Biomarkers in prostate cancer surveillance and screening: past, present, and future

Proteomic Identification of Small Extracellular Vesicle Proteins LAMB1 and Histone H4 for Prostate Cancer Diagnosis and Risk Stratification

Diagnosis and stratification of prostate cancer (PCa) patients using the prostate-specific antigen (PSA) test is challenging. Extracellular vesicles (EVs), as a new star of liquid biopsy, has attracted interest to complement inaccurate PSA screening and invasiveness of tissue biopsy. In this study, a panel of potential small EV (sEV) protein biomarkers is identified from PCa cell lines using label-free LC-MS/MS proteomics. These biomarkers underwent further validation with plasma and urine samples from different PCa stages through parallel reaction monitoring-based targeted proteomics, western blotting, and ELISA. Additionally, a tissue microarray containing cancerous and noncancerous tissues is screened to provide additional evidence of selected sEV proteins associated with cancer origin. Results indicate that sEV protein LAMB1 is highly expressed in human plasma of metastatic PCa patients compared with localised PCa patients and control subjects, while sEV protein Histone H4 is highly expressed in human urine of high-risk PCa patients compared to low-risk PCa patients and control subjects. These two sEV proteins demonstrate higher specificity and sensitivity than the PSA test and show promise for metastatic PCa diagnosis, progression monitoring, and risk stratification.

Liquid biomarkers in prostate cancer: recent advancements and future directions

PURPOSE OF REVIEW

Traditional diagnostic approaches of prostate cancer like PSA are limited by high false-positive rates and insufficient capture of tumour heterogeneity, necessitating the development of more precise tools. This review examines the latest advancements in liquid biomarkers for prostate cancer, focusing on their potential to refine diagnostic accuracy and monitor disease progression.

RECENT FINDINGS

Liquid biomarkers have gained prominence because of their minimally invasive nature and ability to reflect the molecular characteristics of prostate cancer. Circulating tumour cells provide insight into tumour cell dissemination and are indicative of aggressive disease phenotypes, with single-cell analyses revealing genomic instability and treatment resistance. Circulating tumour DNA offers real-time tumour genomic information, aiding in treatment decision-making in advanced prostate cancer, where it has been associated with clinical progression. MicroRNAs act as oncogenes or tumour suppressors and exhibit diagnostic and prognostic potential; however, their clinical utility is constrained by the lack of consistent validation. Extracellular vesicles contain tumour-derived biomolecules, with specific proteins demonstrating prognostic relevance. Applications of these markers to urinary testing have been demonstrated.

SUMMARY

Liquid biomarkers show potential in refining prostate cancer management. Future research should aim to integrate these biomarkers into a cohesive framework in line with precision medicine principles.

Can systemic immune-inflammation index and hematologic parameters aid in decision-making for active surveillance or curative treatment in low-risk prostate cancer?

INTRODUCTION

Pathologic Gleason Score (GS) upgrading is common in patients with low-risk localized prostate cancer (PCa) who are followed by active surveillance (AS) or undergo radical prostatectomy (RP). This fact raises concerns about inadequate treatment, especially in AS patients. We aimed to analyze the association of preoperative neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and systemic immune-inflammation (SII) index with GS upgrading.

MATERIALS AND METHODS

This study was approved by the Ethical Review Committee of Afyonkarahisar Health Sciences University. Data of the patients who underwent RP for PCa at three different centers between 2018 and 2023 were retrospectively analyzed. The patients were divided into 2 groups based on GR upgrading status as "upgrading" and "non-upgrading". Among the patients who underwent RP, 77 patients who fully met the criteria for AS were identified. The patients eligible for AS were divided into "non-upgrading" and "upgrading" groups. These groups were compared regarding NLR, PLR, and SII index values.

RESULTS

Overall, data from 250 patients were reviewed. Among these, 147 had GS upgrading, while 103 had no upgrading. Seventy-seven patients were eligible for AS. Among these patients, 30 had upgrading, while 47 were in the "non-upgrading" group. Our analysis revealed that an NLR of 1.85 and above was associated with a 2.238-fold increase in the risk of GS upgrading (p = 0.009). Also, a PLR of 115.7 and above was affiliated with a 2.992-fold increase in the GS upgrading risk (p < 0.001). The analysis regarding patients who underwent RP but were eligible for AS revealed that an NLR of ≥1.68 was associated with a 3.25-fold risk increase in GS upgrading. On the other hand, a PLR≥134.5 and an SII index≥630.7 were affiliated with a 12.303-fold and 6.562-fold increase in the risk of upgrading (p = 0.019, p = 0.018).

