IMPROVER (Involving Men with Prostate Cancer in Engaged Research): Assessing Patient Experience With Testing, Diagnosis, And Surveillance.

BACKGROUND: Our understanding of patient experiences with prostate cancer testing for diagnosis and surveillance is limited. The aim of this study was to collaborate with patients and clinicians to understand their lived experience and unmet needs around the early detection, diagnosis and monitoring (active surveillance) of prostate cancer. METHODS: Two focus groups were held with patients (n = 20) and healthcare professionals (n = 16), to identify the main challenges in prostate cancer detection, diagnosis, and monitoring. This information formed the basis of an online questionnaire for broader dissemination. RESULTS: A total of 1138 analyzable responses were obtained from people tested for prostate cancer (69% tested positive) in Europe and the US. Only 29 healthcare professionals completed the survey. Almost one-third of people reported knowing very little/nothing about prostate cancer prior to testing. Prior disease awareness was significantly higher in those who tested negative (P < .0001). Most respondents (n = 857; 75%) felt informed about the steps involved in testing. Receiving written information was a key factor; 91% of those who felt uninformed were not given any written information. Overall, most people felt "satisfied" with the typical prostate cancer tests: PSA, DRE, mpMRI, and biopsy. However, dissatisfaction for prostate biopsy (12%) was almost double that of other tests (P < .0001). Most patients understood why each test was done, and felt that their results and next steps were clearly explained to them; though PSA scored lowest in all of these fields. Apart from PSA, test satisfaction was lower when used repeatedly for surveillance, compared to once-off detection/diagnosis. CONCLUSIONS: Greater public awareness and education around prostate cancer, as well as clear and accessible written information for patients at the beginning of their cancer journey is needed. Further research is needed into alternative, less invasive tests, particularly when used repeatedly in the surveillance population.

Involving patients in healthcare research is well documented but can it work in lab-based research?

Public and Patient Involvement in research is becoming a requirement on most research funding applications; this includes both healthcare and lab-based research. Whilst case studies and practical guides have been developed and are well documented for PPI in healthcare research, there is very little guidance available for PPI in lab-based research. In this piece we discuss our experience of how we have successfully involved patients in our translational cancer research, which is focused on developing personalised treatment for high-grade serous ovarian cancer. We discuss the benefits it has made to both our research and to us as researchers. The patients involved write about their experience, what they enjoyed, and the benefits they felt. Although PPI is quite topical and is being widely discussed, there is hesitancy among researchers, especially those in lab-based research about getting started because of a lack of practical guidance about how to implement it. Here, we have shared our experience, hopefully providing a practical example of how PPI can be incorporated into a lab-based research project.

This piece is co-authored by researchers and ovarian cancer patients and presents their experience of patient involvement in a laboratory-based cancer research project focused on the personalised treatment of high-grade serous ovarian cancer. Discussions with five ovarian cancer patients about their treatment experience highlighted the fact that drugs showing equivalent clinical efficacy are not necessarily tolerated equally by individual patients. This led researchers to alter their original experimental design, by including a number of the same drug type instead of focusing on only one. The researchers also discuss the benefits it has made to both the research and to them as researchers. The patients involved write about their experience, what they enjoyed, and the benefits they felt.

Cannabidiol Inhibits the Proliferation and Invasiveness of Prostate Cancer Cells.

