A dual program for translation regulation in cellular proliferation and differentiation.

A dichotomous choice for metazoan cells is between proliferation and differentiation. Measuring tRNA pools in various cell types, we found two distinct subsets, one that is induced in proliferating cells, and repressed otherwise, and another with the opposite signature. Correspondingly, we found that genes serving cell-autonomous functions and genes involved in multicellularity obey distinct codon usage. Proliferation-induced and differentiation-induced tRNAs often carry anticodons that correspond to the codons enriched among the cell-autonomous and the multicellularity genes, respectively. Because mRNAs of cell-autonomous genes are induced in proliferation and cancer in particular, the concomitant induction of their codon-enriched tRNAs suggests coordination between transcription and translation. Histone modifications indeed change similarly in the vicinity of cell-autonomous genes and their corresponding tRNAs, and in multicellularity genes and their tRNAs, suggesting the existence of transcriptional programs coordinating tRNA supply and demand. Hence, we describe the existence of two distinct translation programs that operate during proliferation and differentiation.

Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry.

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

Prognostic Value of Low-Pass Whole Genome Sequencing of Circulating Tumor DNA in Metastatic Castration-Resistant Prostate Cancer.

BACKGROUND: Multiple treatments are available for metastatic castration-resistant prostate cancer (mCRPC), including androgen receptor signaling inhibitors (ARSI) enzalutamide and abiraterone, but therapy resistance remains a major clinical obstacle. We examined the clinical utility of low-pass whole-genome sequencing (LPWGS) of circulating tumor DNA (ctDNA) for prognostication in mCRPC. METHODS: A total of 200 plasma samples from 143 mCRPC patients collected at the start of first-line ARSI treatment (baseline) and at treatment termination (n = 57, matched) were analyzed by LPWGS (median: 0.50X) to access ctDNA% and copy number alteration (CNA) patterns. The best confirmed prostate specific antigen (PSA) response (≥50% decline [PSA50]), PSA progression-free survival (PFS), and overall survival (OS) were used as endpoints. For external validation, we used plasma LPWGS data from an independent cohort of 70 mCRPC patients receiving first-line ARSI. RESULTS: Baseline ctDNA% ranged from ≤3.0% to 73% (median: 6.6%) and CNA burden from 0% to 82% (median: 13.1%) in the discovery cohort. High ctDNA% and high CNA burden at baseline was associated with poor PSA50 response (P = 0.0123/0.0081), poor PFS (P < 0.0001), and poor OS (P < 0.0001). ctDNA% and CNA burden was higher at PSA progression than at baseline in 32.7% and 42.3% of the patients. High ctDNA% and high CNA burden at baseline was also associated with poor PFS and OS (P ≤ 0.0272) in the validation cohort. CONCLUSIONS: LPWGS of ctDNA provides clinically relevant information about the tumor genome in mCRPC patients. Using LPWGS data, we show that high ctDNA% and CNA burden at baseline is associated with short PFS and OS in 2 independent cohorts.

Independent validation of a pre-specified four-kallikrein marker model for prediction of adverse pathology and biochemical recurrence.

BACKGROUND: Accurate markers for prostate cancer (PC) risk stratification could aid decision-making for initial management strategies. The 4Kscore has an undefined role in predicting outcomes after radical prostatectomy (RP). METHODS: We included 1476 patients with 4Kscore measured prior to RP at two institutions. The 4Kscore was assessed for prediction of adverse pathology at RP and biochemical recurrence (BCR) relative to a clinical model. We pre-specified that all analyses would be assessed in biopsy Grade Group 1 (GG1) or 2 (GG2) PC patients, separately. RESULTS: The 4Kscore increased discrimination for adverse pathology in all patients (delta area under the receiver operative curve (AUC) 0.009, 95% confidence interval (CI) 0.002, 0.016; clinical model AUC 0.767), driven by GG1 (delta AUC 0.040, 95% CI 0.006, 0.073) rather than GG2 patients (delta AUC 0.005, 95% CI -0.012, 0.021). Adding 4Kscore improved prediction of BCR in all patients (delta C-index 0.014, 95% CI 0.007, 0.021; preop-BCR nomogram C-index 0.738), again with larger changes in GG1 than in GG2. CONCLUSIONS: This study validates prior investigations on the use of 4Kscore in men with biopsy-confirmed PC. Men with GG1 PC and a high 4Kscore may benefit from additional testing to guide treatment selection. Further research is warranted regarding the value of the 4Kscore in men with biopsy GG2 PC.

