Effects of the microenvironment on Fas/Fas ligand interactions and their implications for UV-induced immune suppression

Skin cancer is the most common malignancy in humans. Although highly treatable, non-melanoma skin cancer is commonly followed by other non-cutaneous malignancies. Ultraviolet radiation (UVR) acts as both tumor initiator and promoter, and also results in the suppression of specific immune responses. The systemic suppression of immune responses is initiated by DNA damage, which promotes IL-10 production, an important cytokine as anti-IL-10 can abrogate the suppression, and upregulates the pro-apoptotic proteins Fas and Fas ligand (FasL). FasL is a critical factor for UV-induced immune suppression, and the suppressor cell induced by UV expresses FasL. ^ We hypothesized that the microenvironment affects Fas/FasL interactions, and that these interactions are important to the phenomenon of UV induced immune suppression. To determine the effects of the interaction of FasL and IL-10, splenocytes isolated from C57Bl/6 mice were cultured in the presence or absence of IL-10 post-mitogenic activation. We determined that IL-10 protects from Fas-mediated apoptosis by lowering Fas sensitivity and lowering the levels of either Fas or FasL. This protection is stronger when IL-10 is given immediately after mitogenic activation, and does not increase any of the inhibitors of apoptosis studied. In vivo, splenocytes from UV-irradiated mice are resistant to Fas-mediated apoptosis and present very high levels of IL-10, lowered Fas sensitivity and lowered caspase cleavage despite higher expression of Fas and FasL than non-irradiated mice. ^ UV-induced immune suppression affects female mice preferentially, which led us to look at prolactin as a possible component of this suppression since this hormone has also been associated with increased skin carcinogenesis. The interaction of FasL and prolactin results in suppression of the delayed type hypersensitivity response to Candida albicans. This lack of response depends on FasL as is not seen in gld mice. Similar to UV-induced immune suppression, the suppression is caused by a Th2 deviation, and correlates with a significant increase in Fas expression. In the presence of UV, the effects of prolactin seemed to be protective, and UV actually restores the DTH response.^ Taken together, these observations suggest that the microenvironment dictates the outcome of the interaction of FasL with Fas going from promoting apoptosis to preventing apoptosis or mediating a Th2 deviation and suppression of a Th1 response. ^

Mechanisms involved in suppression of the elicitation of immune responses by ultraviolet light

The ultraviolet radiation (UVR) present in sunlight is the primary cause of nonmelanoma skin cancer and has been implicated in the development of cutaneous malignant melanoma. Ultraviolet radiation also suppresses the immune response. In the majority of studies investigating the mechanisms regulating UV-induced immune suppression, UV is used to suppress the induction of immune responses. Equally important, is the ability of UVR to suppress established immune responses, such as the recall reaction in humans, which protects against microbial infections. We established a murine model to help elucidate the immunological mechanisms governing UV-induced suppression of the elicitation of immune responses. 80 kJ/m2 of UVR nine days after sensitization consistently suppressed the elicitation of delayed type hypersensitivity reaction to C. albicans . We found ultraviolet A (320±400 nm) radiation was as effective as solar-simulated ultraviolet A + B (290±400 nm) in suppressing the elicitation of an established immune response. The mechanisms involved in UV-induced suppression of the induction & elicitation of the immune response are similar. For example, mice irradiated with UV after immunization generated antigen-specific T suppressor cells. Injection of monoclonal antibodies to IL-10 or recombinant IL-12 immediately after exposure to UVR blocked immune suppression. Liposomes containing bacteriophage T4N5 to the skin of mice also prevented immune suppression, demonstrating an essential role for ultraviolet-induced DNA damage in the suppression of established immune reactions. ^ In addition to damaging DNA, UV initiates immune suppression through the isomerization of urocanic acid in the epidermis. Here we provide evidence that cis-UCA induces systemic immunosuppression via the serotonin (5-hydroxyyryptamine; 5-HT) receptor. Biochemical and immunological analysis indicate that cis-UCA binds to, and activates, the serotonin receptor. Moreover, serotonin specific antibodies block UV- and/or cis-UCA-induced immune suppression. Our findings identify cis-UCA as novel serotonin receptor ligand and indicate that serotonin receptor engagement can activate immune suppression. Cumulatively, our data suggest that similar immune regulatory mechanisms are activated regardless of whether we expose mice to solar-simulated UV (UVA + UVB) radiation or UVA only, and that ultraviolet radiation activates similar immunologic pathways to suppress the induction or the elicitation of the immune response. ^

