Background:In this paper, the utility of urine-circulating microRNAs (miRNAs) as the potential biomarker of prostate cancer (PCa), the second most prevalent male cancer worldwide, was evaluated.Methods:Cancerous (N=56) and non-cancerous (N=16) prostate tissues were analysed on TaqMan Low Density Array, with the initial screening of 754 miRNAs in a subset of the samples. The abundance of selected miRNAs was analysed in urine specimens from two independent cohorts of patients with PCa (N=215 overall), benign prostatic hyperplasia (BPH; N=23), and asymptomatic controls (ASC; N=62) by means of quantitative reverse transcription PCR.Results:Over 100 miRNAs were found deregulated in PCa as compared with non-cancerous prostate tissue. After thorough validation, four miRNAs were selected for the analysis in urine specimens. The abundance of miR-148a and miR-375 in urine was identified as specific biomarkers of PCa in both cohorts. Combined analysis of urine-circulating miR-148a and miR-375 was highly sensitive and specific for PCa in both cohorts (AUC=0.79 and 0.84) and strongly improved the diagnostic power of the PSA test (AUC=0.85, cohort PCa1), including the grey diagnostic zone (AUC=0.90).Conclusions:Quantitative measurement of urine-circulating miR-148a and miR-375 can serve as the non-invasive tool for sensitive and specific detection of PCa.

Hypermethylation of cytosines in CpG-rich islands of the promoter regions of regulatory genes has been discovered as a common mechanism of gene silencing during carcinogenesis. We analysed 64 primary lung carcinomas for promoter methylation of the tumour suppressor genes (TSGs) p16 (p16 INK4a /CDKN2A) and p14 (p14 ARF ) by methylation-specific PCR, in order to evaluate aberrant methylation as a potential biomarker for epigenetic alterations in tobacco-related lung cancer. Methylation of p16 was observed in 34% (22/64) of the lung tumours examined. In particular, p16 methylation occurred in nonsmall cell lung cancer (NSCLC) only, with 41 % (22/54) of the tumours being positive. The highest frequency was found in large cell carcinoma (5/7, 71%), followed by adenocarcinoma (9/25, 36%) and squamous cell carcinoma (7/21, 33%). Methylation of the p14 gene was less frequent in lung cancer (4/52, 8%). When association with tobacco smoking was analysed, 42% (21/50) of NSCLC from ever smokers exhibited p16 methylation. Interestingly, the analysis revealed a significantly higher risk of p16 methylation in former smokers as compared to current smokers [odds ratio (OR) 5.1; 95% confidence interval (CI) 1.3-22]. The difference was retained after adjustment for age (OR 3.7; 95% CI 0.9 -17). The promoter methylation results were then combined with data on genetic alterations determined previously in the same set of tumours. This data similarly showed that p16 methylation in parallel with p53 gene mutation or p14 methylation occurred more frequently in former smokers than in current smokers (44% vs. 14%; P ‫؍‬ 0.035). Taken together, our data suggest that analysis of promoter methylation in TSGs may provide a valuable biomarker for identification of groups with an elevated risk of cancer, such as smokers and ex-smokers.

BackgroundMolecular studies of breast cancer revealed biological heterogeneity of the disease and opened new perspectives for personalized therapy. While multiple gene expression-based systems have been developed, current clinical practice is largely based upon conventional clinical and pathologic criteria. This gap may be filled by development of combined multi-IHC indices to characterize biological and clinical behaviour of the tumours. Digital image analysis (DA) with multivariate statistics of the data opens new opportunities in this field.MethodsTissue microarrays of 109 patients with breast ductal carcinoma were stained for a set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16). Aperio imaging platform with the Genie, Nuclear and Membrane algorithms were used for the DA. Factor analysis of the DA data was performed in the whole group and hormone receptor (HR) positive subgroup of the patients (n = 85).ResultsMajor factor potentially reflecting aggressive disease behaviour (i-Grade) was extracted, characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α. The i-Grade factor scores revealed bimodal distribution and were strongly associated with higher Nottingham histological grade (G) and more aggressive intrinsic subtypes. In HR-positive tumours, the aggressiveness of the tumour was best defined by positive Ki67 and negative ER loadings. High Ki67/ER factor scores were strongly associated with the higher G and Luminal B types, but also were detected in a set of G1 and Luminal A cases, potentially indicating high risk patients in these categories. Inverse relation between HER2 and PR expression was found in the HR-positive tumours pointing at differential information conveyed by the ER and PR expression. SATB1 along with HIF-1α reflected the second major factor of variation in our patients; in the HR-positive group they were inversely associated with the HR and BCL2 expression and represented the major factor of variation. Finally, we confirmed high expression levels of p16 in Triple-negative tumours.ConclusionFactor analysis of multiple IHC biomarkers measured by automated DA is an efficient exploratory tool clarifying complex interdependencies in the breast ductal carcinoma IHC profiles and informative value of single IHC markers. Integrated IHC indices may provide additional risk stratifications for the currently used grading systems and prove to be useful in clinical outcome studies.Virtual SlidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1512077125668949