Up to 25% of patients discontinue adjuvant aromatase inhibitor (AI) therapy due to intolerable symptoms. Predictors of which patients will be unable to tolerate these medications have not been defined. We hypothesized that inherited variants in candidate genes are associated with treatment discontinuation because of AI-associated toxicity.
We prospectively evaluated reasons for treatment discontinuation in women with hormone receptor-positive breast cancer initiating adjuvant AI through a multicenter, prospective, randomized clinical trial of exemestane versus letrozole. Using multiple genetic models, we evaluated potential associations between discontinuation of AI therapy because of toxicity and 138 variants in 24 candidate genes, selected a priori, primarily with roles in estrogen metabolism and signaling. To account for multiple comparisons, statistical significance was defined as p<0.00036.
Of the 467 enrolled patients with available germline DNA, 152 (33%) discontinued AI therapy because of toxicity. Using a recessive statistical model, an intronic variant in ESR1 (rs9322336) was associated with increased risk of musculoskeletal toxicity-related exemestane discontinuation (HR 5.0 (95% CI 2.1–11.8), p<0.0002).
An inherited variant potentially affecting estrogen signaling may be associated with exemestane-associated toxicity, which could partially account for intra-patient differences in AI tolerability. Validation of this finding is required.
breast cancer; aromatase inhibitor; single nucleotide polymorphism; treatment discontinuation; toxicity
Several risk factors have been identified as potential contributors to pancreatic cancer development, including environmental and lifestyle factors, such as smoking, drinking and diet, and medical conditions such as diabetes and pancreatitis, all of which generate oxidative stress and DNA damage. Oxidative stress status can be modified by environmental factors and also by an individual's unique genetic makeup. Here we examined the contribution of environment and genetics to an individual's level of oxidative stress, DNA damage and susceptibility to pancreatic cancer in a pilot study using three groups of subjects: a newly diagnosed pancreatic cancer group, a healthy genetically-unrelated control group living with the case subject, and a healthy genetically-related control group which does not reside with the subject. Oxidative stress and DNA damage was evaluated by measuring total antioxidant capacity, direct and oxidative DNA damage by Comet assay, and malondialdehyde levels. Direct DNA damage was significantly elevated in pancreatic cancer patients (age and sex adjusted mean ± standard error: 1.00±0.05) versus both healthy unrelated and related controls (0.70±0.06, p<0.001 and 0.82±0.07, p = 0.046, respectively). Analysis of 22 selected SNPs in oxidative stress and DNA damage genes revealed that CYP2A6 L160H was associated with pancreatic cancer. In addition, DNA damage was found to be associated with TNFA −308G>A and ERCC4 R415Q polymorphisms. These results suggest that measurement of DNA damage, as well as select SNPs, may provide an important screening tool to identify individuals at risk for development of pancreatic cancer.
We previously demonstrated that maternal and fetal genotypes are independently associated with neonatal respiratory distress syndrome (RDS). The objective of the current study is to determine the impact of maternal and fetal single nucleotide polymorphisms (SNPs) in key betamethasone (BMZ) pathways on respiratory outcomes that serve as markers for severity of disease.
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 controlling for relevant clinical variables to determine SNP impact on bronchopulmonary dysplasia (BPD), need for respiratory support, and surfactant therapy use was performed.
109 women delivering 117 infants were analyzed. 14.5% of the infants developed BPD, 70.8% needed some respiratory support after birth, and 27.5% needed surfactant. In a multivariable regression analysis, gestational age at delivery was associated with most neonatal respiratory outcomes (p≤0.01) and chorioamnionitis was associated with BPD (p<0.03). Genotypes associated with respiratory severity outcomes were as follows: BPD- Fetal IPO13 (rs4448553; OR 0.01, 95% CI 0.00–0.92); Surfactant use- Maternal IPO13 (rs2428953 and 2486014; OR 13.8, 95%CI 1.80–105.5 and OR 35.5, 95% CI 1.71–736.6, respectively).
Several discrete maternal and fetal SNPs in the Importin 13 gene (IPO13) may be associated with neonatal respiratory outcomes after maternal antenatal corticosteroid treatment for anticipated preterm birth.
antenatal corticosteroids; pharmacogenetics; preterm birth
Clinically validated biomarkers for anti-angiogenesis agents are not available. We have previously reported associations between candidate VEGFA SNPs and overall survival (OS) in E2100. The associations between tumor VEGFA amplification and outcome are evaluated here.
Patients and Methods
E2100 was a phase III trial comparing paclitaxel with or without bevacizumab for patients with metastatic breast cancer. Fluorescence in situ hybridization to assess gene amplification status for VEGFA was performed on paraffin embedded tumors from 363 patients in E2100. Evaluation for association between amplification status and outcomes was performed.
ER+ or PR+ tumors were less likely to have VEGFA amplification compared with ER/PR-tumors (p=0.020). VEGFA amplification was associated with worse OS (20.2 vs. 25.3 months; p=0.013) in univariate analysis with a trend for worse OS in multivariate analysis (p=0.08). There was a significant interaction between VEGFA amplification, hormone-receptor status, and study arm. Patients with VEGFA amplification and triple negative breast cancers (TNBCs) or HER2 amplification had inferior OS (p=0.047); amplification did not affect OS for those who were ER+ or PR+ and HER2-. Those who received bevacizumab with VEGFA amplification had inferior PFS (p=0.010) and OS (p=0.042); no association was seen in the control arm. Test for interaction between study arm and VEGFA amplification with OS was not significant.
VEGFA amplification in univariate analysis was associated with poor outcomes; this was particularly prominent in HER2+ or TNBCs. Additional studies are necessary to confirm the trend for poor OS seen on multivariate analysis for patients treated with bevacizumab.
Breast cancer; VEGF amplification; bevacizumab
DAPK1, a tumor suppressor, is a rate-limiting effector in an ER stress-dependent apoptotic pathway. Its expression is epigenetically suppressed in several tumors. A mechanistic basis for epigenetic/transcriptional repression of DAPK1 was investigated in certain forms of AML with poor prognosis, which lacked ER stress-induced apoptosis.
Heterogeneous primary AMLs were screened to identify a subgroup with Flt3ITD in which repression of DAPK1, among NF-κB- and c- jun-responsive genes, was studied. RNAi knockdown studies were performed in Flt3ITD+ve cell line, MV-4-11, to establish genetic epistasis in the pathway Flt3ITD-TAK1-DAPK1 repression, and chromatin immunoprecipitations were performed to identify proximate effector proteins, including TAK1-activated p52NF-κB, at the DAPK1 locus.
AMLs characterized by normal karyotype with Flt3ITD were found to have 10-100-fold lower DAPK1 transcripts normalized to the expression of c-jun, a transcriptional activator of DAPK1, as compared to a heterogeneous cytogenetic category. Meis1, a c-jun-responsive adverse AML prognostic gene signature was also measured as control. These Flt3ITD+ve AMLs over-express relB, a transcriptional repressor, which forms active heterodimers with p52NF-κB. Chromatin immunoprecipitation assays identified p52NF-κB binding to the DAPK1 promoter along with HDAC2 and HDAC6 in the Flt3ITD+ve human AML cell line MV-4-11. Knockdown of p52NF-κB or its upstream regulator, NIK, de-repressed DAPK1. DAPK1-repressed primary Flt3ITD+ve AMLs had selective nuclear activation of p52NF-κB.
Flt3ITD promotes a non-canonical pathway via TAK1 and p52NF-κB to suppress DAPK1 in association with HDACs, which explains DAPK1 repression in Flt3ITD+ve AML.
DAPK1; NFκB; histone deacetylase; endoplasmic reticulum; Flt3
Recent candidate gene studies using a human liver bank and in vivo validation in healthy volunteers identified polymorphisms in cytochrome P450 (CYP) 3A4 gene (CYP3A4*22), Ah-receptor nuclear translocator (ARNT), and peroxisome proliferator-activated receptor-α (PPAR-α) genes that are associated with the CYP3A4 phenotype. We hypothesized that the variants identified in these genes may be associated with altered clopidogrel response, since generation of clopidogrel active metabolite is, partially mediated by CYP3A activity. Blood samples from 211 subjects, of mixed racial background, with established coronary artery disease, who had received clopidogrel, were analyzed. Platelet aggregation was determined using light transmittance aggregometry (LTA). Genotyping for CYP2C19*2, CYP3A4*22, PPAR-α (rs4253728, rs4823613), and ARNT (rs2134688) variant alleles was performed using Taqman® assays. CYP2C19*2 genotype was associated with increased on-treatment platelet aggregation (adenosine diphosphate 20 μM; P=0.025). No significant difference in on-treatment platelet aggregation, as measured by LTA during therapy with clopidogrel, was demonstrated among the different genotypes of CYP3A4*22, PPAR-α, and ARNT. These findings suggest that clopidogrel platelet inhibition is not influenced by the genetic variants that have previously been associated with reduced CYP3A4 activity.
clopidogrel; pharmacogenetics; CYP450; platelet aggregation
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
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
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.