Recurrence rate after radical prostatectomy following primary staging of high-risk prostate cancer with 68Ga-PSMA PET/CT.

BACKGROUND: Accurate primary staging is one of the most important issues for initial management of prostate cancer (PCa) patients to perform an optimal selection of patients for curative intended treatment. 68Ga-Prostate-Specific-Membrane-Antigen (PSMA) PET/CT was found superior to conventional imaging both for detection of recurrence after curative intended treatment and for primary staging. We studied the recurrence rate after radical prostatectomy in high-risk PCa patients primary staged with 68Ga-PSMA PET/CT compared with conventional imaging. MATERIAL AND METHODS: The study included 247 D'Amico high-risk PCa patients treated with radical prostatectomy (RP) after primary staging with 68Ga-PSMA PET/CT and a reference group of 137 high-risk patients with RP after conventional imaging (99mTc bone scintigraphy and CT). Recurrence rates were assessed by Cox regression and Kaplan-Meier analysis. RESULTS: The 5-year recurrence-free survival rate was 71.1% in the 68Ga-PSMA PET/CT cohort compared with 56.4% in the conventional imaging cohort. Primary staging by 68Ga-PSMA PET/CT reduced biochemical recurrence (BCR) risk by 42% (HR = 0.58 (0.41-0.83), p = .004). CONCLUSION: The present data could indicate a lower recurrence rate after RP following primary staging with 68Ga-PSMA PET/CT compared to conventional imaging, likely due to improved selection of patients for surgery.

Immune cell analyses of the tumor microenvironment in prostate cancer highlight infiltrating regulatory T cells and macrophages as adverse prognostic factors.

Improved risk stratification is needed for patients with localized prostate cancer. This study characterized and assessed the prognostic potential of distinct immune cell infiltration patterns in the prostate tumor microenvironment. Using tissue microarrays, multiplex immunohistochemistry/immunofluorescence, and automated digital pathology, we analyzed radical prostatectomy specimens from two large patient cohorts (training: n = 470; validation: n = 333) to determine infiltration levels of seven immune cell types in malignant versus benign prostate tissue: CD3+ CD8- FoxP3- T helper cells, CD3+ CD8+ FoxP3- cytotoxic T cells (CTLs), CD3+ CD8- FoxP3+ regulatory T cells (Tregs ), CD20+ B cells, CD68+ CD163- M1 macrophages, CD68+ CD163+ M2 macrophages, and tryptase+ mast cells. Results were further validated by cell type enrichment analyses of bulk tumor RNAseq data from a third independent patient cohort (n = 99). Prognostic potential was assessed by Kaplan-Meier and uni-/multi-variate Cox regression analyses. Clinical endpoint was biochemical recurrence. All seven immune cell types were enriched in prostate cancer versus benign stroma, while there was selective enrichment for B cells, Tregs , M1 and M2 macrophages, and depletion of mast cells and CTLs in prostate cancer epithelium. In all three cohorts, high levels of infiltrating Tregs , M1, and M2 macrophages in stroma and/or epithelium were associated with biochemical recurrence (p < 0.05; log-rank test). After adjustment for routine clinical variables, Tregs and M2 macrophages remained significant adverse predictors of biochemical recurrence (p < 0.05; multivariate Cox regression). Our comprehensive analyses of immune cell infiltration patterns in the prostate tumor microenvironment highlight infiltrating Tregs , M1, and M2 macrophages as adverse predictors of prostate cancer outcome. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A polymorphism in the promoter of FRAS1 is a candidate SNP associated with metastatic prostate cancer.

