Search

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.

Abstract Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated the mechanisms through which cancer cells escape treatment, but their relation toward the tumor microenvironment (TME) remains elusive. Here we present a comprehensive transcriptomic landscape of the prostate TME at multiple points in the standard treatment timeline employing single-cell RNA-sequencing and spatial transcriptomics data from 120 patients. We identify club-like cells as a key epithelial cell subtype that acts as an interface between the prostate and the immune system. Tissue areas enriched with club-like cells have depleted androgen signaling and upregulated expression of luminal progenitor cell markers. Club-like cells display a senescence-associated secretory phenotype and their presence is linked to increased polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) activity. Our results indicate that club-like cells are associated with myeloid inflammation previously linked to androgen deprivation therapy resistance, providing a rationale for their therapeutic targeting.

Background and objective: Prostate-specific antigen (PSA) is of limited value as a surrogate marker for overall survival (OS) in prostate cancer (PC). Serum thymidine kinase 1 (sTK1) is an enzyme expressed by actively dividing cells. Our aim was to evaluate the value of sTK1 as prognostic biomarker in metastatic hormone-sensitive PC (mHSPC) and metastatic castration-resistant PC (mCRPC). Methods: sTK1 was examined in three cohorts: (1) 43 men with de novo mHSPC managed with androgen deprivation monotherapy; (2) 99 patients with mCRPC managed with androgen receptor signaling inhibitors (ARSIs); and (3) 98 patients with mCRPC treated with docetaxel. sTK1 levels were determined at treatment initiation. OS was evaluated using Cox regression analysis. Key findings and limitations: In the mHSPC cohort, sTK1 levels in the highest quartile were associated with OS (hazard ratio [HR] 7.77, 95% confidence interval [CI] 2.25–26.9) in comparison to the lowest quartile after multivariable adjustment for age, Gleason score, and PSA. Similarly, sTKI was associated with poor OS in the mCRPC group treated with ARSIs (upper quartile: HR 5.22, 95% CI 2.23–12.2) after multivariable adjustment for age, PSA, and Eastern Cooperative Oncology Group performance status. In the docetaxel-treated mCRPC group the association between OS and sTK1 was lower but still significant (multivariable-adjusted HR 2.28, 95% CI 1.13–4.60). Limitations include the nonrandomized inclusion of patients for different treatments, which could lead to selection bias. Conclusions and clinical implications: sTK1 predicted OS in mHSPC and mCRPC, demonstrating additional value over established clinical risk factors. sTK1 should be measured in randomized clinical trials of treatments for advanced PC to validate its predictive value. Patient summary: We found that for patients with metastatic prostate cancer, high levels of a protein called TK1 that is involved in cell division was linked to higher risk of death. Our findings need to be confirmed in other studies.

Cryptophytes are a promising source of bioactive compounds that have not been fully explored. This research investigated the antimicrobial activity of total phenolic compounds (TPC) and exopolysaccharides (EPS) extracted from several cryptophytes against a range of harmful foodborne bacteria and fungi. To measure the minimum inhibitory concentration (MIC) value, the broth microdilution method was used. In the antibacterial evaluation of TPC, the MIC ranged between 31.25 and 500 μg/mL, while for the antifungal activity test, it varied from 31.25 to 125 μg/mL. In the antibacterial activity test of EPS, the MIC values ranged from 125 to 1,000 μg/mL, whereas in the antifungal susceptibility test, it ranged between 62.5 and 1,000 μg/mL. The most resistant pathogen against TPC was Escherichia coli, while Campylobacter jejuni was the most susceptible. In the case of EPS, the most resistant pathogen was Salmonella Typhimurium, while Aspergillus versicolor exhibited the highest susceptibility. Overall, in terms of antimicrobial activity, TPC was more effective than EPS. Finally, the tolerance level (TL) for TPC and EPS was ≤4 in all tested samples, indicating their bactericidal/fungicidal mechanism of action. In conclusion, TPC and EPS isolated from cryptophytes demonstrated remarkable antimicrobial properties and ability to fully eradicate pathogens, and could be considered as natural preservatives in the food industry.