Insights into the biology of lymphatic metastasis

Recent data suggest that the generation of new lymphatic vessels (i.e. lymphangiogenesis) may be a rate-limiting step in the dissemination of tumor cells to regional lymph nodes. However, efforts to study the cellular and molecular interactions that take place between tumor cells and lymphatic endothelial cells have been limited due to a lack of lymphatic endothelial cell lines available for study. ^ I have used a microsurgical approach to establish conditionally immortalized lymphatic endothelial cell lines from the afferent mesenteric lymphatic vessels of mice. Characterization of lymphatic endothelial cells, and tumor-associated lymphatic vessels revealed high expression levels of VCAM-1, which is known to facilitate adhesion of some tumor cells to vascular endothelial cells. Further investigation revealed that murine melanoma cells selected for high expression of α4, a counter-receptor for VCAM-1, demonstrated enhanced adhesion to lymphatic endothelial cells in vitro, and increased tumorigenicity and lymphatic metastasis in vivo, despite similar lymphatic vessel numbers. ^ Next, I examined the effects of growth factors that regulate lymphangiogenesis, and report that several growth factors are capable of activating survival and proliferation pathways of lymphatic endothelial cells. The dual protein tyrosine kinase inhibitor AEE788 (EGFR and VEGFR-2) inhibited the activation of Akt and MAPK in lymphatic endothelial cells responding to multiple growth factors. Moreover, oral treatment of mice with AEE788 decreased lymphatic vessel density and production of lymphatic metastasis by human colon cancer cells growing in the cecum of nude mice. ^ In the last set of experiments, I investigated the surgical management of lymphatic metastasis using a novel model of sentinel lymphadenectomy in live mice bearing subcutaneous B16-BL6 melanoma. The data demonstrate that this procedure when combined with wide excision of the primary melanoma, significantly enhanced survival of syngeneic C57BL/6 mice. ^ Collectively, these results indicate that the production of lymphatic metastasis depends on lymphangiogenesis, tumor cell adhesion to lymphatic endothelial cells, and proliferation of tumor cells in lymph nodes. Thus, lymphatic metastasis is a multi-step, complex, and active process that depends upon multiple interactions between tumor cells and tumor associated lymphatic endothelial cells. ^

Monte Carlo and analytical dose calculations for ocular proton therapy

Uveal melanoma is a rare but life-threatening form of ocular cancer. Contemporary treatment techniques include proton therapy, which enables conservation of the eye and its useful vision. Dose to the proximal structures is widely believed to play a role in treatment side effects, therefore, reliable dose estimates are required for properly evaluating the therapeutic value and complication risk of treatment plans. Unfortunately, current simplistic dose calculation algorithms can result in errors of up to 30% in the proximal region. In addition, they lack predictive methods for absolute dose per monitor unit (D/MU) values. ^ To facilitate more accurate dose predictions, a Monte Carlo model of an ocular proton nozzle was created and benchmarked against measured dose profiles to within ±3% or ±0.5 mm and D/MU values to within ±3%. The benchmarked Monte Carlo model was used to develop and validate a new broad beam dose algorithm that included the influence of edgescattered protons on the cross-field intensity profile, the effect of energy straggling in the distal portion of poly-energetic beams, and the proton fluence loss as a function of residual range. Generally, the analytical algorithm predicted relative dose distributions that were within ±3% or ±0.5 mm and absolute D/MU values that were within ±3% of Monte Carlo calculations. Slightly larger dose differences were observed at depths less than 7 mm, an effect attributed to the dose contributions of edge-scattered protons. Additional comparisons of Monte Carlo and broad beam dose predictions were made in a detailed eye model developed in this work, with generally similar findings. ^ Monte Carlo was shown to be an excellent predictor of the measured dose profiles and D/MU values and a valuable tool for developing and validating a broad beam dose algorithm for ocular proton therapy. The more detailed physics modeling by the Monte Carlo and broad beam dose algorithms represent an improvement in the accuracy of relative dose predictions over current techniques, and they provide absolute dose predictions. It is anticipated these improvements can be used to develop treatment strategies that reduce the incidence or severity of treatment complications by sparing normal tissue. ^