BACKGROUND: Inflammation and one of its mediators, NF-kappa B (NFκB), have been implicated in prostate cancer carcinogenesis. We assessed whether germline polymorphisms associated with NFκB are associated with the risk of developing lethal disease (metastases or death from prostate cancer). METHODS: Using a Bayesian approach leveraging NFκB biology with integration of publicly available datasets we used a previously defined genome-wide functional association network specific to NFκB and lethal prostate cancer. A dense-module-searching method identified modules enriched with significant genes from a genome-wide association study (GWAS) study in a discovery data set, Physicians' Health Study and Health Professionals Follow-up Study (PHS/HPFS). The top 48 candidate single nucleotide polymorphisms (SNPs) from the dense-module-searching method were then assessed in an independent prostate cancer cohort and the one SNP reproducibly associated with lethality was tested in a third cohort. Logistic regression models evaluated the association between each SNP and lethal prostate cancer. The candidate SNP was assessed for association with lethal prostate cancer in 6 of 28 studies in the prostate cancer association group to investigate cancer associated alterations in the genome (PRACTICAL) Consortium where there was some medical record review for death ascertainment which also had SNP data from the ONCOARRAY platform. All men self-identified as Caucasian. RESULTS: The rs1910301 SNP which was reproducibly associated with lethal disease was nominally associated with lethal disease (odds ratio [OR] = 1.40; p = .02) in the discovery cohort and the minor allele was also associated with lethal disease in two independent cohorts (OR = 1.35; p = .04 and OR = 1.35; p = .07). Fixed effects meta-analysis of all three cohorts found an association: OR = 1.37 (95% confidence interval [CI]: 1.15-1.62, p = .0003). This SNP is in the promoter region of FRAS1, a gene involved in epidermal-basement membrane adhesion and is present at a higher frequency in men with African ancestry. No association was found in the subset of studies from the PRACTICAL consortium studies which had a total of 106 deaths out total of 3263 patients and a median follow-up of 4.4 years. CONCLUSIONS: Through its connection with the NFκB pathway, a candidate SNP with a higher frequency in men of African ancestry without cancer was found to be associated with lethal prostate cancer across three well-annotated independent cohorts of Caucasian men.

The effect of assessing genetic risk of prostate cancer on the use of PSA tests in primary care: A cluster randomized controlled trial.

BACKGROUND: Assessing genetic lifetime risk for prostate cancer has been proposed as a means of risk stratification to identify those for whom prostate-specific antigen (PSA) testing is likely to be most valuable. This project aimed to test the effect of introducing a genetic test for lifetime risk of prostate cancer in general practice on future PSA testing. METHODS AND FINDINGS: We performed a cluster randomized controlled trial with randomization at the level of general practices (73 in each of two arms) in the Central Region (Region Midtjylland) of Denmark. In intervention practices, men were offered a genetic test (based on genotyping of 33 risk-associated single nucleotide polymorphisms) in addition to the standard PSA test that informed them about lifetime genetic risk of prostate cancer and distinguished between "normal" and "high" risk. The primary outcome was the proportion of men having a repeated PSA test within 2 years. A multilevel logistic regression model was used to test the association. After applying the exclusion criteria, 3,558 men were recruited in intervention practices, with 1,235 (34.7%) receiving the genetic test, and 4,242 men were recruited in control practices. Men with high genetic risk had a higher propensity for repeated PSA testing within 2 years than men with normal genetic risk (odds ratio [OR] = 8.94, p < 0.01). The study was conducted in routine practice and had some selection bias, which is evidenced by the relatively large proportion of younger and higher income participants taking the genetic test. CONCLUSIONS: Providing general practitioners (GPs) with access to a genetic test to assess lifetime risk of prostate cancer did not reduce the overall number of future PSA tests. However, among men who had a genetic test, knowledge of genetic risk significantly influenced future PSA testing. TRIAL REGISTRATION: This study is registered with ClinicalTrials.gov, number NCT01739062.

