A four-group urine risk classifier for predicting outcomes in patients with prostate cancer.

OBJECTIVES: To develop a risk classifier using urine-derived extracellular vesicle (EV)-RNA capable of providing diagnostic information on disease status prior to biopsy, and prognostic information for men on active surveillance (AS). PATIENTS AND METHODS: Post-digital rectal examination urine-derived EV-RNA expression profiles (n = 535, multiple centres) were interrogated with a curated NanoString panel. A LASSO-based continuation ratio model was built to generate four prostate urine risk (PUR) signatures for predicting the probability of normal tissue (PUR-1), D'Amico low-risk (PUR-2), intermediate-risk (PUR-3), and high-risk (PUR-4) prostate cancer. This model was applied to a test cohort (n = 177) for diagnostic evaluation, and to an AS sub-cohort (n = 87) for prognostic evaluation. RESULTS: Each PUR signature was significantly associated with its corresponding clinical category (P < 0.001). PUR-4 status predicted the presence of clinically significant intermediate- or high-risk disease (area under the curve = 0.77, 95% confidence interval [CI] 0.70-0.84). Application of PUR provided a net benefit over current clinical practice. In an AS sub-cohort (n = 87), groups defined by PUR status and proportion of PUR-4 had a significant association with time to progression (interquartile range hazard ratio [HR] 2.86, 95% CI 1.83-4.47; P < 0.001). PUR-4, when used continuously, dichotomized patient groups with differential progression rates of 10% and 60% 5 years after urine collection (HR 8.23, 95% CI 3.26-20.81; P < 0.001). CONCLUSION: Urine-derived EV-RNA can provide diagnostic information on aggressive prostate cancer prior to biopsy, and prognostic information for men on AS. PUR represents a new and versatile biomarker that could result in substantial alterations to current treatment of patients with prostate cancer.

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets.

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.

DESNT: A Poor Prognosis Category of Human Prostate Cancer.

BACKGROUND: A critical problem in the clinical management of prostate cancer is that it is highly heterogeneous. Accurate prediction of individual cancer behaviour is therefore not achievable at the time of diagnosis leading to substantial overtreatment. It remains an enigma that, in contrast to breast cancer, unsupervised analyses of global expression profiles have not currently defined robust categories of prostate cancer with distinct clinical outcomes. OBJECTIVE: To devise a novel classification framework for human prostate cancer based on unsupervised mathematical approaches. DESIGN, SETTING, AND PARTICIPANTS: Our analyses are based on the hypothesis that previous attempts to classify prostate cancer have been unsuccessful because individual samples of prostate cancer frequently have heterogeneous compositions. To address this issue, we applied an unsupervised Bayesian procedure called Latent Process Decomposition to four independent prostate cancer transcriptome datasets obtained using samples from prostatectomy patients and containing between 78 and 182 participants. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Biochemical failure was assessed using log-rank analysis and Cox regression analysis. RESULTS AND LIMITATIONS: Application of Latent Process Decomposition identified a common process in all four independent datasets examined. Cancers assigned to this process (designated DESNT cancers) are characterized by low expression of a core set of 45 genes, many encoding proteins involved in the cytoskeleton machinery, ion transport, and cell adhesion. For the three datasets with linked prostate-specific antigen failure data following prostatectomy, patients with DESNT cancer exhibited poor outcome relative to other patients (p=2.65×10-5, p=4.28×10-5, and p=2.98×10-8). When these three datasets were combined the independent predictive value of DESNT membership was p=1.61×10-7 compared with p=1.00×10-5 for Gleason sum. A limitation of the study is that only prediction of prostate-specific antigen failure was examined. CONCLUSIONS: Our results demonstrate the existence of a novel poor prognosis category of human prostate cancer and will assist in the targeting of therapy, helping avoid treatment-associated morbidity in men with indolent disease. PATIENT SUMMARY: Prostate cancer, unlike breast cancer, does not have a robust classification framework. We propose that this failure has occurred because prostate cancer samples selected for analysis frequently have heterozygous compositions (individual samples are made up of many different parts that each have different characteristics). Applying a mathematical approach that can overcome this problem we identify a novel poor prognosis category of human prostate cancer called DESNT.

