A prospective genome-wide study of prostate cancer metastases reveals association of wnt pathway activation and increased cell cycle proliferation with primary resistance to abiraterone acetate-prednisone.

Background: Genomic aberrations have been identified in metastatic castration-resistant prostate cancer (mCRPC), but molecular predictors of resistance to abiraterone acetate/prednisone (AA/P) treatment are not known. Patients and methods: In a prospective clinical trial, mCRPC patients underwent whole-exome sequencing (n = 82) and RNA sequencing (n = 75) of metastatic biopsies before initiating AA/P with the objective of identifying genomic alterations associated with resistance to AA/P. Primary resistance was determined at 12 weeks of treatment using criteria for progression that included serum prostate-specific antigen measurement, bone and computerized tomography imaging and symptom assessments. Acquired resistance was determined using the end point of time to treatment change (TTTC), defined as time from enrollment until change in treatment from progressive disease. Associations of genomic and transcriptomic alterations with primary resistance were determined using logistic regression, Fisher's exact test, single and multivariate analyses. Cox regression models were utilized for determining association of genomic and transcriptomic alterations with TTTC. Results: At 12 weeks, 32 patients in the cohort had progressed (nonresponders). Median study follow-up was 32.1 months by which time 58 patients had switched treatments due to progression. Median TTTC was 10.1 months (interquartile range: 4.4-24.1). Genes in the Wnt/ß-catenin pathway were more frequently mutated and negative regulators of Wnt/ß-catenin signaling were more frequently deleted or displayed reduced mRNA expression in nonresponders. Additionally, mRNA expression of cell cycle regulatory genes was increased in nonresponders. In multivariate models, increased cell cycle proliferation scores (≥ 50) were associated with shorter TTTC (hazard ratio = 2.11, 95% confidence interval: 1.17-3.80; P = 0.01). Conclusions: Wnt/ß-catenin pathway activation and increased cell cycle progression scores can serve as molecular markers for predicting resistance to AA/P therapy.

New insights into the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation.

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at the single-nucleotide polymorphism (SNP), gene and pathway levels. Coverage of genetic variants was increased compared with previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. A total of 7062 950 SNPs were analyzed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (P=1.80e-08, ITGA9 (integrin α9)) and rs76191705 (P=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At the gene level, no consistent effect was found. At the pathway level, the Gene Ontology (GO) terms GO: 0005694 (chromosome) and GO: 0044427 (chromosomal part) were associated with improvement (corrected P=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (P=0.047), whereas rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in clarifying their role.

Genetic Breast Cancer Susceptibility Variants and Prognosis in the Prospectively Randomized SUCCESS A Study.

Large-scale genotyping studies have identified over 70 single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. However, knowledge regarding genetic risk factors associated with the prognosis is limited. The aim of this study was therefore to investigate the prognostic effect of nine known breast cancer risk SNPs. BC patients (n = 1687) randomly sampled in an adjuvant, randomized phase III trial (SUCCESS A study) were genotyped for nine BC risk SNPs: rs17468277 (CASP8) , rs2981582 (FGFR2) , rs13281615(8q24), rs3817198 (LSP1) , rs889312 (MAP3K1) , rs3803662 (TOX3) , rs13387042(2q35), rs4973768 (SLC4A7) , rs6504950 (COX11) . Cox proportional hazards models were used to test the SNPs' association with overall survival (OS) and progression-free survival (PFS). Additional analyses were carried out for molecular subgroups. rs3817198 in LSP1 (lymphocyte-specific protein 1) was the only SNP that significantly influenced OS (p = 0.01) and PFS (p < 0.01) in the likelihood ratio test comparing the genetic survival model with the clinical survival model. In the molecular subgroups, triple-negative patients with two minor alleles in rs3817198 had a much better prognosis relative to OS (adjusted HR 0.03; 95% CI 0.002 - 0.279) and PFS (HR 0.09; 95% CI 0.02 - 0.36) than patients with the common alleles. The same effect on PFS was shown for patients with luminal A tumors (HR 0.19; 95% CI 0.05 - 0.84), whereas patients with luminal B tumors had a poorer PFS with two minor alleles (HR 2.13; 95% CI 1.02 - 4.40). The variant in rs3817198 has a prognostic effect particularly in the subgroup of patients with triple-negative BC, suggesting a possible link with immunomodulation and BC.