Elevated miR-615-3p Expression Predicts Adverse Clinical Outcome and Promotes Proliferation and Migration of Prostate Cancer Cells.

miR-615-3p has previously been described as up-regulated in prostate cancer (PC) tissue samples compared with nonmalignant controls; however, its prognostic potential and functional role in PC remain largely unknown. In this study, we investigated the clinical and biological relevance of miR-615-3p in PC. The expression of miR-615-3p was measured in PC tissue specimens from 239 men who underwent radical prostatectomy (RP), and it was investigated if miR-615-3p could predict postoperative biochemical recurrence (BCR). These findings were subsequently validated in three independent RP cohorts (n = 222, n = 273, and n = 387) and functional overexpression studies conducted in PC cells (PC3M). High miR-615-3p expression was significantly associated with BCR in four independent PC patient cohorts (P < 0.05, log-rank test). In addition, high miR-615-3p expression was a significant predictor of PC-specific survival in univariate (hazard ratio, 3.75; P < 0.001) and multivariate (hazard ratio, 2.66; P = 0.008) analysis after adjustment for the Cancer of the Prostate Risk Assessment Post-Surgical (CAPRA-S) nomogram in a merged RP cohort (n = 734). Moreover, overexpression of miR-615-3p in PC cells (PC3M) significantly increased cell viability, proliferation, apoptosis, and migration. Together, our results suggest that miR-615-3p is a significant predictor of postoperative BCR and PC-specific survival and has oncogenic functions in PC cells.

A five-microRNA model (pCaP) for predicting prostate cancer aggressiveness using cell-free urine.

Improved biomarkers for prostate cancer (PC) risk stratification are urgently needed. Here, we aimed to develop a novel multimarker model for prediction of biochemical recurrence (BCR) after curatively intended radical prostatectomy (RP), based on minimally invasive sampling of blood and urine. We initially measured the levels of 45 selected miRNAs by RT-qPCR in exosome enriched cell-free urine samples collected prior to RP from 215 PC patients (Cohort 1, training). We trained a novel logistic regression model (pCaP), comprising five urine miRNAs (miR-151a-5p, miR-204-5p, miR-222-3p, miR-23b-3p and miR-331-3p) and serum prostate-specific antigen (PSA), which significantly predicted time to BCR in Cohort 1 (univariate Cox regression analysis: HR = 3.12, p < 0.001). Next, using the same exact numeric cutoff for dichotomization as trained in Cohort 1, we tested and successfully validated the prognostic potential of pCaP in two additional cohorts, including 199 (Cohort 2, HR = 2.24, p = 0.002) and 205 (Cohort 3, HR = 2.15, p = 0.004) RP patients, respectively. pCaP remained a significant predictor of BCR, also after adjustment for pathological T-stage, surgical margin status and Gleason grade group (p < 0.05 in multivariate Cox regression analysis: HR = 2.72, 1.94 and 1.83 for Cohorts 1, 2 and 3, respectively). Additionally, pCaP scores correlated positively with the established clinical risk stratification nomogram CAPRA in all three PC cohorts (Pearson's rho: 0.45, 0.39 and 0.44). Together, our results suggest that the minimally invasive pCaP model could potentially be used in the future to improve PC risk stratification and to guide more personalized treatment decisions. Further clinical validation studies are warranted.

A novel combined miRNA and methylation marker panel (miMe) for prediction of prostate cancer outcome after radical prostatectomy.

Improved prognostic biomarkers are needed to guide personalized prostate cancer (PC) treatment decisions. Due to the prominent molecular heterogeneity of PC, multimarker panels may be more robust. Here, 25 selected top-candidate miRNA and methylation markers for PC were profiled by qPCR in malignant radical prostatectomy (RP) tissue specimens from 198 PC patients (Cohort 1, training). Using GLMnet, we trained a novel multimarker model (miMe) comprising nine miRNAs and three methylation markers that predicted postoperative biochemical recurrence (BCR) independently of the established clinicopathological CAPRA-S nomogram in Cox multivariate regression analysis in Cohort 1 (HR [95% CI]: 1.53 [1.26-1.84], p < 0.001). This result was successfully validated in two independent RP cohorts (Cohort 2, n = 159: HR [95% CI]: 1.35 [1.06-1.73], p = 0.015. TCGA, n = 350: HR [95% CI]: 1.34 [1.01-1.77], p = 0.04). Notably, in CAPRA-S low-risk patients, a high miMe score was associated with >6 times higher risk of BCR, suggesting that miMe may help identify PC patients at high risk of progression despite favorable clinicopathological factors postsurgery. Finally, miMe was a significant predictor of cancer-specific survival (p = 0.019, log-rank test) in a merged analysis of 357 RP patients. In conclusion, we trained, tested and validated a novel 12-marker panel (miMe) that showed significant independent prognostic value in three RP cohorts. In the future, combining miMe score with existing clinical nomograms may improve PC risk stratification and thus help guide treatment decisions.

