Accurate assessment of CYP2D6 phenotypes from genotype is inadequate in patients taking CYP2D6 substrate together with CYP2D6 inhibitors. We propose a novel CYP2D6 scoring systems that incorporates the impact of concomitant medications with the genotype in calculating the CYP2D6 activity score.
Training (n=159) and validation (n=81) data sets were obtained from a prospective cohort tamoxifen pharmacogenetics registry. Two inhibitor factors were defined: one genotype-independent and one genotype-based. Three CYP2D6 gene score systems, and their combination with the inhibitor factors, were compared. These three scores were based on Zineh, Zanger, and Gaedigk's approaches. Endoxifen/NDM-Tam plasma ratio was used as the phenotype.
The overall performance of the three gene score systems without consideration of CYP2D6 inhibiting medications in predicting CYP2D6 phenotype was poor both in the training (R2=0.24, 0.22 and 0.18) and the validation set, (R2=0.30, 0.24 and 0.15). Once the CYP2D6 genotype-independent inhibitor factor was integrated into the score calculation, the R2 values in the training and validation data sets are nearly twice as high as the genotype only scoring model: (0.44, 0.43, 0.38) and (0.53, 0.50, 0.41) respectively.
The integration of the inhibitory effect of concomitant medications with the CYP2D6 genotype into the composite CYP2D6 Activity Score doubled our ability to predict the CYP2D6 phenotype. However, endoxifen phenotypes still varied substantially, even with incorporation of CYD2D6 genotype and inhibiting factors, suggesting that other, yet unidentified, factors must be involved in tamoxifen activation.
activity score; CYP2D6; inhibition; tamoxifen
Background. The genome-wide association studies (GWAS) have been successful during the last few years. A key challenge is that the interpretation of the results is not straightforward, especially for transacting SNPs. Integration of transcriptome data into GWAS may provide clues elucidating the mechanisms by which a genetic variant leads to a disease. Methods. Here, we developed a novel mediation analysis approach to identify new expression quantitative trait loci (eQTL) driving CYP2D6 activity by combining genotype, gene expression, and enzyme activity data. Results. 389,573 and 1,214,416 SNP-transcript-CYP2D6 activity trios are found strongly associated (P < 10−5, FDR = 16.6% and 11.7%) for two different genotype platforms, namely, Affymetrix and Illumina, respectively. The majority of eQTLs are trans-SNPs. A single polymorphism leads to widespread downstream changes in the expression of distant genes by affecting major regulators or transcription factors (TFs), which would be visible as an eQTL hotspot and can lead to large and consistent biological effects. Overlapped eQTL hotspots with the mediators lead to the discovery of 64 TFs.
Conclusions. Our mediation analysis is a powerful approach in identifying the trans-QTL-phenotype associations. It improves our understanding of the functional genetic variations for the liver metabolism mechanisms.
To ascertain whether single nucleotide polymorphisms (SNPs) in the Vascular Endothelial Growth factor (VEGFA), Complement Factor H (CFH), and LOC387715 genes could predict outcome to anti-VEGF therapy for patients with age related macular degeneration (AMD).
Patients with “wet” AMD were identified by chart review. Baseline optical coherence tomography (OCT) and visual acuity (VA) data, and at least 6 months of clinical follow up after 3 initial monthly injections of bevacizumab or ranibizumab were required for inclusion. Based on OCT and VA, patients were categorized into two possible clinical outcomes: (a) responders and (b) non-responders. DNA was extracted from saliva and genotyped for candidate SNPs in the VEGFA, LOC387715, and CFH genes. Clinical outcomes were statistically compared to patient genotypes.
101 patients were recruited, and one eye from each patient was included in the analysis. 97% of samples were successfully genotyped for all SNPs. We found a statistically significant association between the LOC387715 A69S TT genotype and outcome based on OCT.
Genetic variation may be associated with outcome in patients receiving anti-VEGF therapy.
age related macular degeneration; ARMS2; bevacizumab; complement factor H (CFH); LOC387715; ranibizumab; single nucleotide polymorphisms; vascular endothelial growth factor
Background and Aim
Liver cirrhosis is associated with decreased hepatic cytochrome P4503A (CYP3A) activity but the pathogenesis of this phenomenon is not well elucidated. In this study, we examined if certain microRNAs (miRNA) are associated with decreased hepatic CYP3A activity in cirrhosis.
Hepatic CYP3A activity and miRNA microarray expression profiles were measured in cirrhotic (n=28) and normal (n=12) liver tissue. Hepatic CYP3A activity was measured via midazolam hydroxylation in human liver microsomes. Additionally, hepatic CYP3A4 protein concentration and the expression of CYP3A4 mRNA were measured. Analyses were conducted to identify miRNAs which were differentially expressed between two groups but also were significantly associated with lower hepatic CYP3A activity.
