The Role of Acidic Fibroblast Growth Factor and Fibroblast Growth Factor Receptor 4 in High Grade Serous Carcinoma

Background: High grade serous carcinoma whether ovarian, tubal or primary peritoneal, continues to be the most lethal gynecologic malignancy in the USA. Although combination chemotherapy and aggressive surgical resection has improved survival in the past decade the majority of patients still succumb to chemo-resistant disease recurrence. It has recently been reported that amplification of 5q31-5q35.3 is associated with poor prognosis in patients with high grade serous ovarian carcinoma. Although the amplicon contains over 50 genes, it is notable for the presence of several members of the fibroblast growth factor signaling axis. In particular acidic fibroblast growth factor (FGF1) has been demonstrated to be one of the driving genes in mediating the observed prognostic effect of the amplicon in ovarian cancer patients. This study seeks to further validate the prognostic value of fibroblast growth receptor 4 (FGFR4), another candidate gene of the FGF/FGFR axis located in the same amplicon. The emphasis will be delineating the role the FGF1/FGFR4 signaling axis plays in high grade serous ovarian carcinoma; and test the feasibility of targeting the FGF1/FGFR4 axis therapeutically. Materials and Methods: Spearman and Pearson correlation studies on data generated from array CGH and transcriptome profiling analyses on 51 microdissected tumor samples were used to identify genes located on chromosome 5q31-35.3 that showed significant correlation between DNA and mRNA copy numbers. Significant correlation between FGF1 and FGFR4 DNA copy numbers was further validated by qPCR analysis on DNA isolated from 51 microdissected tumor samples. Immunolocalization and quantification of FGFR4 expression were performed on paraffin embedded tissue samples from 183 cases of high-grade serous ovarian carcinoma. The expression was then correlated with clinical data to assess impact on survival. The expression of FGF1 and FGFR4 in vitro was quantified by real-time PCR and western blotting in six high-grade serous ovarian carcinoma cell lines and compared to those in human ovarian surface epithelial cells to identify overexpression. The effect of FGF1 on these cell lines after serum starvation was quantified for in vitro cellular proliferation, migration/invasion, chemoresistance and survival utilizing a combination of commercially available colorimetric, fluorometric and electrical impedance assays. FGFR4 expression was then transiently silenced via siRNA transfection and the effects on response to FGF1, cellular proliferation, and migration were quantified. To identify relevant cellular pathways involved, responsive cell lines were transduced with different transcription response elements using the Cignal-Lenti reporter system and treated with FGF1 with and without transient FGFR4 knock down. This was followed by western blot confirmation for the relevant phosphoproteins. Anti-FGF1 antibodies and FGFR trap proteins were used to attempt inhibition of FGF mediated phenotypic changes and relevant signaling in vitro. Orthotopic intraperitoneal tumors were established in nude mice using serous cell lines that have been previously transfected with luciferase expressing constructs. The mice were then treated with FGFR trap protein. Tumor progression was then followed via bioluminescent imaging. The FGFR4 gene from 52 clinical samples was sequenced to screen for mutations. Results: FGFR4 DNA and mRNA copy numbers were significantly correlated and FGFR4 DNA copy number was significantly correlated with that of FGF1. Survival of patients with high FGFR4 expressing tumors was significantly shorter that those with low expression(median survival 28 vs 55 month p< 0.001) In a multivariate cox regression model FGFR expression significantly increased risk of death (HR 2.1, p<0.001). FGFR4 expression was significantly higher in all cell lines tested compared to HOSE, OVCA432 cell line in particular had very high expression suggesting amplification. FGF1 was also particularly overexpressed in OVCA432. FGF1 significantly increased cell survival after serum deprivation in all cell lines. Transient knock down of FGFR4 caused significant reduction in cell migration and proliferation in vitro and significantly decreased the proliferative effects of FGF1 in vitro. FGFR1, FGFR4 traps and anti-FGF1 antibodies did not show activity in vitro. OVCA432 transfected with the cignal lenti reporter system revealed significant activation of MAPK, NFkB and WNT pathways, western blotting confirmed the results. Reverse phase protein array (RPPA) analysis also showed activation of MAPK, AKT, WNT pathways and down regulation of E Cadherin. FGFR trap protein significantly reduced tumor growth in vivo in an orthotopic mouse model. Conclusions: Overexpression and amplification of several members of the FGF signaling axis present on the amplicon 5q31-35.3 is a negative prognostic indicator in high grade serous ovarian carcinoma and may drive poor survival associated with that amplicon. Activation of The FGF signaling pathway leads to downstream activation of MAPK, AKT, WNT and NFkB pathways leading to a more aggressive cancer phenotype with increased tumor growth, evasion of apoptosis and increased migration and invasion. Inhibition of FGF pathway in vivo via FGFR trap protein leads to significantly decreased tumor growth in an orthotopic mouse model.

