Targeting of Intracellular Survival Pathways in Human Prostate Cancer Cells

Abstract

Although significant advances in the treatment of prostate cancer have been made, advanced prostate cancer is essentially incurable and remains the second leading cause of cancer-related deaths among men in the U.S. The current treatment landscape underscores the fact that additional strategies are needed to improve treatment outcomes of both castration sensitive and castration resistant advanced prostate cancer. Prostate cancer is characterized by a remarkable degree of heterogeneity in terms of its underlying biology and clinical behavior. Although pre-clinical models cannot adequately reflect the varied clinical behavior of prostate cancer, they are important for enhancing our understanding of prostate cancer biology and potentially identifying new therapeutic targets. In this thesis, we undertook the approach of studying several cell culture models of prostate cancer that in aggregate encompass many of the varied aspects of the prostate cancer disease spectrum seen clinically. Using these models, we focused on the erbB-PI3K-AKT axis as a paradigm of growth factor-receptor tyrosine kinase (RTK) signaling, and the androgen-AR axis, as well as the compensatory cross-talks within and across the pathways, to study the effects of combinatoric targeting of specific nodes in these signaling pathways. Chapter 1 provides background, pre-clinical and clinical context, and translational relevance of the studies presented in this thesis. Our research work is divided into two broad areas, namely the AR negative prostate cancer cells that include both drug-sensitive and drug-resistant models (Chapter 2), and the AR positive prostate cancer cells. These are characterized by a range of molecular signatures, including changes in AR/AR-V7 expression, functional PTEN status, wild-type (wt) or mutant p53 background, and altered underlying sensitivities to androgen receptor axis targeted (ARAT) agents (Chapter 3). The present work adds to the significant body of literature in this area of study and highlights the potential relevance of combinatoric targeting across a range of underlying molecular lesions that define the different phenotypes of prostate cancer.