Hepatic CYP3A activity in cirrhotic livers was 1.7-fold lower than in the normal livers (0.28 ± 0.06 vs. 0.47 ± 0.07mL* min-1*mg protein-1 (mean ± SEM), P=0.02). Six microRNAs (miR-155, miR-454, miR-582-5p, let-7f-1*, miR-181d, and miR-500) had >1.2-fold increase in cirrhotic livers and also had significant negative correlation with hepatic CYP3A activity (range of r = -0.44 to -0.52, P <0.05). Notably, miR-155, a known regulator of liver inflammation, had the highest fold increase in cirrhotic livers (2.2-fold, P=4.16E-08) and significantly correlated with hepatic CYP3A activity (r=-0.50, P=0.017). The relative expression (2-ΔΔCt mean ± SEM) of hepatic CYP3A4 mRNA was significantly higher in cirrhotic livers (21.76 ± 2.65 vs. 5.91 ± 1.29, P=2.04E-07) but their levels did not significantly correlate with hepatic CYP3A activity (r=-0.43, P=0.08).
The strong association between certain miRNAs, notably miR-155, and lower hepatic CYP3A activity suggest that altered miRNA expression may regulate hepatic CYP3A activity.
Analysis of global gene expression in mesenteric control and collateral arteries was used to investigate potential molecules, pathways, and mechanisms responsible for impaired collateral growth in the Spontaneously Hypertensive Rat (SHR). A fundamental difference was observed in overall gene expression pattern in SHR versus Wistar Kyoto (WKY) collaterals; only 6% of genes altered in collaterals were similar between rat strains. Ingenuity® Pathway Analysis (IPA) identified major differences between WKY and SHR in networks and biological functions related to cell growth and proliferation and gene expression. In SHR control arteries, several mechano-sensitive and redox-dependent transcription regulators were downregulated including JUN (−5.2×, P = 0.02), EGR1 (−4.1×, P = 0.01), and NFĸB1 (−1.95×, P = 0.04). Predicted binding sites for NFĸB and AP-1 were present in genes altered in WKY but not SHR collaterals. Immunostaining showed increased NFĸB nuclear translocation in collateral arteries of WKY and apocynin-treated SHR, but not in untreated SHR. siRNA for the p65 subunit suppressed collateral growth in WKY, confirming a functional role of NFkB. Canonical pathways identified by IPA in WKY but not SHR included nitric oxide and renin–angiotensin system signaling. The angiotensin type 1 receptor (AGTR1) exhibited upregulation in WKY collaterals, but downregulation in SHR; pharmacological blockade of AGTR1 with losartan prevented collateral luminal expansion in WKY. Together, these results suggest that collateral growth impairment results from an abnormality in a fundamental regulatory mechanism that occurs at a level between signal transduction and gene transcription and implicate redox-dependent modulation of mechano-sensitive transcription factors such as NFĸB as a potential mechanism.
Arteriogenesis; collateral gene expression; microarray analysis; peripheral vascular disease
To evaluate the screening performance of individual and combined use of clinical breast examination, ultrasonography and mammography in Chinese women, we conducted a biennial breast cancer screening program among 14,464 women aged 35 to 74 years old who lived in Qibao County, Minhang district of Shanghai, China, between May 2008 and Sept 2012. All participants were submitted to clinical breast examination, and then women with positive results and all women at age of 45-69 years old were preformed breast ultrasonography and mammography. The examination results were compared against pathological findings as the gold standard of reference. A total of 66 women were diagnosed with breast cancer in the two rounds of the screening, yielding an incident rate of 194 per 100,000 person-years. The sensitivity of clinical breast examination, ultrasonography and mammography alone were 61.4%, 53.7% and 67.3%, respectively. While mammography performed better in elder age groups and hormone receptor positive disease groups, ultrasonography had a higher sensitivity in younger age group and did not differ in sensitivity by estrogen receptor or progesterone receptor status. Combined use of the two imaging examinations increased the sensitivity in almost all age groups, but had a higher sensitivity in hormone receptor positive cancers than in those negative. Our results suggest that the Qibao modality is an effective strategy for breast cancer screening among Chinese women, especially for early detection of elder and hormone receptor positive breast cancer.
Breast cancer screening; Clinical breast examination; Mammography; Breast ultrasonography; Sensitivity; Specificity
The class of acetylcholinesterase inhibitors (ChEI), including donepezil, rivastigmine, and galantamine, have similar efficacy profiles in patients with mild to moderate Alzheimer’s disease (AD). However, few studies have evaluated adherence to these agents. We sought to prospectively capture the rates and reasons for nonadherence to ChEI and determine factors influencing tolerability and adherence.
