Temporal Stability and Prognostic Biomarker Potential of the Prostate Cancer Urine miRNA Transcriptome

Application of machine learning for high-throughput tumor marker screening

High-throughput sequencing and multiomics technologies have allowed increasing numbers of biomarkers to be mined and used for disease diagnosis, risk stratification, efficacy assessment, and prognosis prediction. However, the large number and complexity of tumor markers make screening them a substantial challenge. Machine learning (ML) offers new and effective ways to solve the screening problem. ML goes beyond mere data processing and is instrumental in recognizing intricate patterns within data. ML also has a crucial role in modeling dynamic changes associated with diseases. Used together, ML techniques have been included in automatic pipelines for tumor marker screening, thereby enhancing the efficiency and accuracy of the screening process. In this review, we discuss the general processes and common ML algorithms, and highlight recent applications of ML in tumor marker screening of genomic, transcriptomic, proteomic, and metabolomic data of patients with various types of cancers. Finally, the challenges and future prospects of the application of ML in tumor therapy are discussed.

WS2 nanosheets-based electrochemical biosensor for highly sensitive detection of tumor marker miRNA-4484

In this paper, a few-layer WS2 nanosheets-based electrochemical biosensor was fabricated for the highly sensitive detection of breast cancer tumor marker miRNA-4484. Firstly, few-layer WS2 nanosheets were prepared by shear stripping and characterized by SEM, TEM, AFM and UV spectrophotometer. After modification of few-layer WS2 nanosheets on the electrode surface, the miRNA probe was fixed on the few-layer WS2 nanosheets by polycytosine (PolyC). Then short-chain miRNA containing PolyC was used as the blocking agent to close the excess active sites on the surface of WS2 nanosheets to complete the fabrication of the sensor biosensing interface. Finally, the current changes caused by the specific binding of miRNA-4484 to the probe were analyzed by differential pulse voltammetry (DPV). The results showed that the sensor had a good linear relationship for the detection of miRNA-4484 in the concentration range of 1 aM-100 fM, and the detection limit was as low as 1.61 aM. In addition, the electrochemical sensor had excellent selectivity, stability and reproducibility. The artificial sample tests indicated that the developed biosensors have the potential for clinical application in the future.

Prostate cancer reshapes the secreted and extracellular vesicle urinary proteomes

Urine is a complex biofluid that reflects both overall physiologic state and the state of the genitourinary tissues through which it passes. It contains both secreted proteins and proteins encapsulated in tissue-derived extracellular vesicles (EVs). To understand the population variability and clinical utility of urine, we quantified the secreted and EV proteomes from 190 men, including a subset with prostate cancer. We demonstrate that a simple protocol enriches prostatic proteins in urine. Secreted and EV proteins arise from different subcellular compartments. Urinary EVs are faithful surrogates of tissue proteomes, but secreted proteins in urine or cell line EVs are not. The urinary proteome is longitudinally stable over several years. It can accurately and non-invasively distinguish malignant from benign prostatic lesions and can risk-stratify prostate tumors. This resource quantifies the complexity of the urinary proteome and reveals the synergistic value of secreted and EV proteomes for translational and biomarker studies.

Prediction of prostate cancer aggressiveness using magnetic resonance imaging radiomics: a dual-center study

PURPOSE

The Gleason score (GS) and positive needles are crucial aggressive indicators of prostate cancer (PCa). This study aimed to investigate the usefulness of magnetic resonance imaging (MRI) radiomics models in predicting GS and positive needles of systematic biopsy in PCa.

MATERIAL AND METHODS

A total of 218 patients with pathologically proven PCa were retrospectively recruited from 2 centers. Small-field-of-view high-resolution T2-weighted imaging and post-contrast delayed sequences were selected to extract radiomics features. Then, analysis of variance and recursive feature elimination were applied to remove redundant features. Radiomics models for predicting GS and positive needles were constructed based on MRI and various classifiers, including support vector machine, linear discriminant analysis, logistic regression (LR), and LR using the least absolute shrinkage and selection operator. The models were evaluated with the area under the curve (AUC) of the receiver-operating characteristic.

RESULTS

The 11 features were chosen as the primary feature subset for the GS prediction, whereas the 5 features were chosen for positive needle prediction. LR was chosen as classifier to construct the radiomics models. For GS prediction, the AUC of the radiomics models was 0.811, 0.814, and 0.717 in the training, internal validation, and external validation sets, respectively. For positive needle prediction, the AUC was 0.806, 0.811, and 0.791 in the training, internal validation, and external validation sets, respectively.

CONCLUSIONS

MRI radiomics models are suitable for predicting GS and positive needles of systematic biopsy in PCa. The models can be used to identify aggressive PCa using a noninvasive, repeatable, and accurate diagnostic method.