Independent Validation of a Diagnostic Noninvasive 3-MicroRNA Ratio Model (uCaP) for Prostate Cancer in Cell-Free Urine.

BACKGROUND: Detection of prostate cancer (PC) based on serum prostate-specific antigen (PSA) testing leads to many unnecessary prostate biopsies, overdiagnosis, and overtreatment of clinically insignificant tumors. Thus, novel and more accurate molecular biomarkers are required. METHODS: Using reverse transcription quantitative PCR, we measured the concentrations of 45 preselected microRNAs (miRNAs) in extracellular vesicle-enriched cell-free urine samples from 4 independent patient cohorts from Spain and Denmark, including 758 patients with clinically localized PC, 289 noncancer controls with benign prostatic hyperplasia (BPH), and 233 patients undergoing initial transrectal ultrasound (TRUS)-guided prostate biopsy owing to PC suspicion (101 with benign and 132 with malignant outcome). Diagnostic potential was assessed by ROC and decision curve analysis. RESULTS: We identified and successfully validated 8 upregulated and 21 downregulated miRNAs in urine from PC patients. Furthermore, we validated a previously identified 3-miRNA diagnostic ratio model, uCaP (miR-222-3p*miR-24-3p/miR-30c-5p). High uCaP scores were distinctive of PC in urine samples from BPH vs PC patients in 3 independent cohorts [area under the curve (AUC) = 0.84, 0.71, 0.72]. Additionally, uCaP predicted TRUS biopsy results with greater accuracy than PSA (AUC uCaP = 0.644; AUC PSA = 0.527) for patients within the diagnostic gray zone (PSA ≤ 10 ng/mL). CONCLUSIONS: We successfully validated a urine-based diagnostic 3-miRNA signature for PC (uCaP) in 3 independent patient cohorts from 2 countries. In the future, the simple and noninvasive uCaP test may be used to help more accurately select patients for prostate biopsy. Prospective clinical validation is warranted.

Epigenetics of Urological Cancers.

The major urological cancers comprise prostate adenocarcinoma, urinary bladder (or upper urinary tract) carcinoma, renal cell carcinoma, testicular cancer and penile carcinoma, in this order of incidence, each with various histological and molecular subtypes [...].

Aberrant DOCK2, GRASP, HIF3A and PKFP Hypermethylation has Potential as a Prognostic Biomarker for Prostate Cancer.

Prostate cancer (PCa) is a clinically heterogeneous disease and currently, accurate diagnostic and prognostic molecular biomarkers are lacking. This study aimed to identify novel DNA hypermethylation markers for PCa with future potential for blood-based testing. Accordingly, to search for genes specifically hypermethylated in PCa tissue samples and not in blood cells or other cancer tissue types, we performed a systematic analysis of genome-wide DNA methylation data (Infinium 450K array) available in the Marmal-aid database for 4072 malignant/normal tissue samples of various types. We identified eight top candidate markers (cg12799885, DOCK2, FBXO30, GRASP, HIF3A, MOB3B, PFKP, and TPM4) that were specifically hypermethylated in PCa tissue samples and hypomethylated in other benign and malignant tissue types, including in peripheral blood cells. Potential as diagnostic and prognostic biomarkers was further assessed by the quantitative methylation specific PCR (qMSP) analysis of 37 nonmalignant and 197 PCa tissue samples from an independent population. Here, all eight hypermethylated candidates showed high sensitivity (75⁻94%) and specificity (84⁻100%) for PCa. Furthermore, DOCK2, GRASP, HIF3A and PKFP hypermethylation was significantly associated with biochemical recurrence (BCR) after radical prostatectomy (RP; 197 patients), independent of the routine clinicopathological variables. DOCK2 is the most promising single candidate marker (hazard ratio (HR) (95% confidence interval (CI)): 1.96 (1.24⁻3.10), adjusted p = 0.016; multivariate cox regression). Further validation studies are warranted and should investigate the potential value of these hypermethylation candidate markers for blood-based testing also.

PINCAGE: probabilistic integration of cancer genomics data for perturbed gene identification and sample classification.

