(620d) Modeling and Analysis of the Role of Signal Transduction Pathways in the Development of Androgen Independent Prostate Cancer
AIChE Annual Meeting
Thursday, November 7, 2013 - 9:24am to 9:42am
Prostate cancer is the most common cancer in men and the second leading cause of cancer- related death in the United States. Androgens, such as testosterone, are required for prostate cancer growth. Androgen ablation in combination with radiation or chemotherapy remains the primary non-surgical treatment for androgen-dependent prostate cancer. However, androgen ablation typically fails to permanently arrest cancer progression. As testosterone is withdrawn, malfunctioning cells lose their androgen sensitivity and proliferate without hormone. These testosterone insensitive cells often result in Androgen-Independent Prostate Cancer (AIPC). AIPC is closely related to metastasis and decreased survival. In this study, we developed a physiochemical model of an archetypal network, namely, hormone and growth factor signaling in human prostate cancer cells. The model describes the integration of two simultaneous extracellular signaling inputs, namely, androgen and growth factors into a G1/S cell-cycle checkpoint decision (including the regulation of Cyclin D alternative splicing). The model, containing 780 species and 1674 interactions, was identified using data generated from 43 studies in LNCaP cell lines. The model focuses on the outlaw pathway, in which constitutively or overly-activated receptor tyrosine kinases (RTKs) stimulate Akt and mitogen-activated protein kinases (MAPKs), which in turn activate cytosolic androgen receptor (AR) in the absence of androgen. Interestingly, among the few genes activated AR represses is cellular prostatic acid phosphatase (cPAcP), itself a key regulatory of RTK activation. Thus, the outlaw pathway encodes crosstalk between RTK-dependent kinase and AR activation inside of a positive feedback loop. The model was validated with multiple experiments in LNCaP cell lines. In addition data from drug trials was used to evaluate the model’s performance predicting the response of prostate tumors to specific drugs. For example, in response to Enzalutamide, an AR inhibitor, the model predicted a decline in PSA expression similar to patient response. Sensitivity analysis, conducted over an ensemble of prostate signaling models, suggested that in an androgen free environment general translation was more sensitive in androgen dependent cells, while in androgen independent cells the PI3K/MAPK pathway species were more sensitive. In a constant androgen environment sensitive species were conserved between the cell lines. These results suggest targeting the PI3K/MAPK pathway in addition to anti androgen therapies as a treatment for AIPC.