A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

Computerized provider order entry adoption: implications for clinical workflow.

OBJECTIVE: To identify and describe unintended adverse consequences related to clinical workflow when implementing or using computerized provider order entry (CPOE) systems. METHODS: We analyzed qualitative data from field observations and formal interviews gathered over a three-year period at five hospitals in three organizations. Five multidisciplinary researchers worked together to identify themes related to the impacts of CPOE systems on clinical workflow. RESULTS: CPOE systems can affect clinical work by 1) introducing or exposing human/computer interaction problems, 2) altering the pace, sequencing, and dynamics of clinical activities, 3) providing only partial support for the work activities of all types of clinical personnel, 4) reducing clinical situation awareness, and 5) poorly reflecting organizational policy and procedure. CONCLUSIONS: As CPOE systems evolve, those involved must take care to mitigate the many unintended adverse effects these systems have on clinical workflow. Workflow issues resulting from CPOE can be mitigated by iteratively altering both clinical workflow and the CPOE system until a satisfactory fit is achieved.

Stability of specific immunoglobulin secretion by EBV-transformed lymphoblastoid cells and human-murine heterohybridomas

The purpose of this project was to determine if stability of specific antibody secretion improved after fusion of Epstein-Barr virus (EBV)-transformed lymphoblastoid cells with P3X63Ag8.653 murine myeloma cells. Production of human monoclonal antibodies by Epstein-Barr virus transformation and somatic cell fusion has been used by many laboratories, however the steps involved have not been fully optimized. B lymphocytes isolated from the peripheral blood of normal donors were enriched for Thomsen-Friedenreich (T) antigen-reactive cells by panning on asialoglycophorin. The EBV-transformed lymphoblastoid cell lines generated from asialoglycophorin-adherent B lymphocytes were treated in three different manners: (1) cloned and maintained in culture as monoclonal lymphoblastoid cell lines, (2) cloned and fused with murine myeloma cells or (3) fused shortly after transfomation without prior cloning. Cloned lymphoblastoid cell lines maintained in culture without fusion either died or lost specific antibody secretion within five months. Uncloned lymphoblastoid cells remained viable for up to three months but lost specific antibody secretion within two months probably due to overgrowth by nonspecific clones. In an attempt to increase longevity and to stabilize specific antibody secretion by these cells, the cloned lymphoblastoid cells were fused with murine myeloma cells. In nine of ten fusions no hybrids were recovered. As an alternate approach, uncloned lymphoblastoid cells secreting T antigen-specific antibody were hybridized with murine myeloma cells, hybrids secreting T antigen-specific antibody were recovered in six of seven fusions. Furthermore, T antigen-specific antibodies of high titer were secreted by the heterohybridoma clones for more than five months of continuous culture. These heterohybridoma cells secreted more immunoglobulin, produced greater titers of antibody and maintained specific antibody secretion longer than either monoclonal or polyclonal EBV-transformed lymphoblastoid cells. These studies have conclusively demonstrated that fusion of polyclonal lymphoblastoid cells secreting T antigen-specific antibody with murine myeloma cells results in prolongation of human monoclonal antibody production compared with unfused monoclonal or polyclonal lymphoblastoid cell lines. This procedure should be generally applicable for the production of stable human monoclonal antibody-secreting cells lines from peripheral blood lymphocytes. ^