The role and mechanism of supressor of cytokine signaling 1 in brain metastasis

Brain metastasis, which occurs in 40%-60% of patients with advanced melanoma, has led directly to death in the majority of cases. Unfortunately, little is known about the biological and molecular basis of melanoma brain metastases. In our previous study, we developed a model to study human melanoma brain metastasis and found that Stat3 activity was increased in human brain metastatic melanoma cells when compared with that in cutaneous melanoma cells. The increased activation of Stat3 is also responsible for affecting melanoma angiogenesis in vivo and melanoma cell invasion in vitro and significantly affecting the expression of bFGF, VEGF, and MMP-2 in vivo and in vitro. Interestingly, a member of a new family of cytokine-inducible inhibitors of signal transduction, termed suppressors of cytokine signaling 1 (SOCS1) was found to negatively regulate the Janus kinase signal transducer and activator of transcription (Jak/STAT) signaling cascade. Here we report that restoration of SOCS1 expression by transfecting of SOCS1-expressing vector effectively inhibited melanoma brain metastasis through inhibiting Stat3 activation and further affecting melanoma angiogenesis and melanoma cell invasion in vitro, and significantly affected the expression of vascular endothelial growth factor (VEGF) and matrix metalloproteinase-2 (MMP-2) in vitro and in vivo. In addition, we used cDNA array to compare mRNA expression in the SOCS1-transfected and vector-transfected cell lines and found some genes are tightly correlated to the restoration of SOCS1. One of them is Caveolin-1 (Cav-1). Cav-1 was reported to function as a tumor suppressor gene by several groups. Finally, the Cav-1 expression is up-regulated in SOCS1-overexpressing cell line. Further study found the regulation of Cav-1 by SOCS1 occurs through inhibiting Stat3 activation. Activated Stat3 binds directly to Cav-1 promoter and the Cav-1 promoter within -575bp is essential for active Stat3 binding. My studies reveal that Stat3 activation and SOCS1 expression play important roles in melanoma metastases. Moreover, the expression between SOCS1, Stat3 and Cav-1 forms a feedback regulation loop. ^

