Diagnostic performance of expression of PCA3, Hepsin and miR biomarkers inejaculate in combination with serum PSA for the detection of prostate cancer

The Bone Microenvironment Soil in Prostate Cancer Metastasis: An miRNA Approach

Bone metastatic prostate cancer (PCa) is associated with a high risk of mortality. Changes in the expression pattern of miRNAs seem to be related to early aspects of prostate cancer, as well as its establishment and proliferation, including the necessary steps for metastasis. Here we compiled, for the first time, the important roles of miRNAs in the development, diagnosis, and treatment of bone metastasis, focusing on recent in vivo and in vitro studies. PCa exosomes are proven to promote metastasis-related events, such as osteoblast and osteoclast differentiation and proliferation. Aberrant miRNA expression in PCa may induce abnormal bone remodeling and support tumor development. Furthermore, miRNAs are capable of binding to multiple mRNA targets, a dynamic property that can be harnessed for the development of treatment tools, such as antagomiRs and miRNA mimics, which have emerged as promising candidates in PCa treatment. Finally, miRNAs may serve as noninvasive biomarkers, as they can be detected in tissue and bodily fluids, are highly stable, and show differential expression between nonmetastatic PCa and bone metastatic samples. Taken together, the findings underscore the importance of miRNA expression profiles and miRNA-based tools as rational technologies to increase the quality of life and longevity of patients.

Clinical Significance of Hepsin and Underlying Signaling Pathways in Prostate Cancer

The hepsin gene encodes a type II transmembrane serine protease. Previous studies have shown the overexpression of hepsin in prostate cancer, and the dysregulation of hepsin promotes cancer cell proliferation, migration, and metastasis in vitro and in vivo. The review incorporated with our work showed that hepsin expression levels were specifically increased in prostate cancer, and higher expression in metastatic tumors than in primary tumors was also observed. Moreover, increased expression was associated with poor outcomes for patients with prostate cancer. Using in silico protein–protein interaction prediction, mechanistic analysis showed that hepsin interacted with eight other oncogenic proteins, whose expression was significantly correlated with hepsin expression in prostate cancer. The oncogenic functions of hepsin are mainly linked to proteolytic activities that disrupt epithelial integrity and regulatorily interact with other genes to influence cell-proliferation, EMT/metastasis, inflammatory, and tyrosine-kinase-signaling pathways. Moreover, genomic amplifications of hepsin, not deletions or other alterations, were significantly associated with prostate cancer metastasis. Targeting hepsin using a specific inhibitor or antibodies significantly attenuates its oncogenic behaviors. Therefore, hepsin could be a novel biomarker and therapeutic target for prostate cancer.

Semen sampling as a simple, noninvasive surrogate for prostate health screening

The detection rates for prostate cancer (pCa) by invasive biopsy are high, fully justifying its use in confirmatory testing. False-positive results of prior, relatively insensitive screening tests, however, can lead to expensive and often unnecessary surgery. Several reports have suggested the potential use of the ejaculate to screen for prostate conditions. Hitherto, the potential impact of sterilization on the diagnostic potential of seminal plasma screening has not been examined. Herein, we report cellular and molecular comparisons of semen samples obtained from normal (N = 5), vasectomized (N = 5) and prostate pathology patients (N = 4; confirmed by a biopsy) that were centrifuged over 60% PureSperm cushions. Non-penetrating cells were washed prior to immunocytochemistry with prostatic epithelial cell markers including PSMA, NKX3.1 and CD24. KRT18 was used to highlight epithelial cells in these samples. RNA sequencing was then used to identify differentially expressed small RNAs associated with vasectomy and prostate pathology. Specific gene transcripts were confirmed by RT-qPCR. PMSA⁺/KRT18⁺, CD24⁺/KRT18⁺ and NKX3.1/⁺KRT18⁺ cells were observed, albeit infrequently in most processed semen samples by indirect immunocytochemistry. Targeted RT-qPCR supported their enrichment, along with their putative designation as prostatic luminal cells. Small RNAs in seminal plasma were highly heterogeneous, with tRNAs and miRNAs being the dominant forms. Hsa-miR-143 and hsa-miR-199 were among the most prominent of the differentially expressed miRNAs upregulated in samples with prostate pathology but not vasectomy. The targets of these small RNAs illustrate biological processes involved among others in transcription regulation and collagen metabolism. Our outcomes strongly support an appraisal of selected biologically meaningful small RNAs of ejaculate semen for prostate health screening. A long-term goal would be a simple, routine, noninvasive test for monitoring prostate health, potentially among younger men.