A considerable number of antibacterial agents are derived from bacterial metabolites. Similarly, numerous known compounds that impede bacterial virulence stem from bacterial metabolites. Enteropathogenic Escherichia coli (EPEC) is a notable human pathogen causing intestinal infections, particularly affecting infant mortality in developing regions. These infections are characterized by microvilli effacement and intestinal epithelial lesions linked with aberrant actin polymerization. This study aimed to identify potential antivirulence compounds for EPEC infections among bacterial metabolites harvested from marine actinobacteria (Kocuria sp. and Rhodococcus spp.) from the Arctic Sea by the application of virulence-based screening assays. Moreover, we demonstrate the suitability of these antivirulence assays to screen actinobacteria extract fractions for the bioassay-guided identification of metabolites. We discovered a compound in the fifth fraction of a Kocuria strain that interferes with EPEC-induced actin polymerization without affecting growth. Furthermore, a growth-inhibiting compound was identified in the fifth fraction of a Rhodococcus strain. Our findings include the bioassay-guided identification, HPLC-MS-based dereplication, and isolation of a large phospholipid and a likely antimicrobial peptide, demonstrating the usefulness of this approach in screening for compounds capable of inhibiting EPEC virulence.

Jonne Åkerla,1,2 Jaakko Nevalainen,3 Jori S Pesonen,4 Antti Pöyhönen,5 Juha Koskimäki,1 Jukka Häkkinen,6 Teuvo LJ Tammela,1,2 Anssi Auvinen3 1Department of Urology, Tampere University Hospital, Tampere, Finland; 2Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; 3Faculty of Social Sciences, Tampere University, Tampere, Finland; 4Department of Surgery, Päijät-Häme Central Hospital, Lahti, Finland; 5Centre for Military Medicine, The Finnish Defence Forces, Riihimäki, Finland; 6Department of Urology, Länsi-Pohja healthcare District, Kemi, FinlandCorrespondence: Jonne Åkerla, Department of Urology, Tampere University Hospital, Teiskontie 35, Tampere, 33521, Finland, Tel +358 311 611, Fax +358 311 64256, Email jonne.akerla@gmail.comPurpose: To evaluate a random forest (RF) algorithm of lower urinary tract symptoms (LUTS) as a predictor of all-cause mortality in a population-based cohort.Materials and Methods: A population-based cohort of 3143 men born in 1924, 1934, and 1944 was evaluated using a mailed questionnaire including the Danish Prostatic Symptom Score (DAN-PSS-1) to assess LUTS as well as questions on medical conditions and behavioral and sociodemographic factors. Surveys were repeated in 1994, 1999, 2004, 2009 and 2015. The cohort was followed-up for vital status until the end of 2018. RF uses an ensemble of classification trees for prediction with a good flexibility and without overfitting. RF algorithms were developed to predict the five-year mortality using LUTS, demographic, medical, and behavioral factors alone and in combinations.Results: A total of 2663 men were included in the study, of whom 917 (34%) died during follow-up (median follow-up time 15.0 years). The LUTS-based RF algorithm showed an area under the curve (AUC) 0.60 (95% CI 0.52– 0.69) for five-year mortality. An expanded RF algorithm, including LUTS, medical history, and behavioral and sociodemographic factors, yielded an AUC 0.73 (0.65– 0.81), while an algorithm excluding LUTS yielded an AUC 0.71 (0.62– 0.78).Conclusion: An exploratory RF algorithm using LUTS can predict all-cause mortality with acceptable discrimination at the group level. In clinical practice, it is unlikely that LUTS will improve the accuracy to predict death if the patient’s background is well known.Keywords: lower urinary tract symptoms, mortality, machine learning, cohort studies

The digital twin (DT), which involves creating a virtual replica of a physical asset or system, has emerged as a transformative set of tools across various industries. In the oil and gas (O&G) industry, the development of DTs represents a significant evolution in how companies manage complex operations, enhance safety, and optimize decision-making processes. Despite these significant advancements, the underlying tools, technologies, and frameworks for developing DTs in O&G applications remain non-standardized and unfamiliar to many O&G practitioners, highlighting the need for a systematic literature review (SLR) on the topic. Thus, this paper offers an SLR of the existing literature on DT development for O&G from 2018 onwards, utilizing Scopus and Web of Science Core Collection. We provide a comprehensive overview of this field, demonstrate how it is evolving, and highlight standard practices and research opportunities in the area. We perform broad classifications of the 98 studies, categorizing the DTs by their development methodologies, implementation objectives, data acquisition, asset digital development, data integration and preprocessing, data analysis and modeling, evaluation and validation, and deployment tools. We also include a bibliometric analysis of the selected papers, highlighting trends and key contributors. Given the increasing number of new DT developments in O&G and the many new technologies available, we hope to provide guidance on the topic and promote knowledge production and growth concerning the development of DTs for O&G.