NEAT1 promotes the progression of prostate cancer by targeting the miR-582-5p/EZH2 regulatory axis

In several forms of malignant tumors, nuclear enriched abundant transcript 1 (NEAT1), a lncRNA, has been identified to play an important role. NEAT1's regulation patterns in prostate cancer (PCa) are, however, mainly unknown. This study was aimed to evaluate and study the roles and regulatory mechanisms of NEAT1 in PCa. NEAT1, miR-582-5p, and enhancer of zeste homolog 2 (EZH2) expression were detected by qRT-PCR. The PCa cells' invasive, migrative, and proliferative activities in vitro were assessed using transwell migration and invasion, wound-healing, cloning creation, and CCK-8 assays. In the present study, impaired proliferative, migrative, and invasive capacities were observed in the NEAT1-deficient PCa (PC3 and LNCaP) cells. Further mechanistic studies found that NEAT1 performs its function through sponging miR-582-5p. Furthermore, EZH2 was confirmed to be the downstream target gene of miRNA-582-5p. The impaired progression caused by NEAT1 deficiency in PCa cells was significantly restored by the inhibition of miR-582-5p, while these effects were largely abolished by the deletion of EZH2. Finally, the xenograft nude mouse model showed that knocking down the expression of NEAT1 suppressed the growth of PCa. In conclusion, NEAT1 promotes the progression of PCa by controlling the miR-582-5p and miR-582-5p-mediated EZH2.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10616-023-00612-z.

Epigenetic modifications in obesity-associated diseases

The global prevalence of obesity has reached epidemic levels, significantly elevating the susceptibility to various cardiometabolic conditions and certain types of cancer. In addition to causing metabolic abnormalities such as insulin resistance (IR), elevated blood glucose and lipids, and ectopic fat deposition, obesity can also damage pancreatic islet cells, endothelial cells, and cardiomyocytes through chronic inflammation, and even promote the development of a microenvironment conducive to cancer initiation. Improper dietary habits and lack of physical exercise are important behavioral factors that increase the risk of obesity, which can affect gene expression through epigenetic modifications. Epigenetic alterations can occur in early stage of obesity, some of which are reversible, while others persist over time and lead to obesity-related complications. Therefore, the dynamic adjustability of epigenetic modifications can be leveraged to reverse the development of obesity-associated diseases through behavioral interventions, drugs, and bariatric surgery. This review provides a comprehensive summary of the impact of epigenetic regulation on the initiation and development of obesity-associated cancers, type 2 diabetes, and cardiovascular diseases, establishing a theoretical basis for prevention, diagnosis, and treatment of these conditions.

Prospective Validation Study of a Novel Integrated Pathway Based on Clinical Features, Magnetic Resonance Imaging Biomarkers, and MicroRNAs for Early Detection of Prostate Cancer

BACKGROUND

Prostate cancer (PCa) is the most diagnosed cancer in men, with an increasing need to integrate noninvasive imaging and circulating microRNAs beyond prostate-specific antigen for screening and early detection.

OBJECTIVE

To validate magnetic resonance imaging (MRI) biomarkers and circulating microRNAs as triage tests for patients directed to prostate biopsy, and to test different diagnostic pathways to compare their performance on patients' outcome, in terms of unnecessary biopsy avoidance.

DESIGN, SETTING, AND PARTICIPANTS

A prospective single-center cohort study, enrolling patients with PCa suspicion who underwent MRI, MRI-directed fusion biopsy (MRDB), and circulating microRNAs, was conducted. A network-based analysis was used to identify MRI biomarkers and microRNA drivers of clinically significant PCa.

INTERVENTION

MRI, MRDB, and blood sampling.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The decision curve analysis was exploited to assess the performance of the proposed diagnostic pathways and to quantify their benefit in terms of biopsy avoidance.

RESULTS AND LIMITATIONS

Overall, 261 men were enrolled and underwent MRDB for PCa detection. A total of 178 patients represented the entire cohort: 55 (30.9%) were negative for PCa, 39 (21.9%) had grade group (GG) 1 PCa, and 84 (47.2%) had GG >1 PCa. The proposed integrated pathway, including clinical data, MRI biomarkers, and microRNAs, provided the best net benefit with a biopsy avoidance rate of about 20% at a low disease probability. The main limitation is the monocentric design in a referral center.

CONCLUSIONS

The integrated pathway represents a validated model that sees MRI biomarkers and microRNAs as a prebiopsy triage of patients at a risk for clinically significant PCa. The proposed pathway showed the highest net benefit in terms of unnecessary biopsy avoidance.

PATIENT SUMMARY

The proposed integrated pathway for early detection of prostate cancer (PCa) allows accurate patient allocation to biopsy and patients' stratification into risk group categories, reducing overdiagnosis and overtreatment of clinically insignificant PCa.

Molecular Mechanisms of Prostate Cancer Development in the Precision Medicine Era: A Comprehensive Review

The progression of prostate cancer (PCa) relies on the activation of the androgen receptor (AR) by androgens. Despite efforts to block this pathway through androgen deprivation therapy, resistance can occur through several mechanisms, including the abnormal activation of AR, resulting in castration-resistant PCa following the introduction of treatment. Mutations, amplifications, and splicing variants in AR-related genes have garnered attention in this regard. Furthermore, recent large-scale next-generation sequencing analysis has revealed the critical roles of AR and AR-related genes, as well as the DNA repair, PI3K, and cell cycle pathways, in the onset and progression of PCa. Moreover, research on epigenomics and microRNA has increasingly become popular; however, it has not translated into the development of effective therapeutic strategies. Additionally, treatments targeting homologous recombination repair mutations and the PI3K/Akt pathway have been developed and are increasingly accessible, and multiple clinical trials have investigated the efficacy of immune checkpoint inhibitors. In this comprehensive review, we outline the status of PCa research in genomics and briefly explore potential future developments in the field of epigenetic modifications and microRNAs.

MicroRNAs for detecting occult genitourinary cancer

PURPOSE OF REVIEW

Genitourinary (GU) malignancies are a real burden in global health worldwide. Each model has its own clinical challenges, and the early screening and/or detection of occult cancer in follow-up is transversal to all of them. MicroRNAs (miRNAs) have been proposed as minimally invasive liquid biopsy cancer biomarkers, due to their stability and low degradation.