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

Psychosocial measures reported by parents in studies of skin cancer prevention

Background. Because it is important to minimize children's sun exposure to reduce skin cancer risk, much of the extensive skin cancer prevention literature consists of studies of children's sun protection, sun avoidance and ultraviolet radiation (UVR) exposure. Little attention has been focused on the measurement of psychosocial constructs in these studies. Identification of the psychosocial correlates or determinants of children's skin cancer risk or risk-reduction behavior is critical to more fully understand and predict behavior. Furthermore, psychosocial variables may be influenced by interventions to reduce risk. Thus, it is important to examine the psychosocial measures used in studies of children's skin cancer prevention. Information on the validity and reliability of psychosocial measures may increase confidence in study findings based on these measures. In particular, self-efficacy and barriers are key constructs in several major theoretical frameworks and parental measures have been associated with children's sun protection. However, there is conceptual overlap of self-efficacy and barriers measures and little is known about the psychometric properties of these measures.^ Study Aims and Methods. The overall goal of this dissertation was to examine the measurement of psychosocial constructs relevant to children's skin cancer prevention. Because children depend primarily on their parents for skin cancer prevention, measures of parents' psychosocial constructs are the focus. Study 1 was a systematic review of parental psychosocial measures used in studies of children's sun protection, sun avoidance and UVR exposure. The specific aims of Study 1 were to (1) describe psychosocial measures reported by parents, including available information on the psychometric properties of these measures and their use in analyses and (2) provide recommendations for the development, refinement and standardized reporting of measures. ^ Study 2 examined the psychometric properties of measures of parental self-efficacy and barriers regarding children's sun protection. Melanoma patients (N=205) who were parents of children ≤ 12 years of age completed a telephone interview that included self-efficacy and barriers measures specific to sunscreen, clothing, shade and limiting time outdoors. The specific aims of Study 2 were to (1) use a confirmatory factor analytic approach to examine the factorial validity of parental self-efficacy and barriers measures, (2) examine the convergent and discriminant validity of behavior-specific measures of self-efficacy and barriers and (3) assess the reliability of item and scale measures.^ Results. In Study 1, a search of standard databases yielded 48 eligible studies. Most studies assessed only one or two psychosocial constructs. Knowledge was measured most frequently. There was little discussion of measure source, development, theoretical background or psychometric properties, besides internal consistency reliability. There was conceptual overlap of some measures. In Study 2, confirmatory factor analytic findings supported the factorial validity of the self-efficacy and barriers measures. When all eight self-efficacy and barriers measures were included in the same model, a modified eight-factor model adequately fit the data, providing preliminary evidence that the measures are distinct. Measure associations supported the convergent validity of all measures and the discriminant validity of most measures. The self-efficacy and barriers measures were reliable.^ Conclusions. Recommendations based on the literature review include developing and refining psychosocial measures based on theory. Describing a measure's theoretical basis and psychometric properties would facilitate critical evaluation. Standardized reporting of source, development, theory, construct, items and analytic role would facilitate comparison of findings, continual refinement and future applications of measures. In the validation study, self-efficacy and barriers measures were examined in a sample of parents with a personal history of melanoma. Findings suggested that these measures are valid and reliable for use in studies of children's sun protection. There was preliminary evidence that these measures are distinct but additional study is needed. ^

Assessment of cancer incidence in Titus County, Texas, 1977--1984

The purpose of this study was to determine the incidence of cancer in Titus County, Texas, through the identification of all cases of cancer that occurred in residents of the county during the period from 1977 to 1984. Data gathered from Texas Cancer Registry, hospital records, and death certificates were analyzed with regard to anatomic site, race, sex, age, city of residence, and place of birth. Adjustment of incidence rates by sex and race allowed comparisons with U.S. rates provided by the Surveillance, Epidemiology, and End Results Program (SEER).^ Seven hundred sixty-six (766) cancer cases were identified for the eight year period during 171,536 person-years of observation. In whites, statistically significant standardized incidence ratios (SIR) were found for leukemia (males SIR = 2.70 and females SIR = 2.26), melanoma (males SIR = 1.90 and females SIR = 2.25), lung (males SIR = 1.45) and for multiple myeloma (both sexes combined SIR = 1.86). In blacks, significant excess numbers of cases were found for Hodgkin's disease (males SIR = 8.33 and females SIR = 13.3) and for esophagus and bone considering both sexes together (SIR = 2.68 and 12.54, respectively). Rates for blacks were based on a small population and therefore unstable. A statistically significant excess number of cases for all sites combined was found in Mount Pleasant residents (age-adjusted incidence rate = 563.6 per 100,000 per year).^ A review of possible environmental risk factors in the area: hazardous waste disposal site, lignite deposits, and petrochemical and poultry industries are presented. A need for further epidemiological and environmental studies to identify etiological factors that could be responsible for the excess number of leukemia cases are recommended. For melanoma, a public health educational program to teach the population methods of protection from sun exposure is also suggested. ^