MOTIVATION: Cancer development and progression is driven by a complex pattern of genomic and epigenomic perturbations. Both types of perturbations can affect gene expression levels and disease outcome. Integrative analysis of cancer genomics data may therefore improve detection of perturbed genes and prediction of disease state. As different data types are usually dependent, analysis based on independence assumptions will make inefficient use of the data and potentially lead to false conclusions. MODEL: Here, we present PINCAGE (Probabilistic INtegration of CAncer GEnomics data), a method that uses probabilistic integration of cancer genomics data for combined evaluation of RNA-seq gene expression and 450k array DNA methylation measurements of promoters as well as gene bodies. It models the dependence between expression and methylation using modular graphical models, which also allows future inclusion of additional data types. RESULTS: We apply our approach to a Breast Invasive Carcinoma dataset from The Cancer Genome Atlas consortium, which includes 82 adjacent normal and 730 cancer samples. We identify new biomarker candidates of breast cancer development (PTF1A, RABIF, RAG1AP1, TIMM17A, LOC148145) and progression (SERPINE3, ZNF706). PINCAGE discriminates better between normal and tumour tissue and between progressing and non-progressing tumours in comparison with established methods that assume independence between tested data types, especially when using evidence from multiple genes. Our method can be applied to any type of cancer or, more generally, to any genomic disease for which sufficient amount of molecular data is available. AVAILABILITY AND IMPLEMENTATION: R scripts available at http://moma.ki.au.dk/prj/pincage/ CONTACT: : michal.switnicki@clin.au.dk or jakob.skou@clin.au.dk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BS-SNPer: SNP calling in bisulfite-seq data.

UNLABELLED: Sodium bisulfite conversion followed by sequencing (BS-Seq, such as whole genome bisulfite sequencing or reduced representation bisulfite sequencing) has become popular for studying human epigenetic profiles. Identifying single nucleotide polymorphisms (SNPs) is important for quantification of methylation levels and for study of allele-specific epigenetic events such as imprinting. However, SNP calling in such data is complex and time consuming. Here, we present an ultrafast and memory-efficient package named BS-SNPer for the exploration of SNP sites from BS-Seq data. Compared with Bis-SNP, a popular BS-Seq specific SNP caller, BS-SNPer is over 100 times faster and uses less memory. BS-SNPer also offers higher sensitivity and specificity compared with existing methods. AVAILABILITY AND IMPLEMENTATION: BS-SNPer is written in C++ and Perl, and is freely available at https://github.com/hellbelly/BS-Snper.

Prevalence of the HOXB13 G84E mutation in Danish men undergoing radical prostatectomy and its correlations with prostate cancer risk and aggressiveness.

OBJECTIVES: To determine the prevalence of the HOXB13 G84E mutation (rs138213197) in Danish men with or without prostate cancer (PCa) and to investigate possible correlations between HOXB13 mutation status and clinicopathological characteristics associated with tumour aggressiveness. MATERIALS AND METHODS: We conducted a case-control study including 995 men with PCa (cases) who underwent radical prostatectomy (RP) between 1997 and 2011 at the Department of Urology, Aarhus University Hospital, Denmark. As controls, we used 1622 healthy men with a normal prostate specific antigen (PSA) level. RESULTS: The HOXB13 G84E mutation was identified in 0.49% of controls and in 2.51% of PCa cases. The mutation was associated with a 5.12-fold increased relative risk (RR) of PCa (95% confidence interval [CI] 2.26-13.38; P = 13 × 10(-6) ). Furthermore, carriers of the risk allele were significantly more likely to have a higher PSA level at diagnosis (mean PSA 19.9 vs 13.6 ng/mL; P = 0.032), a pathological Gleason score ≥7 (83.3 vs 60.9%; P = 0.032), and positive surgical margins (56.0 vs 28.5%; P = 0.006) than non-carriers. Risk allele carriers were also more likely to have aggressive disease (54.2 vs 28.6%; P = 0.011), as defined by a preoperative PSA ≥20 ng/mL, pathological Gleason score ≥ (4+3) and/or presence of regional/distant disease. At a mean follow-up of 7 months, we found no significant association between HOXB13 mutation status and biochemical recurrence in this cohort of men who underwent RP. CONCLUSIONS: This is the first study to investigate the HOXB13 G84E mutation in Danish men. The mutation was detected in 0.49% of controls and in 2.51% of cases, and was associated with 5.12-fold increased RR of being diagnosed with PCa. In our RP cohort, HOXB13 mutation carriers were more likely to develop aggressive PCa. Further studies are needed to assess the potential of HOXB13 for future targeted screening approaches.

