Prostate cancer relapsing from antiandrogen therapies can exhibit variant histology with altered lineage marker expression, suggesting that lineage plasticity facilitates therapeutic resistance. The mechanisms underlying prostate cancer lineage plasticity are incompletely understood. Studying mouse models, we demonstrate that Rb1 loss facilitates lineage plasticity and metastasis of prostate adenocarcinoma initiated by Pten mutation. Additional loss of Trp53 causes resistance to antiandrogen therapy. Gene expression profiling indicates that mouse tumors resemble human prostate cancer neuroendocrine variants; both mouse and human tumors exhibit increased expression of epigenetic reprogramming factors such as Ezh2 and Sox2. Clinically relevant Ezh2 inhibitors restore androgen receptor expression and sensitivity to antiandrogen therapy. These findings uncover genetic mutations that enable prostate cancer progression; identify mouse models for studying prostate cancer lineage plasticity; and suggest an epigenetic approach for extending clinical responses to antiandrogen therapy.

Understanding metabolic dysregulation in different disease settings is vital for the safe and effective incorporation of metabolism-targeted therapeutics in the clinic. Here, using transcriptomic data for 10,704 tumor and normal samples from The Cancer Genome Atlas, across 26 disease sites, we present a novel bioinformatics pipeline that distinguishes tumor from normal tissues, based on differential gene expression for 114 metabolic pathways. We confirm pathway dysregulation in separate patient populations, demonstrating the robustness of our approach. Bootstrapping simulations were then applied to assess the biological significance of these alterations. We provide distinct examples of the types of analysis that can be accomplished with this tool to understand cancer specific metabolic dysregulation, highlighting novel pathways of interest, and patterns of metabolic flux, in both common and rare disease sites. Further, we show that Master Metabolic Transcriptional Regulators explain why metabolic differences exist, can segregate patient populations, and predict responders to different metabolism-targeted therapeutics.

Purpose Current clinical parameters do not stratify indolent from aggressive prostate cancer (PCa). Aggressive PCa, defined by the progression from localized disease to metastasis, is responsible for the majority of PCa-associated mortality. Recent gene expression profiling has proven successful in predicting the outcome of PCa patients, however they have yet to provide targeted therapy approaches that could inhibit a patient’s progression to metastatic disease. Experimental Design We have interrogated a total of seven primary PCa cohorts (N = 1,900), two metastatic castration resistant PCa datasets (N = 293) and one prospective cohort (N = 1,385) to assess the impact of TOP2A and EZH2 expression on PCa cellular program and patient outcomes. We also performed immunohistochemical staining for TOP2A and EZH2 in a cohort of primary PCa patients (N = 89) with known outcome. Finally, we explored the therapeutic potential of a combination therapy targeting both TOP2A and EZH2 using novel PCa-derived murine cell lines. Results We demonstrate by genome-wide analysis of independent primary and metastatic PCa datasets that concurrent TOP2A and EZH2 mRNA and protein up-regulation selected for a subgroup of primary and metastatic patients with more aggressive disease and notable overlap of genes involved in mitotic regulation. Importantly, TOP2A and EZH2 in PCa cells act as key driving oncogenes, a fact highlighted by sensitivity to combination-targeted therapy. Conclusions Overall, our data supports further assessment of TOP2A and EZH2 as biomarkers for early identification of patients with increased metastatic potential that may benefit from adjuvant or neo-adjuvant targeted therapy approaches.

The retinoblastoma tumor suppressor gene (RB1) plays a critical role in coordinating multiple pathways that impact cancer initiation, disease progression, and therapeutic responses. Here we probed molecular features associated with the RB-pathway across 31 tumor-types. While the RB-pathway has been purported to exhibit multiple mutually exclusive genetic events, only RB1 alteration is mutually exclusive with deregulation of CDK4/6 activity. An ER+ breast cancer model with targeted RB1 deletion was used to identify signatures of CDK4/6 activity and RB-dependency (CDK4/6-RB integrated signature). This signature was prognostic in tumor-types with gene expression features indicative of slower growth. Single copy loss on chromosome 13q encompassing the RB1 locus is prevalent in many cancers, yielding reduced expression of multiple genes in cis, and is inversely related to the CDK4/6-RB integrated signature supporting a cause-effect relationship. Genes that are positively and inversely correlated with the CDK4/6-RB integrated signature define new tumor-specific pathways associated with RB-pathway activity.