High androgen receptor (AR) level in primary tumour predicts increased prostate cancer‐specific mortality. However, the mechanisms that regulate AR function in prostate cancer are poorly known. We report here a new paradigm for the forkhead protein FoxA1 action in androgen signalling. Besides pioneering the AR pathway, FoxA1 depletion elicited extensive redistribution of AR‐binding sites (ARBs) on LNCaP‐1F5 cell chromatin that was commensurate with changes in androgen‐dependent gene expression signature. We identified three distinct classes of ARBs and androgen‐responsive genes: (i) independent of FoxA1, (ii) pioneered by FoxA1 and (iii) masked by FoxA1 and functional upon FoxA1 depletion. FoxA1 depletion also reprogrammed AR binding in VCaP cells, and glucocorticoid receptor binding and glucocorticoid‐dependent signalling in LNCaP‐1F5 cells. Importantly, FoxA1 protein level in primary prostate tumour had significant association to disease outcome; high FoxA1 level was associated with poor prognosis, whereas low FoxA1 level, even in the presence of high AR expression, predicted good prognosis. The role of FoxA1 in androgen signalling and prostate cancer is distinctly different from that in oestrogen signalling and breast cancer.

TMPRSS2-ERG and other gene fusions involving ETS factors and genes with strong promoter elements are common in prostate cancer. Although ERG activation has been linked to invasive properties of prostate cancers, the precise mechanisms and pathways of ERG-mediated oncogenesis remain poorly understood. Here, we show that ERG knockdown in VCaP prostate cancer cells causes an activation of cell adhesion, resulting in strongly induced active β 1 -integrin and E-cadherin expression as well as changes in WNT signaling. These observations were corroborated by data from ERG-overexpressing nontransformed prostate epithelial cells as well as gene expression data from clinical prostate cancer samples, which both indicated a link between ERG and epithelial-to-mesenchymal transition (EMT). Upregulation of several WNT pathway members was seen in ERG-positive prostate cancers, with frizzled-4 (FZD4) showing the strongest overexpression as verified by both reverse transcription-PCR and immunostaining. Both ERG knockin and knockdown modulated the levels of FZD4 expression. FZD4 silencing could mimic the ERG knockdown phenotype by inducing active β 1 -integrin and E-cadherin expression, whereas FZD4 overexpression reversed the phenotypic effects seen with ERG knockdown. Taken together, our results provide mechanistic insights to ERG oncogenesis in prostate cancer, involving activation of WNT signaling through FZD4, leading to cancer-promoting phenotypic effects, including EMT and loss of cell adhesion. Cancer Res; 70(17); 6735-45. ©2010 AACR.

There are currently no effective therapies for metastatic prostate cancer because the molecular mechanisms that underlie the metastatic spread of primary prostate cancer are unclear. Transcription factor Stat3 is constitutively active in malignant prostate epithelium, and its activation is associated with high histological grade and advanced cancer stage. Progression of prostate cancer to metastatic disease is one of the key problems in the clinical management of prostate cancer.1 This is because there are currently no effective therapies for metastatic prostate cancer, and metastatic prostate cancer is the lethal form of the disease. Identification of the molecular changes that lead to formation of distant metastasis is critical for improvement of therapeutic interventions for metastatic prostate cancer and for development of strategies to prevent primary prostate cancer from metastasizing.Transcription factor Stat3 has been implicated in the promotion of growth and progression of prostate cancer. Stat3, which is both a cytoplasmic signaling molecule and a nuclear transcription factor, belongs to the sevenmember Stat gene family of transcription factors.2 Stat3 becomes active by phosphorylation of a specific tyrosine residue in the carboxy-terminal domain by a tyrosine kinase (pY705).3 Activation of Stat3 is supplemented by phosphorylation of a specific serine residue (S727).4 After phosphorylation, Stat3 homodimerizes and translocates to the nucleus where it binds to specific Stat3 response elements of target gene promoters to regulate transcription.3 Transcription factor Stat3 is constitutively active in clinical human prostate cancer, 5-9 and activation of Stat3 has been associated with advanced stage of prostate cancer. 5,9 Moreover, several reports implicate Stat3 in promotion of prostate cancer cell proliferation and inhibition of apoptosis. 5,10,11

Body fluids are a rich source of extracellular vesicles (EVs), which carry cargo derived from the secreting cells. So far, biomarkers for pathological conditions have been mainly searched from their protein, (mi)RNA, DNA and lipid cargo. Here, we explored the small molecule metabolites from urinary and platelet EVs relative to their matched source samples. As a proof-of-concept study of intra-EV metabolites, we compared alternative normalization methods to profile urinary EVs from prostate cancer patients before and after prostatectomy and from healthy controls.Methods: We employed targeted ultra-performance liquid chromatography-tandem mass spectrometry to profile over 100 metabolites in the isolated EVs, original urine samples and platelets. We determined the enrichment of the metabolites in the EVs and analyzed their subcellular origin, pathways and relevant enzymes or transporters through data base searches. EV- and urine-derived factors and ratios between metabolites were tested for normalization of the metabolomics data.Results: Approximately 1 x 1010 EVs were sufficient for detection of metabolite profiles from EVs. The profiles of the urinary and platelet EVs overlapped with each other and with those of the source materials, but they also contained unique metabolites. The EVs enriched a selection of cytosolic metabolites including members from the nucleotide and spermidine pathways, which linked to a number of EV-resident enzymes or transporters. Analysis of the urinary EVs from the patients indicated that the levels of glucuronate, D-ribose 5-phosphate and isobutyryl-L-carnitine were 2-26-fold lower in all pre-prostatectomy samples compared to the healthy control and post-prostatectomy samples (p < 0.05). These changes were only detected from EVs by normalization to EV-derived factors or with metabolite ratios, and not from the original urine samples.Conclusions: Our results suggest that metabolite analysis of EVs from different samples is feasible using a high-throughput platform and relatively small amount of sample material. With the knowledge about the specific enrichment of metabolites and normalization methods, EV metabolomics could be used to gain novel biomarker data not revealed by the analysis of the original EV source materials.

Summary Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest—namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial—ENTHUSE M1—in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39–4·62, p<0·0001; reference model: 2·56, 1·85–3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified...

The molecular mechanisms that promote progression of localized prostate cancer to hormone-refractory and disseminated disease are poorly understood. Prolactin (Prl) is a local growth factor produced in high-grade prostate cancer, and exogenously added Prl in tissue or explant cultures of normal and malignant prostate is a strong mitogen and survival factor for prostate epithelium.

Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

There are no effective therapies for disseminated prostate cancer. Constitutive activation of Stat5 in prostate cancer is associated with cancer lesions of high histological grade. We have shown that Stat5 is activated in 61% of distant metastases of clinical prostate cancer. Active Stat5 increased metastases formation of prostate cancer cells in nude mice by 11-fold in an experimental metastases assay. Active Stat5 promoted migration and invasion of prostate cancer cells, and induced rearrangement of the microtubule network. Active Stat5 expression was associated with decreased cell surface E-cadherin levels, while heterotypic adhesion of prostate cancer cells to endothelial cells was stimulated by active Stat5. Activation of Stat5 and Stat5-induced binding of prostate cancer cells to endothelial cells were decreased by inhibition of Src but not of Jak2. Gene expression profiling indicated that 21% of Stat5-regulated genes in prostate cancer cells were related to metastases, while 7.9% were related to proliferation and 3.9% to apoptosis. The work presented here provides the first evidence of Stat5 involvement in the induction of metastatic behavior of human prostate cancer cells in vitro and in vivo. Stat5 may provide a therapeutic target protein for disseminated prostate cancer.