We designed a pragmatic randomized clinical trial to evaluate the adherence to ChEIs among older adults with AD. Participants include AD patients receiving care within memory care practices in the greater Indianapolis area. Participants will be followed at 6-week intervals up to 18 weeks to measure the primary outcome of ChEI discontinuation and adherence rates and secondary outcomes of behavioral and psychological symptoms of dementia. The primary outcome will be assessed through two methods, a telephone interview of an informal caregiver and electronic medical record data captured from each healthcare system through a regional health information exchange. The secondary outcome will be measured by the Healthy Aging Brain Care Monitor and the Neuropsychiatric Inventory. In addition, the trial will conduct an exploratory evaluation of the pharmacogenomic signatures for the efficacy and the adverse effect responses to ChEIs. We hypothesized that patient-specific factors, including pharmacogenomics and pharmacokinetic characteristics, may influence the study outcomes.
This pragmatic trial will engage a diverse population from multiple memory care practices to evaluate the adherence to and tolerability of ChEIs in a real world setting. Engaging participants from multiple healthcare systems connected through a health information exchange will capture valuable clinical and non-clinical influences on the patterns of utilization and tolerability of a class of medications with a high rate of discontinuation.
Dementia; Adherence; Tolerability; Pharmacogenomics
To determine the impact of maternal and fetal single nucleotide polymorphisms (SNPs) in key betamethasone (BMZ) pathways on neonatal outcomes.
DNA was obtained from women given BMZ and their infants. Samples were genotyped for 73 exploratory drug metabolism and glucocorticoid pathway SNPs. Clinical variables and neonatal outcomes were obtained. Logistic regression analysis using relevant clinical variables and genotypes to model for associations with neonatal respiratory distress syndrome (RDS) was performed.
109 women delivering 117 babies were analyzed. Sixty-four babies (49%) developed RDS. Multivariable analysis revealed that RDS was associated with maternal SNPs in CYP3A5 (OR 1.63, 95%CI 1.16–2.30) and the glucocorticoid receptor (OR 0.28, 95%CI0.08–0.95) and fetal SNPs in ADCY9 (OR 0.17, 95%CI 0.03–0.80) and CYP3A7*1E (rs28451617, OR 23.68, 95%CI 1.33–420.6).
Maternal and fetal genotypes are independently associated with neonatal RDS after treatment with BMZ for preterm labor.
betamethasone; neonatal respiratory distress syndrome; preterm birth; pharmacogenetics
Effects of aromatase inhibitor (AI) therapy on the plasma lipid profile are not clear. Here the authors describe changes in fasting lipids (total cholesterol, high-density lipoprotein [HDL], low-density lipoprotein [LDL], and triglycerides) before and after 3 months of exemestane or letrozole treatment. HDL was reduced in the entire cohort (P < .001) and in the exemestane group (P < .001) but unchanged in the letrozole group (P = .169). LDL was increased in the entire cohort (P = .005) and in the letrozole group (P = .002) but unchanged in the exemestane group (P = .361). This effect was at least partially attributable to washout of tamoxifen as only patients with prior use of tamoxifen experienced a significant increase in LDL. Baseline HDL was an independent predictor of the change in HDL (r2 = −0.128, P < .001), and prior tamoxifen use was associated with greater increases in LDL (r2 = 0.057, P < .001). Use of lipid-altering medications did not protect against the exemestane-induced drop in HDL or the increase in LDL observed in women with prior use of tamoxifen taking letrozole. In conclusion, AI treatment and/or washout of tamoxifen induced detrimental changes in the lipid profile of postmenopausal women with breast cancer.
exemestane; letrozole; breast cancer; lipid profile; cholesterol
Aromatase inhibitors (AIs) are effective for treatment of hormone receptor–positive breast cancer, but adherence and persistence with therapy are poor. Predictors of treatment discontinuation are not clearly defined. It is unknown whether patients with intolerable toxicity from one AI are able to tolerate another.
Patients and Methods
Women with early-stage breast cancer initiating AI therapy were enrolled onto a multicenter, prospective, open-label randomized trial of exemestane versus letrozole. Patients completed symptom questionnaires at baseline and serially during therapy. Patients who developed AI-associated intolerable symptoms and discontinued treatment were given the option to switch to the other study AI after a 2- to 8-week washout period.