Dynamic Remodeling of the Stressed Heart: Role of Protein Degradation Pathways

The heart is a remarkable organ. In order to maintain its function, it remodels in response to a variety of environmental stresses, including pressure overload, volume overload, mechanical or pharmacological unloading and hormonal or metabolic disturbances. All these responses are linked to the inherent capacity of the heart to rebuild itself. Particularly, cardiac pressure overload activates signaling pathways of both protein synthesis and degradation. While much is known about regulators of protein synthesis, little is known about regulators of protein degradation in hypertrophy. The ubiquitin-proteasome system (UPS) selectively degrades unused and abnormal intracellular proteins. I speculated that the UPS may play an important role in both qualitative and quantitative changes in the composition of heart muscle during hypertrophic remodeling. My study hypothesized that cardiac remodeling in response to hypertrophic stimuli is a dynamic process that requires activation of highly regulated mechanisms of protein degradation as much as it requires protein synthesis. My first aim was to adopt a model of left ventricular hypertrophy and determine its gene expression and structural changes. Male Sprague-Dawley rats were submitted to ascending aortic banding and sacrificed at 7 and 14 days after surgery. Sham operated animals served as controls. Effective aortic banding was confirmed by hemodynamic assessment by Doppler flow measurements in vivo. Banded rats showed a four-fold increase in peak stenotic jet velocities. Histomorphometric analysis revealed a significant increase in myocyte size as well as fibrosis in the banded animals. Transcript analysis showed that banded animals had reverted to the fetal gene program. My second aim was to assess if the UPS is increased and transcriptionally regulated in hypertrophic left ventricular remodeling. Protein extracts from the left ventricles of the banded and control animals were used to perform an in vitro peptidase assay to assess the overall catalytic activity of the UPS. The results showed no difference between hypertrophied and control animals. Transcript analysis revealed decreases in transcript levels of candidate UPS genes in the hypertrophied hearts at 7 days post-banding but not at 14 days. However, protein expression analysis showed no difference at either time point compared to controls. These findings indicate that elements of the UPS are downregulated in the early phase of hypertrophic remodeling and normalizes in a later phase. The results provide evidence in support of a dynamic transcriptional regulation of a major pathway of intracellular protein degradation in the heart. The discrepancy between transcript levels on the one hand and protein levels on the other hand supports post-transcriptional regulation of the UPS pathway in the hypertrophied heart. The exact mechanisms and the functional consequences remain to be elucidated.

DOWNREGULATION OF PAX2 SUPPRESSES OVARIAN CANCER CELL GROWTH

PAX2 is one of nine PAX genes regulating tissue development and cellular differentiation in embryos. PAX2 promotes cell proliferation, oncogenic transformation, cell-lineage specification, migration, and survival. Unattenuated PAX2 has been found in several cancer types. We therefore sought to elucidate the role of PAX2 in ovarian carcinomas. We found that PAX2 was expressed in low-grade serous, clear cell, endometrioid and mucinous cell ovarian carcinomas, which are relatively chemoresistant compared to high grade serous ovarian carcinomas. Four ovarian cancer cell lines, RMUGL (mucinous), TOV21G (clear cell), MDAH-2774 (endometrioid) and IGROV1 (endometrioid), which express high-levels of PAX2, were used to study the function of PAX2. Lentiviral shRNAs targeting PAX2 were used to knock down PAX2 expression in these cell lines. Cellular proliferation and motility assays subsequently showed that PAX2 stable knockdown had slower growth and migration rates. Microarray gene expression profile analysis further identified genes that were affected by PAX2 including the tumor suppressor gene G0S2. Reverse phase protein array (RPPA) data showed that PAX2 knockdown affected several genes that are involved in apoptosis, which supports the fact that downregulation of PAX2 in PAX2-expressing ovarian cancer cells inhibits cell growth. We hypothesize that this growth inhibition is due to upregulation of the tumor suppressor gene G0S2 via induction of apoptosis. PAX2 represents a potential therapeutic target for chemoresistant PAX2-expressing ovarian carcinomas.