THE CYTOPLASMIC TAIL OF MHC CLASS I MOLECULES PLAYS A CRITICAL ROLE IN DENDRITIC CELL-INDUCED T CELL IMMUNITY

The presentation of MHC class I (MHC-I)/peptide complexes by dendritic cells (DCs) is critical for the maintenance of central tolerance to self and for the regulation of cytotoxic T lymphocytes (CTL)-mediated adaptive immune responses against pathogens and cancer cells. Interestingly, several findings have suggested that the cytoplasmic tail of MHC class I plays a functional role in the regulation of CTL immune responses. For example, our previous studies demonstrated that exon 7-deleted MHC-I molecules not only showed extended DC cell surface half-lives but also induced significantly increased CTL responses to viral challange invivo. Although exon 7-deleted variant of MHC-I does not occur naturally in humans, the animal studies prompted us to examine whether exon 7-deleted MHC-I molecules could generate augmented CTL responses in a therapeutic DC-based vaccine setting. To examine the stimulatory capacity of exon 7-deleted MHC-I molecules, we generated a lentivirus-mediated gene transfer system to induce the expression of different MHC-I cytoplasmic tail isoforms in both mouse and human DCs. These DCs were then used as vaccines in a melanoma mouse tumor model and in a human invitro co-culture system. In this thesis, we show that DCs expressing exon 7-deleted MHC-I molecules, stimulated remarkably higher levels of T-cell cytokine production and significantly increased the proliferation of meanoma-specific (Pmel-1) T cells compared with DCs expressing wild type MHC-I. We also demonstrate that, in combination with adoptive transfer of Pmel-1 T-cell, DCs expressing exon 7-deleted Db molecules induced greater anti-tumor responses against established B16 melanoma tumors, significantly extending mouse survival as compared to DCs expressing wild-type Db molecules. Moreover, we also observed that human DCs expressing exon 7-deleted HLA-A2 molecules showed similarly augmented CTL stimulatory ability. Mechanistic studies suggest that exon 7-deleted MHC-I molecules showed impaired lateral membrane movement and extended cell surface half-lives within the DC/T-cell interface, leading to increased spatial availability of MHC-I/peptide complexes for recognition by CD8+ T cells. Collectively, these results suggesr that targeting exon 7 within the cytoplasmic tail of MHC-I molecules in DC vaccines has the potential to enhance CD8+ T cell stimulatory capacity and improve clinical outcomes in patients with cancer or viral infections.

Knowledge, Attitudes, and Utilization of BRCA Testing Among Obstetricians and Gynecologists

Hereditary breast and ovarian cancer (HBOC) is an inherited cancer syndrome that is associated with mutations in the BRCA1 and BRCA2 genes. Carriers of BRCA mutations, both men and women, are at an increased risk for developing certain cancers. Carriers are most notably at an increased risk to develop breast and ovarian cancers; however an increased risk for prostate cancer, melanoma, and pancreatic cancers has also been associated with these mutations. In 2009 the American Congress of Obstetricians and Gynecologists (ACOG) released a practice bulletin stating that evaluating a patient’s risk for HBOC should be a routine part of obstetric and gynecologic practice. A survey was created and completed by 83 obstetricians and gynecologists in the greater Houston, TX area. The survey consisted of four sections designed to capture demographic information, attitudes towards HBOC and BRCA testing, utilization of BRCA testing, and the overall knowledge of respondents with regards to HBOC and BRCA testing. This study found that the majority of participants indicated that they felt that obstetricians and gynecologists should have the primary responsibility of identifying patients who may be at increased risk of carrying a BRCA mutation. Moreover, this study found that the majority of participants indicated that they felt comfortable or very comfortable in identifying patients at an increased risk of carrying a BRCA mutation. However, only about a quarter of participants indicated that they order BRCA genetic testing one to two times per month or more. Lastly, this study demonstrates that the overall knowledge of HBOC and BRCA testing among this population of obstetricians and gynecologists is poor. The results of this study stress the need for more education regarding HBOC, genetic testing, and strategies for identifying patients that may be at risk for having a mutation in a BRCA gene. Furthermore, it reiterates the importance of raising awareness to current practice guidelines and recommendations that can assist obstetricians and gynecologist to better identify and manage patients that may be at an increased risk of having HBOC.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Novel Imaging-Based Techniques Reveal a Role for PD-1/PD-L1 in Tumor Immune Surveillance in the Lung