Of the 503 enrolled women, 32.4% discontinued initial AI therapy within 2 years because of adverse effects; 24.3% discontinued specifically because of musculoskeletal symptoms. Median time to treatment discontinuation as a result of any symptom was 6.1 months (range, 0.1 to 21.2 months) and was significantly shorter in patients randomly assigned to exemestane (hazard ratio [HR], 1.5; 95% CI, 1.1 to 2.1; P = .02). Younger age and taxane-based chemotherapy were associated with higher likelihood of treatment discontinuation (HR, 1.4; 95% CI, 1.02 to 1.9; P = .04; and HR, 1.9; 95% CI, 1.00 to 3.6; P = .048, respectively). Of the 83 patients who chose to switch to the second AI, 38.6% continued the alternate AI for a median of 13.7 months.
Premature discontinuation of initial AI therapy as a result of symptoms is common, although more than one third of patients may be able to tolerate a different AI medication. Additional research is needed to identify predictive tools and interventions for AI-associated treatment-emergent symptoms.
To explore the effect of metoprolol on myocardial apoptosis and caspase-9 activation after coronary microembolization (CME) in rats.
Forty rats were randomly divided into four groups (n=10 each): a sham operation (control) group, CME plus saline (CME) group, CME plus metoprolol (metoprolol) group and caspase-9 inhibitor Z-LEHD-FMK (ZLF) group. CME was induced by injecting 3000 polyethylene microspheres (42 μm diameter) into the left ventricle during a 10 s occlusion of the ascending aorta. Echocardiography, terminal deoxynucleotidyl transferase dUTP nick end labelling and Western blotting were used to evaluate cardiac function, apoptosis and activation of caspase-9/caspase-3, respectively, 6 h after CME.
The echocardiographic parameters of left ventricular function were significantly decreased in the CME group compared with the control group (P<0.05); however, the metoprolol group and ZLF group showed significantly improved cardiac function compared with CME alone (P<0.05). Compared with the control group, the myocardial apoptosis rate and the levels of activated caspase-9 and -3 increased significantly in the CME group (P<0.05). Again, these effects were ameliorated by metoprolol and ZLF (P<0.05).
The present study demonstrates that metoprolol and ZLF can protect the rat myocardium during CME by inhibiting apoptosis and improving cardiac function, likely by inhibiting apoptosis/ mitochondrial apoptotic pathway. These results suggest that antiapoptotic therapies may be useful in treating CME.
Apoptosis; Caspase-3; Caspase-9; Coronary microembolization; Metoprolol
Drug pharmacokinetics parameters, drug interaction parameters, and pharmacogenetics data have been unevenly collected in different databases and published extensively in the literature. Without appropriate pharmacokinetics ontology and a well annotated pharmacokinetics corpus, it will be difficult to develop text mining tools for pharmacokinetics data collection from the literature and pharmacokinetics data integration from multiple databases.
A comprehensive pharmacokinetics ontology was constructed. It can annotate all aspects of in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. It covers all drug metabolism and transportation enzymes. Using our pharmacokinetics ontology, a PK-corpus was constructed to present four classes of pharmacokinetics abstracts: in vivo pharmacokinetics studies, in vivo pharmacogenetic studies, in vivo drug interaction studies, and in vitro drug interaction studies. A novel hierarchical three level annotation scheme was proposed and implemented to tag key terms, drug interaction sentences, and drug interaction pairs. The utility of the pharmacokinetics ontology was demonstrated by annotating three pharmacokinetics studies; and the utility of the PK-corpus was demonstrated by a drug interaction extraction text mining analysis.
The pharmacokinetics ontology annotates both in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. The PK-corpus is a highly valuable resource for the text mining of pharmacokinetics parameters and drug interactions.
Bidirectional promoters are shared promoter sequences between divergent gene pair (genes proximal to each other on opposite strands), and can regulate the genes in both directions. In the human genome, > 10% of protein-coding genes are arranged head-to-head on opposite strands, with transcription start sites that are separated by < 1,000 base pairs. Many transcription factor binding sites occur in the bidirectional promoters that influence the expression of 2 opposite genes. Recently, RNA polymerase II (RPol II) ChIP-seq data are used to identify the promoters of coding genes and non-coding RNAs. However, a bidirectional promoter with RPol II ChIP-Seq data has not been found.
In some bidirectional promoter regions, the RPol II forms a bi-peak shape, which indicates that 2 promoters are located in the bidirectional region. We have developed a computational approach to identify the regulatory regions of all divergent gene pairs using genome-wide RPol II binding patterns derived from ChIP-seq data, based upon the assumption that the distribution of RPol II binding patterns around the bidirectional promoters are accumulated by RPol II binding of 2 promoters. In HeLa S3 cells, 249 promoter pairs and 1094 single promoters were identified, of which 76 promoters cover only positive genes, 86 promoters cover only negative genes, and 932 promoters cover 2 genes. Gene expression levels and STAT1 binding sites for different promoter categories were therefore examined.