RECENT FINDINGS

The different GU tumor models are in different stages concerning miRNAs as biomarkers for cancer detection. Testicular germ cell tumors (TGCTs) already have a specific defined target, miR-371a-3p, that has shown high sensitivity and specificity in different clinical settings, and is now in final stages of preanalytical testing before entering the clinic. The other GU malignancies are in a different stage, with many liquid biopsy studies (both in urine and plasma/serum) being currently performed, but there is not an agreeable miRNA or set of miRNAs that is ready to follow the footsteps of miR-371a-3p in TGCTs.

SUMMARY

Further studies with proper molecular characterization of miRNA profiles of GU malignancies and standardization of sampling, biobanking and formal analysis may aid in the advance and choosing of specific target sets to be used for occult cancer detection.

DNA Tile and Invading Stacking Primer-Assisted CRISPR-Cas12a Multiple Amplification System for Entropy-Driven Electrochemical Detection of MicroRNA with Tunable Sensitivity

Conventional electrochemical detection of microRNA (miRNA) encounters issues of poor sensitivity and fixed dynamic range. Here, we report a DNA tile and invading stacking primer-assisted CRISPR-Cas12a multiple amplification strategy to construct an entropy-controlled electrochemical biosensor for the detection of miRNA with tunable sensitivity and dynamic range. To amplify the signal, a cascade amplification of the CRISPR-Cas12a system along with invading stacking primer signal amplification (ISPSA) was designed to detect trace amounts of miRNA-31 (miR-31). The target miR-31 could activate ISPSA and produce numerous DNAs, triggering the cleavage of the single-stranded linker probe (LP) that connects a methylene blue-labeled DNA tile with a DNA tetrahedron to form a Y-shaped DNA scaffold on the electrode. Based on the decrease of current, miR-31 can be accurately and efficiently detected. Impressively, by changing the loop length of the LP, it is possible to finely tune the entropic contribution while keeping the enthalpic contribution constant. This strategy has shown a tunable limit of detection for miRNA from 0.31 fM to 0.56 pM, as well as a dynamic range from ∼2200-fold to ∼270,000-fold. Moreover, it demonstrated satisfactory results in identifying cancer cells with a high expression of miR-31. Our strategy broadens the application of conventional electrochemical biosensing and provides a tunable strategy for detecting miRNAs at varying concentrations.

Prostate Cancer Reshapes the Secreted and Extracellular Vesicle Urinary Proteomes

Urine is a complex biofluid that reflects both overall physiologic state and the state of the genitourinary tissues through which it passes. It contains both secreted proteins and proteins encapsulated in tissue-derived extracellular vesicles (EVs). To understand the population variability and clinical utility of urine, we quantified the secreted and EV proteomes from 190 men, including a subset with prostate cancer. We demonstrate that a simple protocol enriches prostatic proteins in urine. Secreted and EV proteins arise from different subcellular compartments. Urinary EVs are faithful surrogates of tissue proteomes, but secreted proteins in urine or cell line EVs are not. The urinary proteome is longitudinally stable over several years. It can accurately and non-invasively distinguish malignant from benign prostatic lesions, and can risk-stratify prostate tumors. This resource quantifies the complexity of the urinary proteome, and reveals the synergistic value of secreted and EV proteomes for translational and biomarker studies.

Recent Advances in Blood-Based Liquid Biopsy Approaches in Prostate Cancer

ABSTRACT

The advent of high-throughput technologies has enabled the analysis of minute amounts of tumor-derived material purified from body fluids, termed "liquid biopsies." Prostate cancer (PCa) management, like in many other cancer types, has benefited from liquid biopsies at several stages of the disease. Although initially describing circulating tumor cells in blood, the term "liquid biopsy" has come to more prominently include cell-free, circulating tumor DNA, as well as RNA, proteins, and other molecules. They provide tumor molecular information representing the entire, often-heterogeneous disease, relatively noninvasively and longitudinally. Blood has been the main liquid biopsy specimen in PCa, and urine has also proven beneficial. Technological advances have allowed clinical implementation of some liquid biopsies in PCa, in disease monitoring and precision oncology. This narrative review introduces the main types of blood-based PCa liquid biopsies focusing on advances in the past 5 years. Clinical adoption of liquid biopsies to detect and monitor the evolving PCa tumor biology promises to deepen our understanding of the disease and improve patient outcomes.

In situ imaging miRNAs using multifunctional linear DNA nanostructure

The microRNAs (miRNAs) play a critical role in many biological processes and are essential biomarkers for diagnosing disease. However, the sensitive and specific quantification of microRNAs (miRNAs) expression in living cells still faces a huge challenge. Our study designed a multifunctional linear DNA nanostructure (MLN) as a carrier of molecular beacons (MB-21) for detecting and intracellular imaging miRNA-21. The MLN-MB consists of three parts: aptamer, MLN, and MB-21. The aptamer (AS1411) could media MLN-MB enter live cells without additional transfection reagents. Once inside the cells, the intracellular miRNA-21 could hybridize the MB-21s, resulting in significantly enhanced fluorescence signals. The whole process was enzyme-free, autonomous, and continuous, which avoided the necessity of adding external fuel strands or enzymes. We demonstrated that the MLN-MB could be used to screen the miRNA-21 with a detection limit of 320 pM in a short time (10 min) and show high specificity toward miRNA-21 against other miRNAs. Moreover, the proposed MLN-MB could detect the miRNA-21 in complex matrixes stably. With its outstanding stability, dual recognition, and biocompatibility, MLN-MB is capable of delivering into living cells to identify specific cancer cells. Therefore, our sensing approach, with high sensitivity, specificity, and simplicity advantages, holds great potential for early cancer diagnosis.

