Pediatric considerations for pharmacogenetic selective serotonin reuptake inhibitors clinical decision support.

Pharmacogenetic testing for psychiatry is growing at a rapid pace, with multiple sites utilizing results to help clinical decision-making. Genotype-guided dosing and drug selection have been implemented at several sites, including Vanderbilt University Medical Center, where clinical decision support (CDS) based on pharmacogenetic results went live for selective serotonin reuptake inhibitors in 2020 for both adult and pediatric patients. Effective and appropriate implementation of CYP2D6- and CYP2C19-guided CDS for the pediatric population requires consideration of the evidence for the pharmacogenetic associations, medication indications, and appropriate alternative therapies to be used when a pharmacogenetic contraindication is identified. In this article, we review these pediatric pharmacogenetic considerations for selective serotonin reuptake inhibitor CDS. We include a case study, the current literature supporting clinical recommendations, considerations when designing pediatric CDS, future implications, and examples of sertraline, (es)citalopram, paroxetine, and fluvoxamine alerts.

Bioinformatics and in-silico findings reveal medical features and pharmacological targets of biochanin A against colorectal cancer and COVID-19.

Severe mortality due to the COVID-19 pandemic resulted from the lack of effective treatment. Although COVID-19 vaccines are available, their side effects have become a challenge for clinical use in patients with chronic diseases, especially cancer patients. In the current report, we applied network pharmacology and systematic bioinformatics to explore the use of biochanin A in patients with colorectal cancer (CRC) and COVID-19 infection. Using the network pharmacology approach, we identified two clusters of genes involved in immune response (IL1A, IL2, and IL6R) and cell proliferation (CCND1, PPARG, and EGFR) mediated by biochanin A in CRC/COVID-19 condition. The functional analysis of these two gene clusters further illustrated the effects of biochanin A on interleukin-6 production and cytokine-cytokine receptor interaction in CRC/COVID-19 pathology. In addition, pathway analysis demonstrated the control of PI3K-Akt and JAK-STAT signaling pathways by biochanin A in the treatment of CRC/COVID-19. The findings of this study provide a therapeutic option for combination therapy against COVID-19 infection in CRC patients.

Systems pharmacogenomics identifies novel targets and clinically actionable therapeutics for medulloblastoma.

BACKGROUND: Medulloblastoma (MB) is the most common malignant paediatric brain tumour and a leading cause of cancer-related mortality and morbidity. Existing treatment protocols are aggressive in nature resulting in significant neurological, intellectual and physical disabilities for the children undergoing treatment. Thus, there is an urgent need for improved, targeted therapies that minimize these harmful side effects. METHODS: We identified candidate drugs for MB using a network-based systems-pharmacogenomics approach: based on results from a functional genomics screen, we identified a network of interactions implicated in human MB growth regulation. We then integrated drugs and their known mechanisms of action, along with gene expression data from a large collection of medulloblastoma patients to identify drugs with potential to treat MB. RESULTS: Our analyses identified drugs targeting CDK4, CDK6 and AURKA as strong candidates for MB; all of these genes are well validated as drug targets in other tumour types. We also identified non-WNT MB as a novel indication for drugs targeting TUBB, CAD, SNRPA, SLC1A5, PTPRS, P4HB and CHEK2. Based upon these analyses, we subsequently demonstrated that one of these drugs, the new microtubule stabilizing agent, ixabepilone, blocked tumour growth in vivo in mice bearing patient-derived xenograft tumours of the Sonic Hedgehog and Group 3 subtype, providing the first demonstration of its efficacy in MB. CONCLUSIONS: Our findings confirm that this data-driven systems pharmacogenomics strategy is a powerful approach for the discovery and validation of novel therapeutic candidates relevant to MB treatment, and along with data validating ixabepilone in PDX models of the two most aggressive subtypes of medulloblastoma, we present the network analysis framework as a resource for the field.

Molecular landscape and subtype-specific therapeutic response of nasopharyngeal carcinoma revealed by integrative pharmacogenomics.