The regulatory region of bidirectional promoter identification based upon RPol II binding patterns provides important temporal and spatial measurements regarding the initiation of transcription. From gene expression and transcription factor binding site analysis, the promoters in bidirectional regions may regulate the closest gene, and STAT1 is involved in primary promoter.
Typical analysis of time-series gene expression data such as clustering or graphical models cannot distinguish between early and later drug responsive gene targets in cancer cells. However, these genes would represent good candidate biomarkers.
We propose a new model - the dynamic time order network - to distinguish and connect early and later drug responsive gene targets. This network is constructed based on an integrated differential equation. Spline regression is applied for an accurate modeling of the time variation of gene expressions. Then a likelihood ratio test is implemented to infer the time order of any gene expression pair. One application of the model is the discovery of estrogen response biomarkers. For this purpose, we focused on genes whose responses are late when the breast cancer cells are treated with estradiol (E2).
Our approach has been validated by successfully finding time order relations between genes of the cell cycle system. More notably, we found late response genes potentially interesting as biomarkers of E2 treatment.
Alternative splicing increases proteome diversity by expressing multiple gene isoforms that often differ in function. Identifying alternative splicing events from RNA-seq experiments is important for understanding the diversity of transcripts and for investigating the regulation of splicing.
We developed Alt Event Finder, a tool for identifying novel splicing events by using transcript annotation derived from genome-guided construction tools, such as Cufflinks and Scripture. With a proper combination of alignment and transcript reconstruction tools, Alt Event Finder is capable of identifying novel splicing events in the human genome. We further applied Alt Event Finder on a set of RNA-seq data from rat liver tissues, and identified dozens of novel cassette exon events whose splicing patterns changed after extensive alcohol exposure.
Alt Event Finder is capable of identifying de novo splicing events from data-driven transcript annotation, and is a useful tool for studying splicing regulation.
Genetic variation in the expression of human xenobiotic metabolism enzymes and transporters (XMETs) leads to inter-individual variability in metabolism of therapeutic agents as well as differed susceptibility to various diseases. Recent expression quantitative traits loci (eQTL) mapping in a few human cells/tissues have identified a number of single nucleotide polymorphisms (SNPs) significantly associated with mRNA expression of many XMET genes. These eQTLs are therefore important candidate markers for pharmacogenetic studies. However, questions remain about whether these SNPs are causative and in what mechanism these SNPs may function. Given the important role of microRNAs (miRs) in gene transcription regulation, we hypothesize that those eQTLs or their proxies in strong linkage disequilibrium (LD) altering miR targeting are likely causative SNPs affecting gene expression. The aim of this study is to identify eQTLs potentially regulating major XMETs via interference with miR targeting. To this end, we performed a genome-wide screening for eQTLs for 409 genes encoding major drug metabolism enzymes, transporters and transcription factors, in publically available eQTL datasets generated from the HapMap lymphoblastoid cell lines and human liver and brain tissue. As a result, 308 eQTLs significantly (p < 10−5) associated with mRNA expression of 101 genes were identified. We further identified 7,869 SNPs in strong LD (r2 ≥ 0.8) with these eQTLs using the 1,000 Genome SNP data. Among these 8,177 SNPs, 27 are located in the 3′-UTR of 14 genes. Using two algorithms predicting miR-SNP interaction, we found that almost all these SNPs (26 out of 27) were predicted to create, abolish, or change the target site for miRs in both algorithms. Many of these miRs were also expressed in the same tissue that the eQTL were identified. Our study provides a strong rationale for continued investigation for the functions of these eQTLs in pharmacogenetic settings.
eQTL; xenobiotic metabolism enzyme and transporter; microRNA; pharmacogenetics; 3′-UTR
Estrogens control multiple functions of hormone-responsive breast cancer cells. They regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer. ERα requires distinct co-regulator or modulators for efficient transcriptional regulation, and they form a regulatory network. Knowing this regulatory network will enable systematic study of the effect of ERα on breast cancer.
To investigate the regulatory network of ERα and discover novel modulators of ERα functions, we proposed an analytical method based on a linear regression model to identify translational modulators and their network relationships. In the network analysis, a group of specific modulator and target genes were selected according to the functionality of modulator and the ERα binding. Network formed from targets genes with ERα binding was called ERα genomic regulatory network; while network formed from targets genes without ERα binding was called ERα non-genomic regulatory network. Considering the active or repressive function of ERα, active or repressive function of a modulator, and agonist or antagonist effect of a modulator on ERα, the ERα/modulator/target relationships were categorized into 27 classes.
