Simulation study of joint transition and Weibull survival model with shared parameters

This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^

A Bayesian approach to estimating the intraclass correlation coefficient

A Bayesian approach to estimating the intraclass correlation coefficient was used for this research project. The background of the intraclass correlation coefficient, a summary of its standard estimators, and a review of basic Bayesian terminology and methodology were presented. The conditional posterior density of the intraclass correlation coefficient was then derived and estimation procedures related to this derivation were shown in detail. Three examples of applications of the conditional posterior density to specific data sets were also included. Two sets of simulation experiments were performed to compare the mean and mode of the conditional posterior density of the intraclass correlation coefficient to more traditional estimators. Non-Bayesian methods of estimation used were: the methods of analysis of variance and maximum likelihood for balanced data; and the methods of MIVQUE (Minimum Variance Quadratic Unbiased Estimation) and maximum likelihood for unbalanced data. The overall conclusion of this research project was that Bayesian estimates of the intraclass correlation coefficient can be appropriate, useful and practical alternatives to traditional methods of estimation. ^

THE p63 ISOFORM ∆Np63α INHIBITS EPITHELIAL – MESENCHYMAL TRANSITION BY PROMOTING THE EXPRESSION OF MIR-205 IN HUMAN BLADDER CANCER CELLS

p63, a p53 family member, is a transcription factor that has complex roles in cancer. This study focuses on the role of the ∆Np63α isoform in bladder cancer (BC). Epithelial – mesenchymal transition (EMT) is a physiological process that plays an important part in metastasis and drug resistance. At the molecular level, EMT is characterized by the loss of the epithelial marker E-cadherin, and the acquisition of the transcriptional repressors of E-cadherin (ZEB1, ZEB2, TWIST, SNAI1 and SNAI2). Recent publications highlight the role of microRNAs belonging to the miR-200 family and miR-205 in preventing EMT through suppression of ZEB1 and ZEB2. p53, the homologue of p63, is implicated in regulating EMT by modulating the expression of miR-200c; however, the mechanisms underlying miR-205 control remain unclear. Here we show that ∆Np63α regulates the transcription of miR-205 and controls EMT in human BC cells. We observed a strong correlation between the expression of ∆Np63α, miR-205 and E-cadherin in a panel of BC cell lines (n=28) and also in bladder primary tumors from a cohort of patients (n=98). A remarkably inverse correlation is observed between ∆Np63α and ZEB1/2 in cell lines. Stable knockdown (KD) ∆Np63α in UC6, an “epithelial” BC cell line, decreased the expression of miR-205 and induced ZEB1/2 expression, the effects that were reversed by expression of exogenous miR-205. Moreover, overexpressing ∆Np63α in UC3, a “messenchymal” BC cell line, brought about opposite results, an increase in miR-205 expression and a reduction in ZEB1/2 expression. Modulation of ∆Np63α expression resulted in a parallel change in the expression of miR-205 and miR-205 “host” gene (miR-205HG). Nuclear run-on and chromatin immunoprecipitation experiments demonstrated that ∆Np63α regulates the transcription of miR-205 through controlling the recruitment of RNA Polymerase II to the promoter of miR-205HG. Interestingly, high miR-205 expression correlated with poor clinical outcome in BC patients, consistent with our recent publication highlighting the enrichment of ∆Np63 in a lethal subset of muscle invasive BC. In summary, our data present the important roles of ∆Np63α in preventing EMT mediated by miR-205. Our study also identifies miR-205 as a potential molecular marker to predict clinical outcome in BC patients.