Electronic Medical Record-Integrated Pharmacogenomics and Related Clinical Decision Support Concepts.

Advances in pharmacogenomics (PGx) have the potential to transform healthcare by allowing precision medicine to become a reality. However, PGx knowledge is new, complex, and evolving, and relying on the cognition of clinicians alone is insufficient for clinical implementation. Integrating clinical decision support (CDS) tools in the electronic health record (EHR) is critical for translating PGx into clinical practice. Herein, we review current strategies to implement PGx using EHR-CDS functionalities.

The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Outcomes and Metrics of Pharmacogenetic Implementations Across Diverse Healthcare Systems.

Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the National Institutes of Health (NIH) Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real-world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene-drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.

Genomewide Association Studies in Pharmacogenomics: Meeting Report of the NIH Pharmacogenomics Research Network-RIKEN (PGRN-RIKEN) Collaboration.

Genomewide association studies (GWAS) have resulted in the identification of many heritable genetic factors that underlie risk for human disease or variation in physiologic traits. In contrast, there are fewer GWAS of drug response phenotypes, despite extensive unexplained interindividual variability. To address this urgent need, the NIH Pharmacogenomics Research Network (PGRN) and the Center for Integrative Medical Sciences (IMS) at RIKEN support a collaboration, PGRN-RIKEN, with the goal of accelerating GWAS of drug response phenotypes.

TSPAN5, ERICH3 and selective serotonin reuptake inhibitors in major depressive disorder: pharmacometabolomics-informed pharmacogenomics.

Millions of patients suffer from major depressive disorder (MDD), but many do not respond to selective serotonin reuptake inhibitor (SSRI) therapy. We used a pharmacometabolomics-informed pharmacogenomics research strategy to identify genes associated with metabolites that were related to SSRI response. Specifically, 306 MDD patients were treated with citalopram or escitalopram and blood was drawn at baseline, 4 and 8 weeks for blood drug levels, genome-wide single nucleotide polymorphism (SNP) genotyping and metabolomic analyses. SSRI treatment decreased plasma serotonin concentrations (P<0.0001). Baseline and plasma serotonin concentration changes were associated with clinical outcomes (P<0.05). Therefore, baseline and serotonin concentration changes were used as phenotypes for genome-wide association studies (GWAS). GWAS for baseline plasma serotonin concentrations revealed a genome-wide significant (P=7.84E-09) SNP cluster on chromosome four 5' of TSPAN5 and a cluster across ERICH3 on chromosome one (P=9.28E-08) that were also observed during GWAS for change in serotonin at 4 (P=5.6E-08 and P=7.54E-07, respectively) and 8 weeks (P=1.25E-06 and P=3.99E-07, respectively). The SNPs on chromosome four were expression quantitative trait loci for TSPAN5. Knockdown (KD) and overexpression (OE) of TSPAN5 in a neuroblastoma cell line significantly altered the expression of serotonin pathway genes (TPH1, TPH2, DDC and MAOA). Chromosome one SNPs included two ERICH3 nonsynonymous SNPs that resulted in accelerated proteasome-mediated degradation. In addition, ERICH3 and TSPAN5 KD and OE altered media serotonin concentrations. Application of a pharmacometabolomics-informed pharmacogenomic research strategy, followed by functional validation, indicated that TSPAN5 and ERICH3 are associated with plasma serotonin concentrations and may have a role in SSRI treatment outcomes.

Elevated baseline serum glutamate as a pharmacometabolomic biomarker for acamprosate treatment outcome in alcohol-dependent subjects.