Nasopharyngeal carcinoma (NPC) is a malignant head and neck cancer type with high morbidity in Southeast Asia, however the pathogenic mechanism of this disease is poorly understood. Using integrative pharmacogenomics, we find that NPC subtypes maintain distinct molecular features, drug responsiveness, and graded radiation sensitivity. The epithelial carcinoma (EC) subtype is characterized by activations of microtubule polymerization and defective mitotic spindle checkpoint related genes, whereas sarcomatoid carcinoma (SC) and mixed sarcomatoid-epithelial carcinoma (MSEC) subtypes exhibit enriched epithelial-mesenchymal transition (EMT) and invasion promoting genes, which are well correlated with their morphological features. Furthermore, patient-derived organoid (PDO)-based drug test identifies potential subtype-specific treatment regimens, in that SC and MSEC subtypes are sensitive to microtubule inhibitors, whereas EC subtype is more responsive to EGFR inhibitors, which is synergistically enhanced by combining with radiotherapy. Through combinational chemoradiotherapy (CRT) screening, effective CRT regimens are also suggested for patients showing less sensitivity to radiation. Altogether, our study provides an example of applying integrative pharmacogenomics to establish a personalized precision oncology for NPC subtype-guided therapies.

HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine.

Pharmacotranscriptomics has become a powerful approach for evaluating the therapeutic efficacy of drugs and discovering new drug targets. Recently, studies of traditional Chinese medicine (TCM) have increasingly turned to high-throughput transcriptomic screens for molecular effects of herbs/ingredients. And numerous studies have examined gene targets for herbs/ingredients, and link herbs/ingredients to various modern diseases. However, there is currently no systematic database organizing these data for TCM. Therefore, we built HERB, a high-throughput experiment- and reference-guided database of TCM, with its Chinese name as BenCaoZuJian. We re-analyzed 6164 gene expression profiles from 1037 high-throughput experiments evaluating TCM herbs/ingredients, and generated connections between TCM herbs/ingredients and 2837 modern drugs by mapping the comprehensive pharmacotranscriptomics dataset in HERB to CMap, the largest such dataset for modern drugs. Moreover, we manually curated 1241 gene targets and 494 modern diseases for 473 herbs/ingredients from 1966 references published recently, and cross-referenced this novel information to databases containing such data for drugs. Together with database mining and statistical inference, we linked 12 933 targets and 28 212 diseases to 7263 herbs and 49 258 ingredients and provided six pairwise relationships among them in HERB. In summary, HERB will intensively support the modernization of TCM and guide rational modern drug discovery efforts. And it is accessible through http://herb.ac.cn/.

Phase I, Pharmacogenomic, Drug Interaction Study of Sorafenib and Bevacizumab in Combination with Paclitaxel in Patients with Advanced Refractory Solid Tumors.

VEGF blockade does not uniformly result in clinical benefit. We evaluated safety, dose-limiting toxicities (DLT), recommended phase II dose (RP2D), antitumor efficacy, and exploratory biomarkers including pharmacogenomics and pharmacokinetics with sorafenib, bevacizumab, and paclitaxel in patients with refractory cancers. The study had a "3 + 3" design, using paclitaxel 80 mg/m2 every week for 3 weeks, in every 4 week cycles, bevacizumab 5 mg/kg every 2 weeks, and sorafenib 200 or 400 mg twice a day, 5 or 7 days/week (5/7, 7/7). The MTD cohort was expanded. Twenty-seven patients enrolled in 3 cohorts: sorafenib 200 mg twice a day 5/7, 200 mg twice a day 7/7, and 400 mg twice a day 5/7. DLTs were grade 3 neutropenia >7 days (cohort 1, 1), grade 3 hypertension (cohort 2, 1), grade 3 hand-foot skin reaction (HFSR; cohort 3, 2). MTD was sorafenib 200 mg twice a day 7/7. Six DLTs occurred in cohort 2 expansion: grade 3 HFSR (2), grade 2 HFSR with sorafenib delay >7 days (2), grade 4 cerebrovascular accident (1), grade 3 neutropenia >7 days (1). RP2D was sorafenib 200 mg twice a day 5/7. Most patients (62%) dose reduced sorafenib to 200 mg daily 5/7 after a median 3 (range, 2-17) cycles. Response rates were 48% overall (27) and 64% for ovarian cancers (14). VEGF-A-1154AA and -7TT recessive homozygous genotypes conferred worse overall survival versus alternative genotypes (7 vs. 22 months). Intermittent, low-dose sorafenib (200 mg twice a day 5/7) combined with bevacizumab and paclitaxel was tolerable and had high antitumor efficacy in patients with refractory cancer (NCT00572078).

The genetics of rheumatoid arthritis.