MiR-182-5p and miR-375-3p Have Higher Performance Than PSA in Discriminating Prostate Cancer from Benign Prostate Hyperplasia

Simple Summary

Prostate cancer (PCa) is the most prevalent neoplasia among men worldwide but is commonly “mimicked” by benign prostate hyperplasia (BPH). Their discrimination by the prostate-specific antigen (PSA) is often uncertain, resulting in lengthy diagnostic protocols and recurrent tissue biopsies. The development of more appropriate biomarkers, possibly present in liquid biopsy, would significantly improve PCa and BPH patient management. To address this challenge, in this study miR-375-3p, miR-182-5p, miR-21-5p, and miR-148a-3p were analyzed by ddPCR in blood plasma and seminal plasma of patients with PCa and BPH prior to tissue biopsy. Among other findings, miR-182-5p and miR-375-3p were found to have statistically significantly higher expression in PCa patients compared to BPH in blood, with a combined specificity of 90.2% to predict positive or negative biopsy results. The data presented emphasize the great potential of miRNAs as liquid biopsy biomarkers for PCa.

Abstract

Prostate cancer (PCa) is the most commonly diagnosed neoplasm among men. Since it often resembles benign prostate hyperplasia (BPH), biomarkers with a higher differential value than PSA are required. Epigenetic biomarkers in liquid biopsies, especially miRNA, could address this challenge. The absolute expression of miR-375-3p, miR-182-5p, miR-21-5p, and miR-148a-3p were quantified in blood plasma and seminal plasma of 65 PCa and 58 BPH patients by digital droplet PCR. The sensitivity and specificity of these microRNAs were determined using ROC curve analysis. The higher expression of miR-182-5p and miR-375-3p in the blood plasma of PCa patients was statistically significant as compared to BPH (p = 0.0363 and 0.0226, respectively). Their combination achieved a specificity of 90.2% for predicting positive or negative biopsy results, while PSA cut-off of 4 µg/L performed with only 1.7% specificity. In seminal plasma, miR-375-3p, miR-182-5p, and miR-21-5p showed a statistically significantly higher expression in PCa patients with PSA >10 µg/L compared to ones with PSA ≤10 µg/L. MiR-182-5p and miR-375-3p in blood plasma show higher performance than PSA in discriminating PCa from BPH. Seminal plasma requires further investigation as it represents an obvious source for PCa biomarker identification.

Radiomic and Genomic Machine Learning Method Performance for Prostate Cancer Diagnosis: Systematic Literature Review

BACKGROUND

Machine learning algorithms have been drawing attention at the joining of pathology and radiology in prostate cancer research. However, due to their algorithmic learning complexity and the variability of their architecture, there is an ongoing need to analyze their performance.

OBJECTIVE

This study assesses the source of heterogeneity and the performance of machine learning applied to radiomic, genomic, and clinical biomarkers for the diagnosis of prostate cancer. One research focus of this study was on clearly identifying problems and issues related to the implementation of machine learning in clinical studies.

METHODS

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol, 816 titles were identified from the PubMed, Scopus, and OvidSP databases. Studies that used machine learning to detect prostate cancer and provided performance measures were included in our analysis. The quality of the eligible studies was assessed using the QUADAS-2 (quality assessment of diagnostic accuracy studies-version 2) tool. The hierarchical multivariate model was applied to the pooled data in a meta-analysis. To investigate the heterogeneity among studies, I2 statistics were performed along with visual evaluation of coupled forest plots. Due to the internal heterogeneity among machine learning algorithms, subgroup analysis was carried out to investigate the diagnostic capability of machine learning systems in clinical practice.

RESULTS

In the final analysis, 37 studies were included, of which 29 entered the meta-analysis pooling. The analysis of machine learning methods to detect prostate cancer reveals the limited usage of the methods and the lack of standards that hinder the implementation of machine learning in clinical applications.

CONCLUSIONS

The performance of machine learning for diagnosis of prostate cancer was considered satisfactory for several studies investigating the multiparametric magnetic resonance imaging and urine biomarkers; however, given the limitations indicated in our study, further studies are warranted to extend the potential use of machine learning to clinical settings. Recommendations on the use of machine learning techniques were also provided to help researchers to design robust studies to facilitate evidence generation from the use of radiomic and genomic biomarkers.

Prostac: A New Composite Score With Potential Predictive Value in Prostate Cancer

Prostate cancer (PCa) is the most commonly diagnosed solid organ cancer in men worldwide. Current diagnosis of PCa includes use of initial prostate specific antigen assay which has a high false positive rate, low specificity, and low sensitivity. The side effects of unnecessary prostate biopsies that healthy men are subjected to, often result in unintended health complications. New PCa biomarkers are being discovered to address this unmet need. Here, we report on the creation of a composite score (Prostac) based on three recently discovered PCa biomarkers, Plasmacytoma Variant Translocation 1 (PVT1) exons 4A, 4B, and 9. Statistical analysis of copy numbers derived from a real-time quantitative polymerase chain (qPCR) reaction - based assay, showed these PCa biomarkers to be linearly separable and significantly over expressed in PCa epithelial cells. We train a supervised learning algorithm using support vector machines to generate a classification hyperplane from which a user-friendly composite score is developed. Cross validation of Prostac using data from prostate epithelial cells (RWPE1) and PCa cells (MDA PCa 2b) accurately classified 100% of PCa cells. Creation of the Prostac score lays the groundwork for clinical trial of its use in PCa diagnosis.