Cancer survivorship was recently identified as a prostate cancer (PCa) research priority by PIONEER, a European network of excellence for big data in PCa. Despite being a research priority, cancer survivorship lacks a clear and agreed definition, and there is a distinct paucity of patient-reported outcome (PRO) data available on the subject. Data collection on cancer survivorship depends on the availability and implementation of (validated) routinely collected patient-reported outcome measures (PROMs). There have been recent advances in the availability of such PROMs. For instance, the European Organisation for Research and Treatment of Cancer Quality of Life Group (EORTC QLG) is developing survivorship questionnaires. This provides an excellent first step in improving the data available on cancer survivorship. However, we propose that an agreed, standardised definition of (prostate) cancer survivorship must first be established. Only then can real-world data on survivorship be collected to strengthen our knowledge base. With more men than ever surviving PCa, this type of research is imperative to ensure that the quality of life of these men is considered as much as their quantity of life. Patient summary: As there are more prostate cancer survivors than ever before, research into cancer survivorship is crucial. We highlight the importance of such research and provide recommendations on how to carry it out. The first step should be establishing agreement on a standardised definition of survivorship. From this, patient-reported outcome measures can then be used to collect important survivorship data.

Abstract To compare the effect of statin use in relation to castration-resistant prostate cancer (CRPC) treatment, we assessed the risk of ADT-treated PCa-patients to initiate CRPC treatment by statin use and the outcomes of CRPC treatment by statin use. Our study cohort consisted of 1169 men who participated in the Finnish Randomized Study of Screening for Prostate Cancer (FinRSPC) and initiated androgen deprivation therapy (ADT) during the follow-up (1996–2017). Statin use was associated with slightly decreased risk of initiating CRPC treatment (HR 0.68; 95% CI 0.47–0.97) with a 5.7 years’ median follow-up until CRPC for non-users and 7.5 years for statin users. The risk of discontinuation of first or second line CRPC treatment due to inefficacy was not modified by statin use and the results remained similar in subgroup analysis assessing separately patients treated with taxans or androgen receptor signaling inhibitors. We observed an inverse association between statin use and the risk of initiation of the CRPC treatment. No beneficial risk modification by statin use during CRPC treatment was observed. These results suggest that statins might be beneficial during hormone-sensitive phase but not in the later phases of prostate cancer treatment.

Esta narração nasce de desassossegos que emergem do ser extensionista em um Centro Universitário, no município de Petrópolis, Rio de Janeiro. No encontro com gentes das classes populares, se evidenciou um jeito próprio de fazer extensão. Uma extensão fundamentada em uma prática dialógica, que se coloca à deriva no caminho, se expõe ao encontro e às mudanças que acontecem em decorrência das interações. Uma extensão que se compromete com essas gentes, na transformação do mundo. O exercício investigativo foi delineado metodologicamente como uma pesquisa com o cotidiano. O diálogo e a escuta são procedimentos que potencializam suas reflexões, tecidas por meio de registros de campo combinando a razão e o amor, o corpo e o coração, atuando a partir do diálogo amoroso, buscando o que poderia se chamar uma extensão sentipensante. Aposta no paradigma indiciário proposto por Ginzburg para captar pistas e indícios presentes nas vozes, nos gestos e nos silêncios das gentes da pesquisa. Com esse trabalho, se aprendeu que é possível uma extensão comprometida, amorosa e libertadora, que atue nas frestas desse modelo hegemônico de universidade, que subalterniza, exclui e provoca apagamentos de saberes, experiências e histórias.

Abstract Background Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question. Methods We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high-risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones. Results In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, 5 years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, 3 years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance the identification of key drivers. Evolutionary analysis’ potential impact on therapy selection appears positive in these pilot cases. Conclusions PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value.

