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Prostate and bladder cancer represent the two most frequently diagnosed genito-urinary malignancies. Diet has been implicated in both prostate and bladder cancer. Given their prolonged latency and high prevalence rates, both prostate and bladder cancer represent attractive candidates for dietary preventive measures, including the use of nutritional supplements. Flavonols, a class of flavonoids, are commonly found in fruit and vegetables and are known for their protective effect against diabetes and cardiovascular diseases. Furthermore, a higher dietary intake of flavonols was associated with a lower risk of both bladder and prostate cancer in epidemiological studies. In this systematic review, we gathered all available evidence supporting the anti-cancer potential of selected flavonols (kaempferol, fisetin and myricetin) against bladder and prostate cancer. A total of 21, 15 and 7 pre-clinical articles on bladder or prostate cancer reporting on kaempferol, fisetin and myricetin, respectively, were found, while more limited evidence was available from animal models and epidemiological studies or clinical trials. In conclusion, the available evidence supports the potential use of these flavonols in prostate and bladder cancer, with a low expected toxicity, thus providing the rationale for clinical trials that explore dosing, settings for clinical use as well as their use in combination with other pharmacological and non-pharmacological interventions.

The objective of the current research was to explore the potential prognostic value of readily available clinical and pathologic variables in bladder cancer. The novel association found between cholesterol levels and prognosis may provide the rationale for exploring novel treatments. Patients included had histologically confirmed urothelial bladder cancer and were treated with at least 3 cycles of cisplatin-based neoadjuvant chemotherapy before radical cystectomy with lymphadenectomy. A total of 245 patients at low, intermediate and high risk, presenting with 0-1, 2 or 3-4 risk factors, including positive lymph nodes, Hb <12.8, NLR ≥2.7 and cholesterol levels ≥199, were included. Five-year cancer-specific survival rate was 0.67, 0.78 and 0.94 at high, intermediate and low risk, respectively. Total cholesterol levels at the time of cystectomy may represent a commonly assessable prognostic factor and may be incorporated in a clinically meaningful risk-group classification model.

Reticulocyte (r) and red blood cell (RBC) indices provide reliable parameters for screening and monitoring iron deficiency anemia (IDA) patients and β-thalassemia trait (BTT) carriers. The aim of this study is to identify a simple method for use to distinguish β-thalassemia trait carriers from IDA and to evaluate the correlation between BTT genetic mutation and MCV values and new discrimination index for the detection of β-thalassemia trait (DI-BTT). We analyzed CHr, MCHCr, MCVr, RBC, mean cellular hemoglobin concentration (MCHC) and mean cellular volume (MCV) indices among a pediatric population of IDA patients (n=90), β-thalassemia trait carriers (n=72) and normal controls (NC) (n=131). Furthermore, to distinguish IDA patients from β-thalassemia trait carriers we evaluated clinical utility of new DI for the detection BTTcarriers, using the following polynomial: (RBC × MCHC × 50/MCV)/CHr. We found that CHr, MCVr and DI-BTT mean values were significantly different between β-thalassemia trait carriers and IDA patients. CHr, MCVr and DI-BTT plotting curves showed exclusive distribution in β-thalassemia trait carriers. Moreover, DI-BTT was very accurate in differentiating β-thalassemia trait carriers from IDA patients. All BTT patients showed a heterozygous mutation of the β-globin gene including CD39, IVS1.110, IVS1.6 and IVS2.745, IVS2.1 and IVS1.1. The highest MCV values were displayed by those carrying the IVS1.6 mutation., Conclusions: The simultaneous measurement and plotting of CHr and MCVr indices, as well as the DI-BTT allow to distinguish β-thalassemia carriers from IDA patients., Competing Interests: Conflict of interest The authors declare no conflict of interest.

Biomarkers can improve prostate cancer diagnosis and treatment. Accuracy of prostate-specific antigen (PSA) for early diagnosis of prostate cancer is not satisfactory, as it is an organ- but not cancer-specific biomarker, and it can be improved by using models that incorporate PSA along with other test results, such as prostate cancer antigen 3, the molecular forms of PSA (proPSA, benign PSA and intact PSA), as well as kallikreins. Recent reports suggest that new tools may be provided by metabolomic studies as shown by preliminary data on sarcosine. Additional molecular biomarkers have been identified by the use of genomics, proteomics and metabolomics. We review the most relevant biomarkers for early diagnosis and management of localized prostate cancer.

Background/aim: Several efforts have been made to find biomarkers that could help clinicians to preoperatively determine prostate cancer (PCa) pathological characteristics and choose the best therapeutic approach, avoiding over-treatment. On this effort, prostate cancer antigen 3 (PCA3), prostate health index (phi) and sarcosine have been presented as promising tools. We evaluated the ability of these biomarkers to predict the pathologic PCa characteristics within a prospectively collected contemporary cohort of patients who underwent radical prostatectomy (RP) for clinically localized PCa at a single high-volume Institution., Materials and Methods: The prognostic performance of PCA3, phi and sarcosine were evaluated in 78 patients undergoing RP for biopsy-proven PCa. Receiver operating characteristic (ROC) curve analyses tested the accuracy (area under the curve (AUC)) in predicting PCa pathological characteristics. Decision curve analyses (DCA) were used to assess the clinical benefit of the three biomarkers., Results: We found that PCA3, phi and sarcosine levels were significantly higher in patients with tumor volume (TV)≥0.5 ml, pathologic Gleason sum (GS)≥7 and pT3 disease (all p-values≤0.01). ROC curve analysis showed that phi is an accurate predictor of high-stage (AUC 0.85 [0.77-0.93]), high-grade (AUC 0.83 [0.73-0.93]) and high-volume disease (AUC 0.94 [0.88-0.99]). Sarcosine showed a comparable AUC (0.85 [0.76-0.94]) only for T3 stage prediction, whereas PCA3 score showed lower AUCs, ranging from 0.74 (for GS) to 0.86 (for TV)., Conclusion: PCA3, phi and sarcosine are predictors of PCa characteristics at final pathology. Successful clinical translation of these findings would reduce the frequency of surveillance biopsies and may enhance acceptance of active surveillance (AS)., (Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.)

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2-10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2-10 ng/ml at initial biopsy, outperforming currently used %fPSA.