Using the gene expression data and ERα Chip-seq data from the MCF-7 cell line, the ERα genomic/non-genomic regulatory networks were built by merging ERα/ modulator/target triplets (TF, M, T), where TF refers to the ERα, M refers to the modulator, and T refers to the target. Comparing these two networks, ERα non-genomic network has lower FDR than the genomic network. In order to validate these two networks, the same network analysis was performed in the gene expression data from the ZR-75.1 cell. The network overlap analysis between two cancer cells showed 1% overlap for the ERα genomic regulatory network, but 4% overlap for the non-genomic regulatory network.
We proposed a novel approach to infer the ERα/modulator/target relationships, and construct the genomic/non-genomic regulatory networks in two cancer cells. We found that the non-genomic regulatory network is more reliable than the genomic regulatory network.
A number of empirical Bayes models (each with different statistical distribution assumptions) have now been developed to analyze differential DNA methylation using high-density oligonucleotide tiling arrays. However, it remains unclear which model performs best. For example, for analysis of differentially methylated regions for conservative and functional sequence characteristics (e.g., enrichment of transcription factor-binding sites (TFBSs)), the sensitivity of such analyses, using various empirical Bayes models, remains unclear. In this paper, five empirical Bayes models were constructed, based on either a gamma distribution or a log-normal distribution, for the identification of differential methylated loci and their cell division—(1, 3, and 5) and drug-treatment-(cisplatin) dependent methylation patterns. While differential methylation patterns generated by log-normal models were enriched with numerous TFBSs, we observed almost no TFBS-enriched sequences using gamma assumption models. Statistical and biological results suggest log-normal, rather than gamma, empirical Bayes model distribution to be a highly accurate and precise method for differential methylation microarray analysis. In addition, we presented one of the log-normal models for differential methylation analysis and tested its reproducibility by simulation study. We believe this research to be the first extensive comparison of statistical modeling for the analysis of differential DNA methylation, an important biological phenomenon that precisely regulates gene transcription.
Histologic classification of thymomas has significant limitations with respect to both subtype definitions and consistency. In order to better understand the biology of the disease processes, we performed whole genome gene expression analysis. RNA was extracted from fresh frozen tumors from 34 patients with thymomas and followup data was available. Using the Illumina BeadStudio® platform and Human Ref-8 Beadchip, gene expression data was analyzed with Partek Genomics Suite®, and Ingenuity Pathways Analysis (IPA). Unsupervised clustering of gene expression data, representing one of the largest series in literature, resulted in identification of four molecular clusters of tumors (C1–C4), which correlated with histology (P = 0.002). However, neither histology nor clusters correlated with clinical outcomes. Correlation of gene expression data with clinical data showed that a number of genes were associated with either advanced stage at diagnosis or development of recurrence or metastases. The top pathways associated with metastases were amino acid metabolisms, biosynthesis of steroids and glycosphingolipids, cell cycle checkpoint proteins and Notch signaling. The differential expression of some of the top genes related to both metastases and stage was confirmed by RT-PCR in all cases of metastases and matched nonmetastatic cases. A number of potential candidates for therapeutics were also identified.
Drug-drug interactions (DDIs) are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on substrates and inhibitors of cytochrome P450 (CYP) metabolism enzymes identified from published in vitro pharmacology experiments. Using a clinical repository of over 800,000 patients, we narrowed this theoretical set of DDIs to 3670 drug pairs actually taken by patients. Finally, we sought to identify novel combinations that synergistically increased the risk of myopathy. Five pairs were identified with their p-values less than 1E-06: loratadine and simvastatin (relative risk or RR = 1.69); loratadine and alprazolam (RR = 1.86); loratadine and duloxetine (RR = 1.94); loratadine and ropinirole (RR = 3.21); and promethazine and tegaserod (RR = 3.00). When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Based on additional literature data on in vitro drug metabolism and inhibition potency, loratadine and simvastatin and tegaserod and promethazine were predicted to have a strong DDI through the CYP3A4 and CYP2D6 enzymes, respectively. This new translational biomedical informatics approach supports not only detection of new clinically significant DDI signals, but also evaluation of their potential molecular mechanisms.