CONCLUSION

The decision of AS should be carefully reappraised, and treatment methods such as RP or radiotherapy should be considered in patients with high NLR, PLR, or SII index values.

Exploring the potential of EphA2 receptor signaling pathway: a comprehensive review in cancer treatment

The protein encoded by the ephrin type-A receptor 2 (EphA2) gene is a member of the ephrin receptor subfamily of the receptor tyrosine kinase family (RTKs). Eph receptors play a significant role in various biological processes, particularly cancer progression, development, and pathogenesis. They have been observed to regulate cancer cell growth, migration, invasion, tumor development, invasiveness, angiogenesis, and metastasis. To target EphA2 activity, various molecular, genetic, biochemical, and pharmacological strategies have been extensively tested in laboratory cultures and animal models. Notably, drugs, such as dasatinib, initially designed to target the kinase family, have demonstrated an additional capability to target EphA2 activity. Additionally, a novel monoclonal antibody named EA5 has emerged as a promising option to counteract the effects of EphA2 overexpression and restore tamoxifen sensitivity in EphA2-transfected MCF-7 cells during in vitro experiments. This antibody mimicked the binding of Ephrin A to EphA2. These methods offer potential avenues for inhibiting EphA2 activity, which could significantly decelerate breast cancer progression and restore sensitivity to certain drugs. This review article comprehensively covers EphA2's involvement in multiple malignancies, including ovarian, colorectal, breast, lung, glioma, and melanoma. Furthermore, we discuss the structure of EphA2, the Eph-Ephrin signaling pathway, various EphA2 inhibitors, and the mechanisms of EphA2 degradation. This article provides an extensive overview of EphA2's vital role in different types of cancers and outlines potential therapeutic approaches to target EphA2, shedding light on the underlying molecular mechanisms that make it an attractive target for cancer treatment.

Prostate cancer-derived small extracellular vesicle proteins: the hope in diagnosis, prognosis, and therapeutics

Current diagnostic tools for prostate cancer (PCa) diagnosis and risk stratification are insufficient. The hidden onset and poor efficacy of traditional therapies against metastatic PCa make this disease a heavy burden in global men's health. Prostate cancer-derived extracellular vesicles (PCDEVs) have garnered attention in recent years due to their important role in communications in tumor microenvironment. Recent advancements have demonstrated PCDEVs proteins play an important role in PCa invasion, progression, metastasis, therapeutic resistance, and immune escape. In this review, we briefly discuss the applications of sEV proteins in PCa diagnosis and prognosis in liquid biopsy, focus on the roles of the PCa-derived small EVs (sEVs) proteins in tumor microenvironment associated with cancer progression, and explore the therapeutic potential of sEV proteins applied for future metastatic PCa therapy.

Development and clinical utility analysis of a prostate zonal segmentation model on T2-weighted imaging: a multicenter study

OBJECTIVES

To automatically segment prostate central gland (CG) and peripheral zone (PZ) on T2-weighted imaging using deep learning and assess the model's clinical utility by comparing it with a radiologist annotation and analyzing relevant influencing factors, especially the prostate zonal volume.

METHODS

A 3D U-Net-based model was trained with 223 patients from one institution and tested using one internal testing group (n = 93) and two external testing datasets, including one public dataset (ETD_pub, n = 141) and one private dataset from two centers (ETD_pri, n = 59). The Dice similarity coefficients (DSCs), 95th Hausdorff distance (95HD), and average boundary distance (ABD) were calculated to evaluate the model's performance and further compared with a junior radiologist's performance in ETD_pub. To investigate factors influencing the model performance, patients' clinical characteristics, prostate morphology, and image parameters in ETD_pri were collected and analyzed using beta regression.

RESULTS

The DSCs in the internal testing group, ETD_pub, and ETD_pri were 0.909, 0.889, and 0.869 for CG, and 0.844, 0.755, and 0.764 for PZ, respectively. The mean 95HD and ABD were less than 7.0 and 1.3 for both zones. The U-Net model outperformed the junior radiologist, having a higher DSC (0.769 vs. 0.706) and higher intraclass correlation coefficient for volume estimation in PZ (0.836 vs. 0.668). CG volume and Magnetic Resonance (MR) vendor were significant influencing factors for CG and PZ segmentation.

CONCLUSIONS

The 3D U-Net model showed good performance for CG and PZ auto-segmentation in all the testing groups and outperformed the junior radiologist for PZ segmentation. The model performance was susceptible to prostate morphology and MR scanner parameters.

Role and Application of Biocatalysts in Cancer Drug Discovery

A biocatalyst is an enzyme that speeds up or slows down the rate at which a chemical reaction occurs and speeds up certain processes by 108 times. It is used as an anticancer agent because it targets drug activation inside the tumor microenvironment while limiting damage to healthy cells. Biocatalysts have been used for the synthesis of different heterocyclic compounds and is also used in the nano drug delivery systems. The use of nano-biocatalysts for tumor-targeted delivery not only aids in tumor invasion, angiogenesis, and mutagenesis, but also provides information on the expression and activity of many markers related to the microenvironment. Iosmapinol, moclobemide, cinepazide, lysine dioxygenase, epothilone, 1-homophenylalanine, and many more are only some of the anticancer medicines that have been synthesised using biocatalysts. In this review, we have highlighted the application of biocatalysts in cancer therapies as well as the use of biocatalysts in the synthesis of drugs and drug-delivery systems in the tumor microenvironment.

Role of inflammatory factors in prediction of Gleason score and its upgrading in localized prostate cancer patients after radical prostatectomy

Purpose

To investigate the role of inflammatory factors including systemic immune-inflammation index (SII) and neutrophil to lymphocyte ratio (NLR) in predicting Gleason Score (GS) and Gleason Score upgrading (GSU) in localized prostate cancer (PCa) after radical prostatectomy (RP).

Methods

The data of 297 patients who underwent prostate biopsy and RP in our center from January 2014 to March 2020 were retrospectively analyzed. Preoperative clinical characteristics including age, values of tPSA, total prostate volume (TPV), f/t PSA ratio, body mass index (BMI), biopsy GS and inflammatory factors including SII, NLR, lymphocyte to monocyte (LMR), neutrophil ratio (NR), platelet to lymphocyte ratio (PLR), lymphocyte ratio (LR), mean platelet volume (MPV) and red cell distribution (RDW) as well as pathological T (pT) stage were collected and compared according to the grades of RP GS (GS ≤ 6 and GS≥7), respectively. ROC curve analysis was used to confirm the discriminative ability of inflammatory factors including SII, NLR and their combination with tPSA for predicting GS and GSU. By using univariate and multivariate logistic regression analysis, the association between significant inflammatory markers and grades of GS were evaluated.

Results

Patients enrolled were divided into low (GS ≤ 6) and high (GS≥7) groups by the grades of GS. The median values of clinical factors were 66.08 ± 6.04 years for age, 36.62 ± 23.15 mL for TPV, 26.16 ± 33.59 ng/mL for tPSA and 0.15 ± 0.25 for f/t PSA ratio, 22.34 ± 3.14 kg/m² for BMI, 15 (5.1%) were pT1, 116 (39.1%) were pT2 and 166 (55.9%) were pT3. According to the student's t test, patients in high GS group had a greater proportion of patients with pT3 (P<0.001), and higher NLR (P=0.04), SII (P=0.037) and tPSA (P=0.015) compared with low GS group, the distribution of age, TPV, f/t PSA ratio, BMI, LMR, NR, PLR, LR, MPV and RDW did not show any significantly statistical differences. The AUC for SII, NLR and tPSA was 0.732 (P=0.007), 0.649 (P=0.045) and 0.711 (P=0.015), with threshold values of 51l.08, 2.3 and 10.31ng/mL, respectively. According to the multivariable logistic regression models, NLR ≥ 2.3 (OR, 2.463; 95% CI, 0.679-10.469, P=0.042), SII ≥ 511.08 (OR, 3.519; 95% CI 0.891-12.488; P=0.003) and tPSA ≥ 10.31 ng/mL (OR, 4.146; 95% CI, 1.12-15.35; P=0.033) were all independent risk factors associated with higher GS. The AUC for combination of SII, NLR with tPSA was 0.758 (P=0.003) and 0.756 (P=0.003), respectively. GSU was observed in a total of 48 patients with GS ≤ 6 (55.17%). Then patients were divided into 2 groups (high and low) according to the threshold value of SII, NLR, tPSA, SII+tPSA and NLR+tPSA, respectively, when the GSU rates were compared with regard to these factors, GSU rate in high level group was significantly higher than that in low level group, P=0.001, 0.044, 0.017, <0.001 and <0.001, respectively.

