers, asking about their experience with fecal DNA, OncoVue, BRCA, MMR, CYP2D6, tumor gene expression profiling, UGT1A1, and KRAS. Results. Clinicians reported low confidence in their knowledge of medical genetics; most confident were OB-GYNs and specialists. Clinicians were more likely to have ordered/recommended BRCA and MMR than the other tests, and OB-GYNs were twice as likely to have ordered/recommended BRCA testing than primary care providers. Less than 10% of providers ordered/recommended OncoVue, fecal DNA, CYP2D6, or UGT1A1; less than 30% ordered/recommended tumor gene expression profiles or KRAS. The most common reason for not ordering/recommending these tests was lack of familiarity. Conclusions. Use of appropriate, evidence-based testing can help reduce incidence and mortality of certain cancers, but these tests need to be better integrated into clinical practice. Continued evaluation of emerging technologies, dissemination of findings, and an increase in provider confidence and knowledge are necessary to achieve this end.

Pharmacogenetics and pharmacogenomics: role of mutational analysis in anti-cancer targeted therapy

The goal of cancer pharmacogenomics is to obtain benefit from personalized approaches of cancer treatment and prevention. Recent advances in genomic research have shed light on the crucial role of genetic variants, mainly involving genes encoding drug-metabolizing enzymes, drug transporters and targets, in driving different treatment responses among individuals, in terms of therapeutic efficacy and safety. Although a considerable amount of new targeted agents have been designed based on a finely understanding of molecular alterations in cancer, a wide gap between pharmacogenomic knowledge and clinical application still persists. This review focuses on the relevance of mutational analyses in predicting individual response to antitumor therapy, in order to improve the translational impact of genetic information on clinical practice.