CHARACTERIZATION AND COMPARISON OF SUBHUMAN PRIMATE AND HUMAN TYPE C RETROVIRAL GENE PRODUCTS

The viral specific precursor polyproteins of simian sarcoma/simian associated virus (SiSV/SiAV), baboon endogenous viruses (BaEV), and three human isolate retroviruses, have been analyzed by radioimmunoprecipitation and tryptic peptide mapping. Cells infected with the BaEV isolates are characterized by identical precursor polyproteins: gPr80-85('env), Pr70-71('gag), and Pr65-67('gag). By tryptic digest mapping, m7-BaEV and 455K-BaEV were shown to be highly related. By comparison, mapping studies showed that BILN-BaEV was less highly related to m7-BaEV than was 455K-BaEV. Chase-incubated cells infected with BaEV also contained a stable, p28-related polyprotein termed P72('gag). This polyprotein appeared to arise by posttranslational modification of Pr70-71('gag). Tryptic digest mapping of BaEV and HL23V precursor polyproteins suggested that the BaEV-like component of HL23V was more closely related to m7-BaEV than to 455K-BaEV or BILN-BaEV.^ The intracellular precursor polyproteins of SiSV(SiAV) and gibbon ape leukemia virus (GaLV) were compared to the intracellular proteins of the human retrovirus isolates, HL23V, HEL12V, and A1476V. Cells infected with SiSV(SiAV) were characterized by polyproteins Pr200('gag-pol), gPr80('env), Pr80('gag), pr60('gag), and Pr40('gag). We have found that the human isolates are identical to true SiAV with regard to the size and structure of their precursor polyproteins. Both gPr80('env) and Pr60('gag) of SiAV were identical by tryptic peptide mapping to the respective proteins from the three human retroviral isolates examined. We have also shown that these viruses differ significantly from each of the GaLV isolates studied. Since SiAV differs substantially from any known GaLV isolate, we feel that it is unlikely that SiAV is a subtype of GaLV which exists today in the gibbon gene pool. The experimental evidence suggests that SiAV may be an exogenous human retrovirus that was transmitted originally into the human gene pool in the distant past by cross-species infection with GaLV(,SF) or with the GaLV(,SF) progenitor virus. It is, therefore, quite possible that SiAV expression in the pet woolly monkey arose from a recent infection of that monkey with SiAV from humans.^

Emodin, a tyrosine kinase inhibitor, and human cancer

Many human diseases, including cancers, result from aberrations of signal transduction pathways. The recent understanding of the molecular biochemistry of signal transduction in normal and transformed cells enable us to have a better insight about cancer and design new drugs to target this abnormal signaling in the cancer cells. Tyrosine kinase pathway plays a very important role in normal and cancer cells. Enhanced activity of tyrosine kinases has been associated with many human cancer types. Therefore, identifying the type of tyrosine kinases involved in a particular cancer type and blocking these tyrosine kinase pathways may provide a way to treat cancer. Receptor tyrosine kinase expression, namely epidermal growth factor receptor (EGFR) family, was examined in the oral squamous cell carcinoma patients. The expression levels of different members of the EGFR family were found to be significantly associated with shorter patients' survival. Combining EGFR, HER-2/neu, and HER-3 expression can significantly improve the predicting power. The effect of emodin, a tyrosine kinase inhibitor, on these receptors in head and neck squamous cell carcinoma cell lines was examined. Emodin was found to suppress the tyrosine phosphorylation of HER-2/neu and EGF-induced tyrosine phosphorylation of EGFR. Emodin also induced apoptosis and downregulated the expression of anti-apoptotic protein bcl-2 in oral squamous cell carcinoma cells. It is known that tyrosine kinase pathways are involved in estrogen receptor signaling pathway. Therefore, the effects of inhibiting the tyrosine kinase pathway in estrogen receptor-positive breast cancers was studied. Emodin was found to act similarly to antiestrogens, capable of inhibiting estrogen-stimulated growth and DNA synthesis, and the phosphorylation of Rb protein. Interestingly, emodin, and other tyrosine kinase inhibitors, such as RG 13022 and genistein, depleted cellular levels of estrogen receptor protein. Emodin-induced depletion of estrogen receptor was mediated by the proteasome degradation pathway. In summary, we have demonstrated that tyrosine kinase pathways play an important role in oral squamous cell carcinoma and estrogen receptor-positive breast cancer. Targeting the tyrosine kinases by inhibitors, such as emodin, may provide a potential way to treat the cancer patients. ^