Identification of Key MicroRNAs and Mechanisms in Prostate Cancer Evolution Based on Biomarker Prioritization Model and Carcinogenic Survey

Background: Prostate cancer (PCa) is occurred with increasing incidence and heterogeneous pathogenesis. Although clinical strategies are accumulated for PCa prevention, there is still a lack of sensitive biomarkers for the holistic management in PCa occurrence and progression. Based on systems biology and artificial intelligence, translational informatics provides new perspectives for PCa biomarker prioritization and carcinogenic survey.

Methods: In this study, gene expression and miRNA-mRNA association data were integrated to construct conditional networks specific to PCa occurrence and progression, respectively. Based on network modeling, hub miRNAs with significantly strong single-line regulatory power were topologically identified and those shared by the condition-specific network systems were chosen as candidate biomarkers for computational validation and functional enrichment analysis.

Results: Nine miRNAs, i.e., hsa-miR-1-3p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-182-5p, hsa-miR-198, hsa-miR-22-3p, hsa-miR-24-3p, hsa-miR-34a-5p, and hsa-miR-499a-5p, were prioritized as key players for PCa management. Most of these miRNAs achieved high AUC values (AUC > 0.70) in differentiating different prostate samples. Among them, seven of the miRNAs have been previously reported as PCa biomarkers, which indicated the performance of the proposed model. The remaining hsa-miR-22-3p and hsa-miR-499a-5p could serve as novel candidates for PCa predicting and monitoring. In particular, key miRNA-mRNA regulations were extracted for pathogenetic understanding. Here hsa-miR-145-5p was selected as the case and hsa-miR-145-5p/NDRG2/AR and hsa-miR-145-5p/KLF5/AR axis were found to be putative mechanisms during PCa evolution. In addition, Wnt signaling, prostate cancer, microRNAs in cancer etc. were significantly enriched by the identified miRNAs-mRNAs, demonstrating the functional role of the identified miRNAs in PCa genesis.

Conclusion: Biomarker miRNAs together with the associated miRNA-mRNA relations were computationally identified and analyzed for PCa management and carcinogenic deciphering. Further experimental and clinical validations using low-throughput techniques and human samples are expected for future translational studies.

Can the combination of biparametric magnetic resonance imaging and PSA-related indicators predict the prostate biopsy outcome?

To assess the value of biparametric magnetic resonance imaging (bpMRI) for detecting and ruling out prostate cancer in patients with elevated prostate-specific antigen (PSA). The basic information and bpMRI images of enrolled patients who took transperineal template saturate biopsy were retrospectively collected for analysis. Based on our results, we found that free/total PSA, and PI-RADS score were independent risk factors of PCa (p < .05), the PSA density, PI-RADS score were the independent risk factors of csPCa (p < .05). PI-RADS score threshold of 3 could achieve the highest Yonder index for predicting PCa, and PI-RADS score threshold of 4 could achieve the highest Yonder index for predicting csPCa. Therefore, we draw a conclusion that PI-RADSv2 score-based bpMRI could diminish the unnecessary prostate biopsies in patients with elevated PSA when combined with other PSA-related indicators.

Personalized strategies in population screening for prostate cancer

This review discusses evidence for population-based screening with contemporary screening tools. In Europe, prostate-specific antigen (PSA)-based screening led to a relative reduction of prostate cancer (PCa) mortality, but also to a substantial amount of overdiagnosis and unnecessarily biopsies. Risk stratification based on a single variable (a clinical variable or based on the presence of a lesion on prostate imaging) or based on multivariable approaches can aid in reducing unnecessary prostate biopsies and overdiagnosis by selecting men who can benefit from further clinical assessment. Multivariable approaches include clinical variables, and biomarkers, often combined in risk calculators or nomograms. These risk calculators can also incorporate the result of MRI imaging. In general, as compared to a purely PSA based approach, the combination of relevant prebiopsy information results in superior selection of men at higher risk of harboring clinically significant prostate cancer. Currently, it is not possible to draw any conclusions on the superiority of these multivariable risk-based approaches since head-to-head comparisons are virtually lacking. Recently initiated large population-based screening studies in Finland, Germany and Sweden, incorporating various multivariable risk stratification approaches will hopefully give more insight in whether the harm-benefit ratio can be improved, that is, maintain (or improving) the ability to reduce metastatic disease and prostate cancer mortality while reducing harm caused by unnecessary testing and overdiagnosis including related overtreatment.