Conclusion

High SII, NLR and tPSA were associated with higher GS and higher GSU rate. SII was likely to be a more favorable biomarker for it had the largest AUC area compared with tPSA and NLR; the combination of SII or NLR with tPSA had greater values for predicting GS and GSU compared with NLR, SII or tPSA alone, since the AUC area of combination was much higher. SII, NLR were all useful inflammatory biomarkers for predicting GS and detecting GSU among localized PCa patients with biopsy GS ≤ 6.

microRNA-205 in prostate cancer: Overview to clinical translation

Prostate cancer (PrCa) is the most common type of cancer among men in the United States. The metastatic and advanced PrCa develops drug resistance to current regimens which accounts for the poor management. microRNAs (miRNAs) have been well-documented for their diagnostic, prognostic, and therapeutic roles in various human cancers. Recent literature confirmed that microRNA-205 (miR-205) has been established as one of the tumor suppressors in PrCa. miR-205 regulates number of cellular functions, such as proliferation, invasion, migration/metastasis, and apoptosis. It is also evident that miR-205 can serve as a key biomarker in diagnostic, prognostic, and therapy of PrCa. Therefore, in this review, we will provide an overview of tumor suppressive role of miR-205 in PrCa. This work also outlines miR-205's specific role in targeted mechanisms for chemosensitization and radiosensitization in PrCa. A facile approach of delivery paths for successful clinical translation is documented. Together, all these studies provide a novel insight of miR-205 as an adjuvant agent for reducing the widening gaps in clinical outcome of PrCa patients.

Expression Analysis of miRNAs and Their Potential Role as Biomarkers for Prostate Cancer Detection

Prostate cancer (PCa) is the second most frequent cancer diagnosed in men worldwide. The detection methods for PCa are either unreliable, like prostate-specific antigen (PSA), or extremely invasive, such as in the case of biopsies. Therefore, there is an urgent necessity for reliable and less invasive detection procedures that can differentiate between patients with benign diseases and those with cancer. In this matter, microRNAs (miRNAs) are suggested as potential biomarkers for cancer. MiRNAs have been found to be dysregulated in several different cancers, and these genetic alterations may present specific signatures for a given malignancy. Here, we examined the expression of miR141-3p, miR145-5p, miR146a-5p, and miR148b-3p in human tissue samples of PCa (n = 41) and benign prostatic diseases (BPD) (n = 30) using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). We combined the expression results with patient clinicopathological characteristics in logistic regression models to create accurate PCa predictive models. A model including information of miR148b-3p and patient age showed relevant prediction results (area under the curve [AUC] = 0.818, precision = 0.763, specificity = 0.762, and accuracy = 0.762). A model including all four miRNAs and patient age presented outstanding prediction results (AUC = 0.918, precision = 0.861, specificity = 0.861, and accuracy = 0.857). Our results represent a potential novel procedure based on logistic regression models that utilize miRNA expressions and patient age to assist with PCa diagnosis.

Prostate Cancer Secretome and Membrane Proteome from Pten Conditional Knockout Mice Identify Potential Biomarkers for Disease Progression

Prostate cancer (PCa) is the second most common cause of mortality among men. Tumor secretome is a promising strategy for understanding the biology of tumor cells and providing markers for disease progression and patient outcomes. Here, transcriptomic-based secretome analysis was performed on the PCa tumor transcriptome of Genetically Engineered Mouse Model (GEMM) Pb-Cre4/Pten^f/f mice to identify potentially secreted and membrane proteins—PSPs and PMPs. We combined a selection of transcripts from the GSE 94574 dataset and a list of protein-coding genes of the secretome and membrane proteome datasets using the Human Protein Atlas Secretome. Notably, nine deregulated PMPs and PSPs were identified in PCa (DMPK, PLN, KCNQ5, KCNQ4, MYOC, WIF1, BMP7, F3, and MUC1). We verified the gene expression patterns of Differentially Expressed Genes (DEGs) in normal and tumoral human samples using the GEPIA tool. DMPK, KCNQ4, and WIF1 targets were downregulated in PCa samples and in the GSE dataset. A significant association between shorter survival and KCNQ4, PLN, WIF1, and F3 expression was detected in the MSKCC dataset. We further identified six validated miRNAs (mmu-miR-6962-3p, mmu-miR- 6989-3p, mmu-miR-6998-3p, mmu-miR-5627-5p, mmu-miR-15a-3p, and mmu-miR-6922-3p) interactions that target MYOC, KCNQ5, MUC1, and F3. We have characterized the PCa secretome and membrane proteome and have spotted new dysregulated target candidates in PCa.