Acamprosate has been widely used since the Food and Drug Administration approved the medication for treatment of alcohol use disorders (AUDs) in 2004. Although the detailed molecular mechanism of acamprosate remains unclear, it has been largely known that acamprosate inhibits glutamate action in the brain. However, AUD is a complex and heterogeneous disorder. Thus, biomarkers are required to prescribe this medication to patients who will have the highest likelihood of responding positively. To identify pharmacometabolomic biomarkers of acamprosate response, we utilized serum samples from 120 alcohol-dependent subjects, including 71 responders (maintained continuous abstinence) and 49 non-responders (any alcohol use) during 12 weeks of acamprosate treatment. Notably, baseline serum glutamate levels were significantly higher in responders compared with non-responders. Importantly, serum glutamate levels of responders are normalized after acamprosate treatment, whereas there was no significant glutamate change in non-responders. Subsequent functional studies in animal models revealed that, in the absence of alcohol, acamprosate activates glutamine synthetase, which synthesizes glutamine from glutamate and ammonia. These results suggest that acamprosate reduces serum glutamate levels for those who have elevated baseline serum glutamate levels among responders. Taken together, our findings demonstrate that elevated baseline serum glutamate levels are a potential biomarker associated with positive acamprosate response, which is an important step towards development of a personalized approach to treatment for AUD.

Genetic markers associated with abstinence length in alcohol-dependent subjects treated with acamprosate.

Acamprosate supports abstinence in some alcohol-dependent subjects, yet predictors of response are unknown. To identify response biomarkers, we investigated associations of abstinence length with polymorphisms in candidate genes in glycine and glutamate neurotransmission pathways and genes previously implicated in acamprosate response. Association analyses were conducted in the discovery sample of 225 alcohol-dependent subjects treated with acamprosate for 3 months in community-based treatment programs in the United States. Data from 110 alcohol-dependent males treated with acamprosate in the study PREDICT were used for replication of the top association findings. Statistical models were adjusted for relevant covariates, including recruitment site and baseline clinical variables associated with response. In the discovery sample, shorter abstinence was associated with increased intensity of alcohol craving and lower number of days between the last drink and initiation of acamprosate treatment. After adjustment for covariates, length of abstinence was associated with the GRIN2B rs2058878 (P=4.6 × 10(-5)). In the replication sample, shorter abstinence was associated with increased craving, increased depressive mood score and higher alcohol consumption. Association of abstinence length with GRIN2B rs2058878 was marginally significant (P=0.0675); as in the discovery sample, the minor A allele was associated with longer abstinence. Furthermore, rs2300272, which is in strong linkage disequilibrium with rs2058878, was also associated with abstinence length (P=0.049). This is the first report of a replicated association of genetic markers with the length of abstinence in acamprosate-treated alcoholics. Investigation of the underlying mechanisms of this association and its usefulness for individualized treatment selection should follow.

Inflammation-related genetic variants predict toxicity following definitive radiotherapy for lung cancer.

Definitive radiotherapy improves locoregional control and survival in inoperable non-small cell lung cancer patients. However, radiation-induced toxicities (pneumonitis/esophagitis) are common dose-limiting inflammatory conditions. We therefore conducted a pathway-based analysis to identify inflammation-related single-nucleotide polymorphisms associated with radiation-induced pneumonitis or esophagitis. A total of 11,930 single-nucleotide polymorphisms were genotyped in 201 stage I-III non-small cell lung cancer patients treated with definitive radiotherapy. Validation was performed in an additional 220 non-small cell lung cancer cases. After validation, 19 single-nucleotide polymorphisms remained significant. A polygenic risk score was generated to summarize the effect from validated single-nucleotide polymorphisms. Significant improvements in discriminative ability were observed when the polygenic risk score was added into the clinical/epidemiological variable-based model. We then used 277 lymphoblastoid cell lines to assess radiation sensitivity and expression quantitative trait loci (eQTL) relationships of the identified single-nucleotide polymorphisms. Three genes (PRKCE, DDX58, and TNFSF7) were associated with radiation sensitivity. We concluded that inflammation-related genetic variants could contribute to the development of radiation-induced toxicities.

Pharmacometabolomics: implications for clinical pharmacology and systems pharmacology.

Metabolomics, the study of metabolism at an "omic" level, has the potential to transform our understanding of mechanisms of drug action and the molecular basis for variation in drug response. It is now possible to define metabolic signatures of drug exposure that can identify pathways involved in both drug efficacy and adverse drug reactions. In addition, the "metabotype," the metabolic "signature" of a patient, is a unique identity that contains information about drug response and disease heterogeneity. The application of metabolomics for the study of drug effects and variation in drug response is creating "pharmacometabolomics," a discipline that will contribute to personalized drug therapy and will complement pharmacogenomics by capturing environmental and microbiome-level influences on response to drug therapy. This field has the potential to transform pharmacology and clinical pharmacology in significant ways and will contribute to efforts for personalized therapy. This overview highlights developments in the new discipline of pharmacometabolomics.