Drug-drug interactions are a common cause of adverse drug events. In this paper, we developed an automated search algorithm which can predict new drug interactions based on published literature. Using a large electronic medical record database, we then analyzed the correlation between concurrent use of these potentially interacting drugs and the incidence of myopathy as an adverse drug event. Myopathy comprises a range of musculoskeletal conditions including muscle pain, weakness, and tissue breakdown (rhabdomyolysis). Our statistical analysis identified 5 drug interaction pairs: (loratadine, simvastatin), (loratadine, alprazolam), (loratadine, duloxetine), (loratadine, ropinirole), and (promethazine, tegaserod). When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Further investigation suggests that two major drug metabolism proteins, CYP2D6 and CYP3A4, are involved with these five drug pairs' interactions. Overall, our method is robust in that it can incorporate all published literature, all FDA approved drugs, and very large clinical datasets to generate predictions of clinically significant interactions. The interactions can then be further validated in future cell-based experiments and/or clinical studies.
Proliferating-cell nuclear antigen (PCNA) plays an important role in DNA replication and repair. The expression and potential utility of this marker in prostatic neoplasia is uncertain. With the development of this new caPCNA selective antibody, we explored the potential utility of this marker in prostate cancer.
Using a traditional primary Fab2′ rabbit anti-caPCNA antibody-HRP conjugated secondary anti-Fab2′ antibody format, the expression of the caPCNA was analyzed in prostate tissue from 89 radical prostatectomy specimens. The caPCNA expression was correlated with clinicopathologic characteristics.
The fraction of cells staining positively with caPCNA antibody in prostatic adenocarcinoma (mean, 23%) was significantly higher than that in benign prostatic epithelium (mean, 2%; p < 0.001) or high-grade prostatic intraepithelial neoplasia (PIN) (mean, 6%; p < 0.05). Moreover, the intensity of caPCNA expression in prostatic adenocarcinoma (mean, 2.9) was significantly higher than that in benign prostatic tissue (mean, 0.7; p < 0.001) or high-grade PIN (mean, 2.0; p < 0.001). Benign prostatic epithelium showed only minimal or negative reactivity. There was significant correlation between the percentage of caPCNA expression and primary Gleason grade (p = 0.01), and with Gleason score (p = 0.02). Adenocarcinomas with positive vascular invasion had a significantly higher percentage of cells staining with caPCNA antibody (p < 0.0001) and a higher intensity of caPCNA expression (p = 0.04).
Our data indicate that increased expression of the cancer-associated isoform of PCNA is common in prostatic adenocarcinoma and its precursor and may be a useful biomarker.
Prostate; biomarkers; proliferating-cell nuclear antigen (PCNA); Gleason grading; neoplasia; high-grade prostatic intraepithelial neoplasia (PIN); targeted therapy; progression; carcinogenesis
This study was performed to discover prognostic genomic markers associated with post-operative outcome of stage I-III non-small cell lung cancer (NSCLC) that are reproducible between geographically distant and demographically distinct patient populations.
American patients (n=27) were stratified on the basis of recurrence and microarray profiling of their tumors was performed to derive a training set of 44 genes. A larger Korean patient validation cohort (n=138) was also stratified by recurrence and screened for these genes. Four reproducible genes were identified and used to construct genomic and clinicogenomic Cox models for both cohorts.
Four genomic markers, DBN1 (drebrin 1), CACNB3 (calcium channel beta 3), FLAD1 (PP591; flavin adenine dinucleotide synthetase), and CCND2 (cyclin D2), exhibited highly significant differential expression in recurrent tumors in the training set (P<0.001). In the validation set, DBN1, FLAD1 (PP591) and CACNB3 were significant by Cox univariate analysis (P≤0.035), whereas only DBN1 was significant by multivariate analysis. Genomic and clinicogenomic models for recurrence free survival (RFS) were equally effective for risk stratification of stage I-II or I-III patients (all models P<0.0001). For stage I-II or I-III patients, 5-y RFS of the low- and high-risk patients was ∼ 70 vs. 30% for both models. The genomic model for overall survival (OS) of stage I-III patients was improved by addition of pT and pN stage (P<0.0013 vs. 0.010).
A 4-gene prognostic model incorporating the multivariate marker DBN1 exhibits potential clinical utility for risk stratification of stage I-III NSCLC patients.