Radiomics-Based Machine Learning Models for Predicting P504s/P63 Immunohistochemical Expression: A Noninvasive Diagnostic Tool for Prostate Cancer

Objective

To develop and validate a noninvasive radiomic-based machine learning (ML) model to identify P504s/P63 status and further achieve the diagnosis of prostate cancer (PCa).

Methods

A retrospective dataset of patients with preoperative prostate MRI examination and P504s/P63 pathological immunohistochemical results between June 2016 and February 2021 was conducted. As indicated by P504s/P63 expression, the patients were divided into label 0 (atypical prostatic hyperplasia), label 1 (benign prostatic hyperplasia, BPH) and label 2 (PCa) groups. This study employed T2WI, DWI and ADC sequences to assess prostate diseases and manually segmented regions of interest (ROIs) with Artificial Intelligence Kit software for radiomics feature acquisition. Feature dimensionality reduction and selection were performed by using a mutual information algorithm. Based on screened features, P504s/P63 prediction models were established by random forest (RF), gradient boosting decision tree (GBDT), logistic regression (LR), adaptive boosting (AdaBoost) and k-nearest neighbor (KNN) algorithms. The performance was evaluated by the area under the ROC curve (AUC) and accuracy.

Results

A total of 315 patients were enrolled. Among the 851 radiomic features, the 32 top features were derived from T2WI, in which the gray-level run length matrix (GLRLM) and gray-level cooccurrence matrix (GLCM) features accounted for the largest proportion. Among the five models, the RF algorithm performed best in general evaluations (microaverage AUC=0.920, macroaverage AUC=0.870) and provided the most accurate result in further sublabel prediction (the accuracies of label 0, 1, and 2 were 0.831, 0.831, and 0.932, respectively). In comparative sequence analyses, T2WI was the best single-sequence candidate (microaverage AUC=0.94 and macroaverage AUC=0.78). The merged datasets of T2WI, DWI, and ADC yielded optimal AUCs (microaverage AUC=0.930 and macroaverage AUC=0.900).

Conclusions

The radiomic-based RF classifier has the potential to be used to evaluate the presurgical P504s/P63 status and further diagnose PCa noninvasively and accurately.

LncRNA Biomarkers of Inflammation and Cancer

Long noncoding RNAs (lncRNAs) are promising candidates as biomarkers of inflammation and cancer. LncRNAs have several properties that make them well-suited as molecular markers of disease: (1) many lncRNAs are expressed in a tissue-specific manner, (2) distinct lncRNAs are upregulated based on different inflammatory or oncogenic stimuli, (3) lncRNAs released from cells are packaged and protected in extracellular vesicles, and (4) circulating lncRNAs in the blood are detectable using various RNA sequencing approaches. Here we focus on the potential for lncRNA biomarkers to detect inflammation and cancer, highlighting key biological, technological, and analytical considerations that will help advance the development of lncRNA-based liquid biopsies.

RNA-based biomarkers for the diagnosis, prognosis, and therapeutic response monitoring of prostate cancer

Prostate cancer (CaP) is the most common malignant neoplasm of the urinary tract. The current recommendations for CaP diagnosis rely on the prostate-specific antigen levels and a digital rectal examination for anatomical abnormalities. However, these diagnostic tools are not highly sensitive. In particular, prostate-specific antigen has a low positive predictive value (approximately 30%). Thus, there is a need to develop biomarkers to improve the early clinical detection of CaP. Several novel technologies enable the identification of biomarkers from diverse sources, including the urine, serum, and prostate tissues. Furthermore, advances in genomic techniques have enabled the analysis of novel biomarkers, such as deoxyribonucleic acids (DNAs), ribonucleic acids (RNAs), proteins, and circulating tumor cells. Previous studies have demonstrated that RNAs are potential diagnostic biomarkers for various cancers using high-throughput sequencing analysis. The sensitivity and specificity of RNA biomarkers are higher than those of protein biomarkers. Polymerase chain reaction enables the amplification of trace levels of RNAs with high sensitivity and specificity. RNA biomarkers provide dynamic insights into cellular states and regulatory processes when compared with DNA biomarkers. Additionally, multiple copies of various RNAs in a cell provide more information than DNA. The levels of specific RNAs in CaP tissues are upregulated when compared with those in non-cancerous tissues. Additionally, RNAs can be easily isolated from various body fluids. Thus, RNAs are potential non-invasive biomarkers for CaP. Moreover, the analysis of RNA levels adjusted for each stage of CaP enables the determination of prognostic individualized therapy for aggressive or progressive CaP. This review focused on the diagnostic and prognostic values of RNAs for CaP.