Pharmacogenomics of selective serotonin reuptake inhibitor treatment for major depressive disorder: genome-wide associations and functional genomics.

A genome-wide association (GWA) study of treatment outcomes (response and remission) of selective serotonin reuptake inhibitors (SSRIs) was conducted using 529 subjects with major depressive disorder. While no SNP associations reached the genome-wide level of significance, 14 SNPs of interest were identified for functional analysis. The rs11144870 SNP in the riboflavin kinase (RFK) gene on chromosome 9 was associated with 8-week treatment response (odds ratio (OR)=0.42, P=1.04 × 10⁻6). The rs915120 SNP in the G protein-coupled receptor kinase 5 (GRK5) gene on chromosome 10 was associated with 8-week remission (OR=0.50, P=1.15 × 10⁻5). Both SNPs were shown to influence transcription by a reporter gene assay and to alter nuclear protein binding using an electrophoretic mobility shift assay. This report represents an example of joining functional genomics with traditional GWA study results derived from a GWA analysis of SSRI treatment outcomes. The goal of this analytical strategy is to provide insights into the potential relevance of biologically plausible observed associations.

Catechol O-methyltransferase pharmacogenomics and selective serotonin reuptake inhibitor response.

We applied a systematic pharmacogenetic approach to investigate the role of genetic variation in the gene encoding catechol O-methyltransferase (COMT) in individual variation in selective serotonin reuptake inhibitor (SSRI) response among depressed patients. In all, 23 single-nucleotide polymorphisms (SNPs) in COMT were genotyped using DNA from the Sequenced Treatment Alternatives to Relieve Depression (STAR(*)D) study (N=1914). One SNP, rs13306278, located in the distal promoter region of COMT, showed significant association with remission in White non-Hispanic (WNH) subjects (P=0.038). Electromobility shift assay for rs13306278 showed alternation in the ability of the variant sequence to bind nuclear proteins. A replication study was performed using samples from the Mayo Clinic Pharmacogenetics Research Network Citalopram/Escitalopram Pharmacogenomic study (N=422) that demonstrated a similar trend for association. Our findings suggest that novel genetic markers in the COMT distal promoter may influence SSRI response phenotypes.

Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics.

Often, analysis for pharmacogenomic studies involving multiple drugs from the same class is completed by analyzing each drug individually for association with genomic variation. However, by completing the analysis of each drug individually, we may be losing valuable information. When studying multiple drugs from the same drug class, one may wish to determine genomic variation that explains the difference in response between individuals for the drug class, as opposed to each individual drug. Therefore, we have developed a multivariate model to assess whether genomic variation impacts a class of drugs. In addition to determine genomic effects that are similar for the drugs, we will also be able to determine genomic effects that differ between the drugs (that is, interaction). We will illustrate the utility of this multivariate model for cytotoxicity and genomic data collected on the Coriell Human Variation Panel for the class of anti-purine metabolites (6-mercaptopurine and 6-thioguanine).

The impact of pharmacogenomics on the management of cardiac disease.

Pharmacogenomics promises to help maximize efficacy and minimize adverse drug reactions. It could have a significant impact on the treatment of cardiovascular disease, the leading cause of death in the United States. The past decade has seen pharmacogenomics move from study of a candidate gene to genome-wide approaches, with the development of a series of pharmacogenetic tests. However, many barriers need to be overcome for cardiovascular pharmacogenomics to have its promised clinical impact.

Glycine and a glycine dehydrogenase (GLDC) SNP as citalopram/escitalopram response biomarkers in depression: pharmacometabolomics-informed pharmacogenomics.

