Prostate-Specific Antigen (PSA) based screening of prostate cancer (PCa) needs refinement. The aim of this study was the identification of urinary biomarkers to predict the Prostate Imaging-Reporting and Data System (PI-RADS) score and the presence of PCa prior to prostate biopsy. Urine samples from patients with elevated PSA were collected prior to prostate biopsy (cohort = 99). The re-analysis of mass spectrometry data from 45 samples was performed to identify urinary biomarkers to predict the PI-RADS score and the presence of PCa. The most promising candidates, i.e. SPARC-like protein 1 (SPARCL1), Lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1), Alpha-1-microglobulin/bikunin precursor (AMBP), keratin 13 (KRT13), cluster of differentiation 99 (CD99) and hornerin (HRNR), were quantified by ELISA and validated in an independent cohort of 54 samples. Various biomarker combinations showed the ability to predict the PI-RADS score (AUC = 0.79). In combination with the PI-RADS score, the biomarkers improve the detection of prostate carcinoma-free men (AUC = 0.89) and of those with clinically significant PCa (AUC = 0.93). We have uncovered the potential of urinary biomarkers for a test that allows a more stringent prioritization of mpMRI use and improves the decision criteria for prostate biopsy, minimizing patient burden by decreasing the number of unnecessary prostate biopsies.

An overview of the role of glycosylation in prostate cancer (PCa) development and progression is presented, focusing on recent advancements in defining the N-glycome through glycomic profiling and glycoproteomic methodologies. Glycosylation is a common post-translational modification typified by oligosaccharides attached N-linked to asparagine or O-linked to serine or threonine on carrier proteins. These attached sugars have crucial roles in protein folding and cellular recognition processes, such that altered glycosylation is a hallmark of cancer pathogenesis and progression. In the past decade, advancements in N-glycan profiling workflows using Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) technology have been applied to define the spatial distribution of glycans in PCa tissues. Multiple studies applying N-glycan MALDI-MSI to pathology-defined PCa tissues have identified significant alterations in N-glycan profiles associated with PCa progression. N-glycan compositions progressively increase in number, and structural complexity due to increased fucosylation and sialylation. Additionally, significant progress has been made in defining the glycan and glycopeptide compositions of prostatic-derived glycoproteins like prostate-specific antigen in tissues and biofluids. The glycosyltransferases involved in these changes are potential drug targets for PCa, and new approaches in this area are summarized. These advancements will be discussed in the context of the further development of clinical diagnostics and therapeutics targeting glycans and glycoproteins associated with PCa progression. Integration of large scale spatial glycomic data for PCa with other spatial-omic methodologies is now feasible at the tissue and single-cell levels.

UNASSIGNED: The aim of our study was to investigate whether repeat prostate-specific antigen (PSA) testing as currently recommended improves risk stratification for men undergoing magnetic resonance imaging (MRI) and targeted biopsy for suspected prostate cancer (PCa).
UNASSIGNED: Consecutive men undergoing MRI and prostate biopsy who had at least two PSA tests before prostate biopsy were retrospectively registered and assigned to a development cohort (n = 427) or a validation (n = 174) cohort. Change in PSA level was assessed as a predictor of clinically significant PCa (csPCa; Gleason score ≥3 + 4, grade group ≥2) by multivariable logistic regression analysis. We developed a multivariable prediction model (MRI-RC) and a dichotomous biopsy decision strategy incorporating the PSA change. The performance of the MRI-RC model and dichotomous decision strategy was assessed in the validation cohort and compared to prediction models and decision strategies not including PSA change in terms of discriminative ability and decision curve analysis.
UNASSIGNED: Men who had a decrease on repeat PSA testing had significantly lower risk of csPCa than men without a decrease (odds ratio [OR] 0.3, 95% confidence interval [CI] 0.16-0.54; p < 0.001). Men with an increased repeat PSA had a significantly higher risk of csPCa than men without an increase (OR 2.97, 95% CI 1.62-5.45; p < 0.001). Risk stratification using both the MRI-RC model and the dichotomous decision strategy was improved by incorporating change in PSA as a parameter.
UNASSIGNED: Repeat PSA testing gives predictive information regarding men undergoing MRI and targeted prostate biopsy. Inclusion of PSA change as a parameter in an MRI-RC model and a dichotomous biopsy decision strategy improves their predictive performance and clinical utility without requiring additional investigations.
UNASSIGNED: For men with a suspicion of prostate cancer, repeat PSA (prostate-specific antigen) testing after an MRI (magnetic resonance imaging) scan can help in identifying patients who can safely avoid prostate biopsy.