Convergent etiology of Eker rat and human uterine leiomyoma

The Eker rat model has allowed researchers the unique opportunity to study the tumorigenesis of spontaneously occurring uterine leiomyoma. Animals in this line harbor a germline mutation in the tuberous sclerosis complex-2 (Tsc-2) tumor suppressor gene and develop uterine leiomyomas at a rate of ∼65%. Primary leiomyomas obtained from humans and Eker rats along with Eker-derived leiomyoma cell lines were used in studies described herein to determine the effect of PPARγ ligand treatment on the proliferation of this cell type and to determine the role of tuberin and p27Kip1 in the etiology of this tumor type. Treatment of leiomyoma cells of human and rat origin with PPARγ-activating compounds resulted in decreased proliferation. Additionally, PPARγ ligands inhibited estrogen-dependent gene transactivation in Eker-derived leiomyoma cells suggesting that nuclear receptor cross-talk may exist between PPAR and the ER and may be responsible for the inhibition of proliferation in this cell type. Loss of tuberin, the product of the TSC-2 gene, is associated with Eker rat leiomyoma development while the role of this tumor suppressor in human leiomyoma development is unknown. Data herein show that tuberin expression is diminished in 25% of human leiomyomas tested. Additionally, we observed diminished p27 Kip1 expression in 80% of human uterine leiomyomas compared to normal myometrium. Interestingly, the loss of tuberin expression in human leiomyoma was associated with cytoplasmic p27Kip1 accumulation in this cell type. Furthermore, tuberin-null Eker rat leiomyomas and derived cell lines had predominantly cytoplasmic p27Kip1 compared to tuberin-expressing normal myometrium. Taken together, our data show that human and Eker rat leiomyoma proliferation is inhibited upon PPARγ treatment and that the etiology of human and Eker rat leiomyoma converge at loss of p27Kip1 function. Furthermore, our data indicate that the loss of p27 Kip1 function is mediated by loss of expression (in 80% of human leiomyoma) or cytoplasmic localization potentially resulting from the loss of tuberin. ^

Hepatitis C and human immunodeficiency virus infections in injecting drug users in drug treatment centers in Vietnam

Background. Injecting drug users (IDUs) are at risk of infection with Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV). Independently, each of these viruses is a serious threat to health, with HIV ravaging the body’s immune system, and HCV causing cirrhosis, liver cancer and liver failure. Co-infection with HIV/HCV weakens the response to antiretroviral therapy in HIV patients. IDUs with HIV/HCV co-infection are at a 20 times higher risk of having liver-related morbidity and mortality than IDUs with HIV alone. In Vietnam, studies to ascertain the prevalence of HIV have found high rates, but little is known about their HCV status. ^ Purpose. To measure the prevalence of HCV and HIV infection and identify factors associated with these viruses among IDUs at drug treatment centers in northern Vietnam. ^ Methods. A cross-sectional study was conducted from November 2007 to February 2008 with 455 injecting drug users aged 18 to 39 years, admitted no more than two months earlier to one of four treatment centers in Northern Vietnam (Hatay Province) (response rate=95%). Participants, all of whom had completed detoxification and provided informed consent, completed a risk assessment questionnaire and had their blood drawn to test for the presence of antibody-HCV and antibody-HIV with enzyme immuno assays. Univariate and multivariable logistic regression models were utilized to explore the strength of association using HIV, HCV infections and HIV/HCV co-infection as outcomes and demographic characteristics, drug use and sexual behaviors as factors associated with these outcomes. Unadjusted and adjusted odds ratios and 95% confidence intervals were calculated. ^ Results. Among all IDU study participants, the prevalence of HCV alone was 76.9%, HIV alone was 19.8%. The prevalence of HIV/HCV co-infection was 92.2% of HIV-positive and 23.7% of HCV-positive respondents. No sexual risk behaviors for lifetime, six months or 30 days prior to admission were significantly associated with HCV or HIV infection among these IDUs. Only duration of injection drug use was independently associated with HCV and HIV infection, respectively. Longer duration was associated with higher prevalence. Nevertheless, while HCV infection among IDUs who reported being in their first year of injecting drugs were lower than longer time injectors, their rates were still substantial, 67.5%. ^ Compared with either HCV mono-infection or HIV/HCV non-infection, HIV/HCV co-infection was associated with the length of drug injection history but was not associated with sexual behaviors. Higher education was associated with a lower prevalence of HIV/HCV co-infection. When compared with HIV/HCV non-infection, current marriage was associated with a lower prevalence of HIV/HCV co-infection. ^ Conclusions. HCV was prevalent among IDUs from 18 to 39 years old at four drug treatment centers in northern Vietnam. Co-infection with HCV was predominant among HIV-positive IDUs. HCV and HIV co-infection were closely associated with the length of injection drug history. Further research regarding HCV/HIV co-infection should include non-injecting drug users to assess the magnitude of sexual risk behaviors on HIV and HCV infection. (At these treatment centers non-IDUs constituted 10-20% of the population.) High prevalence of HCV prevalence among IDUs, especially among HIV-infected IDUs, suggests that drug treatment centers serving IDUs should include not only HIV prevention education but they should also include the prevention of viral hepatitis. In addition, IDUs who are HIV-positive need to be tested for HCV to receive the best course of therapy and achieve the best response to HIV treatment. These data also suggest that because many IDUs get infected with HCV in the first year of their injection drug career, and because they also engaged in high risk sexual behaviors, outreach programs should focus on harm reduction, safer drug use and sexual practices to prevent infection among drug users who have not yet begun injecting drugs and to prevent further spread of HCV, HIV and co-infection. ^