Major depressive disorder (MDD) is a common psychiatric disease. Selective serotonin reuptake inhibitors (SSRIs) are an important class of drugs used in the treatment of MDD. However, many patients do not respond adequately to SSRI therapy. We used a pharmacometabolomics-informed pharmacogenomic research strategy to identify citalopram/escitalopram treatment outcome biomarkers. Metabolomic assay of plasma samples from 20 escitalopram remitters and 20 nonremitters showed that glycine was negatively associated with treatment outcome (P = 0.0054). This observation was pursued by genotyping tag single-nucleotide polymorphisms (SNPs) for genes encoding glycine synthesis and degradation enzymes, using 529 DNA samples from SSRI-treated MDD patients. The rs10975641 SNP in the glycine dehydrogenase (GLDC) gene was associated with treatment outcome phenotypes. Genotyping for rs10975641 was carried out in 1,245 MDD patients in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, and its presence was significant (P = 0.02) in DNA taken from these patients. These results highlight a possible role for glycine in SSRI response and illustrate the use of pharmacometabolomics to "inform" pharmacogenomics.

Pharmacogenetics of the mycophenolic acid targets inosine monophosphate dehydrogenases IMPDH1 and IMPDH2: gene sequence variation and functional genomics.

BACKGROUND AND PURPOSE: Inosine monophosphate dehydrogenases, encoded by IMPDH1 and IMPDH2, are targets for the important immunosuppressive drug, mycophenolic acid (MPA). Variation in MPA response may result, in part, from genetic variation in IMPDH1 and IMPDH2. EXPERIMENTAL APPROACH: We resequenced IMPDH1 and IMPDH2 using DNA from 288 individuals from three ethnic groups and performed functional genomic studies of the sequence variants observed. KEY RESULTS: We identified 73 single nucleotide polymorphisms (SNPs) in IMPDH1, 59 novel, and 25 SNPs, 24 novel, in IMPDH2. One novel IMPDH1 allozyme (Leu275) had 10.2% of the wild-type activity as a result of accelerated protein degradation. Decreased activity of the previously reported IMPDH2 Phe263 allozyme was primarily due to decreased protein quantity, also with accelerated degradation. These observations with regard to the functional implications of variant allozymes were supported by the IMPDH1 and IMPDH2 X-ray crystal structures. A novel IMPDH2 intron 1 SNP, G > C IVS1(93), was associated with decreased mRNA quantity, possibly because of altered transcription. CONCLUSIONS AND IMPLICATIONS: These results provide insight into the nature and extent of sequence variation in the IMPDH1 and IMPDH2 genes. They also describe the influence of gene sequence variation that alters the encoded amino acids on IMPDH function and provide a foundation for future translational studies designed to correlate sequence variation in these genes with outcomes in patients treated with MPA.

SLC6A4 variation and citalopram response.

The influence of genetic variations in SLC6A4 (serotonin transporter gene) on citalopram treatment of depression using the Sequenced Treatment to Relieve Depression (STAR*D) sample was assessed. Of primary interest were three previously studied polymorphisms: 1) the VNTR variation of the second intron, 2) the indel promoter polymorphism (5HTTLPR or SERT), and 3) a single nucleotide polymorphism (SNP) rs25531. Additionally, SLC6A4 was resequenced to identify new SNPs for exploratory analyses. DNA from 1914 subjects in the STAR*D study were genotyped for the intron 2 VNTR region, the indel promoter polymorphism, and rs25531. Associations of these variants with remission of depressive symptoms were evaluated following citalopram treatment. In white non-Hispanic subjects, variations in the intron 2 VNTR (point-wise P = 0.041) and the indel promoter polymorphism (point-wise P = 0.039) were associated with remission following treatment with citalopram. The haplotype composed of the three candidate loci was also associated with remission, with a global p-value of 0.040 and a maximum statistic simulation p-value of 0.0031 for the S-a-12 haplotype, under a dominant model. One SNP identified through re-sequencing the SLC6A4 gene, Intron7-83-TC, showed point-wise evidence of association, which did not remain significant after correction for the number of SNPs evaluated in this exploratory analysis. No associations between these SLC6A4 variations and remission were found in the white Hispanic or black subjects. These findings suggest that multiple variations in the SLC6A4 gene are associated with remission in white non-Hispanic depressed adults treated with citalopram. The mechanism of action of these variants remains to be determined.