RA is a chronic systemic inflammatory disease that primarily affects the small joints of the hands and feet, and results in a mean reduction in life expectancy of 3-10 years. RA is a multigene disorder with a substantial genetic component and a heritability estimate of 60%. Large-scale Genome-Wide Association Studies (GWAS) and meta-analyses have revealed common disease-associated variants in the population that may contribute cumulatively to RA pathogenesis. This review identifies the most significant genetic variants associated with RA susceptibility to date, with particular focus on the contribution of the HLA class II genes across different ethnic groups. Also discussed are the potential applications of pharmacogenomics to RA management by identifying polymorphisms associated with variation in treatment response or toxicity. The use of genetic variants to guide treatment strategy has the potential to not only reduce National Health Service costs, but also drastically improve patient experience and quality of life.

Pharmacogenomic assessment of herbal drugs in affective disorders.

Anxiety and depression, the most prevalent psychiatric disorders are co-morbid in nature affecting several people across the world. There is an increase in demand for complementary and alternative medicines, specifically herbal botanicals due to various side effects exhibited by conventional drugs. Herbal drugs mentioned in traditional medicines, face acceptance issues by the medical community due to lack of scientific data regarding their neurochemical pathways. Hence, there has been an increased interest in the quest to unravel the mechanisms of action of herbal psychotropics. With the advancements in "omic technologies" such as genomics, proteomics and metabolomics, research in the field of herbal psychopharmacology has gained momentum, providing a faster and informative platform for thorough evaluation of herbal drugs and formulations. In this article, we have reviewed several medicinal plants and their formulations that have shown potential anxiolytic and anti-depressant activities and have been screened for their biological mechanisms either at the gene, protein or metabolic level.

The Genomic Landscape and Pharmacogenomic Interactions of Clock Genes in Cancer Chronotherapy.

Cancer chronotherapy, treatment at specific times during circadian rhythms, endeavors to optimize anti-tumor effects and to lower toxicity. However, comprehensive characterization of clock genes and their clinical relevance in cancer is lacking. We systematically characterized the alterations of clock genes across 32 cancer types by analyzing data from The Cancer Genome Atlas, Cancer Therapeutics Response Portal, and The Genomics of Drug Sensitivity in Cancer databases. Expression alterations of clock genes are associated with key oncogenic pathways, patient survival, tumor stage, and subtype in multiple cancer types. Correlations between expression of clock genes and of other genes in the genome were altered in cancerous versus normal tissues. We identified interactions between clock genes and clinically actionable genes by analyzing co-expression, protein-protein interaction, and chromatin immunoprecipitation sequencing data and also found that clock gene expression is correlated to anti-cancer drug sensitivity in cancer cell lines. Our study provides a comprehensive analysis of the circadian clock across different cancer types and highlights potential clinical utility of cancer chronotherapy.

Genetic polymorphisms of pharmacogenomic VIP variants in the Yi population from China.

INTRODUCTION: Drug response and target therapeutic dosage are different among individuals. The variability is largely genetically determined. With the development of pharmacogenetics and pharmacogenomics, widespread research have provided us a wealth of information on drug-related genetic polymorphisms, and the very important pharmacogenetic (VIP) variants have been identified for the major populations around the world whereas less is known regarding minorities in China, including the Yi ethnic group. Our research aims to screen the potential genetic variants in Yi population on pharmacogenomics and provide a theoretical basis for future medication guidance. MATERIALS AND METHODS: In the present study, 80 VIP variants (selected from the PharmGKB database) were genotyped in 100 unrelated and healthy Yi adults recruited for our research. Through statistical analysis, we made a comparison between the Yi and other 11 populations listed in the HapMap database for significant SNPs detection. Two specific SNPs were subsequently enrolled in an observation on global allele distribution with the frequencies downloaded from ALlele FREquency Database. Moreover, F-statistics (Fst), genetic structure and phylogenetic tree analyses were conducted for determination of genetic similarity between the 12 ethnic groups. RESULTS: Using the χ2 tests, rs1128503 (ABCB1), rs7294 (VKORC1), rs9934438 (VKORC1), rs1540339 (VDR) and rs689466 (PTGS2) were identified as the significantly different loci for further analysis. The global allele distribution revealed that the allele "A" of rs1540339 and rs9934438 were more frequent in Yi people, which was consistent with the most populations in East Asia. F-statistics (Fst), genetic structure and phylogenetic tree analyses demonstrated that the Yi and CHD shared a closest relationship on their genetic backgrounds. Additionally, Yi was considered similar to the Han people from Shaanxi province among the domestic ethnic populations in China. CONCLUSIONS: Our results demonstrated significant differences on several polymorphic SNPs and supplement the pharmacogenomic information for the Yi population, which could provide new strategies for optimizing clinical medication in accordance with the genetic determinants of drug toxicity and efficacy.