The binding of immune inhibitory receptor Programmed Death 1 (PD-1) on T cells to its ligand PD-L1 has been implicated as a major contributor to tumor induced immune suppression. Clinical trials of PD-L1 blockade have proven effective in unleashing therapeutic anti-tumor immune responses in a subset of patients with advanced melanoma, yet current response rates are low for reasons that remain unclear. Hypothesizing that the PD-1/PD-L1 pathway regulates T cell surveillance within the tumor microenvironment, we employed intravital microscopy to investigate the in vivo impact of PD-L1 blocking antibody upon tumor-associated immune cell migration. However, current analytical methods of intravital dynamic microscopy data lack the ability to identify cellular targets of T cell interactions in vivo, a crucial means for discovering which interactions are modulated by therapeutic intervention. By developing novel imaging techniques that allowed us to better analyze tumor progression and T cell dynamics in the microenvironment; we were able to explore the impact of PD-L1 blockade upon the migratory properties of tumor-associated immune cells, including T cells and antigen presenting cells, in lung tumor progression. Our results demonstrate that early changes in tumor morphology may be indicative of responsiveness to anti-PD-L1 therapy. We show that immune cells in the tumor microenvironment as well as tumors themselves express PD-L1, but immune phenotype alone is not a predictive marker of effective anti-tumor responses. Through a novel method in which we quantify T cell interactions, we show that T cells are largely engaged in interactions with dendritic cells in the tumor microenvironment. Additionally, we show that during PD-L1 blockade, non-activated T cells are recruited in greater numbers into the tumor microenvironment and engage more preferentially with dendritic cells. We further show that during PD-L1 blockade, activated T cells engage in more confined, immune synapse-like interactions with dendritic cells, as opposed to more dynamic, kinapse-like interactions with dendritic cells when PD-L1 is free to bind its receptor. By advancing the contextual analysis of anti-tumor immune surveillance in vivo, this study implicates the interaction between T cells and tumor-associated dendritic cells as a possible modulator in targeting PD-L1 for anti-tumor immunotherapy.

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.

Expression of TNF-$\alpha$ protein and C -FOS and TNF mRNA during human peripheral blood monocyte maturation and activation

