A Quest to Identify Prostate Cancer Circulating Biomarkers with a Bench-to-Bedside Potential

Development and Validation of a Urinary microRNA Biomarker Panel as a Tool for Early Detection of Prostate Cancer in a Chinese Population

Introduction: Urinary microRNAs (miRNAs) may serve as promising biomarkers for non-invasive early detection of prostate cancer (PCa). We aimed to identify multi-miRNA urinary biomarker panel for early detection of PCa. Methods: Urine samples from 83 PCa patients and 88 healthy control subjects in a Chinese population were collected for miRNA profiling. The absolute expression of 360 unique miRNAs were measured in each sample using a highly sensitive and robust RT-qPCR workflow. Candidate urinary miRNA biomarkers were identified based on differential expression between PCa patients and healthy controls. Multi-miRNA biomarker panels were optimized for detection of PCa using three regression algorithms (Lasso, Stepwise, Exhaustive) to identify an optimal biomarker panel with best detection performance and least number of miRNAs. Results: A total of 312 miRNAs were detected in urine samples, 10 candidate urinary miRNA biomarkers differentially expressed between PCa and healthy samples were identified. A panel comprising these 10 miRNAs detected PCa with an area under the curve (AUC) of 0.738. Optimization of multi-miRNA panels resulted in a 6-miRNA biomarker panel (hsa-miR-375, hsa-miR-520d-5p, hsa-miR-199b-5p, hsa-miR-518e-5p, hsa-miR-31-3p and hsa-miR-4306) that had an AUC of 0.750. Conclusion: We identified a urinary miRNA biomarker panel for early detection of PCa in a Chinese population.

Locus-Specific Bisulfate NGS Sequencing of GSTP1, RNF219, and KIAA1539 Genes in the Total Pool of Cell-Free and Cell-Surface-Bound DNA in Prostate Cancer: A Novel Approach for Prostate Cancer Diagnostics

The locus-specific methylation of three genes (GSTP1, RNF219, and KIAA1539, also known as FAM214B) in the total pool of blood cell-free DNA, including cell-free DNA from plasma and cell-surface-bound DNA, of patients with prostate cancer and healthy donors was studied on the MiSeq platform. Our study found a higher methylation index of loci for total cell-free DNA compared with cell-free DNA. For total cell-free DNA, the methylation of GSTP1 in each of the 11 positions provided a complete separation of cancer patients from healthy donors, whereas for cell-free DNA, there were no positions in the three genes allowing for such separation. Among the prostate cancer patients, the minimum proportion of GSTP1 genes methylated in any of the 17 positions was 12.1% of the total circulated DNA fragments, and the minimum proportion of GSTP1 genes methylated in any of the 11 diagnostically specific positions was 8.4%. Total cell-free DNA was shown to be more convenient and informative as a source of methylated DNA molecules circulating in the blood than cell-free DNA.

Locus-Specific Methylation of GSTP1, RNF219, and KIAA1539 Genes with Single Molecule Resolution in Cell-Free DNA from Healthy Donors and Prostate Tumor Patients: Application in Diagnostics

Simple Summary

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men, which is constantly accompanied by benign prostate hyperplasia (BPH). To reach a 100% 5-year survival rate in PCa, which is characteristic for PCa if it is diagnosed in early stages, efficient PCa diagnostics against the background of BPH are demanded. The article describes a liquid biopsy approach to differential PCa diagnostics based on the data on locus-specific methylation of the three genes (GSTP1, RNF219, and KIAA1539) obtained with NGS of cell-free DNA from blood plasma of PCa, BPH, and healthy individuals. We offered a diagnostic approach including the analysis of simultaneous methylation status of two CpGs in one cell-free DNA molecule, allowing the discrimination of all patients with absolute sensitivity and specificity.