A systematic review of the animal and human literature on the use of vaccines to prevent dental caries

Streptococcus mutans has been identified as the primary etiological agent of human dental caries. Since its identification, there has been research focused on the development of a vaccine to prevent this disease. Preliminary research has been conducted to test both active and passive vaccines for Streptococcus mutans in animals and humans. Although a vaccine for dental caries caused by Streptococcus mutans would most likely be administered to children, no testing of any type of dental caries vaccines has been conducted on children as of yet. The public health imperative for the development of a vaccine is great. Not only will a vaccine reduce the various consequences, but it would also improve quality of life for many individuals. Among the many possible vaccine antigen candidates, researchers have also been focusing on protein antigens, GTFs, and Gbps as possible candidates for a vaccine. There are also many routes of administration under research, with topical, oral, and intranasal showing a lot of promise. This review will provide an overview on the current state of research, present key factors influencing prevalence of caries, and summarize and discuss the results of animal and human studies on caries vaccines against Streptococcus mutans. The progress and obstacles facing the development of a vaccine to fight dental caries will also be discussed. ^

A comprehensive review of the environmental impacts and human health risks associated with the occurrence of waste pharmaceuticals in water sources of the United States, and policy implications

The occurrence of waste pharmaceuticals has been identified and well documented in water sources throughout North America and Europe. Many studies have been conducted which identify the occurrence of various pharmaceutical compounds in these waters. This project is an extensive review of the documented evidence of this occurrence published in the scientific literature. This review was performed to determine if this occurrence has a significant impact on the environment and public health. This project and review found that pharmaceuticals such as sex hormone drugs, antibiotic drugs and antineoplastic/cytostatic agents as well as their metabolites have been found to occur in water sources throughout the United States at levels high enough to have noticeable impacts on human health and the environment. It was determined that the primary sources of this occurrence of pharmaceuticals were waste water effluent and solid wastes from sewage treatment plants, pharmaceutical manufacturing plants, healthcare and biomedical research facilities, as well as runoff from veterinary medicine applications (including aquaculture). ^ In addition, current public policies of US governmental agencies such as the Environmental Protection Agency (EPA), Food and Drug Administration (FDA), and Drug Enforcement Agency (DEA) have been evaluated to see if they are doing a sufficient job at controlling this issue. Specific recommendations for developing these EPA, FDA, and DEA policies have been made to mitigate, prevent, or eliminate this issue.^ Other possible interventions such as implementing engineering controls were also evaluated in order to mitigate, prevent and eliminate this issue. These engineering controls include implementing improved current treatment technologies such as the advancement and improvement of waste water treatment processes utilized by conventional sewage treatment and pharmaceutical manufacturing plants. In addition, administrative controls such as the use of “green chemistry” in drug synthesis and design were also explored and evaluated as possible alternatives to mitigate, prevent, or eliminate this issue. Specific recommendations for incorporating these engineering and administrative controls into the applicable EPA, FDA, and DEA policies have also been made.^

Correlation of tuberculosis and human immunodeficiency virus in Harris County, Texas from 2009 through 2010 using Geographic Information Systems