Glycogen Synthase Kinase 3 is Required for Optimal AKT Activation

The phosphatidylinositol 3-kinase (PI3K) pathway, through its major effector node AKT, is critical for the promotion of cell growth, division, motility and apoptosis evasion. This signaling axis is therefore commonly targeted in the form of mutations and amplifications in a myriad of malignancies. Glycogen synthase kinase 3 (GSK3) was first discovered as the kinase responsible for phosphorylating and inhibiting the activity of glycogen synthase, ultimately antagonizing the storage of glucose as glycogen. Its activity counteracts the effects of insulin in glucose metabolism and AKT has long been recognized as one of the key molecules capable of phosphorylating GSK3 and inhibiting its activity. However, here we demonstrate that GSK3 is required for optimal phosphorylation and activation of AKT in different malignant cell lines, and that this effect is independent of the type of growth factor stimulation and can happen even in basal states. Both GSK3 alpha and GSK3 beta isoforms are necessary for AKT to become fully active, displaying a redundant role in the setting. We also demonstrate that this effect of GSK3 on AKT phosphorylation and full activation is dependent on its kinase activity, since highly specific inhibitors targeting GSK3 catalytic activity also promote a reduction in phosphorylated AKT. Analysis of reverse phase protein array screening of MDA-MB-231 breast cancer cells treated with RNA interference targeting GSK3 unexpectedly revealed an increase in levels of phosphorylated MAPK14 (p38). Treatment with the selective p38 inhibitor SB 202190 rescued AKT activation in that cell line, corroborating the importance of unbiased proteomic analysis in exposing cross-talks between signaling networks and demonstrating a critical role for p38 in the regulation of AKT phosphorylation.

A mechanism of insulin-like growth factor binding protein 2-induced cell mobility in glioma

Insulin-like growth factor binding protein 2 (IGFBP2) is a protein known to be overexpressed in a majority of glioblastoma multiforme (GBM) tumors. While it is known the IGFBP2 is involved in promoting GBM tumor cell invasion, no mechanism exists for how the protein is involved in signal transduction pathways leading to enhanced cell invasion. ^ We follow up on preliminary microarray data on IGFBP2-overexpressing GBM cells and protein sequence analysis of IGFBP2 in generating the hypothesis that IGFBP2 interacts with integnn α5 in regulating cell mobility. Microarray data showing upregulation of integrin α5 by IGFBP2 is validated and evidence of protein-protein interaction between IGFBP2 and integrin α5 is found. The exact binding domain on IGFBP2 responsible for its interaction with integrin α5 is also determined, confirming our initial findings and reaffirming that the IGFBP2/integrin α5 interaction is specific. Disruption of this interaction resulted in attenuation of IGFBP2-enhanced cell mobility. Further, we found that cell mobility is only enhanced when IGFBP2 and integrin α5 are both overexpressed and able to interact with each other. ^ We also determined fibronectin to be a critical player in the activation of the IGFBP2/integrin α5 pathway. The activation of this pathway appears to be progressive and initiates once GBM cells have sufficiently established anchorage. ^

High-resolution microarray analysis of chromosome 20q in human colon cancer metastasis model systems

Amplification of human chromosome 20q DNA is the most frequently occurring chromosomal abnormality detected in sporadic colorectal carcinomas and shows significant correlation with liver metastases. Through comprehensive high-resolution microarray comparative genomic hybridization and microarray gene expression profiling, we have characterized chromosome 20q amplicon genes associated with human colorectal cancer metastasis in two in vitro metastasis model systems. The results revealed increasing complexity of the 20q genomic profile from the primary tumor-derived cell lines to the lymph node and liver metastasis derived cell lines. Expression analysis of chromosome 20q revealed a subset of over expressed genes residing within the regions of genomic copy number gain in all the tumor cell lines, suggesting these are Chromosome 20q copy number responsive genes. Bases on their preferential expression levels in the model system cell lines and known biological function, four of the over expressed genes mapping to the common intervals of genomic copy gain were considered the most promising candidate colorectal metastasis-associated genes. Validation of genomic copy number and expression array data was carried out on these genes, with one gene, DNMT3B, standing out as expressed at a relatively higher levels in the metastasis-derived cell lines compared with their primary-derived counterparts in both the models systems analyzed. The data provide evidence for the role of chromosome 20q genes with low copy gain and elevated expression in the clonal evolution of metastatic cells and suggests that such genes may serve as early biomarkers of metastatic potential. The data also support the utility of the combined microarray comparative genomic hybridization and expression array analysis for identifying copy number responsive genes in areas of low DNA copy gain in cancer cells. ^

Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

Improved Techniques for Acquisition and Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Detecting Vascular Permeability in the Central Nervous System

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive technique for quantitative assessment of the integrity of blood-brain barrier and blood-spinal cord barrier (BSCB) in the presence of central nervous system pathologies. However, the results of DCE-MRI show substantial variability. The high variability can be caused by a number of factors including inaccurate T1 estimation, insufficient temporal resolution and poor contrast-to-noise ratio. My thesis work is to develop improved methods to reduce the variability of DCE-MRI results. To obtain fast and accurate T1 map, the Look-Locker acquisition technique was implemented with a novel and truly centric k-space segmentation scheme. In addition, an original multi-step curve fitting procedure was developed to increase the accuracy of T1 estimation. A view sharing acquisition method was implemented to increase temporal resolution, and a novel normalization method was introduced to reduce image artifacts. Finally, a new clustering algorithm was developed to reduce apparent noise in the DCE-MRI data. The performance of these proposed methods was verified by simulations and phantom studies. As part of this work, the proposed techniques were applied to an in vivo DCE-MRI study of experimental spinal cord injury (SCI). These methods have shown robust results and allow quantitative assessment of regions with very low vascular permeability. In conclusion, applications of the improved DCE-MRI acquisition and analysis methods developed in this thesis work can improve the accuracy of the DCE-MRI results.

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Traumatic brain injury stimulates hippocampal catechol-O-methyl transferase expression in microglia.

Outcome following traumatic brain injury (TBI) is in large part determined by the combined action of multiple processes. In order to better understand the response of the central nervous system to injury, we utilized an antibody array to simultaneously screen 507 proteins for altered expression in the injured hippocampus, a structure critical for memory formation. Array analysis indicated 41 candidate proteins have altered expression levels 24h after TBI. Of particular interest was catechol-O-methyl transferase (COMT), an enzyme involved in metabolizing catecholamines released following neuronal activity. Altered catecholamine signaling has been observed after brain injury, and may contribute to the cognitive dysfunctions and behavioral deficits often experienced after TBI. Our data shows that COMT expression in the injured ipsilateral hippocampus was elevated for at least 14 d after controlled cortical impact injury. We found strong co-localization of COMT immunoreactivity with the microglia marker Iba1 near the injury site. Since dopamine transporter expression has been reported to be down-regulated after brain injury, COMT-mediated catecholamine metabolism may play a more prominent role in terminating catecholamine signaling in injured areas.

TIME DEPENDENT ALTERATIONS IN CENTRAL NERVOUS SYSTEM DOPAMINE RECEPTORS INDUCED BY DOPAMINE AGONIST TREATMENT

Levodopa, the precursor of dopamine, is currently the drug of choice in the treatment of Parkinson's disease. Recently, two direct dopamine agonists, bromocriptine and pergolide, have been tested for the treatment of Parkinson's disease because of reduced side effects compared to levodopa. Few studies have evaluated the effects of long-term treatment of dopamine agonists on dopamine receptor regulation in the central nervous system. Thus, the purpose of this study was to determine whether chronic dopamine agonist treatment produces a down-regulation of striatal dopamine receptor function and to compare the results of the two classes of dopaminergic drugs.^ Levodopa with carbidopa, a peripheral decarboxylase inhibitor, was administered orally to rats whereas bromocriptine and pergolide were injected intraperitoneally once daily. Several neurochemical parameters were examined from 1 to 28 days.^ Levodopa minimally decreased striatal D-1 receptor activity but increased the number of striatal D-2 binding sites. Levodopa increased the V(,max) of tyrosine hydroxylase (TH) in all brain regions tested. Protein blot analysis of striatal TH indicated a significant increase in the amount of TH present. Dopamine-beta-hydroxylase (DBH) activity was markedly decreased in all brain regions studied and mixing experiments of control and drug-treated cortices did not show the presence of an increased level of endogenous inhibitors.^ Bromocriptine treatment decreased the number of D-2 binding sites. Striatal TH activity was decreased and protein blot analysis indicated no change in TH quantity. The specificity of bromocriptine for striatal TH suggested that bromocriptine preferentially interacts with dopamine autoreceptors.^ Combination levodopa-bromocriptine was administered for 12 days. There was a decrease in both D-1 receptor activity and D-2 binding sites, and a decrease in brain HVA levels suggesting a postsynaptic receptor action. Pergolide produced identical results to the combination levodopa-bromocriptine studies.^ In conclusion, combination levodopa-bromocriptine and pergolide treatments exhibited the expected down-regulation of dopamine receptor activity. In contrast, levodopa appeared to up-regulate dopamine receptor activity. Thus, these data may help to explain, on a biochemical basis, the decrease in the levodopa-induced side effects noted with combination levodopa-bromocriptine or pergolide therapies in the treatment of Parkinson's disease. ^