HOXC6 in the prognosis of prostate cancer

Aims: Our study aimed to investigate the expression and prognostic role of homeobox C6 (HOXC6) in prostate cancer (PCa). Methods: Relative expression of HOXC6 at mRNA and protein levels in tissues and cell lines of PCa were measured using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analysis, respectively. Association between HOXC6 expression and clinical factors was analyzed by Chi-square test. HOXC6 effects on the proliferation, invasion and metastasis of PCa cells were severally examined through CCK-8 and transwell assays. Results: Relative expressions of HOXC6 at mRNA and protein levels were obviously higher in both PCa tissues and cells than in adjacent non-cancerous tissues and normal human prostate epithelial cells (p < .05). Chi-square test demonstrated that high expression of HOXC6 was significantly associated with PSA concentration, Gleason score and TNM stage (p < .05). The down-regulation of HOCX6 remarkably inhibited the proliferation, migration and invasion of PCa cells. Kaplan-Meier analysis showed that patients with high HOXC6 expression had shorter overall survival than those with low HOXC6 expression (log rank test, p < .001). Conclusion: Up-regulated HOXC6, in PCa patients, could not only participate in the progression of PCa but also function as an independent prognostic marker for the cancer.

A New Era of Prostate Cancer Precision Medicine

Prostate cancer is the second most common male cancer affecting Western society. Despite substantial advances in the exploration of prostate cancer biomarkers and treatment strategies, men are over diagnosed with inert prostate cancer, while there is also a substantial mortality from the invasive disease. Precision medicine is the management of treatment profiles across different cancers predicting therapies for individual cancer patients. With strategies including individual genomic profiling and targeting specific cancer pathways, precision medicine for prostate cancer has the potential to impose changes in clinical practices. Some of the recent advances in prostate cancer precision medicine comprise targeting gene fusions, genome editing tools, non-coding RNA biomarkers, and the promise of liquid tumor profiling. In this review, we will discuss these recent scientific advances to scale up these approaches and endeavors to overcome clinical barriers for prostate cancer precision medicine.

Role of MicroRNAs in Treatment Response in Prostate Cancer

Prostate cancer (PCa) is the most common non-skin cancer in men worldwide, resulting in significant mortality and morbidity. Depending on the grade and stage of the cancer, patients may be given radiation therapy, hormonal therapy, or chemotherapy. However, more than half of these patients develop resistance to treatment, leading to disease progression and metastases, often with lethal consequences. MicroRNAs (miRNAs) are short, non-coding RNAs, which regulate numerous physiological as well as pathological processes, including cancer. miRNAs mediate their regulatory effect predominately by binding to the 3'-untranslated region (UTR) of their target mRNAs. In this review, we will describe the mechanisms by which miRNAs mediate resistance to radiation and drug therapy (i.e. hormone therapy and chemotherapy) in PCa, including control of apoptosis, cell growth and proliferation, autophagy, epithelial-to-mesenchymal transition (EMT), invasion and metastasis, and cancer stem cells (CSCs). Furthermore, we will discuss the utility of circulating miRNAs isolated from different body fluids of prostate cancer patients as non-invasive biomarkers of cancer detection, disease progression, and therapy response. Finally, we will shortlist the candidate miRNAs, which may have a role in drug and radioresistance, that could potentially be used as predictive biomarkers of treatment response.

Semen miRNAs Contained in Exosomes as Non-Invasive Biomarkers for Prostate Cancer Diagnosis

Although it is specific for prostatic tissue, serum prostate-specific antigen (PSA) screening has resulted in an over-diagnosis of prostate cancer (PCa) and many unnecessary biopsies of benign disease due to a well-documented low cancer specificity, thus improvement is required. We profiled the expression level of miRNAs contained in semen exosomes from men with moderately increased PSA levels to assess their usefulness, either alone or in addition to PSA marker, as non-invasive biomarkers, for the early efficient diagnosis and prognosis of PCa. An altered miRNA expression pattern was found by a high throughput profiling analysis in PCa when compared with healthy individuals (HCt) exosomal semen samples. The presence of vasectomy was taken into account for the interpretation of results. Fourteen miRNAs were selected for miRNA validation as PCa biomarkers in a subsequent set of semen samples. In this explorative study, we describe miRNA-based models, which included miRNA expression values together with PSA levels, that increased the classification function of the PSA screening test with diagnostic and/or prognostic potential: [PSA + miR-142-3p + miR-142-5p + miR-223-3p] model (AUC:0,821) to discriminate PCa from BPH (Sn:91,7% Sp:42,9% vs Sn:100% Sp:14,3%); and [PSA + miR-342-3p + miR-374b-5p] model (AUC: 0,891) to discriminate between GS ≥ 7 tumours and men presenting PSA ≥ 4 ng/ml with no cancer or GS6 tumours (Sn:81,8% Sp:95% vs Sn:54,5% Sp:90%). The pathway analysis of predicted miRNA target genes supports a role for these miRNAs in PCa aetiology and/or progression. Our study shows semen exosome miRNA-based models as molecular biomarkers with the potential to improve PCa diagnosis/prognosis efficiency. As the next step, further prospective studies on larger cohorts of patients are required to validate the diagnostic and/or prognostic role of the miRNA panel before it could be adopted into clinical practice.