Prostate cancer is the fifth leading cause of cancer death in men, responsible for over 375,000 deaths in 2020. Novel therapeutic strategies are needed to improve outcomes. Cannabinoids, chemical components of the cannabis plant, are a possible solution. Preclinical evidence demonstrates that cannabinoids can modulate several cancer hallmarks of many tumor types. However, the therapeutic potential of cannabinoids in prostate cancer has not yet been fully explored. The aim of this study was to investigate the antiproliferative and anti-invasive properties of cannabidiol (CBD) in prostate cancer cells in vitro. CBD inhibited cell viability and proliferation, accompanied by reduced expression of key cell cycle proteins, specifically cyclin D3 and cyclin-dependent kinases CDK2, CDK4, and CDK1, and inhibition of AKT phosphorylation. The effects of CBD on cell viability were not blocked by cannabinoid receptor antagonists, a transient receptor potential vanilloid 1 (TRPV1) channel blocker, or an agonist of the G-protein-coupled receptor GPR55, suggesting that CBD acts independently of these targets in prostate cancer cells. Furthermore, CBD reduced the invasiveness of highly metastatic PC-3 cells and increased protein expression of E-cadherin. The ability of CBD to inhibit prostate cancer cell proliferation and invasiveness suggests that CBD may have potential as a future chemotherapeutic agent.

Unveiling the epigenomic mechanisms of acquired platinum-resistance in high-grade serous ovarian cancer.

Resistance to platinum-based chemotherapy is the major cause of death from high-grade serous ovarian cancer (HGSOC). We hypothesise that detection of specific DNA methylation changes may predict platinum resistance in HGSOC. Using a publicly available "discovery" dataset we examined epigenomic and transcriptomic alterations between primary platinum-sensitive (n = 32) and recurrent acquired drug resistant HGSOC (n = 28) and identified several genes involved in immune and chemoresistance-related pathways. Validation via high-resolution melt analysis of these findings, in cell lines and HGSOC tumours, demonstrated the most consistent changes were observed in three of the genes: APOBEC3A, NKAPL and PDCD1. Plasma samples from an independent HGSOC cohort (n = 17) were analysed using droplet digital PCR. Hypermethylation of NKAPL was detected in 46% and hypomethylation of APOBEC3A in 69% of plasma samples taken from women with relapsed HGSOC (n = 13), with no alterations identified in disease-free patients (n = 4). Following these results, and using a CRISPR-Cas9 approach, we were also able to demonstrate that in vitro NKAPL promoter demethylation increased platinum sensitivity by 15%. Overall, this study demonstrates the importance of aberrant methylation, especially of the NKAPL gene, in acquired platinum resistance in HGSOC.

Plant-derived cannabinoids as anticancer agents.

Substantial preclinical evidence demonstrates the antiproliferative, cytotoxic, and antimetastatic properties of plant-derived cannabinoids (phytocannabinoids) such as cannabidiol and tetrahydrocannabinol. The cumulative body of research into the intracellular mechanisms and phenotypic effects of these compounds supports a logical, judicious progression to large-scale phase II/III clinical trials in certain cancer types to truly assess the efficacy of phytocannabinoids as anticancer agents.

Longitudinal analysis of individual cfDNA methylome patterns in metastatic prostate cancer.

BACKGROUND: Disease progression and therapeutic resistance are hallmarks of advanced stage prostate cancer (PCa), which remains a major cause of cancer-related mortality around the world. Longitudinal studies, coupled with the use of liquid biopsies, offer a potentially new and minimally invasive platform to study the dynamics of tumour progression. Our aim was to investigate the dynamics of personal DNA methylomic profiles of metastatic PCa (mPCa) patients, during disease progression and therapy administration. RESULTS: Forty-eight plasma samples from 9 mPCa patients were collected, longitudinally, over 13-21 months. After circulating cell-free DNA (cfDNA) isolation, DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The top 5% most variable probes across time, within each individual, were utilised to study dynamic methylation patterns during disease progression and therapeutic response. Statistical testing was carried out to identify differentially methylated genes (DMGs) in cfDNA, which were subsequently validated in two independent mPCa (cfDNA and FFPE tissue) cohorts. Individual cfDNA global methylation patterns were temporally stable throughout the disease course. However, a proportion of CpG sites presented a dynamic temporal pattern that was consistent with clinical events, including different therapies, and were prominently associated with genes linked to immune response pathways. Additionally, study of the tumour fraction of cfDNA identified > 2000 DMGs with dynamic methylation patterns. CONCLUSIONS: Longitudinal assessment of cfDNA methylation in mPCa patients unveiled dynamic patterns associated with disease progression and therapy administration, thus highlighting the potential of using liquid biopsies to study PCa evolution at a methylomic level.