Determinants of CD4 cell count decline after treatment interruption

Patients who had started HAART (Highly Active Anti-Retroviral Treatment) under previous aggressive DHHS guidelines (1997) underwent a life-long continuous HAART that was associated with many short term as well as long term complications. Many interventions attempted to reduce those complications including intermittent treatment also called pulse therapy. Many studies were done to study the determinants of rate of fall in CD4 count after interruption as this data would help guide treatment interruptions. The data set used here was a part of a cohort study taking place at the Johns Hopkins AIDS service since January 1984, in which the data were collected both prospectively and retrospectively. The patients in this data set consisted of 47 patients receiving via pulse therapy with the aim of reducing the long-term complications. ^ The aim of this project was to study the impact of virologic and immunologic factors on the rate of CD4 loss after treatment interruption. The exposure variables under investigation included CD4 cell count and viral load at treatment initiation. The rates of change of CD4 cell count after treatment interruption was estimated from observed data using advanced longitudinal data analysis methods (i.e., linear mixed model). Using random effects accounted for repeated measures of CD4 per person after treatment interruption. The regression coefficient estimates from the model was then used to produce subject specific rates of CD4 change accounting for group trends in change. The exposure variables of interest were age, race, and gender, CD4 cell counts and HIV RNA levels at HAART initiation. ^ The rate of fall of CD4 count did not depend on CD4 cell count or viral load at initiation of treatment. Thus these factors may not be used to determine who can have a chance of successful treatment interruption. CD4 and viral load were again studied by t-tests and ANOVA test after grouping based on medians and quartiles to see any difference in means of rate of CD4 fall after interruption. There was no significant difference between the groups suggesting that there was no association between rate of fall of CD4 after treatment interruption and above mentioned exposure variables. ^

HEALTH CARE COST INCREASES IN METROPOLITAN AREAS

The research project is an extension of the economic theory to the health care field and health care research projects evaluating the influence of demand and supply variables upon medical care inflation. The research tests a model linking the demographic and socioeconomic characteristics of the population, its community case mix, and technology, the prices of goods and services other than medical care, the way its medical services are delivered and the health care resources available to its population to different utilization patterns which, consequently, lead to variations in health care prices among metropolitan areas. The research considers the relationship of changes in community characteristics and resources and medical care inflation.^ The rapidly increasing costs of medical care have been of great concern to the general public, medical profession, and political bodies. Research and analysis of the main factors responsible for the rate of increase of medical care prices is necessary in order to devise appropriate solutions to cope with the problem. An understanding of the community characteristics and resources-medical care costs relationships in the metropolitan areas potentially offers guidance in individual plan and national policy development.^ The research considers 145 factors measuring community milieu (demographic, social, educational, economic, illness level, prices of goods and services other than medical care, hospital supply, physicians resources and techological factors). Through bivariate correlation analysis, the number of variables was reduced to a set of 1 to 4 variables for each cost equation. Two approaches were identified to track inflation in the health care industry. One approach measures costs of production which accounts for price and volume increases. The other approach measures price increases. One general and four specific measures were developed to represent each of the major approaches. The general measure considers the increase on medical care prices as a whole and the specific measures deal with hospital costs and physician's fees. The relationships among changes in community characteristics and resources and health care inflation were analyzed using bivariate correlation and regression analysis methods. It has been concluded that changes in community characteristics and resources are predictive of hospital costs and physician's fees inflation, but are not predictive of increases in medical care prices. These findings provide guidance in the formulation of public policy which could alter the trend of medical care inflation and in the allocation of limited Federal funds.^