BACKGROUND: Many people struggle with the choice in a series of processes, from prostate cancer (PCa) diagnosis to treatment. We investigated the degree of regret after the prostate biopsy (PBx) and relevant factors in patients recommended for biopsy for suspected PCa.
METHODS: From 06/2020 to 05/2022, 198 people who performed PBx at three institutions were enrolled and analyzed through a questionnaire before and after biopsy. Before the biopsy, a questionnaire was conducted to evaluate the sociodemographic information, anxiety scale, and health literacy, and after PBx, another questionnaire was conducted to evaluate the decision regret scale. For patients diagnosed as PCa after biopsy, a questionnaire was conducted when additional tests were performed at PCa staging work-up.
RESULTS: 190 patients answered the questionnaire before and after PBx. The mean age was 66.2 ± 7.8 years. Overall, 5.5% of men regretted biopsy, but there was no significant difference between groups according to the PCa presence. Multivariate analysis, to identify predictors for regret, revealed that the case when physicians did not properly explain what the prostate-specific antigen (PSA) test was like and what PSA elevation means (OR 20.57, [95% CI 2.45-172.70], p = 0.005), low media literacy (OR 10.01, [95% CI 1.09-92.29], p = 0.042), and when nobody to rely on (OR 8.49, [95% CI 1.66-43.34], p = 0.010) were significantly related.
CONCLUSIONS: Overall regret related to PBx was low. Decision regret was more significantly related to media literacy rather than to educational level. For patients with relatively low media literacy and fewer people to rely on in case of serious diseases, more careful attention and counseling on PBx, including a well-informed explanation on PSA test, is helpful.

OBJECTIVE: To develop a deep learning (DL) zonal segmentation model of prostate MR from T2-weighted images and evaluate TZ-PSAD for prediction of the presence of csPCa (Gleason score of 7 or higher) compared to PSAD.
METHODS: 1020 patients with a prostate MRI were randomly selected to develop a DL zonal segmentation model. Test dataset included 20 cases in which 2 radiologists manually segmented both the peripheral zone (PZ) and TZ. Pair-wise Dice index was calculated for each zone. For the prediction of csPCa using PSAD and TZ-PSAD, we used 3461 consecutive MRI exams performed in patients without a history of prostate cancer, with pathological confirmation and available PSA values, but not used in the development of the segmentation model as internal test set and 1460 MRI exams from PI-CAI challenge as external test set. PSAD and TZ-PSAD were calculated from the segmentation model output. The area under the receiver operating curve (AUC) was compared between PSAD and TZ-PSAD using univariate and multivariate analysis (adjusts age) with the DeLong test.
RESULTS: Dice scores of the model against two radiologists were 0.87/0.87 and 0.74/0.72 for TZ and PZ, while those between the two radiologists were 0.88 for TZ and 0.75 for PZ. For the prediction of csPCa, the AUCs of TZPSAD were significantly higher than those of PSAD in both internal test set (univariate analysis, 0.75 vs. 0.73, p < 0.001; multivariate analysis, 0.80 vs. 0.78, p < 0.001) and external test set (univariate analysis, 0.76 vs. 0.74, p < 0.001; multivariate analysis, 0.77 vs. 0.75, p < 0.001 in external test set).
CONCLUSIONS: DL model-derived zonal segmentation facilitates the practical measurement of TZ-PSAD and shows it to be a slightly better predictor of csPCa compared to the conventional PSAD. Use of TZ-PSAD may increase the sensitivity of detecting csPCa by 2-5% for a commonly used specificity level.

Prostate cancer remains one of the most frequently diagnosed cancers among men in the world today. Since its introduction in 1987 and FDA approval in 1994, prostate specific antigen (PSA) has reduced prostate cancer specific mortality considerably. However, the positive and negative predictive value of PSA is less than ideal and can lead to the over-detection of clinically insignificant prostate cancer. In the search for better screening measures to identify this cohort, liquid biomarkers for prostate cancer have emerged. In this review we will explore the commonly used urine and blood based prostate cancer liquid biomarkers. We detail the mechanism of each test and the validation studies that underscore their efficacy. Additionally, we will examine each test\'s effect on shared decision making as well as their cost efficacy in clinical practice.

