Purpose Liquid biopsies that noninvasively detect molecular correlates of aggressive prostate cancer (PCa) could be used to triage patients, reducing the burdens of unnecessary invasive prostate biopsy and enabling early detection of high-risk disease. DNA hypermethylation is among the earliest and most frequent aberrations in PCa. We investigated the accuracy of a six-gene DNA methylation panel (Epigenetic Cancer of the Prostate Test in Urine [epiCaPture]) at detecting PCa, high-grade (Gleason score greater than or equal to 8) and high-risk (D’Amico and Cancer of the Prostate Risk Assessment] PCa from urine. Patients and Methods Prognostic utility of epiCaPture genes was first validated in two independent prostate tissue cohorts. epiCaPture was assessed in a multicenter prospective study of 463 men undergoing prostate biopsy. epiCaPture was performed by quantitative methylation-specific polymerase chain reaction in DNA isolated from prebiopsy urine sediments and evaluated by receiver operating characteristic and decision curves (clinical benefit). The epiCaPture score was developed and validated on a two thirds training set to one third test set. Results Higher methylation of epiCaPture genes was significantly associated with increasing aggressiveness in PCa tissues. In urine, area under the receiver operating characteristic curve was 0.64, 0.86, and 0.83 for detecting PCa, high-grade PCa, and high-risk PCa, respectively. Decision curves revealed a net benefit across relevant threshold probabilities. Independent analysis of two epiCaPture genes in the same clinical cohort provided analytical validation. Parallel epiCaPture analysis in urine and matched biopsy cores showed added value of a liquid biopsy. Conclusion epiCaPture is a urine DNA methylation test for high-risk PCa. Its tumor specificity out-performs that of prostate-specific antigen (greater than 3 ng/mL). Used as an adjunct to prostate-specific antigen, epiCaPture could aid patient stratification to determine need for biopsy.

We propose Bayesian model averaging (BMA) as a method for postprocessing the results of model-based clustering. Given a number of competing models, appropriate model summaries are averaged, using the posterior model probabilities, instead of being taken from a single "best" model. We demonstrate the use of BMA in model-based clustering for a number of datasets. We show that BMA provides a useful summary of the clustering of observations while taking model uncertainty into account. Further, we show that BMA in conjunction with model-based clustering gives a competitive method for density estimation in a multivariate setting. Applying BMA in the model-based context is fast and can give enhanced modeling performance.

Triple-negative breast cancer (TNBC) is an aggressive form of mammary malignancy currently without satisfactory systemic treatment options. Agents generating reactive oxygen species (ROS), such as ascorbate (Asc) and menadione (Men), especially applied in combination, have been proposed as an alternative anticancer modality. However, their effectiveness can be hampered by the cytoprotective effects of elevated antioxidant enzymes (e.g., peroxiredoxins, PRDX) in cancer. In this study, PRDX1 mRNA and protein expression were assessed in TNBC tissues by analysis of the online RNA-seq datasets and immunohistochemical staining of tissue microarray, respectively. We demonstrated that PRDX1 mRNA expression was markedly elevated in primary TNBC tumors as compared to non-malignant controls, with PRDX1 protein staining intensity correlating with favorable survival parameters. Subsequently, PRDX1 functionality in TNBC cell lines or non-malignant mammary cells was targeted by genetic silencing or chemically by auranofin (AUR). The PRDX1-knockdown or AUR treatment resulted in inhibition of the growth of TNBC cells in vitro. These cytotoxic effects were further synergistically potentiated by the incubation with a combination of the prooxidant agents, Asc and Men. In conclusion, we report that the PRDX1-related antioxidant system is essential for maintaining redox homeostasis in TNBC cells and can be an attractive therapeutic target in combination with ROS-generating agents.

Background: Liquid biopsies offer significant potential for informing on cancer progression and therapeutic resistance via minimally invasive serial monitoring of genetic alterations. Although the cancer epigenome is a central driving force in most neoplasia, the accuracy of monitoring the tumor methylome using liquid biopsies remains relatively unknown. Objectives: to investigate how well two types of liquid biopsy (urine and blood) capture the prostate cancer methylome, and may thus serve as a non-invasive surrogate for studying the tumor epigenome. Methods: A cohort of four metastatic treatment naïve prostate cancer (PCa) patients was selected. Matched biopsy cores (tumor and histologically matched-normal), post-DRE, pre-biopsy urine, and peripheral blood plasma were available for each subject. DNA methylation was profiled utilizing the Infinium® MethylationEPIC BeadChip (Illumina) and analysed using the RnBeads software. Significantly (FDR adjusted P < 0.05) differentially methylated probes (DMPs) between tumor and MN were identified and examined in the liquids (done at a grouped and individual subject level). Results: DNA methylation analysis of urine and blood in men with metastatic PCa showed highly correlated patterns between the different liquid types (ρ = 0.93, P < 0.0001), with large contributions from non-tumor sources. DNA methylation profiles of liquids were more similar between subjects, than intra-individual liquid-tumor correlations. Overall, both urine and plasma are viable surrogates for tumor tissue biopsies, capturing up to 39.40% and 64.14% of tumor-specific methylation alterations, respectively. Conclusion: We conclude that both urine and blood plasma are easily accessible and sensitive biofluids for the study of PCa epigenomic alterations.

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