microRNA diagnostic panel for Alzheimer's disease and epigenetic trade-off between neurodegeneration and cancer

microRNAs (miRNAs) have been extensively studied as potential biomarkers for Alzheimer's disease (AD). Their profiles have been analyzed in blood, cerebrospinal fluid (CSF) and brain tissue. However, due to the high variability between the reported data, stemming from the lack of methodological standardization and the heterogeneity of AD, the most promising miRNA biomarker candidates have not been selected. Our literature review shows that out of 137 miRNAs found to be altered in AD blood, 36 have been replicated in at least one independent study, and out of 166 miRNAs reported as differential in AD CSF, 13 have been repeatedly found. Only 3 miRNAs have been consistently reported as altered in three analyzed specimens: blood, CSF and the brain (hsa-miR-146a, hsa-miR-125b, hsa-miR-135a). Nonetheless, all 36 repeatedly differential miRNAs in AD blood are promising as components of the diagnostic panel. Given their predicted functions, such miRNA panel may report multiple pathways contributing to AD pathology, enabling the design of personalized therapies. In addition, the analysis revealed that the miRNAs dysregulated in AD overlap highly with miRNAs implicated in cancer. However, the directions of the miRNA changes are usually opposite in cancer and AD, indicative of an epigenetic trade-off between the two diseases.

Diagnostic performance of PCA3 and hK2 in combination with serum PSA for prostate cancer

OBJECTIVES

The prostate cancer gene 3 (PCA3), human kallikrein 2, and miRNA-141 are promising prostate cancer (Pca) specific biomarkers. Our aim was to evaluate the detection of PCA3, human glandular kallikrein 2 (hk2), and miRNA-141 mRNA in peripheral blood of patients received prostate biopsy. What's more, we want to detect the value of combination of PSA (prostate specific antigen) in the early diagnosis of PCa.

MATERIALS AND METHODS

Hundred patients were divided into 2 groups according to the results of pathologic diagnosis. Quantitative real-time PCR (qRT-PCR) was used to evaluate the mRNA of PCA3, hk2, and miRNA-141 in peripheral blood. At the same time, analyze those clinical outcomes used in the patients. We compared these different outcomes to evaluate the value of new molecular markers.

RESULTS

The level of mRNA of PCA3, hK2, and miR-141 in Pca group were significantly higher than that in BPH. PSA had the highest sensitivity in predicting Pca diagnosis (76.7%); PCA3 had the highest specificity (82.5%). And the combination of PCA3, PSA, and hK2 improved area under the curve (AUC)-receiver operating characteristic (ROC) curve largely, especially those with PSA 4-10ng/mL.

CONCLUSIONS

PCA3, hK2, and miRNA-141 were biomarkers of Pca with potential clinical application value, especially in patients with PSA gray area. Combining PCA3, PSA, and hK2 performed better than individual biomarkers alone in predicting Pca.

The potential of microRNAs as human prostate cancer biomarkers: A meta-analysis of related studies

Prostate cancer (PC) is a very important kind of male malignancies. When PC evolves into a stage of hormone resistance or metastasis, the fatality rate is very high. Currently, discoveries and advances in miRNAs as biomarkers have opened the potential for the diagnosis of PC, especially early diagnosis. miRNAs not only can noninvasively or minimally invasively identify PC, but also can provide the data for optimization and personalization of therapy. Moreover, miRNAs have been shown to play an important role to predict prognosis of PC. The purpose of this meta‐analysis is to integrate the currently published expression profile data of miRNAs in PC, and evaluate the value of miRNAs as biomarkers for PC. All of relevant records were selected via electronic databases: Pubmed, Embase, Cochrane, and CNKI based on the assessment of title, abstract, and full text. we extracted mean ± SD or fold change of miRNAs expression levels in PC versus BPH or normal controls. Pooled hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS) and recurrence‐free survival (RFS), were also calculated to detect the relationship between high miRNAs expression and PC prognosis. Selected 104 articles were published in 2007‐2017. According to the inclusion criteria, 104 records were included for this meta‐analysis. The pooled or stratified analyze showed 10 up‐regulated miRNAs (miR‐18a, miR‐34a, miR‐106b, miR‐141, miR‐182, miR‐183, miR‐200a/b, miR‐301a, and miR‐375) and 14 down‐regulated miRNAs (miR‐1, miR‐23b/27b, miR‐30c, miR‐99b, miR‐139‐5p, miR‐152, miR‐187, miR‐204, miR‐205, miR‐224, miR‐452, miR‐505, and let‐7c) had relatively good diagnostic and predictive potential to discriminate PC from BPH/normal controls. Furthermore, high expression of miR‐32 and low expression of let‐7c could be used to differentiate metastatic PC from local/primary PC. Additional interesting findings were that the expression profiles of five miRNAs (miR‐21, miR‐30c, miR‐129, miR‐145, and let‐7c) could predict poor RFS of PC, while the evaluation of miR‐375 was associated with worse OS. miRNAs are important regulators in PC progression. Our results indicate that miRNAs are suitable for predicting the different stages of PC. The detection of miRNAs is an effective way to control patient's prognosis and evaluate therapeutic efficacy. However, large‐scale detections based on common clinical guidelines are still necessary to further validate our conclusions, due to the bias induced by molecular heterogeneity and differences in study design and detection methods.