A meta-analysis of genome-wide association studies to identify prostate cancer susceptibility loci associated with aggressive and non-aggressive disease.

Genome-wide association studies (GWAS) have identified multiple common genetic variants associated with an increased risk of prostate cancer (PrCa), but these explain less than one-third of the heritability. To identify further susceptibility alleles, we conducted a meta-analysis of four GWAS including 5953 cases of aggressive PrCa and 11 463 controls (men without PrCa). We computed association tests for approximately 2.6 million SNPs and followed up the most significant SNPs by genotyping 49 121 samples in 29 studies through the international PRACTICAL and BPC3 consortia. We not only confirmed the association of a PrCa susceptibility locus, rs11672691 on chromosome 19, but also showed an association with aggressive PrCa [odds ratio = 1.12 (95% confidence interval 1.03-1.21), P = 1.4 × 10(-8)]. This report describes a genetic variant which is associated with aggressive PrCa, which is a type of PrCa associated with a poorer prognosis.

Prognostic DNA methylation markers for prostate cancer.

Prostate cancer (PC) is the most commonly diagnosed neoplasm and the third most common cause of cancer-related death amongst men in the Western world. PC is a clinically highly heterogeneous disease, and distinction between aggressive and indolent disease is a major challenge for the management of PC. Currently, no biomarkers or prognostic tools are able to accurately predict tumor progression at the time of diagnosis. Thus, improved biomarkers for PC prognosis are urgently needed. This review focuses on the prognostic potential of DNA methylation biomarkers for PC. Epigenetic changes are hallmarks of PC and associated with malignant initiation as well as tumor progression. Moreover, DNA methylation is the most frequently studied epigenetic alteration in PC, and the prognostic potential of DNA methylation markers for PC has been demonstrated in multiple studies. The most promising methylation marker candidates identified so far include PITX2, C1orf114 (CCDC181) and the GABRE~miR-452~miR-224 locus, in addition to the three-gene signature AOX1/C1orf114/HAPLN3. Several other biomarker candidates have also been investigated, but with less stringent clinical validation and/or conflicting evidence regarding their possible prognostic value available at this time. Here, we review the current evidence for the prognostic potential of DNA methylation markers in PC.

Spatial Profiling of Circular RNAs in Cancer Reveals High Expression in Muscle and Stromal Cells.

Circular RNAs (circRNA) are covalently closed molecules that can play important roles in cancer development and progression. Hundreds of differentially expressed circRNAs between tumors and adjacent normal tissues have been identified in studies using RNA sequencing or microarrays, emphasizing a strong translational potential. Most previous studies have been performed using RNA from bulk tissues and lack information on the spatial expression patterns of circRNAs. Here, we showed that the majority of differentially expressed circRNAs from bulk tissue analyses of colon tumors relative to adjacent normal tissues were surprisingly not differentially expressed when comparing cancer cells directly with normal epithelial cells. Manipulating the proliferation rates of cells grown in culture revealed that these discrepancies were explained by circRNAs accumulating to high levels in quiescent muscle cells due to their high stability; on the contrary, circRNAs were diluted to low levels in the fast-proliferating cancer cells due to their slow biogenesis rates. Thus, different subcompartments of colon tumors and adjacent normal tissues exhibited striking differences in circRNA expression patterns. Likewise, the high circRNA content in muscle cells was also a strong confounding factor in bulk analyses of circRNAs in bladder and prostate cancers. Together, these findings emphasize the limitations of using bulk tissues for studying differential circRNA expression in cancer and highlight a particular need for spatial analysis in this field of research. SIGNIFICANCE: The abundance of circRNAs varies systematically between subcompartments of solid tumors and adjacent tissues, implying that differentially expressed circRNAs discovered in bulk tissue analyses may reflect differences in cell type composition between samples.