Cell Cycle Regulatory Roles of Estrogen Receptor alpha (ERα) in Breast Cancer Cells

Previous studies have shown that Estrogen Receptor alpha (ERα) is an important indicator for diagnosis, prognosis and treatment of breast cancers. However, the question remains as to the role of ERα in the cell in the presence versus absence of 17-β estradiol In this dissertation the role of ERα in both its unliganded and liganded state, with respect to the cell cycle will be explored. The cell line models used in this project are ER-positive MCF-7 cells with and without siRNA to ERα and ER-positive MDA-MB-231 cells that have been engineered to express ERα. Cells were synchronized and the cell cycle progression was monitored by flow cytometric analysis. Using these methods, two specific questions were addressed: Does ERα modulate the cell cycle differently under liganded versus unliganded conditions? And, does the presence of ERα regulate cell cycle phase transitions? The results show for the first time that ERα is cell cycle regulated and modulates the progression of cells through S and G2/M phases of the cell cycle. Ligand bound ERα increases progression through S and G2/M phases, whereas unliganded ERα acts as an inhibitor of cell cycle progression. To further investigate the cell cycle regulated effects of liganded ERα, a luciferase assay was performed and showed that the transcription of target genes such as Progestrone Receptor (PgR) and Trefoil protein (pS2) increased duing S and G2/M phases when ERα is bound to ligand. Additionally, complex formation between cyclin B and ER α was shown by immunoprecipitation and led to the discovery that anaphase promoting complex (APC) is the E3 ligase for both cyclin B and ERα at the termination of M phase. Our findings suggest that unliganded ERα has an inhibitory effect on the progression of the cell cycle. Therefore, it is reasonable to speculate that the combination of drugs that lower estrogen level (such as aromatase inhibitors) and preserves ERα from degradation would provide better outcome for breast cancer treatment. We have shown that APC functions as the E3 ligase for ERα and thus might provide a target to design a specific inhibitor of ERα degradation.

BAYESIAN PHASE I DOSE FINDING IN CANCER TRIALS

This dissertation explores phase I dose-finding designs in cancer trials from three perspectives: the alternative Bayesian dose-escalation rules, a design based on a time-to-dose-limiting toxicity (DLT) model, and a design based on a discrete-time multi-state (DTMS) model. We list alternative Bayesian dose-escalation rules and perform a simulation study for the intra-rule and inter-rule comparisons based on two statistical models to identify the most appropriate rule under certain scenarios. We provide evidence that all the Bayesian rules outperform the traditional ``3+3'' design in the allocation of patients and selection of the maximum tolerated dose. The design based on a time-to-DLT model uses patients' DLT information over multiple treatment cycles in estimating the probability of DLT at the end of treatment cycle 1. Dose-escalation decisions are made whenever a cycle-1 DLT occurs, or two months after the previous check point. Compared to the design based on a logistic regression model, the new design shows more safety benefits for trials in which more late-onset toxicities are expected. As a trade-off, the new design requires more patients on average. The design based on a discrete-time multi-state (DTMS) model has three important attributes: (1) Toxicities are categorized over a distribution of severity levels, (2) Early toxicity may inform dose escalation, and (3) No suspension is required between accrual cohorts. The proposed model accounts for the difference in the importance of the toxicity severity levels and for transitions between toxicity levels. We compare the operating characteristics of the proposed design with those from a similar design based on a fully-evaluated model that directly models the maximum observed toxicity level within the patients' entire assessment window. We describe settings in which, under comparable power, the proposed design shortens the trial. The proposed design offers more benefit compared to the alternative design as patient accrual becomes slower.