5-AZA-dC induces epigenetic changes associated with modified glycosylation of secreted glycoproteins and increased EMT and migration in chemo-sensitive cancer cells.

BACKGROUND: Glycosylation, one of the most fundamental post-translational modifications, is altered in cancer and is subject in part, to epigenetic regulation. As there are many epigenetic-targeted therapies currently in clinical trials for the treatment of a variety of cancers, it is important to understand the impact epi-therapeutics have on glycosylation. RESULTS: Ovarian and triple negative breast cancer cells were treated with the DNA methyltransferase inhibitor, 5-AZA-2-deoxycytidine (5-AZA-dC). Branching and sialylation were increased on secreted N-glycans from chemo-sensitive/non-metastatic cell lines following treatment with 5-AZA-dC. These changes correlated with increased mRNA expression levels in MGAT5 and ST3GAL4 transcripts in ovarian cancer cell lines. Using siRNA transient knock down of GATA2 and GATA3 transcription factors, we show that these regulate the glycosyltransferases ST3GAL4 and MGAT5, respectively. Moreover, 5-AZA-dC-treated cells displayed an increase in migration, with a greater effect seen in chemo-sensitive cell lines. Western blots showed an increase in apoptotic and senescence (p21) markers in all 5-AZA-dC-treated cells. The alterations seen in N-glycans from secreted glycoproteins in 5-AZA-dC-treated breast and ovarian cancer cells were similar to the N-glycans previously known to potentiate tumour cell survival. CONCLUSIONS: While the FDA has approved epi-therapeutics for some cancer treatments, their global effect is still not fully understood. This study gives insight into the effects that epigenetic alterations have on cancer cell glycosylation, and how this potentially impacts on the overall fate of those cells.

Development of a multivariable risk model integrating urinary cell DNA methylation and cell-free RNA data for the detection of significant prostate cancer.

BACKGROUND: Prostate cancer exhibits severe clinical heterogeneity and there is a critical need for clinically implementable tools able to precisely and noninvasively identify patients that can either be safely removed from treatment pathways or those requiring further follow up. Our objectives were to develop a multivariable risk prediction model through the integration of clinical, urine-derived cell-free messenger RNA (cf-RNA) and urine cell DNA methylation data capable of noninvasively detecting significant prostate cancer in biopsy naïve patients. METHODS: Post-digital rectal examination urine samples previously analyzed separately for both cellular methylation and cf-RNA expression within the Movember GAP1 urine biomarker cohort were selected for a fully integrated analysis (n = 207). A robust feature selection framework, based on bootstrap resampling and permutation, was utilized to find the optimal combination of clinical and urinary markers in a random forest model, deemed ExoMeth. Out-of-bag predictions from ExoMeth were used for diagnostic evaluation in men with a clinical suspicion of prostate cancer (PSA ≥ 4 ng/mL, adverse digital rectal examination, age, or lower urinary tract symptoms). RESULTS: As ExoMeth risk score (range, 0-1) increased, the likelihood of high-grade disease being detected on biopsy was significantly greater (odds ratio = 2.04 per 0.1 ExoMeth increase, 95% confidence interval [CI]: 1.78-2.35). On an initial TRUS biopsy, ExoMeth accurately predicted the presence of Gleason score ≥3 + 4, area under the receiver-operator characteristic curve (AUC) = 0.89 (95% CI: 0.84-0.93) and was additionally capable of detecting any cancer on biopsy, AUC = 0.91 (95% CI: 0.87-0.95). Application of ExoMeth provided a net benefit over current standards of care and has the potential to reduce unnecessary biopsies by 66% when a risk threshold of 0.25 is accepted. CONCLUSION: Integration of urinary biomarkers across multiple assay methods has greater diagnostic ability than either method in isolation, providing superior predictive ability of biopsy outcomes. ExoMeth represents a more holistic view of urinary biomarkers and has the potential to result in substantial changes to how patients suspected of harboring prostate cancer are diagnosed.

Evaluating liquid biopsies for methylomic profiling of prostate cancer.

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.

Novel Strategies for Cancer Treatment: Highlights from the 55th IACR Annual Conference.

While conventional cancer treatments, such as surgery, radiotherapy and chemotherapy, have been combined for decades in an effort to treat cancer patients, the emergence of novel fields of cancer research have led to a renewed interest in combining conventional treatments with more innovative approaches. The realisation that cancer progression is not exclusively due to changes in the cancer epithelial cells, but also involves changes in the tumour microenvironment, has opened new avenues for combination treatments. Here we discuss the use of combination therapies presented at the 55th Irish Association for Cancer Research (IACR) Annual Conference, highlighting examples of novel therapeutic strategies which, combined with conventional therapies, may greatly enhance not only the overall outcome for patients, but also the quality of life for cancer survivors. Among the novel treatment strategies, immune metabolism, epigenetic therapies and physical exercise are presented. In addition, novel technologies in the field of precision medicine, which will be useful to discover new therapeutics and to stratify patients for combination treatments, are also discussed.

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.

epiCaPture: A Urine DNA Methylation Test for Early Detection of Aggressive Prostate Cancer.

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.

A urine-based DNA methylation assay, ProCUrE, to identify clinically significant prostate cancer.

BACKGROUND: Prevention of unnecessary biopsies and overtreatment of indolent disease remains a challenge in the management of prostate cancer. Novel non-invasive tests that can identify clinically significant (intermediate-risk and high-risk) diseases are needed to improve risk stratification and monitoring of prostate cancer patients. Here, we investigated a panel of six DNA methylation biomarkers in urine samples collected post-digital rectal exam from patients undergoing prostate biopsy, for their utility to guide decision making for diagnostic biopsy and early detection of aggressive prostate cancer. RESULTS: We recruited 408 patients in risk categories ranging from benign to low-, intermediate-, and high-risk prostate cancer from three international cohorts. Patients were separated into 2/3 training and 1/3 validation cohorts. Methylation biomarkers were analyzed in post-digital rectal exam urinary sediment DNA by quantitative MethyLight assay and investigated for their association with any or aggressive prostate cancers. We developed a Prostate Cancer Urinary Epigenetic (ProCUrE) assay based on an optimal two-gene (HOXD3 and GSTP1) LASSO model, derived from methylation values in the training cohort, and assessed ProCUrE's diagnostic and prognostic ability for prostate cancer in both the training and validation cohorts. ProCUrE demonstrated improved prostate cancer diagnosis and identification of patients with clinically significant disease in both the training and validation cohorts. Using three different risk stratification criteria (Gleason score, D'Amico criteria, and CAPRA score), we found that the positive predictive value for ProCUrE was higher (59.4-78%) than prostate specific antigen (PSA) (38.2-72.1%) for all risk category comparisons. ProCUrE also demonstrated additive value to PSA in identifying GS ≥ 7 PCa compared to PSA alone (DeLong's test p = 0.039), as well as additive value to the PCPT risk calculator for identifying any PCa and GS ≥ 7 PCa (DeLong's test p = 0.011 and 0.022, respectively). CONCLUSIONS: ProCUrE is a promising non-invasive urinary methylation assay for the early detection and prognostication of prostate cancer. ProCUrE has the potential to supplement PSA testing to identify patients with clinically significant prostate cancer.

Integrating biomarkers across omic platforms: an approach to improve stratification of patients with indolent and aggressive prostate cancer.