MicroRNAs as clinical tools for diagnosis, prognosis, and therapy in prostate cancer

Prostate cancer (PCa) is one of the most commonly diagnosed cancers among men worldwide. Despite the presence of accumulated clinical strategies for PCa management, limited prognostic/sensitive biomarkers are available to follow up on disease occurrence and progression. MicroRNAs (miRNAs) are small non-coding RNAs that control gene expression through post-transcriptional regulation of their complementary target messenger RNA (mRNA). MiRNAs modulate fundamental biological processes and play crucial roles in the pathology of various diseases, including PCa. Multiple evidence proved an aberrant miRNA expression profile in PCa, which is actively involved in the carcinogenic process. The robust and pleiotropic impact of miRNAs on PCa suggests them as potential candidates to help more understand the molecular landscape of the disease, which is likely to provide tools for early diagnosis and prognosis as well as additional therapeutic strategies to manage prostate tumors. Here, we emphasize the most consistently reported dysregulated miRNAs and highlight the contribution of their altered downstream targets with PCa hallmarks. Also, we report the potential effectiveness of using miRNAs as diagnostic/prognostic biomarkers in PCa and the high-throughput profiling technologies that are being used in their detection. Another key aspect to be discussed in this review is the promising implication of miRNAs molecules as therapeutic tools and targets for fighting PCa.

The Potential of MicroRNAs as Non-Invasive Prostate Cancer Biomarkers: A Systematic Literature Review Based on a Machine Learning Approach

Simple Summary

Prostate cancer (PCa) is the most common cancer in men worldwide. Screening and diagnosis are based on prostate-specific antigen (PSA) blood testing and digital rectal examination. Nevertheless, these methods are not specific and have a high risk of mistaken results. This has led to overtreatment and unnecessary radical therapy; thus, better prognostic tools are urgently needed. In this view, microRNAs (miRs) appear as potential non-invasive biomarkers for PCa diagnosis, prognosis, and therapy. As the scientific literature available in this field is huge and very often controversial, we identified and discussed three topics that characterize the investigated research area by combining the big data from the literature together with a novel machine learning approach. By analyzing the papers clustered into these topics we have offered a deeper understanding of the current research, which helps to contribute to the advancement of this research field.

Abstract

Background: Prostate cancer (PCa) is the second leading cause of cancer-related deaths in men. Although the prostate-specific antigen (PSA) test is used in clinical practice for screening and/or early detection of PCa, it is not specific, thus resulting in high false-positive rates. MicroRNAs (miRs) provide an opportunity as biomarkers for diagnosis, prognosis, and recurrence of PCa. Because the size of the literature on it is increasing and often controversial, this study aims to consolidate the state-of-art of relevant published research. Methods: A Systematic Literature Review (SLR) approach was applied to analyze a set of 213 scientific publications through a text mining method that makes use of the Latent Dirichlet Allocation (LDA) algorithm. Results and Conclusions: The result of this activity, performed through the MySLR digital platform, allowed us to identify a set of three relevant topics characterizing the investigated research area. We analyzed and discussed all the papers clustered into them. We highlighted that several miRs are associated with PCa progression, and that their detection in patients’ urine seems to be the more reliable and promising non-invasive tool for PCa diagnosis. Finally, we proposed some future research directions to help future scientists advance the field further.

miRNA in Molecular Diagnostics

MicroRNAs are a class of small non-coding RNA molecules that regulate gene expression on post-transcriptional level. Their biogenesis consists of a complex series of sequential processes, and they regulate expression of many genes involved in all cellular processes. Their function is essential for maintaining the homeostasis of a single cell; therefore, their aberrant expression contributes to development and progression of many diseases, especially malignant tumors and viral infections. Moreover, they can be associated with certain states of a specific disease, obtained in the least invasive manner for patients and analyzed with basic molecular methods used in clinical laboratories. Because of this, they have a promising potential to become very useful biomarkers and potential tools in personalized medicine approaches. In this review, miRNAs biogenesis, significance in cancer and infectious diseases, and current available test and methods for their detection are summarized.

Dietary stilbenes as modulators of specific miRNAs in prostate cancer

Accumulated experimental data have suggested that natural plant products may be effective miRNA-modulating chemopreventive and therapeutic agents. Dietary polyphenols such as flavonoids, stilbenes, and lignans, among others, have been intensively studied for their miRNA-mediated cardioprotective, antioxidant, anti-inflammatory and anticancer properties. The aim of this review is to outline known stilbene-regulated miRNAs in cancer, with a special focus on the interplay between various miRNAs and MTA1 signaling in prostate cancer. MTA1 is an epigenetic reader and an oncogenic transcription factor that is overexpressed in advanced prostate cancer and metastasis. Not surprisingly, miRNAs that are linked to MTA1 affect cancer progression and the metastatic potential of cells. Studies led to the identification of MTA1-associated pro-oncogenic miRNAs, which are regulated by stilbenes such as resveratrol and pterostilbene. Specifically, it has been shown that inhibition of the activity of the MTA1 regulated oncogenic miR-17 family of miRNAs, miR-22, and miR-34a by stilbenes leads to inhibition of prostatic hyperplasia and tumor progression in mice and reduction of proliferation, survival and invasion of prostate cancer cells in vitro. Taken together, these findings implicate the use of resveratrol and its analogs as an attractive miRNA-mediated chemopreventive and therapeutic strategy in prostate cancer and the use of circulating miRNAs as potential predictive biomarkers for clinical development.