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) and Chr18q12.3 (17.48%). Comprehensive mutation screens of genes, lincRNA encoding sequences, control regions and conserved domains within SCNAs demonstrated that a two-hit genetic model was supported in only a minor proportion of recurrent SCNA losses examined (15/40). We found that recurrent breakpoints and regions of inversion often occur within Knudson model SCNAs, leading to the identification of ZNF292 as a target gene for the deletion at 6q14.3-q15 and NKX3.1 as a two-hit target at 8p21.3-p21.2. The importance of alterations of lincRNA sequences was illustrated by the identification of a novel mutational hotspot at the KCCAT42, FENDRR, CAT1886 and STCAT2 loci at the 16q23.1-q24.3 loss. Our data confirm that the burden of SCNAs is predictive of biochemical recurrence, define nine individual regions that are associated with relapse, and highlight the possible importance of ion channel and G-protein coupled-receptor (GPCR) pathways in cancer development. We concluded that a two-hit genetic model accounts for about one third of SCNA indicating that mechanisms, such haploinsufficiency and epigenetic inactivation, account for the remaining SCNA losses.

Analysis of the genetic phylogeny of multifocal prostate cancer identifies multiple independent clonal expansions in neoplastic and morphologically normal prostate tissue.

Genome-wide DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of three men. Mutations were present at high levels in morphologically normal tissue distant from the cancer, reflecting clonal expansions, and the underlying mutational processes at work in morphologically normal tissue were also at work in cancer. Our observations demonstrate the existence of ongoing abnormal mutational processes, consistent with field effects, underlying carcinogenesis. This mechanism gives rise to extensive branching evolution and cancer clone mixing, as exemplified by the coexistence of multiple cancer lineages harboring distinct ERG fusions within a single cancer nodule. Subsets of mutations were shared either by morphologically normal and malignant tissues or between different ERG lineages, indicating earlier or separate clonal cell expansions. Our observations inform on the origin of multifocal disease and have implications for prostate cancer therapy in individual cases.

Amplification and overexpression of the KIT gene is associated with progression in the seminoma subtype of testicular germ cell tumors of adolescents and adults.

We have previously identified amplification at 4q12 in testicular germ cell tumors of adolescents and adults centered around the KIT gene encoding a tyrosine kinase transmembrane receptor. Analysis of primary testicular germ cell tumors totaling 190 cases revealed 21% of the seminoma subtype with an increased copy number of KIT whereas this change was rarely found in the nonseminomas. In most cases, gain of KIT did not include the immediately flanking noncoding DNA or the flanking genes KDR and PDGFRA. Increased copy number of KIT was not found in the putative precursor lesion, carcinoma in situ (CIS), adjacent to tumor with this change. KIT overexpression was found independent of gain and KIT immunostaining was stronger in selected cases with gain of KIT compared to those without. Taken together with activating mutations of KIT in exon 17 identified in 13% of seminomas, this suggests that the KIT gene product plays a role in the progression of CIS towards seminoma, the further understanding of which may lead to novel less toxic therapeutic approaches.

Transcription factor E2F3 overexpressed in prostate cancer independently predicts clinical outcome.

E2F transcription factors, including E2F3, directly modulate expression of EZH2. Recently, overexpression of the EZH2 gene has been implicated in the development of human prostate cancer. In tissue microrarray studies we now show that expression of high levels of nuclear E2F3 occurs in a high proportion (98/147, 67%) of human prostate cancers, but is a rare event in non-neoplastic prostatic epithelium suggesting a role for E2F3 overexpression in prostate carcinogenesis. Patients with prostate cancer exhibiting immunohistochemically detectable nuclear E2F3 expression have poorer overall survival (P=0.0022) and cause-specific survival (P=0.0047) than patients without detectable E2F3 expression. When patients are stratified according to the maximum percentage of E2F3-positive nuclei identified within their prostate cancers (up to 20, 21-40%, etc.), there is an increasingly significant association between E2F3 staining and risk of death both for overall survival (P=0.0014) and for cause-specific survival (P=0.0004). Multivariate analyses select E2F3 expression as an independent factor predicting overall survival (unstratified P=0.0103, stratified P=0.0086) and cause-specific survival (unstratified P=0.0288, stratified P=0.0072). When these results are considered together with published data on EZH2 and on the E2F3 control protein pRB, we conclude that the pRB-E2F3-EZH2 control axis may have a critical role in modulating aggressiveness of individual human prostate cancer.

Amplification and overexpression of E2F3 in human bladder cancer.

We demonstrate that, in human bladder cancer, amplification of the E2F3 gene, located at 6p22, is associated with overexpression of its encoded mRNA transcripts and high levels of expression of E2F3 protein. Immunohistochemical analyses of E2F3 protein levels have established that around one-third (33/101) of primary transitional cell carcinomas of the bladder overexpress nuclear E2F3 protein, with the proportion of tumours containing overexpressed nuclear E2F3 increasing with tumour stage and grade. When considered together with the established role of E2F3 in cell cycle progression, these results suggest that the E2F3 gene represents a candidate bladder cancer oncogene that is activated by DNA amplification and overexpression.