Prostate cancer is the second most common cancer in men worldwide and causes over 250,000 deaths each year1. Overtreatment of indolent disease also results in significant morbidity2. Common genetic alterations in prostate cancer include losses of NKX3.1 (8p21)3,4 and PTEN (10q23)5,6, gains of the androgen receptor gene (AR)7,8 and fusion of ETS-family transcription factor genes with androgen-responsive promoters9–11. Recurrent somatic base-pair substitutions are believed to be less contributory in prostate tumorigenesis12,13 but have not been systematically analyzed in large cohorts. Here we sequenced the exomes of 112 prostate tumor/normal pairs. Novel recurrent mutations were identified in multiple genes, including MED12 and FOXA1. SPOP was the most frequently mutated gene, with mutations involving the SPOP substrate binding cleft in 6–15% of tumors across multiple independent cohorts. SPOP-mutant prostate cancers lacked ETS rearrangements and exhibited a distinct pattern of genomic alterations. Thus, SPOP mutations may define a new molecular subtype of prostate cancer.

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications.

The bromodomain and extra-terminal (BET) family of proteins, comprised of four members including BRD2, BRD3, BRD4 and the testis-specific isoform BRDT, largely function as transcriptional co-activators 1–3 and play critical roles in various cellular processes, including cell cycle, apoptosis, migration and invasion 4,5. As such, BET proteins enhance the oncogenic functions of major cancer drivers by either elevating their expression such as c-Myc in leukemia 6,7 or by promoting transcriptional activities of oncogenic factors such as AR and ERG in the prostate cancer setting 8. Pathologically, BET proteins are frequently overexpressed and clinically linked to various types of human cancers 5,9,10, therefore pursued as attractive therapeutic targets for selective inhibition in patients. To this end, a number of bromodomain inhibitors, including JQ1 and I-BET, have been developed 11,12 and shown promising outcomes in early clinical trials. Despite resistance to BET inhibitor has been documented in pre-clinical models 13–15 the molecular mechanisms underlying acquired resistance are largely unknown. Here, we report that Cullin 3SPOP earmarks BET proteins including BRD2, BRD3 and BRD4 for ubiquitination-mediated degradation. Pathologically, prostate cancer-associated SPOP mutants fail to interact with and promote the destruction of BET proteins, leading to their elevated abundance in SPOP-deficient prostate cancer. As a result, prostate cancer cells and prostate cancer patient-derived organoids harboring SPOP mutations are more resistant to BET inhibitor-induced cell growth arrest and apoptosis. Therefore, our results elucidate the tumor suppressor role of SPOP in prostate cancer by negatively controlling BET protein stability, and also provide a molecular mechanism for BET inhibitor resistance in prostate cancer patients bearing SPOP mutations.