MiRNA biomarkers in cancers of the male reproductive system: are we approaching clinical application?

BACKGROUND

Specific cancer types face specific clinical management challenges. Owing to their stability, robustness and fast, easy, and cost-effective detection, microRNAs (miRNAs) are attractive candidate biomarkers to the clinic.

OBJECTIVES

Based on a comprehensive review of the relevant literature in the field, we explore the potential of miRNAs as biomarkers to answer relevant clinical dilemmas inherent to cancers of the male reproductive tract (prostate (PCa), testis (TGCTs) and penis (PeCa)) and identify some of the challenges/limitations hampering their widely application.

RESULTS AND DISCUSSION

We conclude that the use of miRNAs as biomarkers is at different stages for these distinct cancer types. While for TGCTs, miRNA-371a-3p is universally accepted to fill in important clinicals gaps and is moving fast towards clinical implementation, for PCa almost no overlap of miRNAs exists between studies, denoting the absence of a consistent miRNA biomarker, and for PeCa the field of miRNAs has just recently started, with only a few studies attempting to explore their clinical usefulness.

CONCLUSION

Technological advances influencing miRNA detection and quantification will be instrumental to continue to move forward with implementation of miRNAs in the clinic as biomarkers for non-invasive diagnosis, risk stratification, treatment monitoring and follow-up. This article is protected by copyright. All rights reserved.

Ultrasensitive Fluorescence Detection and Accurate Colocalization Visualization of Dual-miRNAs in Cancer Cells Based on the Conjugated Chain Reaction of Multifunctional Pentagon DNA Nanostructures

Herein, a multifunctional pentagon DNA nanostructure (MPDN) was assembled by the hybridization of a circular DNA scaffold containing five different fragments with five diverse DNA oligonucleotides for simultaneous sensitive detection and accurate colocalization imaging of dual-miRNAs in cancer cells. Exactly, the MPDN could specifically and efficiently internalize into folate (FA) receptor-overexpressed cells via specific binding of FA and the FA receptor to distinguish cancer cells from normal cells and transform trace amounts of targets miRNA-21 and miRNA-155 into substantial FAM and Cy5-labeled DNA polymers as the signal probe to generate two remarkable fluorescence emissions, realizing simultaneously sensitive detection of dual-miRNAs. Impressively, compared with traditional small fragment DNA probes with high fluidity, the DNA copolymers with extremely low diffusivity kept it in the originally generated position to achieve the colocalization imaging of dual-miRNAs more accurately for revealing the spatial expression information of dual-miRNAs in tissues and cells. This strategy provided programmable tool to simultaneously detect and accurately colocate dual-miRNAs for understanding normal physiology and the tumor mechanism.

Urinary microRNAs and Their Significance in Prostate Cancer Diagnosis: A 5-Year Update

Simple Summary

Current diagnostics of prostate cancer often show unsatisfactory results, leading to delayed detection or overtreatment. Urinary microRNAs are a class of promising non-invasive biomarkers. Although many studies have been conducted on this topic in the last five years, there is little agreement on the data obtained. This review aims to discuss new knowledge but also focuses on technical aspects affecting urinary miRNA analysis.

Abstract

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.

MicroRNAs as Biomarkers for Ionizing Radiation Injury

Accidental radiation exposures such as industrial accidents and nuclear catastrophes pose a threat to human health, and the potential or substantial injury caused by ionizing radiation (IR) from medical treatment that cannot be ignored. Although the mechanisms of IR-induced damage to various organs have been gradually investigated, medical treatment of irradiated individuals is still based on clinical symptoms. Hence, minimally invasive biomarkers that can predict radiation damage are urgently needed for appropriate medical management after radiation exposure. In the field of radiation biomarker, finding molecular biomarkers to assess different levels of radiation damage is an important direction. In recent years, microRNAs have been widely reported as several diseases’ biomarkers, such as cancer and cardiovascular diseases, and microRNAs are also of interest to the ionizing radiation field as radiation response molecules, thus researchers are turning attention to the potential of microRNAs as biomarkers in tumor radiation response and the radiation toxicity prediction of normal tissues. In this review, we summarize the distribution of microRNAs, the progress on research of microRNAs as markers of IR, and make a hypothesis about the origin and destination of microRNAs in vivo after IR.

Optimization of small extracellular vesicle isolation from expressed prostatic secretions in urine for in-depth proteomic analysis

The isolation and subsequent molecular analysis of extracellular vesicles (EVs) derived from patient samples is a widely used strategy to understand vesicle biology and to facilitate biomarker discovery. Expressed prostatic secretions in urine are a tumor proximal fluid that has received significant attention as a source of potential prostate cancer (PCa) biomarkers for use in liquid biopsy protocols. Standard EV isolation methods like differential ultracentrifugation (dUC) co-isolate protein contaminants that mask lower-abundance proteins in typical mass spectrometry (MS) protocols. Further complicating the analysis of expressed prostatic secretions, uromodulin, also known as Tamm-Horsfall protein (THP), is present at high concentrations in urine. THP can form polymers that entrap EVs during purification, reducing yield. Disruption of THP polymer networks with dithiothreitol (DTT) can release trapped EVs, but smaller THP fibres co-isolate with EVs during subsequent ultracentrifugation. To resolve these challenges, we describe here a dUC method that incorporates THP polymer reduction and alkaline washing to improve EV isolation and deplete both THP and other common protein contaminants. When applied to human expressed prostatic secretions in urine, we achieved relative enrichment of known prostate and prostate cancer-associated EV-resident proteins. Our approach provides a promising strategy for global proteomic analyses of urinary EVs.

