METHODS: Multivariable-adjusted Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). After an average of 13.9 years of follow-up, there were 7024 incident prostate cancers and 934 prostate cancer deaths.
RESULTS: Height was not associated with total prostate cancer risk. Subgroup analyses showed heterogeneity in the association with height by tumour grade (P heterogeneity = 0.002), with a positive association with risk for high-grade but not low-intermediate-grade disease (HR for high-grade disease tallest versus shortest fifth of height, 1.54; 95% CI, 1.18-2.03). Greater height was also associated with a higher risk for prostate cancer death (HR = 1.43, 1.14-1.80). Body mass index (BMI) was significantly inversely associated with total prostate cancer, but there was evidence of heterogeneity by tumour grade (P heterogeneity = 0.01; HR = 0.89, 0.79-0.99 for low-intermediate grade and HR = 1.32, 1.01-1.72 for high-grade prostate cancer) and stage (P heterogeneity = 0.01; HR = 0.86, 0.75-0.99 for localised stage and HR = 1.11, 0.92-1.33 for advanced stage). BMI was positively associated with prostate cancer death (HR = 1.35, 1.09-1.68). The results for waist circumference were generally similar to those for BMI, but the associations were slightly stronger for high-grade (HR = 1.43, 1.07-1.92) and fatal prostate cancer (HR = 1.55, 1.23-1.96).
CONCLUSIONS: The findings from this large prospective study show that men who are taller and who have greater adiposity have an elevated risk of high-grade prostate cancer and prostate cancer death.
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.
CONCLUSION: In conclusion, we postulated that the CNVs identified in this study could provide an insight into the development of advanced PCa.
DISCUSSION: Several treatment options are available for different stages of prostate cancer. Hormone therapy known as androgen deprivation therapy (ADT) is the first line treatment used to treat advanced prostate cancer. Chemical castration by gonadotropin-releasing hormone agonists suppresses lutenizing hormone production, which in turn inhibits the production of testosterone and dihydrotestosterone. This will prevent the growth of prostate cancer cells. However, ADT causes deleterious effects on bone health because the androgens are essential in preserving optimal bone health in men.
CONCLUSION: Various observational studies showed that long-term ADT for advanced or metastatic prostate cancer was associated with decreased bone mineral density, as well as altered body composition that might affect bone health. Considering the potential impact of osteoporotic fracture, interventions to mitigate these skeletal adverse effects should be considered by physicians when initiating ADT on their patients.
MATERIAL AND METHODS: A systematic online search was conducted according to Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Eligible publications reporting the overall survival (OS) and/or disease-specific survival (DSS) were included. A total of 14 studies, including 17,869 patients, were considered for analysis. The impact of therapeutic modalities on survival was assessed, with a risk of bias assessment according to the Newcastle Ottawa Scale.
RESULTS: For RP, RT, and HT, the mean 10-year OS was 70.7% (95% CI 61.3-80.2), 65.8% (95% CI 48.1-83.3), and 22.6% (95% CI 4.9-40.3; p = 0.001), respectively. The corresponding 10-year DSS was 84.1% (95% CI 75.1-93.2), 89.4% (95% CI 70.1-108.6), and 50.4% (95% CI 31.2-69.6; p = 0.0127), respectively. Among all treatment combinations, RP displayed significant improvement in OS when included in the treatment (Z = 4.01; p < 0.001). Adjuvant RT significantly improved DSS (Z = 2.7; p = 0.007). Combination of RT and HT favored better OS in comparison to monotherapy with RT or HT (Z = 3.61; p < 0.001).
CONCLUSION: Improved outcomes in advanced PC were detected for RP plus adjuvant RT vs. RP alone and RT plus adjuvant HT vs. RT alone with comparable survival results between both regimens. RP with adjuvant RT may present the modality of choice when HT is contraindicated.
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.
CONCLUSION: Isoglabratephrin could be a new lead to treat human prostate (PC3) and pancreatic (PANC-1) malignancies.
METHODS: PSAV was calculated using logistic regression to determine if PSA or PSAV predicted the result of prostate biopsy (PB) in men with elevated PSA values. Cox regression was used to determine whether PSA or PSAV predicted PSA elevation in men with low PSAs. Interaction terms were included in the models to determine whether BRCA status influenced the predictiveness of PSA or PSAV.
RESULTS: 1634 participants had ⩾3 PSA readings of whom 174 underwent PB and 45 PrCas diagnosed. In men with PSA >3.0 ng ml-l, PSAV was not significantly associated with presence of cancer or high-grade disease. PSAV did not add to PSA for predicting time to an elevated PSA. When comparing BRCA1/2 carriers to non-carriers, we found a significant interaction between BRCA status and last PSA before biopsy (P=0.031) and BRCA2 status and PSAV (P=0.024). However, PSAV was not predictive of biopsy outcome in BRCA2 carriers.
CONCLUSIONS: PSA is more strongly predictive of PrCa in BRCA carriers than non-carriers. We did not find evidence that PSAV aids decision-making for BRCA carriers over absolute PSA value alone.
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.
CONCLUSION: We developed an FS method based on SVM-RFE and AC and successfully showed that its use enabled the identification of the most crucial texture feature of each tissue component. Thus, it makes possible the distinction between multiple Gleason grades (e.g. grade 3 vs. grade 4) and its performance is far superior to other reported FS methods.