Abstract Background Researchers and clinicians using common clinical assessments need to attend to the prevalence of missing data to ensure the validity of the information gathered. The Expanded Prostate Cancer Index Short Form (EPIC-26) is a commonly used measurement scale used for assessing patients’ quality of life, but the measure lacks comprehensive analysis on missing data. We aimed to explore the quantity of missing answers in EPIC-26 and to characterize patterns and possible explanations of missing data in the survey. Methods The survey sample consisted of 625 Finnish prostate cancer patients who participated in a study with a 1-year follow-up with three measurement points (0, 6, and 12 months). Descriptive statistics were used to describe the study population and missingness level. A logistic regression was performed for each EPIC domain to study factors related to missingness during the follow-up. Results Proportions of missing answers in EPIC-26 were low (3.1–3.9%) between survey rounds. As much as 37% of patients left at least one question unanswered during their follow-up. The hormonal domain produced the most missing answers. Questions about breast tenderness/enlargement (question 13.b.), hot flashes (question 13.a.), frequency of erections (question 10.), and ability to reach orgasm (question 8.b.) were most frequently left unanswered. Higher age, lower education level, no relationship, more severe cancer, lower function scores in some EPIC domains, lower treatment satisfaction or self-rated health were associated with missingness. Conclusions Questions 13.b. and 13.a. might be considered female-specific symptoms, thus difficult to comprehend unless patients had already experienced side effects from androgen deprivation therapy. Questions 10. and 8.b. might be difficult to answer if the patient has been sexually inactive. To improve the measure’s validity, the questionnaire’s hormonal section requires additional explanation that the inquired symptoms are common treatment side effects of anti-androgen therapy; questions 8–10 require a not-applicable category for sexually inactive patients.

Introduction Evidence on the effectiveness of prostate cancer screening based on prostate-specific antigen is inconclusive and suggests a questionable balance between benefits and harms due to overdiagnosis, and complications from biopsies and overtreatment. However, diagnostic accuracy studies have shown that detection of clinically insignificant prostate cancer can be reduced by MRI combined with targeted biopsies.The aim of the paper is to describe the analysis of the ProScreen randomised trial to assess the performance of the novel screening algorithm in terms of the primary outcome, prostate cancer mortality and secondary outcomes as intermediate indicators of screening benefits and harms of screening.Methods The trial aims to recruit at least 111 000 men to achieve sufficient statistical power for the primary outcome. Men will be allocated in a 1:3 ratio to the screening and control arms. Interim analysis is planned at 10 years of follow-up, and the final analysis at 15 years. Difference between the trial arms in prostate cancer mortality will be assessed by Gray’s test using intention-to-screen analysis of randomised men. Secondary outcomes will be the incidence of prostate cancer by disease aggressiveness, progression to advanced prostate cancer, death due to any cause and cost-effectiveness of screening.Ethics and dissemination The trial protocol was reviewed by the ethical committee of the Helsinki University Hospital (2910/2017). Results will be disseminated through publications in international peer-reviewed journals and at scientific meetings.Trial registration number NCT03423303

Natural products and analogues are a source of antibacterial drug discovery. Considering drug resistance levels emerging for antibiotics, identification of bacterial metalloenzymes and the synthesis of selective inhibitors are interesting for antibacterial agent development. Peptide nucleic acids are attractive antisense and antigene agents representing a novel strategy to target pathogens due to their unique mechanism of action. Antisense inhibition and development of antisense peptide nucleic acids is a new approach to antibacterial agents. Due to the increased resistance of biofilms to antibiotics, alternative therapeutic options are necessary. To develop antimicrobial strategies, optimised in vitro and in vivo models are needed. In vivo models to study biofilm-related respiratory infections, device-related infections: ventilator-associated pneumonia, tissue-related infections: chronic infection models based on alginate or agar beads, methods to battle biofilm-related infections are discussed. Drug delivery in case of antibacterials often is a serious issue therefore this review includes overview of drug delivery nanosystems.

Summary: The root extract of Peucedanum ostruthium (PO-E) was identified as a promising antibacterial source from a screening of 158 extracts against Staphylococcus aureus. It has also recently been shown to significantly decrease the survival of the nematode Caenorhabditis elegans. We used the biochemometric approach ELINA to investigate the phytochemical characteristics of the multicomponent mixture PO-E to identify the anti-infective constituent(s) targeting S. aureus and C. elegans. 1H NMR spectra of PO-E-derived microfractions were correlated with their respective bioactivity data. Heterocovariance analyses unambiguously identified ostruthin as an anti-staphylococcal constituent, which potently also inhibited Enterococcus spp.. ELINA demonstrated that anthelmintic activity was due to a combinatorial effect of ostruthin and isoimperatorin. A C. elegans-based survival and motility assay confirmed that isoimperatorin, imperatorin, and verapamil modulated the susceptibility of ostruthin. The combinatorial effect of these natural products was shown in larvae studies to be related to the function of the nematodes’ efflux pump.

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

BackgroundA polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.MethodsUnited Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.ResultsThe expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.ConclusionsPHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.ImpactPersonalized genetic risk assessments could inform prostate cancer screening decisions.