Early molecular markers for retrospective biodosimetry and prediction of acute health effects

Radiation-induced biological changes occurring within hours and days after irradiation can be potentially used for either exposure reconstruction (retrospective dosimetry) or the prediction of consecutively occurring acute or chronic health effects. The advantage of molecular protein or gene expression (GE) (mRNA) marker lies in their capability for early (1-3 days after irradiation), high-throughput and point-of-care diagnosis, required for the prediction of the acute radiation syndrome (ARS) in radiological or nuclear scenarios. These molecular marker in most cases respond differently regarding exposure characteristics such as e.g. radiation quality, dose, dose rate and most importantly over time. Changes over time are in particular challenging and demand certain strategies to deal with. With this review, we provide an overview and will focus on already identified and used mRNA GE and protein markers of the peripheral blood related to the ARS. These molecules are examined in light of 'ideal' characteristics of a biomarkers (e.g. easy accessible, early response, signal persistency) and the validation degree. Finally, we present strategies on the use of these markers considering challenges as their variation over time and future developments regarding e.g. origin of samples, point of care and high-throughput diagnosis.

Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry

Prostate cancer is the second most frequently diagnosed non-skin cancer in men worldwide. Patient outcomes are remarkably heterogeneous and the best existing clinical prognostic tools such as International Society of Urological Pathology Grade Group, pretreatment serum PSA concentration and T-category, do not accurately predict disease outcome for individual patients. Thus, patients newly diagnosed with prostate cancer are often overtreated or undertreated, reducing quality of life and increasing disease-specific mortality. Biomarkers that can improve the risk stratification of these patients are, therefore, urgently needed. The ideal biomarker in this setting will be non-invasive and affordable, enabling longitudinal evaluation of disease status. Prostatic secretions, urine and blood can be sources of biomarker discovery, validation and clinical implementation, and mass spectrometry can be used to detect and quantify proteins in these fluids. Protein biomarkers currently in use for diagnosis, prognosis and relapse-monitoring of localized prostate cancer in fluids remain centred around PSA and its variants, and opportunities exist for clinically validating novel and complimentary candidate protein biomarkers and deploying them into the clinic.

A self-quenching fluorescence probe-mediated exponential isothermal amplification system for highly sensitive and specific detection of microRNAs

We designed an efficient self-quenching fluorescence probe and constructed this probe-mediated exponential isothermal amplification system for miRNA detection. Owing to the significant improvement in the detective signal-to-background ratio, a wide dynamic range of 9 orders of magnitude and a limit of detection as low as 0.08 aM can be easily achieved in a single step. Furthermore, benefiting from the additional advantages of high specificity and biocompatibility, the proposed method has been demonstrated to be capable of accurately quantifying miRNA biomarkers in serum, which will provide promising perspectives for clinical diagnosis.

Exosomal transfer of miR-769-5p promotes osteosarcoma proliferation and metastasis by targeting DUSP16

Background

Osteosarcoma (OS) is a malignant tumor originating from mesenchymal stem cells, and has an extremely high fatality rate and ability to metastasize. Although mounting evidence suggests that miR-769-5p is strongly associated with the malignant progression and poor prognosis of various tumors, the exact role of miR-769-5p in OS is still unclear. Therefore, this study aimed to explore the relationship between miR-769-5p and the malignant progression of OS, and its underlying mechanism of action.

Methods

miR-769-5p expression was analyzed in GSE28423 from the GEO database and measured in OS clinical specimens and cell lines. The effects of miR-769-5p on OS proliferation, migration and invasion were measured both in vivo and in vitro. In addition, bioinformatics analyses and luciferase reporter assays were used to explore the target genes of miR-769-5p. Rescue experiments were also conducted. Moreover, a co-culture model was used to test the cell interaction between bone mesenchymal stem cells (BMSC) and OS cells.

Results

We found that miR-769-5p is highly expressed in OS clinical specimens and cell lines. In vivo and in vitro experiments also showed that miR-769-5p significantly promoted the proliferation, migration and invasion of OS cells. Dual-specific phosphatase 16 (DUSP16) was negatively associated with miR-769-5p expression in OS cells and tissue samples and was validated as the downstream target by luciferase reporter assay and western blotting. Rescue experiments showed that DUSP16 reverses the effect of miR-769-5p on OS cells by negatively regulating the JNK/p38 MAPK signaling pathway. Additionally, the results of the co-culture of BMSCs and OS cells confirmed that miR-769-5p was transferred from BMSCs to OS cells through exosomes.

Conclusions

In summary, this study demonstrates for the first time that BMSC-derived exosomal miR-769-5p promotes OS proliferation and metastasis by targeting DUSP16 and activating the JNK/p38 MAPK signaling pathway, which could provide rationale for a new therapeutic strategy for OS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02257-4.