NSCLC recurrence; DBN1; CACNB3; FLAD1; CCND2
It is now established that, as compared to normal cells, the cancer cell genome has an overall inverse distribution of DNA methylation (“methylome”), i.e., predominant hypomethylation and localized hypermethylation, within “CpG islands” (CGIs). Moreover, although cancer cells have reduced methylation “fidelity” and genomic instability, accurate maintenance of aberrant methylomes that underlie malignant phenotypes remains necessary. However, the mechanism(s) of cancer methylome maintenance remains largely unknown. Here, we assessed CGI methylation patterns propagated over 1, 3, and 5 divisions of A2780 ovarian cancer cells, concurrent with exposure to the DNA cross-linking chemotherapeutic cisplatin, and observed cell generation-successive increases in total hyper- and hypo-methylated CGIs. Empirical Bayesian modeling revealed five distinct modes of methylation propagation: (1) heritable (i.e., unchanged) high- methylation (1186 probe loci in CGI microarray); (2) heritable (i.e., unchanged) low-methylation (286 loci); (3) stochastic hypermethylation (i.e., progressively increased, 243 loci); (4) stochastic hypomethylation (i.e., progressively decreased, 247 loci); and (5) considerable “random” methylation (582 loci). These results support a “stochastic model” of DNA methylation equilibrium deriving from the efficiency of two distinct processes, methylation maintenance and de novo methylation. A role for cis-regulatory elements in methylation fidelity was also demonstrated by highly significant (p<2.2×10−5) enrichment of transcription factor binding sites in CGI probe loci showing heritably high (118 elements) and low (47 elements) methylation, and also in loci demonstrating stochastic hyper-(30 elements) and hypo-(31 elements) methylation. Notably, loci having “random” methylation heritability displayed nearly no enrichment. These results demonstrate an influence of cis-regulatory elements on the nonrandom propagation of both strictly heritable and stochastically heritable CGIs.
This study evaluates the relationship between cytochrome P450 (CYP) 3A5 genotype and vincristine-induced peripheral neuropathy in children with precursor B cell acute lymphoblastic leukemia (preB ALL). We have shown in vitro that vincristine is metabolized significantly more efficiently by CYP3A5 than by CYP3A4. We also found that vincristine neurotoxicity is less common in African-Americans (70% express CYP3A5) than in Caucasians. We test the hypothesis that CYP3A5 expressers experience less vincristine neuropathy than do CYP3A5 non-expressers.
This study of pharmacogenetics of vincristine neuropathy in children with preB ALL was completed at Indiana University Simon Cancer Center. Whole blood for DNA extraction and genotyping was collected as well as plasma from a single time-point for analysis of vincristine and primary metabolite (M1) concentrations. Vincristine neuropathy was captured via chart review and graded per the National Cancer Institute Common Terminology Criteria for Adverse Events, version 3.0.
89% of CYP3A5 expressers experienced neurotoxicity versus 100% of non-expressers (p=0.03). The proportion of treatment months with neurotoxicity was significantly different between the expressers and non-expressers (16% vs. 27%, p=0.0007). Limited pharmacokinetic data suggest different rates of vincristine metabolism between CYP3A5 genotype groups with higher primary metabolite (M1) plasma concentrations (p=0.0004) and lower metabolic ratios ([vincristine]/[M1]) (p=0.036) in the CYP3A5 expressers compared to the CYP3A5 non-expressers. M1 concentration was also inversely related to severity of neuropathy (p=0.0316).
In children with preB ALL, CYP3A5 expressers experience less vincristine-induced peripheral neuropathy, produce more M1, and have lower metabolic ratios compared to CYP3A5 non-expressers.
vincristine; pharmacogenetics; acute lymphoblastic leukemia; peripheral neuropathy
The metabolic activation of clopidogrel is a two-step process. It has been suggested that paraoxonase-1 (PON1) is a rate-limiting enzyme in the conversion of 2-oxo- clopidogrel to an active thiol metabolite. Conflicting results have been reported in regard to (1) the association of a common polymorphism of PON1 (Q192R) with reduced rates of coronary stent thrombosis in patients taking clopidogrel and (2) its effects on platelet inhibition in patient populations of European descent.
Blood samples from 151 subjects of mixed racial background with established coronary artery disease and who received clopidogrel were analyzed. Platelet aggregation was determined with light transmittance aggregometry and VerifyNow® P2Y12 assay. Genotyping for cytochrome P450 2C19 (CYP2C19)*2 and *3 and PON1 (Q192R) polymorphisms was performed.
Carriers of CYP2C19*2 alleles exhibited lower levels of platelet inhibition and higher on-treatment platelet aggregation than noncarriers. There was no significant difference in platelet aggregation among PON1 Q192R genotypes. Homozygous carriers of the wild-type variant of PON1 (QQ192) had similar on-treatment platelet reactivity to carriers of increased-function variant alleles during maintenance clopidogrel dosing, as well as after administration of a clopidogrel 600 mg loading dose.
CYP2C19*2 allele is associated with impaired platelet inhibition by clopidogrel and high on-treatment platelet aggregation. PON1 (Q192R) polymorphism does not appear to be a significant determinant of clopidogrel response.
PON1; platelet; aggregation; cytochrome P450 enzymes