Current routine screening methods for the diagnosis of prostate cancer (PCa) have significantly increased early detection of the disease but often show unsatisfactory analytical parameters. A class of promising markers represents urinary microRNAs (miRNAs). In the last five years, there has been an extensive increase in the number of studies on this topic. Thus, this review aims to update knowledge and point out technical aspects affecting urinary miRNA analysis. The review of relevant literature was carried out by searching the PubMed database for the keywords: microRNA, miRNA, urine, urinary, prostate cancer, and diagnosis. Papers discussed in this review were retrieved using PubMed, and the search strategy was as follows: (urine OR urinary) WITH (microRNA OR miRNA) AND prostate cancer. The search was limited to the last 5 years, January 2017 to December 2021. Based on the defined search strategy, 31 original publications corresponding to the research topic were identified, read and reviewed to present the latest findings and to assess possible translation of urinary miRNAs into clinical practice. Reviews or older publications were read and cited if they valuably extended the context and contributed to a better understanding. Urinary miRNAs are potentially valuable markers for the diagnosis of prostate cancer. Despite promising results, there is still a need for independent validation of exploratory data, which follows a strict widely accepted methodology taking into account the shortcomings and factors influencing the analysis.

Heterogeneity of colorectal carcinoma (CRC) represents a major hurdle towards personalized medicine. Efforts based on whole tumor profiling demonstrated that the CRC molecular subtypes were associated with specific tumor morphological patterns representing tumor subregions. We hypothesize that whole-tumor molecular descriptors depend on the morphological heterogeneity with significant impact on current molecular predictors. We investigated intra-tumor heterogeneity by morphology-guided transcriptomics to better understand the links between gene expression and tumor morphology represented by six morphological patterns (morphotypes): complex tubular, desmoplastic, mucinous, papillary, serrated, and solid/trabecular. Whole-transcriptome profiling by microarrays of 202 tumor regions (morphotypes, tumor-adjacent normal tissue, supportive stroma, and matched whole tumors) from 111 stage II-IV CRCs identified morphotype-specific gene expression profiles and molecular programs and differences in their cellular buildup. The proportion of cell types (fibroblasts, epithelial and immune cells) and differentiation of epithelial cells were the main drivers of the observed disparities with activation of EMT and TNF-α signaling in contrast to MYC and E2F targets signaling, defining major gradients of changes at molecular level. Several gene expression-based (including single-cell) classifiers, prognostic and predictive signatures were examined to study their behavior across morphotypes. Most exhibited important morphotype-dependent variability within same tumor sections, with regional predictions often contradicting the whole-tumor classification. The results show that morphotype-based tumor sampling allows the detection of molecular features that would otherwise be distilled in whole tumor profile, while maintaining histopathology context for their interpretation. This represents a practical approach at improving the reproducibility of expression profiling and, by consequence, of gene-based classifiers.

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Background Prostate cancer (PCa) is a heterogeneous malignancy with high variability in clinical course. Insufficient stratification according to the aggressiveness at the time of diagnosis causes unnecessary or delayed treatment. Current stratification systems are not effective enough because they are based on clinical, surgical or biochemical parameters, but do not take into account molecular factors driving PCa cancerogenesis. MicroRNAs (miRNAs) are important players in molecular pathogenesis of PCa and could serve as valuable biomarkers for the assessment of disease aggressiveness and its prognosis. Methods In the study, in total, 280 PCa patients were enrolled. The miRNA expression profiles were analyzed in FFPE PCa tissue using the miRCURY LNA miRNA PCR System. The expression levels of candidate miRNAs were further verified by two‐level validation using the RT‐qPCR method and evaluated in relation to PCa stratification reflecting the disease aggressiveness. Results MiRNA profiling revealed 172 miRNAs dysregulated between aggressive (ISUP 3–5) and indolent PCa (ISUP 1) (p < 0.05). In the training and validation cohort, miR‑15b‑5p and miR‐106b‐5p were confirmed to be significantly upregulated in tissue of aggressive PCa when their level was associated with disease aggressiveness. Furthermore, we established a prognostic score combining the level of miR‑15b‑5p and miR‐106b‐5p with serum PSA level, which discriminated indolent PCa from an aggressive form with even higher analytical parameters (AUC being 0.9338 in the training set and 0.8014 in the validation set, respectively). The score was also associated with 5‐year biochemical progression‐free survival (bPFS) of PCa patients. Conclusions We identified a miRNA expression pattern associated with disease aggressiveness in prostate cancer patients. These miRNAs may be of biological interest as the focus can be also set on their specific role within the molecular pathology and the molecular mechanism that underlies the aggressivity of prostate cancer.