Computational Causal Reasoning Models of Mechanisms of Androgen Stimulation in Prostate Cancer

We describe the development of a very large-scale causal, computable model of biology and its specific application in the identification of molecular cause and effect hypotheses of mechanisms underlying the effects of androgen stimulation in the LNCaP prostate carcinoma cell line. In contrast to previous LNCaP studies in which genes have been hierarchically clustered by their pattern of response to androgen, our causal reasoning methodology identifies possible explanations in terms of discrete and testable molecular mechanisms. We have inferred changes in cell proliferation and fatty-acid synthesis transcriptional control mechanisms based on gene expression changes in transcriptional targets of proteins such as RBI, E2F1,2,3, and SREBF1,2. Further analysis has identified multiple causal pathways linking the activity of the androgen receptor (AR) to these processes, providing succinct, testable hypotheses for subsequent experimentation. This study identified new targets for RNAi-mediated gene knockdowns to study androgen control of cell proliferation in prostate cancer. Causal Reasoning and modeling provides a valuable tool for the analysis of molecular profiling data, can identify distinct mechanisms of action and can be used to design experiments to probe those mechanisms. Causal Reasoning is effective in the study of cellular models of prostate cancer, and this systems approach is broadly applicable to identifying the molecular mechanisms of cancer