Luminal- and basal-like prostate cancers demonstrate divergent clinical behavior, and patients with luminal B tumors respond better to postoperative ADT than do patients with non–luminal B tumors. These findings contribute novel insight into prostate cancer biology, providing a potential clinical tool to personalize ADT treatment for prostate cancer by predicting which men may benefit from ADT after surgery.

Prostate cancer (PC) is a biologically heterogeneous disease with variable molecular alterations underlying cancer initiation and progression. Despite recent advances in understanding PC heterogeneity, better methods for classification of PC are still needed to improve prognostic accuracy and therapeutic outcomes. In this study we computationally assembled a large virtual cohort (n=1,321) of human PC transcriptome profiles from 38 distinct cohorts and, using pathway activation signatures of known relevance to PC, developed a novel classification system consisting of 3 distinct subtypes (named PCS1 to 3). We validated this subtyping scheme in 10 independent patient cohorts and 19 laboratory models of PC, including cell lines and genetically engineered mouse models. Analysis of subtype-specific gene expression patterns in independent datasets derived from luminal and basal cell models provides evidence that PCS1 and PCS2 tumors reflect luminal subtypes, while PCS3 represents a basal subtype. We show that PCS1 tumors progress more rapidly to metastatic disease in comparison to PCS2 or PCS3, including PSC1 tumors of low Gleason grade. To apply this finding clinically, we developed a 37-gene panel that accurately assigns individual tumors to one of the 3 PCS subtypes. This panel was also applied to circulating tumor cells (CTCs) and provided evidence that PCS1 CTCs may reflect enzalutamide resistance. In summary, PCS subtyping may improve accuracy in predicting the likelihood of clinical progression and permit treatment stratification at early and late disease stages.

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Higher B7-H3 expression correlates with Gleason grade, prostate cancer stage and poor oncologic outcomes in prostatectomy cohorts. B7-H3 expression appears to be related to androgen signaling as well as the immune reactome.

Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet.