Prostate Cancer Risk Stratification Research Articles

A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer.

Objective:Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH).Methods:We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy.Results:We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1–2 and 4–5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3).Conclusions:A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies.

Applications of artificial intelligence in prostate cancer imaging.

The purpose of this review was to identify the most recent lines of research focusing on the application of artificial intelligence (AI) in the diagnosis and staging of prostate cancer (PCa) with imaging. The majority of studies focused on the improvement in the interpretation of bi-parametric and multiparametric magnetic resonance imaging, and in the planning of image guided biopsy. These initial studies showed that AI methods based on convolutional neural networks could achieve a diagnostic performance close to that of radiologists. In addition, these methods could improve segmentation and reduce inter-reader variability. Methods based on both clinical and imaging findings could help in the identification of high-grade PCa and more aggressive disease, thus guiding treatment decisions. Though these initial results are promising, only few studies addressed the repeatability and reproducibility of the investigated AI tools. Further, large-scale validation studies are missing and no diagnostic phase III or higher studies proving improved outcomes regarding clinical decision making have been conducted. AI techniques have the potential to significantly improve and simplify diagnosis, risk stratification and staging of PCa. Larger studies with a focus on quality standards are needed to allow a widespread introduction of AI in clinical practice.

Identification of a novel non-invasive biological marker to overcome the shortcomings of PSA in diagnosis and risk stratification for prostate cancer: Initial prospective study of developmental endothelial locus-1 protein

This prospective study sought to clarify the developmental endothelial locus-1 (Del-1) protein as values of diagnosis and risk stratification of prostate cancer (PCa). From February 2017 to December 2019, a total 458 patients who underwent transrectal ultrasound guided prostate biopsy or surgery of benign prostatic hyperplasia agreed to research of Del-1 protein. We prospectively compared and analyzed the Del-1 protein and prostate specific antigen (PSA) in relation to the patients' demographic and clinicopathological characteristics. Mean age was 68.86±8.55 years. Mean PSA and Del-1 protein was 21.72±89.37, 0.099±0.145, respectively. Two hundred seventy-six (60.3%) patients were diagnosed as PCa. Among them, 181 patients underwent radical prostatectomy (RP). There were significant differences in Del-1 protein between benign and PCa group (0.066±0.131 vs 0.121±0.149, respectively, p<0.001). When we set the cut-off value of del-1 protein as 0.120, in patients with 3≤PSA≤8, positive predictive value and specificity of Del-1 protein (≥0.120) for predicting PCa were 88.9% (56/63) and 93.5% (101/108), respectively. Among 181 patients who underwent RP, there were significant differences in Del-1 protein according to stage (pT2 vs pT3a vs ≥pT3b) (0.113±0.078, 0.171±0.121, 0.227±0.161, respectively, p<0.001) and to Gleason score (6 (3+3) or 7 (3+4) vs 7 (4+3) or 8 (4+4) vs 9 or 10) (0.134±0.103, 0.150±0.109, 0.212±0.178, respectively, P = 0.044). Multivariate analysis showed that PSA, Del-1 protein and high Gleason score (≥9) were the independent prognostic factors for predicting higher pT stage (≥3b). Furthermore, age, PSA and Del-1 protein were independent prognostic factors for predicting significant PCa. Patients with PCa showed higher expression of Del-1 protein than benign patients. Del-1 protein increased with the stage and Gleason score of PCa. Collaboration with PSA, Del-1 protein can be a non-invasive useful marker for diagnosis and risk stratification of PCa.

Evaluation of a Multiethnic Polygenic Risk Score Model for Prostate Cancer.

Polygenic risk scores (PRSs) of common genetic variants have shown promise in prostate cancer risk stratification, but their validity across populations has yet to be confirmed. We evaluated a multiethnic PRS model based on 269 germline genetic risk variants (261 were available for analysis) using an independent population of 13 628 US men. The PRS was strongly associated with prostate cancer but not with any other disease. Comparing men in the top PRS decile with those at average risk (40%-60%), the odds ratio of prostate cancer was 3.89 (95% confidence interval = 3.24 to 4.68) for men of European ancestry and 3.81 (95% confidence interval = 1.48 to 10.19) for men of African ancestry. By age 85 years, the cumulative incidence of prostate cancer for European American men was 7.1% in the bottom decile and 54.1% in the top decile. This suggests that the PRS can be used to identify a substantial proportion of men at high risk for prostate cancer.

A novel artefacts removal technique for prostate CT-based radiomics analysis

In a previous study, we demonstrated the value of CT-based radiomics feature for prostate cancer risk stratification. Many hospitals routinely employ (Gold) fiducial markers (FM) based IGRT for prostate cancer patients. In this work, the robustness of CT-based radiomics features against the presence of FM and the associated artefacts was investigated.

Transcript analysis of commercial prostate cancer risk stratification panels in hard-to-predict grade group 2-4 prostate cancers.

Improved prognostication is needed to minimize overtreatment in grade group (GG) 2-4 prostate cancer. Our aim was to determine, at messenger RNA (mRNA) level, the performance of the genes in the commercial panels Decipher, Oncotype DX, Prolaris, and mutational panel MSK-IMPACT to predict metastasis-free and prostate cancer-specific death (PCSD) in patients with GG 2-4 prostate cancer at radical prostatectomy. The retrospective cohort consisted of GG 2-4 patients treated with radical prostatectomy (median follow-up 10.4 years). Seventy-six cases with postoperative metastasis or PCSD and 84 controls with similar clinical baseline risk, but without progression, were analyzed. Index lesion mRNA transcripts were analyzed using NanoString technology. Random forest models were trained using panel gene sets to predict clinical endpoints and area under the curve (AUC), sensitivity, specificity, Youden index, and number needed to diagnose (NND) was measured. Survival probability was assessed with Kaplan-Meier estimator. All gene sets outperformed clinical parameters and predicted metastasis-free and prostate cancer-specific survival. However, there were significant differences between the panels. In metastasis prediction, the genes in Oncotype DX had inferior performance (area under the curve [AUC] = 0.65) compared to other panels (AUC = 0.73-0.74). Decipher, MSK-IMPACT and Prolaris showed similar NND (2.83-3.12) with Oncotype DX having highest NND (4.79). In PCSD prediction, the Prolaris gene set performed worse (AUC = 0.66) than MSK-IMPACT or Decipher (AUC = 0.72). Oncotype DX performed similarly to other panels (AUC = 0.69, p > .05). Oncotype DX demonstrated lowest NND (2.79) compared to other panels (4.22-5.66). Transcript analysis of genes included in commercial panels is feasible in survival prediction of GG 2-4 patients after radical prostatectomy and may aid in clinical decision making. There were significant differences between the panels, and overall stronger predictive gene sets are needed. Prospective investigation is warranted in biopsy materials.

Common genetic and clinical risk factors: association with fatal prostate cancer in the Cohort of Swedish Men.

Background:Clinical variables—age, family history, genetics—are used for prostate cancer risk stratification. Recently, polygenic hazard scores (PHS46, PHS166) were validated as associated with age at prostate cancer diagnosis. While polygenic scores are associated with all prostate cancer (not specific for fatal cancers), PHS46 was also associated with age at prostate cancer death. We evaluated if adding PHS to clinical variables improves associations with prostate cancer death.Methods:Genotype/phenotype data were obtained from a nested case-control Cohort of Swedish Men (n=3,279; 2,163 with prostate cancer, 278 prostate cancer deaths). PHS and clinical variables (family history, alcohol intake, smoking, heart disease, hypertension, diabetes, body mass index) were tested via univariable Cox proportional hazards models for association with age at prostate cancer death. Multivariable Cox models with/without PHS were compared with log-likelihood tests.Results:Median age at last follow-up/prostate cancer death were 78.0 (IQR: 72.3–84.1) and 81.4 (75.4–86.3) years, respectively. On univariable analysis, PHS46 (HR 3.41 [95%CI 2.78–4.17]), family history (HR 1.72 [1.46–2.03]), alcohol (HR 1.74 [1.40–2.15]), diabetes (HR 0.53 [0.37–0.75]) were each associated with prostate cancer death. On multivariable analysis, PHS46 (HR 2.45 [1.99–2.97]), family history (HR 1.73 [1.48–2.03]), alcohol (HR 1.45 [1.19–1.76]), diabetes (HR 0.62 [0.42–0.90]) all remained associated with fatal disease. Including PHS46 or PHS166 improved multivariable models for fatal prostate cancer (p<10−15).Conclusions:PHS had the most robust association with fatal prostate cancer in a multivariable model with common risk factors, including family history. Adding PHS to clinical variables may improve prostate cancer risk stratification strategies.

In Vivo Imaging of Methionine Aminopeptidase II for Prostate Cancer Risk Stratification.

Prostate cancer is one of the most common malignancies worldwide, yet limited tools exist for prognostic risk stratification of the disease. Identification of new biomarkers representing intrinsic features of malignant transformation and development of prognostic imaging technologies are critical for improving treatment decisions and patient survival. In this study, we analyzed radical prostatectomy specimens from 422 patients with localized disease to define the expression pattern of methionine aminopeptidase II (MetAP2), a cytosolic metalloprotease that has been identified as a druggable target in cancer. MetAP2 was highly expressed in 54% of low-grade and 59% of high-grade cancers. Elevated levels of MetAP2 at diagnosis were associated with shorter time to recurrence. Controlled self-assembly of a synthetic small molecule enabled design of the first MetAP2-activated PET imaging tracer for monitoring MetAP2 activity in vivo. The nanoparticles assembled upon MetAP2 activation were imaged in single prostate cancer cells with post-click fluorescence labeling. The fluorine-18-labeled tracers successfully differentiated MetAP2 activity in both MetAP2-knockdown and inhibitor-treated human prostate cancer xenografts by micro-PET/CT scanning. This highly sensitive imaging technology may provide a new tool for noninvasive early-risk stratification of prostate cancer and monitoring the therapeutic effect of MetAP2 inhibitors as anticancer drugs. SIGNIFICANCE: This study defines MetAP2 as an early-risk stratifier for molecular imaging of aggressive prostate cancer and describes a MetAP2-activated self-assembly small-molecule PET tracer for imaging MetAP2 activity in vivo.

Treatment decisions and outcomes for NCCN favorable intermediate-risk prostate cancer patients after receiving the 17-gene genomic prostate cancer score result.

218 Background: Molecular assays are used to improve risk stratification in prostate cancer. This study determined how the 17-gene Genomic Prostate Score (GPS) assay guides treatment decisions in patients with NCCN favorable intermediate-risk prostate cancer. Methods: This retrospective study included 324 patients from 7 urology practices in the United States. All patients had NCCN favorable intermediate-risk prostate cancer, defined as &lt;50% positive biopsy cores and only one of the following risk factors: grade group 2 (Gleason Score 3+4), clinical stage T2b-T2c, or PSA 10-20 ng/mL. All patients also had a GPS assay report dated May 2017 to April 2019. The GPS assay allows risk stratification into post-GPS very low-, low-, favorable intermediate-, unfavorable intermediate-, and high-risk groups, with higher GPS scores representing increased risk. Data were collected from patients' charts/electronic health records. The proportion of patients who selected active surveillance (AS) over immediate definitive treatment and AS, monotherapy, or multimodal therapy was calculated with 95% confidence intervals (CI) using the Clopper-Pearson method. Results: Patients comprised 79% with Gleason Score 3+4, 19% with PSA 10-20 ng/mL, and 2% with clinical stage T2b; median GPS result was 26. Post-GPS risk groups were 0%, 16%, 11%, 57%, and 16% very low-, low-, favorable intermediate-, unfavorable intermediate-, and high-risk groups respectively. Overall, 31% (95% CI 26%, 36%) of patients selected active surveillance (AS), with rate declining as post-GPS risk increased: 57% (95% CI 42%, 71%) selected AS in the post-GPS low-risk, 51% (95% CI 34%, 69%) in the post-GPS favorable intermediate-risk, 26% (95% CI 20%, 33%) in the post-GPS unfavorable intermediate-risk, and 6% (95% CI 1%, 16%) in the post-GPS high-risk group. Post-GPS unfavorable intermediate/high risk-patients were more likely to receive monotherapy than low/favorable intermediate-risk patients (high, 72%; unfavorable intermediate, 64%; favorable intermediate, 37%; and low, 37%); high-risk patients were more likely to receive multimodal therapy (high, 23%; unfavorable intermediate, 10%; favorable intermediate, 11%; and low, 6%). Median follow-up time was 18 months, and one prostate cancer-related metastasis and 2 deaths (neither prostate cancer-related) were reported. Complications (erectile dysfunction, urinary/bowel incontinence) were more common in treated than AS patients. AS persistence was 91% (95% CI 82%, 95%) at 12 months; patients discontinued AS due to disease progression (61%) or patient preference/unknown reasons (39%). Conclusions: The GPS result is associated with selection of AS and treatment intensity in this first examination of genomic classifiers in a cohort of prostate cancer patients with NCCN favorable intermediate-risk.

Common genetic and clinical risk factors: Association with fatal prostate cancer in the Cohort of Swedish Men.

65 Background: Clinical variables (age, family history, and genetics) are commonly used for prostate cancer risk stratification. Recently, polygenic hazard scores (PHS46, PHS166) were validated as associated with age at prostate cancer diagnosis. While polygenic scores, including PHS, are associated with all prostate cancer and are not specific for fatal cancers, PHS46 was also associated with age at prostate cancer death. We evaluated if adding PHS to available clinical variables improves associations with prostate cancer death. Methods: Genotype and phenotype data were obtained from a nested case-control subset (n=3,279; 2,163 were diagnosed with prostate cancer, 278 died of prostate cancer) of the longitudinal, population-based Cohort of Swedish Men. PHS and clinical variables (family history, alcohol intake, smoking, heart disease, hypertension, diabetes history, and body mass index) were independently tested via univariable Cox proportional hazards models for association with age at prostate cancer death. Multivariable Cox models were constructed with clinical variables and PHS. Log-likelihood tests compared models. Results: Median age at last follow-up and at prostate cancer death were 78.0 (IQR: 72.3-84.1) and 81.4 (75.4-86.3) years, respectively. On univariable analysis, PHS46 (HR 3.41 [95% CI 2.78-4.17]), family history (HR 1.72 [1.46-2.03]), alcohol intake (HR 1.74 [1.40-2.15]), and diabetes (HR 0.53 [0.37-0.75]) were each associated with prostate cancer death. A multivariable clinical model including PHS46 improved associations for fatal disease ( p&lt;10−15). On multivariable analysis, PHS46 (HR 2.45 [1.99-2.97]), family history (HR 1.73 [1.48-2.03]), alcohol intake (HR 1.45 [1.19-1.76]), and diabetes (HR 0.62 [0.42-0.90]) all remained associated with prostate cancer death. Similar results were found using the newer PHS166. Conclusions: PHS had the most robust association with fatal prostate cancer in a multivariable model with common clinical risk factors, including family history. Adding PHS to clinical variables may improve individualized prostate cancer risk stratification strategies.

Radical prostate radiotherapy and the use of androgen deprivation in the era of risk stratification: Does real-world practice follow the evidence?

216 Background: Prostate cancer is a common condition with varied pathologies based on stage, grade and presenting PSA allowing non-metastatic cases to be risk stratified at presentation. There is an evidence base for the use of Androgen Deprivation Therapy (ADT) combined with radical radiation showing a survival benefit but with an increase in patient morbidity. Prostate cancer risk stratification can be used to guide ADT therapy duration to reduce toxicity but it is unknown how closely these guidelines are followed internationally. Methods: A cross sectional survey collecting data on 15,255 patients with prostate cancer was conducted across 5 European countries and Japan. Data was interrogated to provide real-world evidence for ADT prescribing in combination with radical radiotherapy treatment and compared against the available evidence base and international best practice guidelines. Results: 3,393 patients were included in data analysis; 53% were high risk, 35% intermediate, and 12% low risk cases. 48% of patients were ages 71-80yrs with 10% being aged over 80. Data, including proposed length of hormone treatment was available for 2,832 patients. Concordance to the evidence base was good for high- and low-risk prostate cancer patients (64% and 96% respectively) but there was more disparity in the intermediate risk group with a concordance rate of only 28%. Conclusions: The data was robust enough to be interrogated and produce meaningful results. Concordance to the evidence base was high in both high and low risk disease although there was a tendency towards over-treatment in both these groups in some of the countries included. There was significant disparity in the intermediate risk group with evidence of both over- and potential under-treatment across all countries. Any potential over treatment with ADT needs to take account of the known evidence base and the potential for bone and metabolic toxicities. The data suggests that guidelines offering greater clarity on the role of ADT in intermediate risk prostate cancer may be beneficial.

Investigation of a 22-gene genomic classifier (GC) for risk stratification and molecular subtyping in an Asian prostate cancer (PCa) cohort.

249 Background: A 22-gene GC has been proposed to refine risk stratification of localized PCa by conventional NCCN criteria, and this may potentially influence treatment recommendations. Nonetheless, majority of studies looking at the utility of GC were conducted in White and non-White men from Western cohorts. We therefore investigated the association of GC with NCCN risk groups (RG) in an Asian PCa cohort. Additionally, we examined for inter-racial differences in molecular subtyping between Asian and White/non-White PCa. Methods: GC (Decipher Biosciences Inc., CA) was performed on diagnostic biopsies of men who were treated with radiotherapy +/- hormonal therapy at a single institution (N = 75). ISUP Gleason’s grade (GG) and tumor cellularity were reviewed by an expert GU pathologist. RNA was extracted from 2 x 2.0-mm tumor cores using Qiagen AllPrep DNA/RNA FFPE Kit (Qiagen, Germany) and gene expression was performed on Affymetrix Human Exon 1.0 ST Array (ThermoFischer, CA). PAM50 molecular subtyping was derived using the DecipherGRID database. Results: We profiled 80 tumors from 75 patients, comprising of 18 (24.0%), 9 (12.0%), 21 (28.0%), and 19 (25.3%) NCCN low-/favorable intermediate-, unfavorable intermediate-, high- and very high-RG, respectively; of note, 8 (10.7%) patients had regional/metastatic disease at diagnosis. Using the GC, 27 (33.8%), 14 (17.5%) and 39 (48.8%) were classified as low- (&lt;0.45), intermediate- (0.45-0.6) and high-RG, respectively (&gt;0.6). When stratified using a three-tier clinico-genomic (CG) classification system (Spratt et al. 2017), 6 of 21 (28.6%) NCCN-defined high-risk and 4 of 19 (21.1%) very high-risk patients were downgraded to CG-defined intermediate-/low-risk, while 2 of 27 (7.4%) NCCN low-/intermediate-risk patients were in fact upgraded to CG high-risk. Next, we interrogated the PAM50 basal-luminal signature in our cohort. Interestingly, when matched to White (N = 5762) and non-White (N = 155) for NCCN RG, ISUP GG and age, we observed a high proportion of basal subtype (62.7%) in Asians, which contrasted the prevalence observed in White (16.7%) and non-White (15.9%) North American patients (Chi-sq P &lt;0.001). Conclusions: Here, we demonstrated the utility of the 22-gene GC for refining the NCCN risk stratification in a largest Asian PCa dataset to-date. An unexpectedly high proportion of PAM50 basal-subtype was observed, suggesting race-specific differences of the tumor transcriptome.

Emerging role of multiparametric magnetic resonance imaging in identifying clinically relevant localized prostate cancer.

To explore the recent advances and utility of multiparametric magnetic resonance imaging (mpMRI) in the diagnosis and risk-stratification of prostate cancer. Low-risk, clinically insignificant prostate cancer has a decreased risk of morbidity or mortality. Meanwhile, patients with intermediate and high-risk prostate cancer may significantly benefit from interventions like radiation or surgery. To appropriately risk stratify these patients, MRI has emerged as the imaging modality in the last decade to assist in defining prostate cancer significance, location, and biologic aggressiveness. Traditional 12-core transrectal ultrasound-guided biopsy is associated with over-detection, and ultimately over-treatment of clinically insignificant disease, and the under-detection of clinically significant disease. Biopsy accuracy is improved with MRI-guided targeted biopsy and with the use of standardized risk stratification imaging score systems. Cancer detection accuracy is further improved with combined biopsy techniques that include both systematic and MRI-targeted biopsy that aid in detection of MRI-invisible lesions. mpMRI is an area of expanding innovation that continues to refine the diagnostic accuracy of prostate biopsies. As mpMRI-targeted biopsy in prostate cancer becomes more commonplace, advances like artificial intelligence and less invasive dynamic metabolic imaging will continue to improve the utility of MRI.

Cáncer de próstata

Prostate cancer is the leading malignancy in men and the second most deadly. Age is the main risk factor for the development of the disease, with an average age at diagnosis of 66 years and an increase in incidence from the age of 55. The prognosis of prostate cancer depends on the stage at diagnosis, with localised disease occurring in up to 80% of cases. However, up to 20%-30% of patients will have recurrent disease. The determining factors for staging and risk stratification in prostate cancer are the extent of disease, Gleason grade and PSA levels. PSA level is also the main screening tool. Tumours confined to the prostate gland are usually treated by radical surgical and radiotherapy-based techniques, always requiring a multidisciplinary approach. Treatment in advanced stages is based in androgen deprivation therapies with androgen-receptor signalling inhibitors abiraterone and enzalutamide, as well as treatment with docetaxel, cabazitaxel and radium-223.

Chromatin conformation changes in peripheral blood can detect prostate cancer and stratify disease risk groups

BackgroundCurrent diagnostic blood tests for prostate cancer (PCa) are unreliable for the early stage disease, resulting in numerous unnecessary prostate biopsies in men with benign disease and false reassurance of negative biopsies in men with PCa. Predicting the risk of PCa is pivotal for making an informed decision on treatment options as the 5-year survival rate in the low-risk group is more than 95% and most men would benefit from surveillance rather than active treatment. Three-dimensional genome architecture and chromosome structures undergo early changes during tumourigenesis both in tumour and in circulating cells and can serve as a disease biomarker.MethodsIn this prospective study we screened whole blood of newly diagnosed, treatment naïve PCa patients (n = 140) and cancer-free controls (n = 96) for the presence of 14,241 chromosomal loops in the loci of 425 genes.ResultsWe have detected specific chromosome conformation changes in the loci of ETS1, MAP3K14, SLC22A3 and CASP2 genes in peripheral blood from PCa patients yielding PCa detection with 80% sensitivity and 80% specificity. Further analysis between PCa risk groups yielded prognostic validation sets consisting of HSD3B2, VEGFC, APAF1, BMP6, ERG, MSR1, MUC1, ACAT1 and DAPK1 genes that achieved 80% sensitivity and 93% specificity stratifying high-risk category 3 vs low risk category 1 and 84% sensitivity and 89% specificity stratifying high risk category 3 vs intermediate risk category 2 disease.ConclusionsOur results demonstrate specific chromosome conformations in the blood of PCa patients that allow PCa diagnosis and risk stratification with high sensitivity and specificity.

Systemic Coagulation Markers Especially Fibrinogen Are Closely Associated with the Aggressiveness of Prostate Cancer in Patients Who Underwent Transrectal Ultrasound-Guided Prostate Biopsy.

Objective It has been well elucidated that multiple types of cancers are at high risk of thrombosis. Several studies have indicated the prognostic value of fibrinogen (Fib) and D-dimer (DD) in prostate cancer (PCa). However, it remains unclear regarding the association of the comprehensive coagulation markers with the clinicopathological features of PCa. Methods A total of 423 pathologically diagnosed patients with PCa were consecutively collected and stratified as low-intermediate-risk or high-risk groups. The association of coagulation parameters including Fib, DD, prothrombin (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and antithrombin III (AT-III) with clinicopathological features was determined by univariate and multivariate logistic regression analyses. Results The levels of Fib, DD, and PT were significantly higher in the high-risk group (p < 0.001, p < 0.001, and p = 0.043, resp.), while APTT, TT, and AT-III were similar between two groups (p > 0.05, all). Univariate logistic regression analysis demonstrated that Fib, DD, and PT were all positively correlated with high-risk PCa (OR = 2.041, p < 0.001; OR = 1.003, p < 0.001; OR = 1.247, p = 0.044). Nonetheless, after adjusting for PSA, grade, and stage, Fib (T3 vs. T1, OR = 15.202, 95% CI: 1.725-133.959, p = 0.014) but not DD or PT was the unique independent factor associated with high-risk PCa in the multivariate regression analysis. Conclusions Our study firstly revealed that Fib but other coagulation markers was independently associated with the severity of PCa, suggesting Fib might be useful in PCa risk stratification beyond PSA, stage, and grade.

Role of MRI for the detection of prostate cancer.

The use of multiparametric MRI has been hastened under expanding, novel indications for its use in the diagnostic and management pathway of men with prostate cancer. This has helped drive a large body of the literature describing its evolving role over the last decade. Despite this, prostate cancer remains the only solid organ malignancy routinely diagnosed with random sampling. Herein, we summarize the components of multiparametric MRI and interpretation, and present a critical review of the current literature supporting is use in prostate cancer detection, risk stratification, and management.

Serum Levels of Prostate Specific Antigen Parameters among Male Patients with Lepromatous Leprosy in Edo State, Nigeria

Aim: This study is aimed at determining the total PSA (tPSA), free PSA (fPSA) concentrations and free to total PSA ratio (f/tPSA) and their utility in prostate cancer (PCa) risk stratification among male lepromatous leprosy patients in Edo state, Nigeria. Methods: Forty participants and thirty controls participated in this study. A structured questionnaire was administered to each participant to elicit details such as their personal data, age, sex, residence, medications, alcohol consumption, smoking habit, length of time of diagnosis, sexual activities, as well as the history of any other underlying diseases. Blood samples were collected from the participants. Total and free PSA concentrations in the samples were measured using ELISA method. Results: Significantly (p = 0.042) higher serum fPSA among the leprosy patients (0.22 ± 0.12 ng/ml) compared with the healthy controls (0.17 ± 0.09 ng/ml). There were no significant (p = 0.055) difference in the mean tPSA between the leprosy patients (2.69 ± 2.25 ng/ml) compared with the control (1.95 ± 0.69 ng/ml). Similarly, no significant (p = 0.548) difference was observed in PSA ratio between the control (0.08 ± 0.04) and the leprosy patients (0.09 ± 0.03). Conclusion: Our study indicated no significant differences in tPSA and f/tPSA between the leprosy patients and their healthy control. Elevated tPSA as well as f/tPSA levels that fell within the high risk zones of PCa were more prevalent among patients aged ≥ 70 years, not married, who rarely had sexual intercourse and those with longer disease duration.

Pelvic lymph node dissection using indocyanine green fluorescence lymphangiography in robotic assisted radical prostatectomy for non-lymph node or distant metastasis prostate cancer patients

Purpose: The utility of indocyanine green dye (ICG) has evolved significantly to the robotic operations including Robotic Assisted Radical Prostatectomy (RARP). The technology can help the identification of sentinel lymphatic drainage in lymphadenectomy for the majority of prostate cancer (PCa) patients. We describe the potential indications of ICG for lymphadenectomy assistant in PCa patients without lymph node or distant metastasis. Materials and Methods: We prospectively analyzed PCa patients without lymph node or distant metastasis with clinical pathological stage T1c to T3a received RARP from November 2019 to May 2020. The clinical data and pathological data, including Gleason score, tumor volume, pathological stage, and surgical findings, were described. All lymph nodes were divided into ICG positive or negative. All patients were divided into low, moderate, and high risk according to the European Association of Urology PCa risk stratification. Results: Cystoscope-guided intraprostatic injection was performed successively in 34 localized PCa patients in this study. The mean age was 66.1 ± 7.8 years old. The patients' number of high, moderate, and low risk was 18, 10, 6. A total of 447 lymph nodes were identified. Two hundred and sixty-two lymph nodes were ICG positive and 181 lymph nodes were ICG negative. ICG positive rate higher in high risk patients 158/259 (61.0%) compare to intermediate/low risk patients 104/188 (55.3%). There was no statistic significant result, but lymph node could be identified in all ICG-positive tissues. There were 12 patients revealed higher Gleason grade group after RARP and two patients revealed lower Gleason grade group after RARP. There were 18 patients showed upgrade stage after RARP and 4 patients showed down stage after RARP. Conclusion: Cystoscope-guided intraprostatic ICG injection with fluorescence lymphangiography can help identify pelvic lymph nodes in RARP for PCa patients without lymph node or distant metastasis.

Establishing a Urine-Based Biomarker Assay for Prostate Cancer Risk Stratification

One of the major features of prostate cancer (PCa) is its heterogeneity, which often leads to uncertainty in cancer diagnostics and unnecessary biopsies as well as overtreatment of the disease. Novel non-invasive tests using multiple biomarkers that can identify clinically high-risk cancer patients for immediate treatment and monitor patients with low-risk cancer for active surveillance are urgently needed to improve treatment decision and cancer management. In this study, we identified 14 promising biomarkers associated with PCa and tested the performance of these biomarkers on tissue specimens and pre-biopsy urinary sediments. These biomarkers showed differential gene expression in higher- and lower-risk PCa. The 14-Gene Panel urine test (PMP22, GOLM1, LMTK2, EZH2, GSTP1, PCA3, VEGFA, CST3, PTEN, PIP5K1A, CDK1, TMPRSS2, ANXA3, and CCND1) was assessed in two independent prospective and retrospective urine study cohorts and showed high diagnostic accuracy to identify higher-risk PCa patients with the need for treatment and lower-risk patients for surveillance. The AUC was 0.897 (95% CI 0.939–0.855) in the prospective cohort (n = 202), and AUC was 0.899 (95% CI 0.964–0.834) in the retrospective cohort (n = 97). In contrast, serum PSA and Gleason score had much lower accuracy in the same 202 patient cohorts [AUC was 0.821 (95% CI 0.879–0.763) for PSA and 0.860 (95% CI 0.910–0.810) for Gleason score]. In addition, the 14-Gene Panel was more accurate at risk stratification in a subgroup of patients with Gleason scores 6 and 7 in the prospective cohort (n = 132) with AUC of 0.923 (95% CI 0.968–0.878) than PSA [AUC of 0.773 (95% CI 0.852–0.794)] and Gleason score [AUC of 0.776 (95% CI 0.854–0.698)]. Furthermore, the 14-Gene Panel was found to be able to accurately distinguish PCa from benign prostate with AUC of 0.854 (95% CI 0.892–0.816) in a prospective urine study cohort (n = 393), while PSA had lower accuracy with AUC of 0.652 (95% CI 0.706–0.598). Taken together, the 14-Gene Panel urine test represents a promising non-invasive tool for detection of higher-risk PCa to aid treatment decision and lower-risk PCa for active surveillance.