UNASSIGNED: To investigate the practical value of the transrectal two-dimensional shear-wave elastography (SWE) in benign prostatic hyperplasia (BPH).
UNASSIGNED: Consecutive male participants with and without BPH constituted the BPH and control group respectively were enrolled prospectively between March and December 2022. Transrectal conventional ultrasound and SWE examinations for the prostate were performed on these participants. Data of quantitative stiffness of the transitional zone (TZ) and peripheral zone (PZ) of prostate, volume of prostate (VP) and volume of TZ (VTZ) and prostate specific androgen (PSA), etc., were collected. Linear regression analyses were used to investigate the associations between quantitative stiffness data and other clinical parameters.
UNASSIGNED: There were 200 participants evaluated, including 100 healthy participants and 100 BPH patients. For every one-year increment in age, it was correlated with 0.50 kPa increasement of TZ stiffness. VP and VTZ were correlated with TZ stiffness. Higher TZ stiffness was associated with higher free prostate specific antigen (PSA) and total PSA.
UNASSIGNED: The prostate is stiffer and larger in BPH group compared to control group. Quantitative stiffness of the TZ was related with age, VP, VTZ and PSA.

Objective: Due to inconsistent results in earlier investigations regarding the relationship between vitamin D and prostate-specific antigen (PSA), this study was conducted to gain a deeper understanding of the association between vitamin D and PSA. Methods: A total of 7174 male samples with 25(OH)D, PSA, and other variables were obtained from the National Health and Nutrition Examination Survey (NHANES) database. Three models, created through stepwise logistic regression, were employed to examine the dose-response association between PSA and 25(OH)D. Subsequently, restricted cubic spline analysis (RCS) was used to explore the nonlinear association between 25(OH)D and PSA. The study also compared the performance of four machine learning models in predicting PSA levels. Results: The dose-response relationship indicated a negative impact of high 25(OH)D levels on PSA (p for trend 0.05). The odds ratio (OR) of Q4 (7.73 with 95% CI (0.26, 15.76)) was significantly higher than Q1 (6.23 with 95% CI (0.24, 12.57)). OR values in Q2 and Q3 were less than 1 (Q2= 0.57 with 95% CI (-6.37, 8.04) and Q3= 0.26 with 95% CI (-5.94, 6.86)), suggesting a potential protective effect of 25(OH)D on PSA. RCS analysis revealed a U-shaped relationship between blood 25(OH)D levels and PSA, with serum 25(OH)D in the range of 20-134 ng/ml showing a potential decrease in PSA levels. Above this range, an increase in 25(OH)D might elevate PSA levels. Age (2.67 with 95% CI 2.24 to 3.1) and BMI (17.52 with 95% CI 7.65 to 26.32), along with the OR of obesity (10.36 with 95% CI 0.68 to 20.18), were identified as potential PSA risk factors. Among the machine learning models, the random forest algorithm performed the best in predicting PSA levels. Conclusion: This study revealed a U-shaped relationship between 25(OH)D and PSA, with PSA potentially declining when 25(OH)D is between 20 and 134 ng/mL and possibly rising above this range. The random forest method proved effective in both predicting PSA levels and guiding vitamin D dosage.

Serum carbohydrate antigen 19-9 (CA19-9) is used for recurrence surveillance in patients with resected pancreatic ductal adenocarcinoma (PDAC). This report describes the association of increasing CA19-9 in a male PDAC survivor with presence of prostatic hyperplasia. Unexplained elevation of CA19-9 in male PDAC survivors might be attributable to benign prostatic conditions.

The accurate and sensitive detection of prostate specific antigen (PSA) is vital for the early diagnosis and treatment of prostate cancer. To this end, an unlabeled fluorescent aptasensor was constructed by using a novel Compound B {1,1\'-(1,4-phenylene) bis(3-ethyl-1H-imidazol-3-ium) iodide} with aggregation-induced emission (AIE) activity as a fluorescence signal and NH2-Fe3O4 particle as an adsorption platform. Compound B could combine with prostate specific antigen aptamers (PSA-Apt) to form a PSA-Apt/B complex, which further generated the AIE effect. Then, PSA was added to the PSA-Apt/B solution. PSA combined with PSA-Apt/B to form the PSA-Apt/B/PSA complex. Next, NH2-Fe3O4 magnetic particles were added to the solution. Given that PSA-Apt/B/PSA would no longer combine with NH2-Fe3O4 magnetic particles, the PSA-Apt/B/PSA complex remained in the supernate after magnet separation, and the supernate showed strong fluorescence (I). When no PSA was added to the PSA-Apt/B solution, PSA-Apt/B could combine with NH2-Fe3O4 magnetic particles and would be sucked into the bottom of the test tube by magnet, and the supernate would show weak fluorescence (I0). Result showed that the difference between the above-mentioned two fluorescence values (∆I = I - I0) had an excellent linear relationship with the PSA concentration within the concentration range of 0.01-10 ng/mL, and its limit of detection was 3 pg/mL (S/N = 3). In addition, the sensor has high accuracy and can be directly used to test PSA in actual serum samples.