Objective and setting To study longitudinally cancer-related experiences of spouses of patients with prostate cancer and the predictors of their psychological recovery and quality of life (QOL) by following the participants of our previous survey at primary cancer treatment in a university hospital.Design A 5-year longitudinal cohort design.Participants and procedure A follow-up questionnaire was mailed to the female spouses/partners who participated in our previous survey (n=104). We quantitatively explored the spouses’ prostate cancer-related experiences since the previous survey and measured their current psychological symptom distress and well-being/QOL. Seventy-seven (74%) of the initial participants responded.Outcomes The main outcome measures were the spouses’ psychological recovery (psychological symptoms at the initial survey vs currently) and well-being/QOL (depressive symptoms, domains of QOL) at 5 years. We analysed their predictors with regression analyses.Results The treatment had been prostatectomy in 70% of the patients. Psychological distress had alleviated in 76% of spouses (p

Androgen deprivation therapy is the cornerstone treatment of advanced prostate cancer. Eventually prostate cancer cells overcome androgen deprivation therapy, giving rise to castration resistant prostate cancer (CRPC) characterized by increased androgen receptor (AR) activity. Understanding the cellular mechanisms leading to CRPC is needed for development of novel treatments. We used long-term cell cultures to model CRPC; a testosterone-dependent cell line (VCaP-T) and cell line adapted to grow in low testosterone (VCaP-CT). These were used to uncover persistent and adaptive responses to testosterone level. RNA was sequenced to study AR-regulated genes. Expression level changed due to testosterone depletion in 418 genes in VCaP-T (AR-associated genes). To evaluate significance for CRPC growth, we compared which of them were adaptive i.e., restored expression level in VCaP-CT. Adaptive genes were enriched to steroid metabolism, immune response and lipid metabolism. The Cancer Genome Atlas Prostate Adenocarcinoma data were used to assess the association with cancer aggressiveness and progression-free survival. Expressions of 47 AR-associated or association gaining genes were statistically significant markers for progression-free survival. These included genes related to immune response, adhesion and transport. Taken together, we identified and clinically validated multiple genes being linked with progression of prostate cancer and propose several novel risk genes. Possible use as biomarkers or therapeutic targets should be studied further.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

ObjectivesTo develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.DesignAnalysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.SettingMultiple institutions that were members of international PRACTICAL consortium.ParticipantsAll consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.Main outcome measuresPrediction with hazard score of age of onset of aggressive cancer in validation set.ResultsIn the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.ConclusionsPolygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

Background: Identification of intervention-related deaths is important for an accurate assessment of the ratio of benefit to harm in screening trials. Objective: To investigate intervention-related deaths by study arm in the European Randomized Study of Prostate Cancer Screening (ERSPC). Design, setting, and participants: ERSPC is a multicenter trial initiated in the 1990s to investigate whether screening on the basis of prostate-specific antigen (PSA) can decrease prostate cancer mortality. The present study included men in the core age group (55–69 yr: screening group n = 112 553, control group n = 128 681) with 16-yr follow-up. Outcome measurements and statistical analysis: Causes of death among men with prostate cancer in ERSPC were predominantly evaluated by independent national committees via review of medical records according to a predefined algorithm. Intervention-related deaths were defined as deaths caused by complications during the screening procedure, treatment, or follow-up. Descriptive statistics were used for the results. Results and limitations: In total, 34 deaths were determined to be intervention-related, of which 21 were in the screening arm and 13 in the control arm. The overall risk of intervention-related death was 1.41 (95% confidence interval 0.99–1.99) per 10 000 randomized men for both arms combined and varied among centers from 0 to 7.0 per 10 000 randomized men. A limitation of this study is that differences in procedures among centers decreased the comparability of the results. Conclusions: Intervention-related deaths were rare in ERSPC. Monitoring of intervention-related deaths in screening trials is important for assessment of harms. Patient summary: We investigated deaths due to screening or treatment to assess harm in a trial of prostate cancer screening. Few such deaths were identified.

Identifying the molecular mechanisms of response to systemic therapy in prostate cancer remains crucial. Here, the authors apply single cell-ATAC and RNAseq to models of early treatment response and resistance to enzalutamide and identify chromatin and gene expression patterns that can predict treatment response.