Potential Role of MicroRNA-375 as Biomarker in Human Cancers Detection: A Meta-Analysis

The association between circulating microRNA-375 (miR-375) expression and cancers has been studied; however, the results are inconsistent. We searched PubMed, Embase, and Web of Science for studies concerning the diagnostic value of miR-375 for cancer. The bivariate meta-analysis model was employed to summarize sensitivity, specificity, and diagnostic odds ratio (DOR) for miR-375 in the diagnosis of cancer. Summary receiver operating characteristic (SROC) curve analysis and the area under the curve (AUC) were also used to check the overall test performance. A total of 645 cancer patients and 421 cancer-free individuals from 12 studies were contained in this meta-analysis. The summary estimates revealed that the pooled sensitivity was 78% (95% confidence interval (CI): 64%-87%), the specificity was 74% (95% CI: 62%-84%), the DOR was 10.04 (95% CI: 6.01-16.77), and the AUC was 0.82 (95% CI: 0.79-0.85). In addition, we found that the diagnostic effect of miR-375 varies according to the race and cancer type. Our data suggest that miR-375 profiling has a potential to be used as a screening test for cancers but the specific race and cancer should be considered. More studies on the diagnostic value of miR-375 for cancer are needed in the future.

Seminal plasma enables selection and monitoring of active surveillance candidates using nuclear magnetic resonance-based metabolomics: A preliminary investigation

Background

Diagnosis and monitoring of localized prostate cancer requires discovery and validation of noninvasive biomarkers. Nuclear magnetic resonance (NMR)-based metabolomics of seminal plasma reportedly improves diagnostic accuracy, but requires validation in a high-risk clinical cohort.

Materials and methods

Seminal plasma samples of 151 men being investigated for prostate cancer were analyzed with ¹H-NMR spectroscopy. After adjustment for buffer (add-to-subtract) and endogenous enzyme influence on metabolites, metabolite profiling was performed with multivariate statistical analysis (principal components analysis, partial least squares) and targeted quantitation.

Results

Seminal plasma metabolites best predicted low- and intermediate-risk prostate cancer with differences observed between these groups and benign samples. Lipids/lipoproteins dominated spectra of high grade samples with less metabolite contributions. Overall prostate cancer prediction using previously described metabolites was not validated.

Conclusion

Metabolomics of seminal plasma in vitro may assist urologists with diagnosis and monitoring of either low or intermediate grade prostate cancer. Less clinical benefit may be observed for high-risk patients. Further investigation in active surveillance cohorts, and/or in combination with in vivo magnetic resonance spectroscopic imaging may further optimize localized prostate cancer outcomes.

miRNAs associated with prostate cancer risk and progression

Prostate cancer is the most common malignancy among men in the US. Though considerable improvement in the diagnosis of prostate cancer has been achieved in the past decade, predicting disease outcome remains a major clinical challenge. Recent expression profiling studies in prostate cancer suggest microRNAs (miRNAs) may serve as potential biomarkers for prostate cancer risk and disease progression. miRNAs comprise a large family of about 22-nucleotide-long non-protein coding RNAs, regulate gene expression post-transcriptionally and participate in the regulation of numerous cellular processes. In this review, we discuss the current status of miRNA in studies evaluating the disease progression of prostate cancer. The discussion highlights key findings from previous studies, which reported the role of miRNAs in risk and progression of prostate cancer, providing an understanding of the influence of miRNA on prostate cancer. Our review indicates that somewhat consistent results exist between these studies and reports on several prostate cancer related miRNAs. Present promising candidates are miR-1, −21, 106b, 141, −145, −205, −221, and −375, which are the most frequently studied and seem to be the most promising for diagnosis and prognosis for prostate cancer. Nevertheless, the findings from previous studies suggest miRNAs may play an important role in the risk and progression of prostate cancer as promising biomarkers.