Network Analysis Integrating microRNA Expression Profiling with MRI Biomarkers and Clinical Data for Prostate Cancer Early Detection: A Proof of Concept Study

The MRI of the prostate is the gold standard for the detection of clinically significant prostate cancer (csPCa). Nonetheless, MRI still misses around 11% of clinically significant disease. The aim was to comprehensively integrate tissue and circulating microRNA profiling, MRI biomarkers and clinical data to implement PCa early detection. In this prospective cohort study, 76 biopsy naïve patients underwent MRI and MRI directed biopsy. A sentinel sample of 15 patients was selected for a pilot molecular analysis. Weighted gene coexpression network analysis was applied to identify the microRNAs drivers of csPCa. MicroRNA-target gene interaction maps were constructed, and enrichment analysis performed. The ANOVA on ranks test and ROC analysis were performed for statistics. Disease status was associated with the underexpression of the miRNA profiled; a correlation was found with ADC (r = -0.51, p = 0.02) and normalized ADC values (r = -0.64, p = 0.002). The overexpression of miRNAs from plasma was associated with csPCa (r = 0.72; p = 0.02), and with PI-RADS assessment score (r = 0.73; p = 0.02); a linear correlation was found with biomarkers of diffusion and perfusion. Among the 800 profiled microRNA, eleven were identified as correlating with PCa, among which miR-548a-3p, miR-138-5p and miR-520d-3p were confirmed using the RT-qPCR approach on an additional cohort of ten subjects. ROC analysis showed an accuracy of >90%. Provided an additional validation set of the identified miRNAs on a larger cohort, we propose a diagnostic paradigm shift that sees molecular data and MRI biomarkers as the prebiopsy triage of patients at risk for PCa. This approach will allow for accurate patient allocation to biopsy, and for stratification into risk group categories, reducing overdiagnosis and overtreatment.

A flexible model-free prediction-based framework for feature ranking

Despite the availability of numerous statistical and machine learning tools for joint feature modeling, many scientists investigate features marginally, i.e., one feature at a time. This is partly due to training and convention but also roots in scientists' strong interests in simple visualization and interpretability. As such, marginal feature ranking for some predictive tasks, e.g., prediction of cancer driver genes, is widely practiced in the process of scientific discoveries. In this work, we focus on marginal ranking for binary classification, one of the most common predictive tasks. We argue that the most widely used marginal ranking criteria, including the Pearson correlation, the two-sample t test, and two-sample Wilcoxon rank-sum test, do not fully take feature distributions and prediction objectives into account. To address this gap in practice, we propose two ranking criteria corresponding to two prediction objectives: the classical criterion (CC) and the Neyman-Pearson criterion (NPC), both of which use model-free nonparametric implementations to accommodate diverse feature distributions. Theoretically, we show that under regularity conditions, both criteria achieve sample-level ranking that is consistent with their population-level counterpart with high probability. Moreover, NPC is robust to sampling bias when the two class proportions in a sample deviate from those in the population. This property endows NPC good potential in biomedical research where sampling biases are ubiquitous. We demonstrate the use and relative advantages of CC and NPC in simulation and real data studies. Our model-free objective-based ranking idea is extendable to ranking feature subsets and generalizable to other prediction tasks and learning objectives.

Clinical proteomics for prostate cancer: understanding prostate cancer pathology and protein biomarkers for improved disease management

Following the introduction of routine Prostate Specific Antigen (PSA) screening in the early 1990′s, Prostate Cancer (PCa) is often detected at an early stage. There are also a growing number of treatment options available and so the associated mortality rate is generally low. However, PCa is an extremely complex and heterogenous disease and many patients suffer disease recurrence following initial therapy. Disease recurrence commonly results in metastasis and metastatic PCa has an average survival rate of just 3–5 years. A significant problem in the clinical management of PCa is being able to differentiate between patients who will respond to standard therapies and those who may benefit from more aggressive intervention at an earlier stage. It is also acknowledged that for many men the disease is not life threatenting. Hence, there is a growing desire to identify patients who can be spared the significant side effects associated with PCa treatment until such time (if ever) their disease progresses to the point where treatment is required. To these important clinical needs, current biomarkers and clinical methods for patient stratification and personlised treatment are insufficient. This review provides a comprehensive overview of the complexities of PCa pathology and disease management. In this context it is possible to review current biomarkers and proteomic technologies that will support development of biomarker-driven decision tools to meet current important clinical needs. With such an in-depth understanding of disease pathology, the development of novel clinical biomarkers can proceed in an efficient and effective manner, such that they have a better chance of improving patient outcomes.

Urinary glycoproteins associated with aggressive prostate cancer

Background: There is an urgent need for the detection of aggressive prostate cancer. Glycoproteins play essential roles in cancer development, while urine is a noninvasive and easily obtainable biological fluid that contains secretory glycoproteins from the urogenital system. Therefore, here we aimed to identify urinary glycoproteins that are capable of differentiating aggressive from non-aggressive prostate cancer.

Methods: Quantitative mass spectrometry data of glycopeptides from a discovery cohort comprised of 74 aggressive (Gleason score ≥8) and 68 non-aggressive (Gleason score = 6) prostate cancer urine specimens were acquired via a data independent acquisition approach. The glycopeptides showing distinct expression profiles in aggressive relative to non-aggressive prostate cancer were further evaluated for their performance in distinguishing the two groups either individually or in combination with others using repeated 5-fold cross validation with logistic regression to build predictive models. Predictive models showing good performance from the discovery cohort were further evaluated using a validation cohort.

