METHODS: Study subjects included men with initial PSA between 4.0 and 10.0 ng/ml that have undergone 12-core TRUS-guided prostate biopsy between 2009 and 2016. The prostate cancer detection rate was calculated, while potential factors associated with detection were investigated via univariable and multivariable analysis.

OBJECTIVE: To examine whether men with low concentrations of circulating free testosterone have a reduced risk of prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS: Analysis of individual participant data from 20 prospective studies including 6933 prostate cancer cases, diagnosed on average 6.8 yr after blood collection, and 12 088 controls in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) of incident overall prostate cancer and subtypes by stage and grade, using conditional logistic regression, based on study-specific tenths of calculated free testosterone concentration.

RESULTS AND LIMITATIONS: Men in the lowest tenth of free testosterone concentration had a lower risk of overall prostate cancer (OR=0.77, 95% confidence interval [CI] 0.69-0.86; p<0.001) compared with men with higher concentrations (2nd-10th tenths of the distribution). Heterogeneity was present by tumour grade (phet=0.01), with a lower risk of low-grade disease (OR=0.76, 95% CI 0.67-0.88) and a nonsignificantly higher risk of high-grade disease (OR=1.56, 95% CI 0.95-2.57). There was no evidence of heterogeneity by tumour stage. The observational design is a limitation.

CONCLUSIONS: Men with low circulating free testosterone may have a lower risk of overall prostate cancer; this may be due to a direct biological effect, or detection bias. Further research is needed to explore the apparent differential association by tumour grade.

METHODS: Tissues were collected from 80 patients with clinically detected prostate cancer and treated with radical prostatectomy. Cases were tested for ERG by immunohistochemistry using the mouse monoclonal antibody EP111. All blocks on 48 cases were tested in order to determine the extent of heterogeneity of ERG expression within individual cases. ERG expression was analysed in relation to patient age, ethnicity and tumour stage and grade.

RESULTS: Forty-six percent of cases were ERG positive. There was no significant association between ERG and tumour grade or stage. Sixty-nine percent of Indian patients had ERG positive tumours; this was significantly higher (p=0.031) than for Chinese (40%) and Malay (44%) patients. Heterogeneity of ERG expression, in which both positive and negative clones were present, was seen in 35% of evaluated cases. Evaluation by tumour foci showed younger patients had more ERG positive tumour foci than older patients (p=0.01). Indian patients were more likely to have the majority of tumour foci with ERG staining positively, compared to either Chinese or Malay patients (P <0.01).

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.

METHODS: To this end, we undertook a pilot genome-wide CNV analysis approach in 36 subjects (18 patients with high-grade PCa and 18 controls that were matched by age and ethnicity) in search of more accurate biomarkers that could potentially explain susceptibility toward high-grade PCa. We conducted this study using the array comparative genomic hybridization technique. Array results were validated in 92 independent samples (46 high-grade PCa, 23 benign prostatic hyperplasia, and 23 healthy controls) using polymerase chain reaction-based copy number counting method.

RESULTS: A total of 314 CNV regions were found to be unique to PCa subjects in this cohort (P<0.05). A log2 ratio-based copy number analysis revealed 5 putative rare or novel CNV loci or both associated with susceptibility to PCa. The CNV gain regions were 1q21.3, 15q15, 7p12.1, and a novel CNV in PCa 12q23.1, harboring ARNT, THBS1, SLC5A8, and DDC genes that are crucial in the p53 and cancer pathways. A CNV loss and deletion event was observed at 8p11.21, which contains the SFRP1 gene from the Wnt signaling pathway. Cross-comparison analysis with genes associated to PCa revealed significant CNVs involved in biological processes that elicit cancer pathogenesis via cytokine production and endothelial cell proliferation.