Abstract

The locus-specific methylation of three genes (GSTP1, RNF219, and KIAA1539 (also known as FAM214B)) in the blood plasma cell-free DNA (cfDNA) of 20 patients with prostate cancer (PCa), 18 healthy donors (HDs), and 17 patients with benign prostatic hyperplasia (BPH) was studied via the MiSeq platform. The methylation status of two CpGs within the same loci were used as the diagnostic feature for discriminating the patient groups. Many variables had good diagnostic characteristics, e.g., each of the variables GSTP1.C3.C9, GSTP1.C9, and GSTP1.C9.T17 demonstrated an 80% sensitivity at a 100% specificity for PCa patients vs. the others comparison. The analysis of RNF219 gene loci methylation allowed discriminating BPH patients with absolute sensitivity and specificity. The data on the methylation of the genes GSTP1 and RNF219 allowed discriminating PCa patients, as well as HDs, with absolute sensitivity and specificity. Thus, the data on the locus-specific methylation of cfDNA (with single-molecule resolution) combined with a diagnostic approach considering the simultaneous methylation of several CpGs in one locus enabled the discrimination of HD, BPH, and PCa patients.

Stroma-derived extracellular vesicle mRNA signatures inform histological nature of prostate cancer

Histological assessment of prostate cancer is the key diagnostic test and can predict disease outcome. This is however an invasive procedure that carries associated risks, hence non-invasive assays to support the diagnostic pathway are much needed. A key feature of disease progression, and subsequent poor prognosis, is the presence of an altered stroma. Here we explored the utility of prostate stromal cell-derived vesicles as indicators of an altered tumour environment. We compared vesicles from six donor-matched pairs of adjacent-normal versus disease-associated primary stromal cultures. We identified 19 differentially expressed transcripts that discriminate disease from normal stromal extracellular vesicles (EVs). EVs isolated from patient serum were investigated for these putative disease-discriminating mRNA. A set of transcripts including Caveolin-1 (CAV1), TMP2, THBS1, and CTGF were found to be successful in discriminating clinically insignificant (Gleason = 6) disease from clinically significant (Gleason > 8) prostate cancer. Furthermore, correlation between transcript expression and progression-free survival suggests that levels of these mRNA may predict disease outcome. Informed by a machine learning approach, combining measures of the five most informative EV-associated mRNAs with PSA was shown to significantly improve assay sensitivity and specificity. An in-silico model was produced, showcasing the superiority of this multi-modal liquid biopsy compared to needle biopsy for predicting disease progression. This proof of concept highlights the utility of serum EV analytics as a companion diagnostic test with prognostic utility, which may obviate the need for biopsy.

MiRNAs and radical prostatectomy: Current data, bioinformatic analysis and utility as predictors of tumour relapse

BACKGROUND

Studies of microRNAs (miRNAs) and genes have particular interest for cancer biology and medicine due to the discovery of new therapeutic targets and markers. These studies are extensively influenced by anticancer therapy, as miRNAs interfere with the therapy's efficacy in prostate cancer (PCa).

OBJECTIVES

In this article, we summarise the available data on the influence of radical prostatectomy (RP) and biochemical recurrence on miRNA expression.

MATERIALS AND METHODS

Molecular targets of these miRNAs, as well as the reciprocal relations between different miRNAs and their targets, were studied using the DIANA, STRING and TransmiR databases. Special attention was dedicated to the mechanisms of PCa development, miRNA, and associated genes as tumour development mediators.

RESULTS AND DISCUSSION

Combined analysis of the databases and available literature indicates that expression of four miRNAs that are associated with prostate cancer relapse and alter their expression after RP, combined with genes that closely interact with selected miRNAs, has high potential for the prediction of PCa relapse after RP. PCa tissues and biofluids, both immediately after RP for diagnostics/prognostics and in long-term (relapse) monitoring, may be used as sources of these miRNAs.

CONCLUSION

An overview of the usefulness of published data and bioinformatics resources looking for diagnostic markers and molecular targets is presented in this article. The selected miRNA and gene panels have good potential as prognostic and PCa relapse markers after RP and likely could also serve as markers for therapeutic efficiency on a broader scale.

