The androgen receptor (AR) is a key regulator of prostate growth and the principal drug target for the treatment of prostate cancer. Previous studies have mapped AR targets and identified some candidates which may contribute to cancer progression, but did not characterize AR biology in an integrated manner. In this study, we took an interdisciplinary approach, integrating detailed genomic studies with metabolomic profiling and identify an anabolic transcriptional network involving AR as the core regulator. Restricting flux through anabolic pathways is an attractive approach to deprive tumours of the building blocks needed to sustain tumour growth. Therefore, we searched for targets of the AR that may contribute to these anabolic processes and could be amenable to therapeutic intervention by virtue of differential expression in prostate tumours. This highlighted calcium/calmodulin-dependent protein kinase kinase 2, which we show is overexpressed in prostate cancer and regulates cancer cell growth via its unexpected role as a hormone-dependent modulator of anabolic metabolism. In conclusion, it is possible to progress from transcriptional studies to a promising therapeutic target by taking an unbiased interdisciplinary approach.

The androgen receptor (AR) regulates prostate cell growth in man, and prostate cancer is the commonest cancer in men in the UK. We present a comprehensive analysis of AR binding sites in human prostate cancer tissues, including castrate-resistant prostate cancer (CRPC). We identified thousands of AR binding sites in CRPC tissue, most of which were not identified in PC cell lines. Many adjacent genes showed AR regulation in xenografts but not in cultured LNCaPs, demonstrating an in-vivo-restricted set of AR-regulated genes. Functional studies support a model of altered signaling in vivo that directs AR binding. We identified a 16 gene signature that outperformed a larger in-vitro-derived signature in clinical data sets, showing the importance of persistent AR signaling in CRPC.

BackgroundUnderstanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.MethodsIn a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.FindingsWe identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.InterpretationFor the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.

DNA-dependent protein kinase (DNA-PK) is a critical player in the DNA damage response (DDR) and instrumental in the non-homologous end-joining pathway (NHEJ) used to detect and repair DNA double-strand breaks (DSBs). We demonstrate that the potent and highly selective DNA-PK inhibitor, AZD7648, is an efficient sensitizer of radiation- and doxorubicin-induced DNA damage, with combinations in xenograft and patient-derived xenograft (PDX) models inducing sustained regressions. Using ATM-deficient cells, we demonstrate that AZD7648, in combination with the PARP inhibitor olaparib, increases genomic instability, resulting in cell growth inhibition and apoptosis. AZD7648 enhanced olaparib efficacy across a range of doses and schedules in xenograft and PDX models, enabling sustained tumour regression and providing a clear rationale for its clinical investigation. Through its differentiated mechanism of action as an NHEJ inhibitor, AZD7648 complements the current armamentarium of DDR-targeted agents and has potential in combination with these agents to achieve deeper responses to current therapies.