METHODS: We used three single nucleotide polymorphisms (SNPs) (rs8176746, rs505922, and rs8176704) to determine ABO genotype in 2,774 aggressive prostate cancer cases and 4,443 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). Unconditional logistic regression was used to calculate age and study-adjusted odds ratios and 95% confidence intervals for the association between blood type, genotype, and risk of aggressive prostate cancer (Gleason score ≥8 or locally advanced/metastatic disease (stage T3/T4/N1/M1).

RESULTS: We found no association between ABO blood type and risk of aggressive prostate cancer (Type A: OR = 0.97, 95%CI = 0.87-1.08; Type B: OR = 0.92, 95%CI =n0.77-1.09; Type AB: OR = 1.25, 95%CI = 0.98-1.59, compared to Type O, respectively). Similarly, there was no association between "dose" of A or B alleles and aggressive prostate cancer risk.

METHODOLOGY: We categorise tissue images based on the texture of individual tissue components via the construction of a single classifier and also construct an ensemble learning model by merging the values obtained by each classifier. Another issue that arises is overfitting due to the high-dimensional texture of individual tissue components. We propose a new FS method, SVM-RFE(AC), that integrates a Support Vector Machine-Recursive Feature Elimination (SVM-RFE) embedded procedure with an absolute cosine (AC) filter method to prevent redundancy in the selected features of the SV-RFE and an unoptimised classifier in the AC.

RESULTS: We conducted experiments on H&E histopathological prostate and colon cancer images with respect to three prostate classifications, namely benign vs. grade 3, benign vs. grade 4 and grade 3 vs. grade 4. The colon benchmark dataset requires a distinction between grades 1 and 2, which are the most difficult cases to distinguish in the colon domain. The results obtained by both the single and ensemble classification models (which uses the product rule as its merging method) confirm that the proposed SVM-RFE(AC) is superior to the other SVM and SVM-RFE-based methods.

MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.

RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.

MATERIALS AND METHODS: An online search was done for studies reporting incidental prostate cancer in cystoprostatectomy specimens. After following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines we identified a total of 34 reports containing 13,140 patients who underwent radical cystoprostatectomy for bladder cancer with no previous history of prostate cancer. A cumulative analysis was performed on the available data regarding prevalence, clinicopathological features and oncologic outcomes. RevMan, version 5.3 was used for data meta-analysis.

RESULTS: Of the 13,140 patients incidental prostate cancer was detected in 3,335 (24.4%). Incidental prostate cancer was significantly associated with greater age (Z = 3.81, p = 0.0001, d = 0.27, 95% CI -0.14-0.68), lymphovascular invasion of bladder cancer (Z = 2.07, p = 0.04, r = 0.14, 95% CI 0.09-0.18) and lower 5-year overall survival (Z = 2.2, p = 0.03). Among patients with clinically significant and insignificant prostate cancer those with clinically significant prostate cancer significantly more frequently showed a positive finding on digital rectal examination (Z = 3.12, p = 0.002, r = 0.10, 95% CI 0-0.19) and lower 5-year overall survival (Z = 2.49, p = 0.01) whereas no effect of age was observed (p = 0.15). Of 1,320 patients monitored for biochemical recurrence prostate specific antigen recurrence, defined as prostate specific antigen greater than 0.02 ng/ml, developed in 25 (1.9%) at between 3 and 102 months.

METHODS: In the present study, a prenylated flavone (isoglabratephrin) was isolated from aerial parts of Tephrosia apollinea using a bioassay-guided technique. Chemical structure of the isolated compound was elucidated using spectroscopic techniques (NMR, IR, and LC-MC), elemental analysis and confirmed by using single crystal X-ray analysis. The antiproliferative effect of isoglabratephrin was tested using three human cancer cell lines (prostate (PC3), pancreatic (PANC-1), and colon (HCT-116) and one normal cell line (human fibroblast).

RESULTS: Isoglabratephrin displayed selective inhibitory activity against proliferation of PC3 and PANC-1 cells with median inhibitory concentration values of 20.4 and 26.6 μg/ml, respectively. Isoglabratephrin demonstrated proapoptotic features, as it induced chromatin dissolution, nuclear condensation, and fragmentation. It also disrupted the mitochondrial membrane potential in the treated cancer cells.

MATERIALS AND METHODS: From March 2015 to August 2016, all men consecutively undergoing transrectal ultrasound (TRUS)-guided prostate biopsy with total PSA values ≤ 20ng/ ml were recruited. Blood samples were taken immediately before undergoing prostate biopsy. The performance of total PSA, %fPSA, %p2PSA and PHI in determining the presence of PCa on prostate biopsy were compared.

RESULTS: PCa was diagnosed in 25 of 84 patients (29.7%). %p2PSA and PHI values were significantly higher (p<0.05) in patients with PCa than those without PCa. The areas under the receiver operating characteristic curves for total PSA, %fPSA, %p2PSA and PHI were 0.558, 0.560, 0.734 and 0.746, respectively. At 90% sensitivity, the specificity of PHI (42.4%) was five times better than total PSA (8.5%) and two times better than %fPSA (20.3%). By utilising PHI cut-off >22.52, 27 of 84 (32.1%) patients could have avoided undergoing biopsy.