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. ^

Intercellular adhesion and membrane polarity in rat hepatocytes: Localization of cell -CAM 105 and other domain-specific membrane proteins {\it in situ\/} and {\it in vitro\/} by electron microscopy

Cell-CAM 105 has been identified as a cell adhesion molecule (CAM) based on the ability of monospecific and monovalent anti-cell-CAM 105 antibodies to inhibit the reaggregation of rat hepatocytes. Although one would expect to find CAMs concentrated in the lateral membrane domain where adhesive interactions predominate, immunofluorescence analysis of rat liver frozen sections revealed that cell-CAM 105 was present exclusively in the bile canalicular (BC) domain of the hepatocyte. To more precisely define the in situ localization of cell-CAM 105, immunoperoxidase and electron microscopy were used to analyze intact and mechanically dissociated fixed liver tissue. Results indicate that although cell-CAM 105 is apparently restricted to the BC domain in situ, it can be detected in the pericanalicular region of the lateral membranes when accessibility to lateral membranes is provided by mechanical dissociation. In contrast, when hepatocytes were labeled following incubation in vitro under conditions used during adhesion assays, cell-CAM 105 had redistributed to all areas of the plasma membrane. Immunofluorescence analysis of primary hepatocyte cultures revealed that cell-CAM 105 and two other BC proteins were localized in discrete domains reminscent of BC while cell-CAM 105 was also present in regions of intercellular contact. These results indicate that the distribution of cell-CAM 105 under the experimental conditions used for cell adhesion assays differs from that in situ and raises the possibility that its adhesive function may be modulated by its cell surface distribution. The implications of these and other findings are discussed with regard to a model for BC formation.^ Analysis of molecular events involved in BC formation would be accelerated if an in vitro model system were available. Although BC formation in culture has previously been observed, repolarization of cell-CAM 105 and two other domain-specific membrane proteins was incomplete. Since DMSO had been used by Isom et al. to maintain liver-specific gene expression in vitro, the effect of this differentiation system on the polarity of these membrane proteins was examined. Based on findings presented here, DMSO apparently prolongs the expression and facilitates polarization of hepatocyte membrane proteins in vitro. ^