Statistical issues on studies of mixed longitudinal design

Mixed longitudinal designs are important study designs for many areas of medical research. Mixed longitudinal studies have several advantages over cross-sectional or pure longitudinal studies, including shorter study completion time and ability to separate time and age effects, thus are an attractive choice. Statistical methodology used in general longitudinal studies has been rapidly developing within the last few decades. Common approaches for statistical modeling in studies with mixed longitudinal designs have been the linear mixed-effects model incorporating an age or time effect. The general linear mixed-effects model is considered an appropriate choice to analyze repeated measurements data in longitudinal studies. However, common use of linear mixed-effects model on mixed longitudinal studies often incorporates age as the only random-effect but fails to take into consideration the cohort effect in conducting statistical inferences on age-related trajectories of outcome measurements. We believe special attention should be paid to cohort effects when analyzing data in mixed longitudinal designs with multiple overlapping cohorts. Thus, this has become an important statistical issue to address. ^ This research aims to address statistical issues related to mixed longitudinal studies. The proposed study examined the existing statistical analysis methods for the mixed longitudinal designs and developed an alternative analytic method to incorporate effects from multiple overlapping cohorts as well as from different aged subjects. The proposed study used simulation to evaluate the performance of the proposed analytic method by comparing it with the commonly-used model. Finally, the study applied the proposed analytic method to the data collected by an existing study Project HeartBeat!, which had been evaluated using traditional analytic techniques. Project HeartBeat! is a longitudinal study of cardiovascular disease (CVD) risk factors in childhood and adolescence using a mixed longitudinal design. The proposed model was used to evaluate four blood lipids adjusting for age, gender, race/ethnicity, and endocrine hormones. The result of this dissertation suggest the proposed analytic model could be a more flexible and reliable choice than the traditional model in terms of fitting data to provide more accurate estimates in mixed longitudinal studies. Conceptually, the proposed model described in this study has useful features, including consideration of effects from multiple overlapping cohorts, and is an attractive approach for analyzing data in mixed longitudinal design studies.^

Chronic stress promotes tumor growth through increased BDNF production and neo-innervation

Background: Activation of the sympathetic nervous system (SNS) in response to chronic biobehavioral stress results in high levels of catecholamines and persistent activation of adrenergic signaling, which promotes tumor growth and progression. However it is unknown how catecholamine levels within the tumor exceed systemic levels in circulation. I hypothesized that neo-innervation of tumors is required for stress-mediated effects on tumor growth. Results: First, I examined whether sympathetic nerves are present in human ovarian cancer samples as well as orthotopic ovarian cancer models. Immunohistochemical (IHC) staining for neurofilament revealed that catecholaminergic neurons are present within tumor tissue. In order to determine whether chronic stress affects the density of nerves in the tumor, I utilized an orthotopic mouse model of ovarian cancer that was exposed to daily restraint stress. IHC analysis revealed that nerve density in tumors increased by more than three-fold in stressed animals versus non-stressed controls. IHC analysis suggested that this results from both recruitment of existing neurons (axonogenesis) as well as new neuron formation (neurogenesis) within the tumor. To determine how tumors are recruiting nerve growth, I utilized a PCR array analysis of 84 nerve growth related genes and their receptors, which showed that stimulation of the SKOV3 ovarian cancer cell line with norepinephrine (NE) leads to increased expression of several neurotrophins, including brain-derived neurotrophic factor (BDNF). Neurite extension assays showed that media conditioned by ovarian cancer cell lines is capable of inducing neurite outgrowth in differentiated neuron-like PC12 cells, and NE treatment of cancer cells potentiates this effect. Norepinephrine-induced neurite extension was abolished after BDNF silencing by siRNA, suggesting that BDNF is critical to tumor cell-induced nerve growth. in vivo BDNF inhibition resulted in complete abrogation of stress-induced increases in tumor weight and nerve density, as well as downstream markers of stress. Discussion: These studies indicate that adrenergic signalling induced by chronic stress promotes neo-innervation in the tumor microenvironment. This results in a mutually beneficial relationship between the tumor cells and neurons. This work is crucial for providing a link between chronic stress and its effects on the tumor and its microenvironment. The data shown here aims to open new venues that can be used in development of therapies designed to block the stress effects on tumor growth.