14-3-3 proteins interact with the beta-thymosin repeat protein Csp24.

Conditioned stimulus pathway protein 24 (Csp24) is a beta-thymosin-like protein that is homologous to other members of the family of beta-thymosin repeat proteins that contain multiple actin binding domains. Actin co-precipitates with Csp24 and co-localizes with it in the cytosol of type-B photoreceptor cell bodies. Several signal transduction pathways have been shown to regulate the phosphorylation of Csp24 and contribute to cellular plasticity. Here, we report the identification of the adapter protein 14-3-3 in lysates of the Hermissenda circumesophageal nervous system and its interaction with Csp24. Immunoprecipitation experiments using an antibody that is broadly reactive with several isoforms of the 14-3-3 family of proteins showed that Csp24 co-precipitates with 14-3-3 protein, and nervous systems stimulated with 5-HT exhibited a significant increase in co-precipitated Csp24 probed with a phosphospecific antibody as compared with controls. These results indicate that post-translational modifications of Csp24 regulate its interaction with 14-3-3 protein, and suggest that this mechanism may contribute to the control of intrinsic enhanced excitability.

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.

Evaluating the Harris County TexHealth 3-Share Plan: An exploratory study

An important health issue in the United States today is the large number of people who have problems accessing needed health care because they lack health insurance coverage. Providing health insurance coverage for the working uninsured is a particularly significant challenge in Texas, which has the highest percentage of uninsured in the nation. In response to the low rate of employer-sponsored coverage in the Houston area and the growing numbers of uninsured, the Harris County Health Care Alliance (HCHA) developed and implemented the Harris County 3-Share Plan. A 3-Share Plan is not insurance, but provides health coverage in the form of a benefits package to employers who subscribe to the program and offer it to their employees. ^ A cross sectional study design was conducted to describe 3-Share employer and employee participants and evaluate their outcomes after its first year of operation. Between September and December 2011, 85% of employers enrolled in the 3-Share Plan completed a survey about the affordability of the 3-Share Plan, their satisfaction with the Plan, and the Plan's impact on employee recruitment, retention, productivity, and absenteeism. Forty-five percent of employees enrolled in the 3-Share Plan responded to a survey asking about the affordability of the 3-Share plan, accessibility of health care, availability of providers on the plan, health plan availability, utilization of primary care providers and the ER, and satisfaction with the plan. ^ A summary of the findings shows employers and employees say that they joined the plan because of the low-cost, and once they had participated in the Plan, the majority of employers and employees found that it is affordable for them. The majority of employees say they are getting access easily and without delay, but for those who aren't able to get access, or are delayed, the main cause is related to non-financial barriers to care. Ultimately, employees are satisfied with the 3-Share, and they plan to continue with health coverage under the 3-Share Plan. The 3-Share Plan will keep people in a system of care, and promote health, which will benefit the individuals, the businesses and the community of Harris County.^

Evaluating the Harris County TexHealth 3-Share plan: An exploratory study

An important health issue in the United States today is the large number of people who have problems accessing needed health care because they lack health insurance coverage. Providing health insurance coverage for the working uninsured is a particularly significant challenge in Texas, which has the highest percentage of uninsured in the nation. In response to the low rate of employer-sponsored coverage in the Houston area and the growing numbers of uninsured, the Harris County Health Care Alliance (HCHA) developed and implemented the Harris County 3-Share Plan. A 3-Share Plan is not insurance, but provides health coverage in the form of a benefits package to employers who subscribe to the program and offer it to their employees. ^ A cross sectional study design was conducted to describe 3-Share employer and employee participants and evaluate their outcomes after its first year of operation. Between September and December 2011, 85% of employers enrolled in the 3-Share Plan completed a survey about the affordability of the 3-Share Plan, their satisfaction with the Plan, and the Plan's impact on employee recruitment, retention, and productivity. Forty-five percent of employees enrolled in the 3-Share Plan responded to a survey asking about the affordability of the 3-Share plan, accessibility of providers on the plan, satisfaction, and utilization of primary care providers and the ER. ^ A summary of the findings shows employers and employees say that they joined the plan because of the low-cost, and once they had participated in the Plan, the majority of employers and employees found that it is affordable for them. The majority of employees say they are getting access easily and without delay, but for those who aren't able to get access, or are delayed, the main cause is related to non-financial barriers to care. Ultimately, employees are satisfied with the 3-Share, and they plan to continue with health coverage under the 3-Share Plan. The 3-Share Plan will keep people in a system of care, and promote health, which will benefit the individuals, the businesses and the community of Harris County.^

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^