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.

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.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

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.

Colorectal cancer (CRC) accounts for 9.7% of all cancers which makes it one of the three most commonly diagnosed cancer types worldwide. Prognosis of the patients with CRC depends mainly on the extent of the disease at the time of diagnosis. Therefore, the early detection of CRC and precancerous lesions is one of the main requirements of successful treatment. In recent years exosomes emerged as potential reservoirs of clinically useful biomarkers. Exosomes are 30-150 nm sized membranous vesicles that are endogenously produced by almost all cell types. They participate in intercellular communication by delivering proteins, microRNAs (miRNAs), mRNAs or long non-coding RNAs (lncRNAs) to recipient cells. In the context of cancer, intercellular communication allows cancer cells to create a favorable microenvironment for their growth. It has been shown that cancer-derived exosomes promote pathways contributing to hallmarks of cancer.To investigate diagnostic potential of exosomal RNA in CRC, blood serum samples were collected from patients with CRC and age- and sex-matched controls. Exosome isolation protocol was optimized, and the presence of vesicles in the exosome size range was confirmed using both dynamic light scattering (DLS) analysis as well as electron microscopy (TEM). Downstream analysis of serum exosomal RNA using next-generation sequencing (Illumina NextSeq 550) from exploratory cohort of CRC samples (N=50) and healthy controls (N=20) revealed both coding and non-coding RNAs to be differentially expressed (FC&gt;1.5, p-value &lt; 0.01). Among these were genes already reported to be dysregulated in CRC such as GAS5, but also lncRNAs previously unreported in CRC exosomes (AC103760.1, LINC02709 or PGBP) were identified. Gene set enrichment analysis (GSEA) was used to link RNAs identified within exosomes to their molecular functions. Using the Hallmark gene sets (MsigDB) as a reference, we discovered high enrichment of genes related to MYC targets, E2F targets and G2M checkpoint in healthy controls compared to CRC samples. All three hallmarks comprise genes crucial for cell proliferation. The first results indicated that the exosomal RNAs could be promising candidates as new diagnostic biomarkers in CRC, although further in vitro and in vivo exploration of identified differentially expressed lncRNAs is necessary. This work was supported by Ministry of Health of the Czech Republic grant nr. NU20-03-00127, NV19-03-00501 and NV19-03-00559. All rights reserved. Citation Format: Tina Catela Ivkovic, Marie Mądrzyk, Karolina Trachtova, Petra Faltejskova-Vychytilova, Tana Machackova, Petra Pokorna, Jaroslav Juracek, Jiri Sana, Ondrej Slaby. Molecular and functional characterization of colorectal cancer derived-exosomes and exosomal coding and long non-coding RNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2802.

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 molecular descriptors depend on morphological heterogeneity of the tumor, a dependency that negatively impacts the efficiency of current molecular predictors. We investigated intra-tumor heterogeneity by morphology-guided transcriptomics to better understand the links between gene expression and tumor morphology. The morphological patterns (morphotypes) considered were complex tubular, desmoplastic, mucinous, papillary, serrated, and solid/trabecular. Whole-transcriptomic profiling by microarrays of 202 tumor regions (representing the six 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-a signaling in contrast to MYC and E2F targets signaling, defining major gradients of changes at molecular level. Several types of 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 of our study show that morphotype-based tumor sampling allows for 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.

Introduction: Currently used molecular diagnostic tests for colorectal cancer (CRC) are underperforming and more sensitive, non-invasive biomarkers are needed. Long non-coding RNAs (lncRNA) and microRNA (miRNA) have shown potential as diagnostic biomarkers. Unfortunately, the identification of non-coding RNA circulating biomarkers in blood serum is significantly burdened by abundant RNA specimens from disrupted blood cells. Recently, small extracellular vesicles (sEVs) emerged as potential reservoirs of clinically relevant biomarkers, including lncRNAs and miRNAs. In theory, sEVs protect RNAs from degradation and might serve as a source of intact RNA for further analyses. However, there is a lack of evidence supporting the superior quality of RNA extracted from sEVs over RNA from whole blood serum. This study aimed to analyze the RNA content of blood serum and the sEVs derived from the blood serum of CRC patients and healthy controls using RNA sequencing. Moreover, small RNA sequencing was used to evaluate the difference in miRNA profiles of sEVs and corresponding blood sera of CRC patients and healthy controls. Methods: Spin-column chromatography (Exiqon), precipitation-based method (Norgen), and size-exclusion chromatography (iZON) were used to extract sEVs from blood sera. The concentration of sEVs was measured by dynamic light scattering (DLS), the size was evaluated by electron microscopy (EM), and sEV-specific content was analyzed by western blot and qRT-PCR. RNA was extracted using the column-based method. Next-generation sequencing (NGS) analyses of blood serum and sEVs extracted from blood serum included samples from 10 CRC patients and 10 healthy controls for RNAseq, and 5 CRC patients and 5 healthy controls for small RNAseq. Differential expression analysis was carried out in R using DESeq2 package. Results: DLS and EM showed that size-exclusion chromatography yielded the purest population of sEVs characterized according to ISEV recommendations. Extraction of sEVs and subsequent RNA extraction and sequencing library preparation from ultra-low input samples were optimized. Over 30k different RNAs were identified in the sEVs derived from blood sera of CRC patients and healthy controls, including lncRNAs, miRNAs, and protein-coding RNAs. A detailed comparison of the transcriptome of blood sera and corresponding sEVs is a part of the poster. Conclusion: sEVs could serve as a source of RNA biomarkers; however, proper characterization and optimal methodology are necessary. This work was supported by the Ministry of Health of the Czech Republic grant No. NU20-03-00127, by The project National Institute for Cancer Research (Programme EXCELES, ID Project No. LX22NPO5102) - Funded by the European Union - Next Generation EU, by the project BBMRI-CZ, nr. LM2018125, and in co-operation with CEMCOF, CEITEC MU (CIISB) supported by MEYS CR, LM2018127. Citation Format: Tana Machackova, Petra Vychytilova-Faltejskova, Marie Madrzyk, Karolina Trachtova, Marketa Pavlikova, Jan Kotoucek, Jana Halamkova, Dagmar Al Tukmachi, Jiri Sana, Petra Pokorna, Milana Sachlova, Ondrej Slaby. Utility of RNA sequencing for transcriptome analysis of small extracellular vesicles derived from blood sera of colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6709.