Background: Systematic identification of data essential for outcome prediction in metastatic prostate cancer (mPC) would accelerate development of precision oncology. Objective: To identify novel phenotypes and features associated with mPC outcome, and to identify biomarker and data requirements to be tested in future precision oncology trials. Design, setting, and participants: We analyzed deep longitudinal clinical, neuroendocrine expression, and autopsy data of 33 men who died from mPC between 1995 and 2004 (PELICAN33), and related findings to mPC biomarkers reported in the literature. Intervention: Thirty-three men prospectively consented to participate in an integrated clinical-molecular rapid autopsy study of mPC. Outcome measurements and statistical analysis: Data exploration with correction for multiple testing and survival analysis from the time of diagnosis to time to death and time to first occurrence of severe pain as outcomes were carried out. The effect of seven complications on the modeled probability of dying within 2 yr after presenting with the complication was evaluated using logistic regression. Results and limitations: Feature exploration revealed novel phenotypes related to mPC outcome. Four complications (pleural effusion, severe anemia, severe or controlled pain, and bone fracture) predict the likelihood of death within 2 yr. Men with Gleason grade group 5 cancers developed severe pain sooner than those with lower-grade tumors. Surprisingly, neuroendocrine (NE) differentiation was frequently observed in the setting of high serum prostate-specific antigen (PSA) levels (≥30 ng/ml). In 4/33 patients, no controlled (requiring analgesics) or severe pain was detected, and strikingly, 14/15 metastatic sites studied in these men did not express NE markers, suggesting an inverse relationship between NE differentiation and pain in mPC. Intracranial subdural metastasis is common (36%) and is usually clinically undetected. Categorization of “skeletal-related events” complications used in recent studies likely obscures the understanding of spinal cord compression and fracture. Early death from prostate cancer was identified in a subgroup of men with a low longitudinal PSA bandwidth. Cachexia is common (body mass index

Global changes in chromatin accessibility may drive cancer progression by reprogramming transcription factor (TF) binding. In addition, histone acetylation readers such as bromodomain-containing protein 4 (BRD4) have been shown to associate with these TFs and contribute to aggressive cancers including prostate cancer (PC). Here, we show that chromatin accessibility defines castration-resistant prostate cancer (CRPC). We show that the deregulation of androgen receptor (AR) expression is a driver of chromatin relaxation and that AR/androgen-regulated bromodomain-containing proteins (BRDs) mediate this effect. We also report that BRDs are overexpressed in CRPCs and that ATAD2 and BRD2 have prognostic value. Finally, we developed gene stratification signature (BROMO-10) for bromodomain response and PC prognostication, to inform current and future trials with drugs targeting these processes. Our findings provide a compelling rational for combination therapy targeting bromodomains in selected patients in which BRD-mediated TF binding is enhanced or modified as cancer progresses.

Enzalutamide significantly improved radiographic progression-free survival (rPFS) and overall survival (OS) among men with chemotherapy-naïve metastatic castration-resistant prostate cancer at the prespecified interim analysis of PREVAIL, a phase 3, double-blind, randomized study. We evaluated the longer-term efficacy and safety of enzalutamide up to the prespecified number of deaths in the final analysis, which included an additional 20 mo of follow-up for investigator-assessed rPFS, 9 mo of follow-up for OS, and 4 mo of follow-up for safety. Enzalutamide reduced the risk of radiographic progression or death by 68% (hazard ratio [HR] 0.32, 95% confidence interval [CI] 0.28-0.37; p

Abstract The three oncogenic PIM family kinases have been implicated in the development of prostate cancer (PCa). The aim of this study was to examine the mRNA and protein expression levels of PIM1, PIM2, and PIM3 in PCa and their associations with the MYC and ERG oncogenes. We utilized prostate tissue specimens of normal, benign prostatic hyperplasia (BPH), prostatic intraepithelial neoplasia (PIN), untreated PCa, and castration‐resistant prostate cancer (CRPC) for immunohistochemical (IHC) analysis. In addition, we analyzed data from publicly available mRNA expression and chromatin immunoprecipitation sequencing (ChIP‐Seq) datasets. Our data demonstrated that PIM expression levels are significantly elevated in PCa compared to benign samples. Strikingly, the expression of both PIM1 and PIM2 was further increased in CRPC compared to PCa. We also demonstrated a significant association between upregulated PIM family members and both the ERG and MYC oncoproteins. Interestingly, ERG directly binds to the regulatory regions of all PIM genes and upregulates their expression. Furthermore, ERG suppression with siRNA reduced the expression of PIM in PCa cells. These results provide evidence for cooperation of PIM and the MYC and ERG oncoproteins in PCa development and progression and may help to stratify suitable patients for PIM‐targeted therapies.