Classifying indolent prostate cancer represents a significant clinical challenge. We investigated whether integrating data from different omic platforms could identify a biomarker panel with improved performance compared to individual platforms alone. DNA methylation, transcripts, protein and glycosylation biomarkers were assessed in a single cohort of patients treated by radical prostatectomy. Novel multiblock statistical data integration approaches were used to deal with missing data and modelled via stepwise multinomial logistic regression, or LASSO. After applying leave-one-out cross-validation to each model, the probabilistic predictions of disease type for each individual panel were aggregated to improve prediction accuracy using all available information for a given patient. Through assessment of three performance parameters of area under the curve (AUC) values, calibration and decision curve analysis, the study identified an integrated biomarker panel which predicts disease type with a high level of accuracy, with Multi AUC value of 0.91 (0.89, 0.94) and Ordinal C-Index (ORC) value of 0.94 (0.91, 0.96), which was significantly improved compared to the values for the clinical panel alone of 0.67 (0.62, 0.72) Multi AUC and 0.72 (0.67, 0.78) ORC. Biomarker integration across different omic platforms significantly improves prediction accuracy. We provide a novel multiplatform approach for the analysis, determination and performance assessment of novel panels which can be applied to other diseases. With further refinement and validation, this panel could form a tool to help inform appropriate treatment strategies impacting on patient outcome in early stage prostate cancer.

Assessing DNA Methylation in Cancer Stem Cells.

Many cancer-associated epigenetic signatures are also commonly observed in stem cells, just as epigenetic stem cell patterns are in cancer cells. DNA methylation is recognized as a hallmark of cancer development and progression. Herein, we describe two approaches to analyze DNA methylation, which can be applied to study or discover DNA methylation aberrations throughout the genome, as well as a more targeted investigation of regions of interest in cancer stem cells.

Epigenetics of malignant melanoma.

Patients with malignant melanoma generally have a good prognosis if the disease presents prior to metastasis. Due to progress with targeted and immunotherapies, the median survival of metastatic melanoma patients is now over 2 years. The disease is characterised by one of the highest somatic mutation rates observed amongst cancer types, with a specific mutational signature based on UV radiation damage evident. Highly prevalent mutations, such as the BRAFV600E, in the MAPK cascade indicate truncal involvement of this pathway in the earliest stage of melanoma. The molecular sub-classification of melanoma based on genetic alterations is now well established. This has paved the way for researchers in epigenetics to investigate specific pathways of known importance, and the involvement of the diverse range of epigenetic mechanisms. Herein, we review the literature to highlight that epigenetic alterations are integrally involved in this malignancy. We focus on the most current evidence around the epigenetic mechanisms: DNA methylation and demethylation including 5-hydroxy-methylcytosine; histone post-translational modifications including variant histones; chromatin remodelling complexes and in particular the polycomb-repressive complex PRC2 and its histone methyltransferase subunit EZH2; and non-coding RNAs. Each mechanism is described generally, studies involving melanoma are assessed and clinical relevance is highlighted where possible.

Analysis of urinary PSA glycosylation is not indicative of high-risk prostate cancer.

The levels of core fucosylation and α2,3-linked sialic acid in serum Prostate Specific Antigen (PSA), using the lectins Pholiota squarrosa lectin (PhoSL) and Sambucus nigra agglutinin (SNA), can discriminate between Benign Prostatic Hyperplasia (BPH) and indolent prostate cancer (PCa) from aggressive PCa. In the present work we evaluated whether these glycosylation determinants could also be altered in urinary PSA obtained after digital rectal examination (DRE) and could also be useful for diagnosis determinations. For this purpose, α2,6-sialic acid and α1,6-fucose levels of urinary PSA from 53 patients, 18 biopsy-negative and 35 PCa patients of different aggressiveness degree, were analyzed by sandwich ELLA (Enzyme Linked Lectin Assay) using PhoSL and SNA. Changes in the levels of specific glycosylation determinants, that in serum PSA samples were indicative of PCa aggressiveness, were not found in PSA from DRE urine samples. Although urine is a simpler matrix for analyzing PSA glycosylation compared to serum, an immunopurification step was necessary to specifically detect the glycans on the PSA molecule. Those specific glycosylation determinants on urinary PSA were however not useful to improve PCa diagnosis. This could be probably due to the low proportion of PSA from the tumor in urine samples, which precludes the identification of aberrantly glycosylated PSA.