Molecular Basis of Prostate Cancer and Natural Products as Potential Chemotherapeutic and Chemopreventive Agents

Prostate cancer is the second most common malignant cancer in males. It involves a complex process driven by diverse molecular pathways that closely related to the survival, apoptosis, metabolic and metastatic characteristics of aggressive cancer. Prostate cancer can be categorized into androgen dependent prostate cancer and castration-resistant prostate cancer and cure remains elusive due to the developed resistance of the disease. Natural compounds represent an extraordinary resource of structural scaffolds with high diversity that can offer promising chemical agents for making prostate cancer less devastating and curable. Herein, those natural compounds of different origins and structures with potential cytotoxicity and/or in vivo anti-tumor activities against prostate cancer are critically reviewed and summarized according to the cellular signaling pathways they interfere. Moreover, the anti-prostate cancer efficacy of many nutrients, medicinal plant extracts and Chinese medical formulations were presented, and the future prospects for the application of these compounds and extracts were discussed. Although the failure of conventional chemotherapy as well as involved serious side effects makes natural products ideal candidates for the treatment of prostate cancer, more investigations of preclinical and even clinical studies are necessary to make use of these medical substances reasonably. Therefore, the elucidation of structure-activity relationship and precise mechanism of action, identification of novel potential molecular targets, and optimization of drug combination are essential in natural medicine research and development.

The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images

Volume of interest segmentation is an essential step in computer-aided detection and diagnosis (CAD) systems. Deep learning (DL)-based methods provide good performance for prostate segmentation, but little is known about the reproducibility of these methods. In this work, an in-house collected dataset from 244 patients was used to investigate the intra-patient reproducibility of 14 shape features for DL-based segmentation methods of the whole prostate gland (WP), peripheral zone (PZ), and the remaining prostate zones (non-PZ) on T2-weighted (T2W) magnetic resonance (MR) images compared to manual segmentations. The DL-based segmentation was performed using three different convolutional neural networks (CNNs): V-Net, nnU-Net-2D, and nnU-Net-3D. The two-way random, single score intra-class correlation coefficient (ICC) was used to measure the inter-scan reproducibility of each feature for each CNN and the manual segmentation. We found that the reproducibility of the investigated methods is comparable to manual for all CNNs (14/14 features), except for V-Net in PZ (7/14 features). The ICC score for segmentation volume was found to be 0.888, 0.607, 0.819, and 0.903 in PZ; 0.988, 0.967, 0.986, and 0.983 in non-PZ; 0.982, 0.975, 0.973, and 0.984 in WP for manual, V-Net, nnU-Net-2D, and nnU-Net-3D, respectively. The results of this work show the feasibility of embedding DL-based segmentation in CAD systems, based on multiple T2W MR scans of the prostate, which is an important step towards the clinical implementation.

Differentially expressed miR-20, miR-21, miR-100, miR-125a and miR-146a as a potential biomarker for prostate cancer

Prostate cancer is the leading cause of death among men worldwide. Deregulation of microRNAs has been reported in many cancers. Expression of microRNAs miR-20a-5p, miR-21-5p, miR-100-5p, miR-125a-5p and miR-146a-5p in tissue blocks of histologically confirmed prostate cancer patients compared with BPH patients, to identify potential microRNA biomarker for prostate cancer. MicroRNA was isolated and expression was quantified by qRT-PCR using Taqman Advanced microRNA assay kits. The interactions between the microRNA:target mRNA were predicted by using bioinformatics tools such as miRwalk and miRTargetlink. The experimentally validated targets were analysed using gprofiler to identify their molecular function, biological process and related pathways. The expression analysis revealed that miR-21 and miR-100 were significantly down-regulated whereas miR-125a was up-regulated in prostate cancer patients. Comparative analysis of the expression levels with tumor grading reveal that miR-100 was significantly down-regulated (p < 0.05) in high grade tumor, indicating that miR-100 associated with prostate cancer. ROC analysis revealed that combined analysis of down-regulated miRNAs (miR-21 and miR-100) shown AUC of 0.72 (95% CI 0.65-0.79). The combined analysis of all five miRNAs showed AUC of 0.87 (95% CI 0.81-0.92). The targets prediction analysis revealed several validated targets including BCL2, ROCK1, EGFR, PTEN, MTOR, NAIF1 and VEGFA. Our results provide evidence that combined analysis of all the five miRNAs as a panel can significantly improve the prediction level of the presence of prostate cancer and may be used as a potential diagnostic biomarker.