Exosomal microRNAs-mediated intercellular communication and exosome-based cancer treatment

Exosomes are extracellular vesicles with a diameter of about 30 to 100 nm, which play a crucial role in intercellular communication. Compared with normal cells, the release rate of tumor-derived exosomes (TDEs) significantly increased, and exosomal contents, especially microRNAs (miRNAs), greatly changed. TDEs contribute to the proliferation, metastasis and resistance of tumor cells, regulate immune response and tumor autophagy, and mediate tumor-stroma communication. In addition, exosomes may be involved in tumor complications. In view of the role of exosomes in intercellular communication, exosomes have been developed as tumor biomarkers, therapeutic targets, and drug delivery systems for tumor diagnosis, prognosis and treatment. Despite the many advantages of exosomes, there are many challenges in exosomal development and application, such as incomprehensive understanding of biological functions, safety and specificity for therapeutic use. This article reviews the biogenesis of TDEs and focuses on the role of exosomal miRNAs in intercellular communication and exosome-based treatment for cancer.

Searching for the Novel Specific Predictors of Prostate Cancer in Urine: The Analysis of 84 miRNA Expression

The aim of this study was to investigate miRNA profiles of clarified urine supernatant and combined urine vesicle fractions of healthy donors and patients with benign prostatic hyperplasia and prostate cancer (PCa). The comparative analysis of miRNA expression was conducted with a custom miRCURY LNA miRNA qPCR panel. Significant combinations of miRNA pairs were selected by the RandomForest-based feature selection algorithm Boruta; the difference of the medians between the groups and a 95% confidence interval was built using the bootstrap approach. The Asymptotic Wilcoxon-Mann-Whitney Test was performed for miRNA combinations to compare different groups of donors. Benjamini-Hochberg correction was used to adjust the statistical significance for multiple comparisons. The most diagnostically significant miRNAs pairs were miR-107-miR-26b.5p and miR-375.3p-miR-26b.5p in the urine supernatant fraction that discriminated the group of healthy patients and PCa patients, as well as miR-31.5p-miR-16.5p, miR-31.5p-miR-200b, miR-31.5p-miR-30e.3p and miR-31.5p-miR-660.5p in the fraction extracellular vesicles that were different between healthy men and benign prostate hyperplasia patients. Such statistical criteria as the occurrence of individual significant miRNA pairs in the total number of comparisons, median ΔCt difference, and confidence interval can be useful tools for determining reliable markers of PCa.

Clair DK, Kyprianou N. Profiles of Radioresistance Mechanisms in Prostate Cancer

Radiation therapy (RT) is commonly used for the treatment of localized prostate cancer (PCa). However, cancer cells often develop resistance to radiation through unknown mechanisms and pose an intractable challenge. Radiation resistance is highly unpredictable, rendering the treatment less effective in many patients and frequently causing metastasis and cancer recurrence. Understanding the molecular events that cause radioresistance in PCa will enable us to develop adjuvant treatments for enhancing the efficacy of RT. Radioresistant PCa depends on the elevated DNA repair system and the intracellular levels of reactive oxygen species (ROS) to proliferate, self-renew, and scavenge anti-cancer regimens, whereas the elevated heat shock protein 90 (HSP90) and the epithelial-mesenchymal transition (EMT) enable radioresistant PCa cells to metastasize after exposure to radiation. The up-regulation of the DNA repairing system, ROS, HSP90, and EMT effectors has been studied extensively, but not targeted by adjuvant therapy of radioresistant PCa. Here, we emphasize the effects of ionizing radiation and the mechanisms driving the emergence of radioresistant PCa. We also address the markers of radioresistance, the gene signatures for the predictive response to radiotherapy, and novel therapeutic platforms for targeting radioresistant PCa. This review provides significant insights into enhancing the current knowledge and the understanding toward optimization of these markers for the treatment of radioresistant PCa.