Human peripheral blood monocytes (HPBM) were isolated by centrifugal elutriation from mononuclear cell enriched fractions after routine plateletapheresis and the relationship between maturation of HPBM to macrophage-like cells and activation for tumoricidal activity determined. HPBM were cultured for various times in RPMI 1640 supplemented with 5% pooled human AB serum and cytotoxicity to $\sp{125}$IUDR labeled A375M, a human melanoma cell line, and TNF-$\alpha$ release determined by cytolysis of actinomycin D treated L929 cells. Freshly isolated HPBM or those exposed to recombinant IFN-$\gamma$(1.0 U/ml) were not cytolytic and did not release TNF-$\alpha$ into culture supernatants. Exposure to bacterial lipopolysaccharide (LPS, 1.0 $\upsilon$g/ml) stimulated cytolytic activity and release of TNF-$\alpha$. Maximal release of TNF-$\alpha$ protein occurred at 8 hrs and returned to baseline by 72 hrs. Expression of TNF-$\alpha$ protein was determined by Western blotting. Neither freshly isolated nor IFN-$\gamma$ treated HPBM expressed TNF protein at any time during in vitro culture. LPS treated HPBM maximally expressed the 17KD TNF-$\alpha$ protein at 8 hrs, and protein was not detected after 36 hrs of in vitro culture. Expression of TNF-$\alpha$ mRNA was determined by Northern blotting. Freshly isolated HPBM express TNF-$\alpha$ mRNA which decays to basal levels by 6 hrs of in vitro culture. IFN-$\gamma$ treatment maintains TNF-$\alpha$ mRNA expression for up to 48 hrs of culture, after which it is undetectable. LPS induces TNF-$\alpha$ mRNA after 30 minutes of exposure with maximal accumulation occurring between 4 to 8 hrs. TNF mRNA was not detected in control HPBM at any time after 6 hrs or IFN-$\gamma$ treated HPBM after 48 hrs of in vitro culture. A pulse of LPS the last 24 hrs of in vitro culture induces the accumulation of TNF-$\alpha$ mRNA in HPBM cultured for 3, 5, and 7 days, with the magnitude of induction decreasing approximately 10 fold between 3 and 7 days. Induction of TNF-$\alpha$ mRNA occurred in the absence of detectable TNF-$\alpha$ protein or supernatant activity. Maturation of HPBM to macrophage-like cells controls competence for activation, magnitude and duration of the activation response. ^

Dissection of antitumor activity by lymphokine -activated killer cells: Role of FcR+ precursors and obligatory role of tumor necrosis factor-$\alpha$ in antibody -dependent cellular cytotoxicity

Human peripheral blood lymphocytes (PBL) cultured for varying lengths of time in IL-2 are able to mediate antibody independent cellular cytotoxicity (AICC) as well as antibody dependent cellular cytotoxicity (ADCC) against a wide range of tumor targets. The objective of our study is to determine the cytotoxic potential of the subset of LAK cells involved in ADCC, the tumor recognition mechanism in ADCC, the kinetics of ADCC mediated by PBL cultured under various conditions and the role of TNF-$\alpha$ in the development and maturation of ADCC effectors in the LAK population.^ The model system in this study for ADCC used a monoclonal antibody 14G2a (IgG2a), that recognizes the GD2 epitope on human melanoma cell line, SK-Mel-1. The target recognition mechanism operative in AICC (traditionally known as lymphokine activated killing or LAK) is an acquired property of these IL-2 activated cells which confers on them the unique ability to distinguish between tumor and normal cells. This recognition probably involves the presence of a trypsin sensitive N-linked glycoprotein epitope on tumor cells. Proteolytic treatment of the tumor cells with trypsin renders them resistant to AICC by PBL cultured in IL-2. However, ADCC is unaffected. This ADCC, mediated by the relatively small population of cells that are positive for the Fc receptor for IgG (FcR), is an indication that this subset of "LAK" cells does not require the trypsin sensitive epitope on tumor cells to mediate killing. Enriching PBL for FcR+ cells markedly enhanced both AICC and ADCC and also reduced the IL-2 requirement of these cells.^ The stoichiometry of Fc receptor (FcR) expression on the cytotoxic effectors does not correlate with ADCC lytic activity. Although FcRs are necessary to mediate ADCC, other factors, appear to regulate the magnitude of cytolytic activity. In order to investigate these putative factors, the kinetics of ADCC development was studied under various conditions (in IL-2 (10u/ml) and 100u/ml), in IL-2(10u/ml) + TNF$\alpha$ (500u/ml) and in TNF-$\alpha$ (500u/ml) alone). Addition of exogenous TNF-$\alpha$ into the four hour cytotoxicity assay did not increase ADCC, nor did anti-TNF antibodies result in inhibition. On the other hand, addition of anti-TNF antibodies to PBL and IL-2 for 24 hours, resulted in a marked inhibition of the ADCC, suggesting that endogenous TNF-$\alpha$ is obligatory for the maturation and differentiation of ADCC effectors. ^