Long Noncoding RNAs as Innovative Urinary Diagnostic Biomarkers

The characterization of circulating tumor cells (CTCs) is now widely studied as a promising source of cancer-derived biomarkers because of their role in tumor formation and progression. However, CTCs analysis presents some limitations and no standardized method for CTCs isolation from urine has been defined so far. In fact, besides blood, urine represents an ideal source of noninvasive biomarkers, especially for the early detection of genitourinary tumors. Besides CTCs, long noncoding RNAs (lncRNAs) have also been proposed as potential noninvasive biomarkers, and the evaluation of the diagnostic accuracy of urinary lncRNAs has dramatically increased over the last years, with many studies being published. Therefore, this review provides an update on the clinical utility of urinary lncRNAs as novel biomarkers for the diagnosis of bladder and prostate cancers.

A preliminary study of micro-RNAs as minimally invasive biomarkers for the diagnosis of prostate cancer patients

Background

A prostate cancer diagnosis is based on biopsy sampling that is an invasive, expensive procedure, and doesn’t accurately represent multifocal disease.

Methods

To establish a model using plasma miRs to distinguish Prostate cancer patients from non-cancer controls, we enrolled 600 patients histologically diagnosed as having or not prostate cancer at biopsy. Two hundred ninety patients were eligible for the analysis. Samples were randomly divided into discovery and validation cohorts.

Results

NGS-miR-expression profiling revealed a miRs signature able to distinguish prostate cancer from non-cancer plasma samples. Of 51 miRs selected in the discovery cohort, we successfully validated 5 miRs (4732-3p, 98-5p, let-7a-5p, 26b-5p, and 21-5p) deregulated in prostate cancer samples compared to controls (p ≤ 0.05). Multivariate and ROC analyses show miR-26b-5p as a strong predictor of PCa, with an AUC of 0.89 (CI = 0.83–0.95;p < 0.001). Combining miRs 26b-5p and 98-5p, we developed a model that has the best predictive power in discriminating prostate cancer from non-cancer (AUC = 0.94; CI: 0,835-0,954).

To distinguish between low and high-grade prostate cancer, we found that miR-4732-3p levels were significantly higher; instead, miR-26b-5p and miR-98-5p levels were lower in low-grade compared to the high-grade group (p ≤ 0.05).

Combining miR-26b-5p and miR-4732-3p we have the highest diagnostic accuracy for high-grade prostate cancer patients, (AUC = 0.80; CI 0,69-0,873).

Conclusions

Noninvasive diagnostic tests may reduce the number of unnecessary prostate biopsies.

The 2-miRs-diagnostic model (miR-26b-5p and miR-98-5p) and the 2-miRs-grade model (miR-26b-5p and miR-4732-3p) are promising minimally invasive tools in prostate cancer clinical management.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01875-0.

Radiation Response in the Tumour Microenvironment: Predictive Biomarkers and Future Perspectives

Radiotherapy (RT) is a primary treatment modality for a number of cancers, offering potentially curative outcomes. Despite its success, tumour cells can become resistant to RT, leading to disease recurrence. Components of the tumour microenvironment (TME) likely play an integral role in managing RT success or failure including infiltrating immune cells, the tumour vasculature and stroma. Furthermore, genomic profiling of the TME could identify predictive biomarkers or gene signatures indicative of RT response. In this review, we will discuss proposed mechanisms of radioresistance within the TME, biomarkers that may predict RT outcomes, and future perspectives on radiation treatment in the era of personalised medicine.

Urine and serum glycosaminoglycan levels in the diagnosis of urological diseases and conditions: A narrative review of the literature

Glycosaminoglycans (GAGs) are sulfated, negatively charged polysaccharides produced in almost every cell of the human body. As GAGs are extracellularly localized, the changes in body fluids such as blood and urine may reflect pathological changes in the urinary system as observed in other pathologies. In this review, we determined the potential of urinary and/or serum GAG levels as a marker for kidney and urothelial system diseases. We performed a search in the PubMed, MEDLINE, and ScienceDirect databases until September 30, 2019. A number of studies reported changes in the urinary and/or plasma GAG levels or composition in urological diseases and conditions, such as renal cell carcinoma, kidney stone, bladder carcinoma, and overactive bladder. GAGs were found to have a predictive biomarker potential that could be limited by generalizability concerns.