Results: Among the 20 candidate glycoproteins, urinary ACPP outperformed the other candidates. Urinary ACPP can also serve as an adjunct to serum PSA to further improve the discrimination power for aggressive prostate cancer (AUC= 0.82, 95% confidence interval 0.75 to 0.89). A three-signature panel including urinary ACPP, urinary CLU, and serum PSA displayed the ability to distinguish aggressive prostate cancer from non-aggressive prostate cancer with an AUC of 0.86 (95% confidence interval 0.8 to 0.92). Another three-signature panel containing urinary ACPP, urinary LOX, and serum PSA also demonstrated its ability in recognizing aggressive prostate cancer (AUC=0.82, 95% confidence interval 0.75 to 0.9). Moreover, consistent performance was observed from each panel when evaluated using a validation cohort.

Conclusion: We have identified glycopeptides of urinary glycoproteins associated with aggressive prostate cancer using a quantitative mass spectrometry-based glycoproteomic approach and demonstrated their potential to serve as noninvasive urinary glycoprotein biomarkers worthy of further validation by a multi-center study.

Identification of a three-miRNA signature as a novel prognostic model for papillary renal cell carcinoma

Background

Papillary renal cell carcinoma (pRCC) accounting for near 20% of renal cell carcinoma is the second most common histological subtype. MiRNAs have been demonstrated to played significant roles on predicting prognosis of patients with tumors. An appropriate and comprehensive miRNAs analysis based on a great deal of pRCC samples from The Cancer Genome Atlas (TCGA) will provide perspective in this field.

Methods

We integrated the expression of mRNAs, miRNAs and the relevant clinical data of 321 pRCC patients recorded in the TCGA database. The survival-related differential expressed miRNAs (sDEmiRs) were estimated by COX regression analysis. The high-risk group and the low-risk group were separated by the median risk score of the risk score model (RSM) based on three screened sDEmiRs. The target genes, underlying molecular mechanisms of these sDEmiRs were explored by computational biology. The expression levels of the three sDEmiRs and their correlations with clinicopathological parameters were further validated by qPCR.

Results

Based on univariate COX analysis (P < 0.001), eighteen differential expressed miRNAs (DEmiRs) were remarkably related with the overall survival (OS) of pRCC patients. Three sDEmiRs with the most significant prognostic values (miR-34a-5p, miR-410-3p and miR-6720-3p) were employed to establish the RSM which was certified as an independent prognosis factor and closely correlated with OS. In the verification of clinical samples, the overexpression of miR-410-3p and miR-6720-3p were detected to be associated with the advanced T-stages, while miR-34a-5p showed the reversed results.

Conclusion

The study developed a RSM based on the identified sDEmiRs with significant prognosis prediction values for pRCC patients. The results pave the avenue for establishing and optimizing a reliable and referable risk assessing model and provide novel insight into the researches of biomarkers and clinical treatment strategies.

microRNAs identified in prostate cancer: Correlative studies on response to ionizing radiation

As the most frequently diagnosed non-skin cancer in men and a leading cause of cancer-related death, understanding the molecular mechanisms that drive treatment resistance in prostate cancer poses a significant clinical need. Radiotherapy is one of the most widely used treatments for prostate cancer, along with surgery, hormone therapy, and chemotherapy. However, inherent radioresistance of tumor cells can reduce local control and ultimately lead to poor patient outcomes, such as recurrence, metastasis and death. The underlying mechanisms of radioresistance have not been fully elucidated, but it has been suggested that miRNAs play a critical role. miRNAs are small non-coding RNAs that regulate gene expression in every signaling pathway of the cell, with one miRNA often having multiple targets. By fine-tuning gene expression, miRNAs are important players in modulating DNA damage response, cell death, tumor aggression and the tumor microenvironment, and can ultimately affect a tumor’s response to radiotherapy. Furthermore, much interest has focused on miRNAs found in biofluids and their potential utility in various clinical applications. In this review, we summarize the current knowledge on miRNA deregulation after irradiation and the associated functional outcomes, with a focus on prostate cancer. In addition, we discuss the utility of circulating miRNAs as non-invasive biomarkers to diagnose, predict response to treatment, and prognosticate patient outcomes.

The ceRNA Network Has Potential Prognostic Value in Clear Cell Renal Cell Carcinoma: A Study Based on TCGA Database

Clear cell renal cell carcinoma (ccRCC) is a very common cancer in urology. Many evidences suggest that complex changed pathways take a nonnegligible part in the occurrence and development of ccRCC. Nevertheless, the underlying mechanism is not clear. In this study, the expression data between ccRCC and normal tissue samples in TCGA database were compared to distinguish differentially expressed genes (DEGs: mRNAs, miRNAs, and lncRNAs). Afterwards, we used GO enrichment and KEGG pathway enrichment analyses to explore the functions of these DEGs. We also found the correlation between three RNAs and created a competing endogenous RNA (ceRNA) network. Moreover, we used univariate Cox regression analysis to select DEGs that are connected with overall survival (OS) of ccRCC patients. We found 1652 mRNAs, 1534 lncRNAs, and 173 miRNAs that were distinguished in ccRCC compared with normal tissues. According to GO analysis, the maladjusted mRNAs are mainly concentrated in immune cell activation and kidney development, while according to KEGG, they are mainly concentrated in pathways related to cancer. A total of 5 mRNAs, 1 miRNA, and 4 lncRNAs were connected with patients' OS. In this article, a network of lncRNA-miRNA-mRNA was established; it is expected to be able to indicate possible molecular mechanisms for initial of ccRCC and provide a new viewpoint for diagnosis of ccRCC.