MiR-193b promoter methylation accurately detects prostate cancer in urine sediments and miR-34b/c or miR-129-2 promoter methylation define subsets of clinically aggressive tumors

Background

Contemporary challenges of prostate cancer (PCa) include overdiagnosis and overtreatment, entailing the need for novel clinical tools to improve risk stratification and therapy selection. PCa diagnosis and prognostication might be perfected using epigenetic biomarkers, among which aberrant DNA methylation of microRNA promoters has not been systematically explored. Herein, we identified aberrantly methylated microRNAs promoters in PCa and assessed its diagnostic and prognostic biomarker potential.

Methods

Using HumanMethylation450 BeadChip-based analysis differentially methylated CpGs in microRNA promoters were identified. Promoter methylation of six microRNAs (miR-34b/c, miR-129-2, miR-152, miR-193b, miR-663a and miR-1258) was analyzed by qMSP in three sets (180 prostatectomies, 95 urine sediments and 74 prostate biopsies). Biomarkers’ diagnostic (validity estimates) and prognostic [disease-free (DFS) and disease-specific survival (DSS)] performance was assessed.

Results

Significantly higher promoter methylation levels in PCa were confirmed for six candidate microRNAs. Except for miR-152, all displayed AUC values higher than 0.90, with miR-1258 and miR-193b disclosing the best performance (AUC = 0.99 and AUC = 0.96, respectively). In urine samples, miR-193b showed the best performance (91.6% sensitivity, 95.7% specificity, AUC = 0.96). Moreover, higher miR-129-2 independently predicted for shorter DSS and miR−34b/c methylation levels independently predicted for shorter DFS and DSS.

Conclusions

Quantitative miR-193b, miR-129-2 and miR-34b/c promoter methylation might be clinically useful PCa biomarkers for non-invasive detection/diagnosis and prognostication, both in tissue and urine samples.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-017-0604-0) contains supplementary material, which is available to authorized users.

The utility of urine-circulating miRNAs for detection of prostate cancer

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.

miR-1207-3p Is a Novel Prognostic Biomarker of Prostate Cancer

MicroRNAs (miRNAs) have been found to be dysregulated in prostate cancer (PCa). In this study, we investigated if miR-1207-3p is capable of distinguishing between indolent and aggressive PCa and if it contributes to explaining the disproportionate aggressiveness of PCa in men of African ancestry (moAA). A total of 404 patients with primary adenocarcinoma of the prostate were recruited between 1988 and 2003 at the Moffitt Cancer Center, Tampa, FL, USA. Patient clinicopathological features and demographic characteristics such as race were identified. RNA samples from 404 postprostatectomy prostate tumor tissue samples were analyzed by real-time quantitative reverse transcription polymerase chain reaction for the mRNA expression of miR-1207-3p. miR-1207-3p expression in PCa that resulted in overall death or PCa-specific death is significantly higher than in PCa cases that did not. The same positive correlation holds true for other clinical characteristics such as biochemical recurrence, Gleason score, clinical stage, and prostate-specific antigen level. Furthermore, miR-1207-3p expression was significantly less in moAA in comparison to Caucasian men. We also evaluated whether miR-1207-3p is associated with clinical outcomes adjusted for age at diagnosis and tumor stage in the modeling. Using competing risk regression, the PCa patients with a high miR-1207-3p expression (≥6 vs 3) had a high risk to develop PCa recurrence (hazard rate = 2.5, P < .001) adjusting for age at diagnosis and tumor stage. In conclusion, miR-1207-3p is a promising novel prognostic biomarker for PCa. Furthermore, miR-1207-3p may also be important in explaining the disproportionate aggressiveness of PCa in moAA.

Progress and potential of exosome analysis for early pancreatic cancer detection

INTRODUCTION

Pancreatic cancer (PaCa) is the most deadly malignancy, due to late diagnosis prohibiting surgery. Thus, strong efforts are taken improving early diagnosis via biomarkers recovered in the serum of PaCa patients.

AREAS COVERED

One promising option are PaCa-derived exosomes in patients' sera. Exosomes, small vesicles delivered by live cells and recovered in all body fluids, are a powerful diagnostic tool due to relative stability and composition covering the whole range of cancer-related biomarkers including proteins, metabolites, DNA, DNA modifications, coding and noncoding RNA. We discuss the mechanisms accounting for the condensed packaging of biomarkers, refer to studies using PaCa serum-exosomes for diagnosis. Based on an extensive literature search, we outline questions that answers may help establishing a serum-exosome-based screening for early PaCa detection. Expert commentary: Improved proteomic and genomic characterization and progress in the biogenesis of exosomes will allow for optimized and unified screening panels for PaCa diagnosis via TEX in body fluids.