A population based ecological study was conducted to identify areas with a high number of TB and HIV new diagnoses in Harris County, Texas from 2009 through 2010 by applying Geographic Information Systems to determine whether distinguished spatial patterns exist at the census tract level through the use of exploratory mapping. As of 2010, Texas has the fourth highest occurrence of new diagnoses of HIV/AIDS and TB.[31] The Texas Department of State Health Services (DSHS) has identified HIV infected persons as a high risk population for TB in Harris County.[29] In order to explore this relationship further, GIS was utilized to identify spatial trends. ^ The specific aims were to map TB and HIV new diagnoses rates and spatially identify hotspots and high value clusters at the census tract level. The potential association between HIV and TB was analyzed using spatial autocorrelation and linear regression analysis. The spatial statistics used were ArcGIS 9.3 Hotspot Analysis and Cluster and Outlier Analysis. Spatial autocorrelation was determined through Global Moran's I and linear regression analysis. ^ Hotspots and clusters of TB and HIV are located within the same spatial areas of Harris County. The areas with high value clusters and hotspots for each infection are located within the central downtown area of the city of Houston. There is an additional hotspot area of TB located directly north of I-10 and a hotspot area of HIV northeast of Interstate 610. ^ The Moran's I Index of 0.17 (Z score = 3.6 standard deviations, p-value = 0.01) suggests that TB is statistically clustered with a less than 1% chance that this pattern is due to random chance. However, there were a high number of features with no neighbors which may invalidate the statistical properties of the test. Linear regression analysis indicated that HIV new diagnoses rates (β=−0.006, SE=0.147, p=0.970) and census tracts (β=0.000, SE=0.000, p=0.866) were not significant predictors of TB new diagnoses rates. ^ Mapping products indicate that census tracts with overlapping hotspots and high value clusters of TB and HIV should be a targeted focus for prevention efforts, most particularly within central Harris County. While the statistical association was not confirmed, evidence suggests that there is a relationship between HIV and TB within this two year period.^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

*Ras proteins and human tumor cell radiosensitivity

Ras proteins (H-, N-, K4A-, and K4B) are associated with cellular resistance to ionizing radiation (IR) and, consequently, may provide a potential target for radiosensitization strategies in cancer treatment. Several approaches have been used to compromise Ras activity and enhance IR-induced cell killing; however, these techniques either target proteins in addition to Ras or only target one member of the Ras family. In this study, I have used an adenovirus (AV1Y28) that expresses a single-chain antibody fragment directed against Ras proteins to investigate the mechanism(s) responsible for Ras-mediated radiation resistance. AV1Y28 enhanced the radiosensitivity of a number of human tumor cell lines without affecting the radiosensitivity of normal human fibroblasts. Whereas AV1Y28-mediated sensitization was independent of ras gene mutational status, it was dependent on active Ras proteins suggesting that AV1Y28 may be useful against a broad range of tumors. AV1Y28-mediated cell killing was not the result of redistributing cells into a more radiosensitive phase of the cell cycle and did not enhance IR-induced apoptosis. Given that Ras proteins transduce environmental signals to the nucleus, the effect of AV1Y28 on the IR-inducible transcription factor NF-κB were determined. Although AV1Y28 inhibited IR-induced NF-κB through the suppression of IKK, additional work established that NF-κB did not play a role in AV1Y28-mediated radiosensitization. However, a novel component of the signaling pathway responsible for IR-induced NF-κB was identified. Previous studies had suggested a relationship between mutant ras genes and IR-induced G2 delay; therefore the effects of AV1Y28 on the progression of cells from G2 to M after IR were determined. Pretreatment of cells with AV1Y28 prevented the IR-induced G2 arrest. AV1Y28-mediated abrogation of IR-induced G2 arrest correlated with those cell line lines that were sensitized by AV1Y28. Moreover, a significant increase in cells undergoing mitotic catastrophe was found after IR in AV1Y28 treated cells. The abrogation of G2 arrest by AV1Y28 was the result of maintaining the active form of cdc2, an inducer of mitosis, after exposure to IR. This study identified the mechanism of AV1Y28-mediated radiosensitization and has provided insight into the signal transduction pathways responsible for Ras-mediated radiation resistance. ^