Personalized Medicine and Nonmotor Symptoms in Parkinson's Disease.

Parkinson's disease (PD) is a multineurotransmitter dysfunction related disorder resulting in a range of motor and nonmotor symptoms. Phenotypic heterogeneity is pronounced in PD and nonmotor symptoms dominant subtypes have been described. These endophenotypes may be underpinned by considerable nondopaminergic dysfunction; however, conventional treatment of PD continues to be mostly reliant on dopamine replacement strategy or manipulation of brain dopaminergic pathways. Consequently, treatment of many nondopaminergic nonmotor and some motor symptoms remains a key unmet need. It is also recognized that treatment strategies for PD are influenced by a number of nondrug-related issues. These include factors such as age, personality, and preferences for treatment, cultural beliefs, lifestyle, pharmacoeconomics, pharmacogenetics as well as comorbidity. Therefore, the success of clinical therapy will rest on how much these factors are considered to develop a truly holistic treatment plan. Personalized medicine is the modern way of delivering this holistic strategy for treatment of PD. Personalized medicine thus encompasses several strands of treatment. From the pharmaceutical point of view, it should involve dopaminergic and nondopaminergic strategies. In addition, there are substrategies involving precision and tailored medicine to suit the needs and requirements of individual patients. Precision medicine would be relevant for patients who may be at risk of developing the clinical syndrome of Parkinson's as identified by specific gene mutations. Precision medicine in this scenario will attempt to be preventive. Tailored medicine would address the "single multifactorial" complex nature of PD and address symptoms as well subtype-specific strategies. Personalized medicine is now practiced for other conditions such as oncology as well as diabetes. In this chapter, we discuss the rationale and the need to develop strategies for personalized medicine for PD.

Integrative Cancer Pharmacogenomics to Infer Large-Scale Drug Taxonomy.

Identification of drug targets and mechanism of action (MoA) for new and uncharacterized anticancer drugs is important for optimization of treatment efficacy. Current MoA prediction largely relies on prior information including side effects, therapeutic indication, and chemoinformatics. Such information is not transferable or applicable for newly identified, previously uncharacterized small molecules. Therefore, a shift in the paradigm of MoA predictions is necessary toward development of unbiased approaches that can elucidate drug relationships and efficiently classify new compounds with basic input data. We propose here a new integrative computational pharmacogenomic approach, referred to as Drug Network Fusion (DNF), to infer scalable drug taxonomies that rely only on basic drug characteristics toward elucidating drug-drug relationships. DNF is the first framework to integrate drug structural information, high-throughput drug perturbation, and drug sensitivity profiles, enabling drug classification of new experimental compounds with minimal prior information. DNF taxonomy succeeded in identifying pertinent and novel drug-drug relationships, making it suitable for investigating experimental drugs with potential new targets or MoA. The scalability of DNF facilitated identification of key drug relationships across different drug categories, providing a flexible tool for potential clinical applications in precision medicine. Our results support DNF as a valuable resource to the cancer research community by providing new hypotheses on compound MoA and potential insights for drug repurposing. Cancer Res; 77(11); 3057-69. ©2017 AACR.

Ayurgenomics for stratified medicine: TRISUTRA consortium initiative across ethnically and geographically diverse Indian populations.