Expression of the TPα and TPß isoforms of the thromboxane prostanoid receptor (TP) in prostate cancer: clinical significance and diagnostic potential.

The prostanoid thromboxane (TX)A2 plays a central role in haemostasis and is increasingly implicated in cancer progression. TXA2 signals through two T Prostanoid receptor (TP) isoforms termed TPα and TPß, with both encoded by the TBXA2R gene. Despite exhibiting several functional and regulatory differences, the role of the individual TP isoforms in neoplastic diseases is largely unknown.This study evaluated expression of the TPα and TPß isoforms in tumour microarrays of the benign prostate and different pathological (Gleason) grades of prostate cancer (PCa). Expression of TPß was significantly increased in PCa relative to benign tissue and strongly correlated with increasing Gleason grade. Furthermore, higher TPß expression was associated with increased risk of biochemical recurrence (BCR) and significantly shorter disease-free survival time in patients post-surgery. While TPα was more variably expressed than TPß in PCa, increased/high TPα expression within the tumour also trended toward increased BCR and shorter disease-free survival time. Comparative genomic CpG DNA methylation analysis revealed substantial differences in the extent of methylation of the promoter regions of the TBXA2R that specifically regulate expression of TPα and TPß, respectively, both in benign prostate and in clinically-derived tissue representative of precursor lesions and progressive stages of PCa. Collectively, TPα and TPß expression is differentially regulated both in the benign and tumourigenic prostate, and coincides with clinical pathology and altered CpG methylation of the TBXA2R gene. Analysis of TPß, or a combination of TPα/TPß, expression levels may have significant clinical potential as a diagnostic biomarker and predictor of PCa disease recurrence.

Improving multivariable prostate cancer risk assessment using the Prostate Health Index.

OBJECTIVES: To analyse the clinical utility of a prediction model incorporating both clinical information and a novel biomarker, p2PSA, in order to inform the decision for prostate biopsy in an Irish cohort of men referred for prostate cancer assessment. PATIENTS AND METHODS: Serum isolated from 250 men from three tertiary referral centres with pre-biopsy blood draws was analysed for total prostate-specific antigen (PSA), free PSA (fPSA) and p2PSA. From this, the Prostate Health Index (PHI) score was calculated (PHI = (p2PSA/fPSA)*√tPSA). The men's clinical information was used to derive their risk according to the Prostate Cancer Prevention Trial (PCPT) risk model. Two clinical prediction models were created via multivariable regression consisting of age, family history, abnormality on digital rectal examination, previous negative biopsy and either PSA or PHI score, respectively. Calibration plots, receiver-operating characteristic (ROC) curves and decision curves were generated to assess the performance of the three models. RESULTS: The PSA model and PHI model were both well calibrated in this cohort, with the PHI model showing the best correlation between predicted probabilities and actual outcome. The areas under the ROC curve for the PHI model, PSA model and PCPT model were 0.77, 0.71 and 0.69, respectively, for the prediction of prostate cancer (PCa) and 0.79, 0.72 and 0.72, respectively, for the prediction of high grade PCa. Decision-curve analysis showed a superior net benefit of the PHI model over both the PSA model and the PCPT risk model in the diagnosis of PCa and high grade PCa over the entire range of risk probabilities. CONCLUSION: A logical and standardized approach to the use of clinical risk factors can allow more accurate risk stratification of men under investigation for PCa. The measurement of p2PSA and the integration of this biomarker into a clinical prediction model can further increase the accuracy of risk stratification, helping to better inform the decision for prostate biopsy in a referral population.