Prostate-based biofluids for the detection of prostate cancer: A comparative study of the diagnostic performance of cell-sourced RNA biomarkers

BACKGROUND

Prostate cancer (PCa) diagnosis requires improvement with the aid of more accurate biomarkers. Postejaculate urethral washings (PEUW) could be a physiological equivalent to urine obtained following rectal prostatic massage, the current basis for the prostate cancer antigen 3 (PCA3) test. The aim of this study was to investigate if PEUW contained prostate-based material, evidenced by the presence of prostate specific antigen (PSA), and to evaluate the diagnostic performance of PEUW-based biomarkers.

METHODS

Male patients referred for elevated serum PSA or abnormal digital rectal examination provided ejaculate and PEUW samples. PSA, PCA3, and β2-microglobulin (β2M) were quantified in ejaculate and PEUW and compared with absolute and clinically significant (according to D'Amico criteria) PCa presence, as determined by biopsies. Diagnostic performance was determined and compared with serum PSA using receiver operating characteristic analysis.

RESULTS

From 83 patients who provided PEUW samples, paired analysis with ejaculate samples was possible for 38 patients, while analysis in an unpaired, extended cohort was possible for 62 patients. PSA and PCA3 were detected in PEUW, normalized to β2M, and PCA3:PSA was calculated. In predicting absolute PCa status, PCA3:β2M in ejaculate [area under the curve (AUC) 0.717] and PEUW (AUC 0.569) were insignificantly better than PCA3:PSA (AUC 0.668 and 0.431, respectively) and comparable with serum PSA (AUC 0.617) with similar trends observed for the extended cohort. When considering clinically significant PCa presence, serum PSA in the comparison (AUC 0.640) and extended cohorts (AUC 0.665) was comparable with PCA3: β2M (AUC 0.667) and PCA3:PSA (AUC 0.605) in ejaculate, with lower estimates for PEUW in the comparison (PCA3: β2M AUC 0.496; PCA3:PSA AUC 0.342) and extended (PCA3: β2M AUC 0.497; PCA3:PSA AUC 0.469) cohorts. The statistical analysis was limited by sample size.

CONCLUSION

PEUW contains prostatic material, but has limited diagnostic accuracy when considering cell-derived DNA analysis. PCA3-based markers in ejaculate are comparable to serum PSA and digital rectal examination-urine markers.

Appraising MicroRNA-155 as a Noninvasive Diagnostic Biomarker for Cancer Detection: A Meta-Analysis

Cancer has been a major public health issue all over the world and cancer patients diagnosed at early stages have a comparatively favorable prognosis. The association between specific dysregulated expressed microRNA-155 (miRNA-155, miR-155) and tumorigenesis has been identified by numerous studies. However, perplexity and inconsistence arise from a wide range of studies due to heterogeneity. Therefore, this meta-analysis was carried out to validate the association between miR-155 and tumorigenesis together with the clinical applicability of miR-155.Relevant studies were searched, identified, and selected from PubMed, Embase, Cochrane, Sinomed, and Wanfang database until July 5, 2015. Then, the sensitivity, specificity, and area under the summary receiver operator characteristic curve (AUC) were calculated to assess the overall performance miR-155 for cancer detection.A total of 25 studies were included in the meta-analysis with a total number of 1896 cancer patients and 1226 healthy controls. The overall sensitivity and specificity was 76.8% (95%CI: 71.1-81.7%) and 82.9% (95% CI: 77.5-87.3%), respectively. In addition, the pooled AUC and partial AUC was 0.867 and 0.718, respectively. Results from subgroup analyses suggested that the diagnostic accuracy of miR-155 in the Caucasian group was significantly higher than that in the Asian group. Similarly, serum sample type may provide better diagnostic value of miR-155 than plasma. Apart from that, miR-155 in breast cancer achieved the highest accuracy compared with miR-155 in other types of cancer.Results from meta-analysis suggested that miR-155 had great potential as a novel noninvasive biomarker for human cancer detection, particularly when breast cancer or Caucasian is involved. However, well-designed cohort or case control studies with large sample size should be implemented to confirm the diagnostic value of miR-155.

The Clinical Relevance of Long Non-Coding RNAs in Cancer

Non-coding RNAs have long been associated with cancer development and progression, and since their earliest discovery, their clinical potential in identifying and characterizing the disease has been pursued. Long non-coding (lncRNAs), a diverse class of RNA transcripts >200 nucleotides in length with limited protein coding potential, has been only modestly studied relative to other categories of non-coding RNAs. However, recent data suggests they too may be important players in cancer. In this article, we consider the value of lncRNAs in the clinical setting, and in particular their potential roles as diagnostic and prognostic markers in cancer. Furthermore, we summarize the most significant studies linking lncRNA expression in human biological samples to cancer outcomes. The diagnostic sensitivity, specificity and validity of these non-coding RNA transcripts is compared in the various biological compartments in which they have been detected including tumor tissue, whole body fluids and exosomes.