BACKGROUND: Genetic differences in the target proteins, metabolizing enzymes and transporters that contribute to inter-individual differences in drug response are not integrated in contemporary drug development programs. Ayurveda, that has propelled many drug discovery programs albeit for the search of new chemical entities incorporates inter-individual variability "Prakriti" in development and administration of drug in an individualized manner. Prakriti of an individual largely determines responsiveness to external environment including drugs as well as susceptibility to diseases. Prakriti has also been shown to have molecular and genomic correlates. We highlight how integration of Prakriti concepts can augment the efficiency of drug discovery and development programs through a unique initiative of Ayurgenomics TRISUTRA consortium. METHODS: Five aspects that have been carried out are (1) analysis of variability in FDA approved pharmacogenomics genes/SNPs in exomes of 72 healthy individuals including predominant Prakriti types and matched controls from a North Indian Indo-European cohort (2) establishment of a consortium network and development of five genetically homogeneous cohorts from diverse ethnic and geo-climatic background (3) identification of parameters and development of uniform standard protocols for objective assessment of Prakriti types (4) development of protocols for Prakriti evaluation and its application in more than 7500 individuals in the five cohorts (5) Development of data and sample repository and integrative omics pipelines for identification of genomic correlates. RESULTS: Highlight of the study are (1) Exome sequencing revealed significant differences between Prakriti types in 28 SNPs of 11 FDA approved genes of pharmacogenomics relevance viz. CYP2C19, CYP2B6, ESR1, F2, PGR, HLA-B, HLA-DQA1, HLA-DRB1, LDLR, CFTR, CPS1. These variations are polymorphic in diverse Indian and world populations included in 1000 genomes project. (2) Based on the phenotypic attributes of Prakriti we identified anthropometry for anatomical features, biophysical parameters for skin types, HRV for autonomic function tests, spirometry for vital capacity and gustometry for taste thresholds as objective parameters. (3) Comparison of Prakriti phenotypes across different ethnic, age and gender groups led to identification of invariant features as well as some that require weighted considerations across the cohorts. CONCLUSION: Considering the molecular and genomics differences underlying Prakriti and relevance in disease pharmacogenomics studies, this novel integrative platform would help in identification of differently susceptible and drug responsive population. Additionally, integrated analysis of phenomic and genomic variations would not only allow identification of clinical and genomic markers of Prakriti for application in personalized medicine but also its integration in drug discovery and development programs.

Pharmacogenetics of asthma: toward precision medicine.

PURPOSE OF REVIEW: Although currently available drugs to treat asthma are effective in most patients, a proportion of patients do not respond or experience side-effects; which is partly genetically determined. Pharmacogenetics is the study of how genetic variations influence drug response. In this review, we summarize prior results and recent studies in pharmacogenetics to determine if we can use genetic profiles for personalized treatment of asthma. RECENT FINDINGS: The field of pharmacogenetics has moved from candidate gene studies in single populations toward genome-wide association studies and meta-analysis of multiple studies. New technologies have been used to enrich results, and an expanding number of genetic loci have been associated with therapeutic responses to asthma drugs. Prospective, genotype-stratified treatment studies have been conducted for ß2-agonists, showing attenuated response in children carrying the Arg16 variant in the ß2-adrenoreceptor gene. SUMMARY: Although there has been much progress, many findings have not been replicated and currently known genetic loci only account for a fraction of variability in drug response. More research is necessary to translate into clinical practice. A polygenic predictive approach integrated in complex networks with other 'omics' technologies could aid to achieve this goal. Finally, to change clinical practice, studies that compare precision medicine with traditional medicine are needed.

Role of pharmacogenetics on deferasirox AUC and efficacy.

AIM: We evaluated deferasirox pharmacokinetic according to SNPs in genes involved in its metabolism and elimination. Moreover, we defined a plasma area under the curve cut-off value predicting therapy response. PATIENTS & METHODS: Allelic discrimination was performed by real-time PCR. Drug plasma concentrations were measured by a high performance liquid chromatography system coupled with an ultraviolet method. RESULTS: Pharmacokinetic parameters were significantly influenced by UGT1A1 rs887829C>T, UGT1A3 rs1983023C>T and rs3806596A>G SNPs. Area under the curve cut-off values of 360 µg/ml/h for efficacy were here defined and 250 µg/ml/h for nonresponse was reported. UGT1A3 rs3806596GG and ABCG2 rs13120400CC genotypes were factors able to predict efficacy, whereas UGT1A3 rs3806596GG was a nonresponse predictor. CONCLUSION: These data show how screening patient's genetic profile may help clinicians to optimize iron chelation therapy with deferasirox.

Recent Advances in Application of Pharmacogenomics for Biotherapeutics.

Biotherapeutics (BTs), one of the fastest growing classes of drug molecules, offer several advantages over the traditional small molecule pharmaceuticals because of their relatively high specificity, low off-target effects, and biocompatible metabolism, in addition to legal and logistic advantages. However, their clinical utility is limited, among other things, by their high immunogenic potential and/or variable therapeutic efficacy in different patient populations. Both of these issues, also commonly experienced with small molecule drugs, have been addressed effectively in a number of cases by the successful application of pharmacogenomic tools and approaches. In this introductory article of the special issue, we review the current state of application of pharmacogenomics to BTs and offer suggestions for further expansion of the field.