Identification of plasma lipid species as promising diagnostic markers for prostate cancer

BACKGROUND

Prostate cancer is a very common and highly fatal in men. Current non-invasive detection methods like serum biomarker are unsatisfactory. Biomarkers with high accuracy for diagnostic of prostate cancer are urgently needed. Many lipid species have been found related to various cancers. The purpose of our study is to explore the diagnostic value of lipids for prostate cancer.

RESULTS

Using triple quadruple liquid chromatography electrospray ionization tandem mass spectrometry, we performed lipidomics profiling of 367 lipids on a total 114 plasma samples from 30 patients with prostate cancer, 38 patients with benign prostatic hyperplasia (BPH), and 46 male healthy controls to evaluate the lipids as potential biomarkers in the diagnosis of prostate cancer. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database was used to construct the potential mechanism pathway. After statistical analysis, five lipids were identified as a panel of potential biomarkers for the detection of prostate cancer between prostate cancer group and the BPH group; the sensitivity, specificity, and area under curve (AUC) of the combination of these five lipids were 73.3, 81.6%, and 0.800, respectively. We also identified another panel of five lipids in distinguishing between prostate cancer group and the control group with predictive values of sensitivity at 76.7%, specificity at 80.4%, and AUC at 0.836, respectively. The glycerophospholipid metabolism pathway of the selected lipids was considered as the target pathway.

CONCLUSIONS

Our study indicated that the identified plasma lipid biomarkers have potential in the diagnosis of prostate cancer.

Clinical implication of prognostic and predictive biomarkers for castration-resistant prostate cancer: a systematic review

Background

Diagnosis of metastatic castrate resistant prostate cancer (mCRPC) with current biomarkers is difficult and often results in unnecessary invasive procedures as well as over-diagnosis and over-treatment. There are a number of prognostic biomarkers for CRPC, but there are no validated predictive biomarkers to guide in clinical decision-making. Specific biomarkers are needed that enable to understand the natural history and complex biology of this heterogeneous malignancy, identify early response to treatment outcomes and to identify the population of men most likely to benefit from the treatment. In this systematic review, we discuss the existing literature for the role of biomarkers in CRPC and how they aid in the prognosis, treatment selection and survival outcomes.

Methods

We performed a literature search on PubMed and EMBASE databases from January 2015 through February 2020 in accordance to Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. Articles were assessed to identify relevant observational studies and randomized controlled trials regarding biomarkers which aid in identifying progression to mCRPC as well as predictive biomarkers which help in treatment selection.

Results

We identified 3640 number of hits of which 58 articles were found to be relevant. Here we addressed biomarkers in the context of prognosis, prediction and patient selection of therapy. These biomarkers were found to be effective as prognostic or predictive factors under variety of conditions. The higher levels for all these biomarkers were associated with shorter median OS and sometimes PFS. Lower amounts of biomarkers in serum or urine were associated with prolonged survival outcomes, longer time to CRPC development or CRPC progression and longer median follow-up irrespective of any therapy.

Conclusion

We observed that the biomarkers included in our study predicted clinically relevant survival outcomes and treatment exposure. Though the current biomarkers are prognostic when measured prior to initiating treatment, not all are validated as predictive markers in post treatment setting. A greater understanding of biomarkers in CRPC is need of the hour for development of more personalized approach to maximize benefit and minimize harm in men with CRPC.

Can natural killer cell activity help screen patients requiring a biopsy for the diagnosis of prostate cancer?

Purpose

To evaluate the usefulness of natural killer cell activity (NKA) in diagnosing prostate cancer (PC).

Materials and Methods

The medical records of patients who underwent transrectal prostate biopsy (TRBx) at Korea University Ansan Hospital between May 2017 and December 2017 were retrospectively reviewed. NKA levels were measured using NK Vue® Tubes (ATgen, Sungnam, Korea). All blood samples were obtained at 8 AM on the day of biopsy. Patients with other malignancies, chronic inflammatory conditions, high prostate-specific antigen (PSA) level (>20ng/mL), or history of taking 5-alpha-reductase inhibitor or testosterone replacement therapy were excluded.

Results

A total of 102 patients who underwent TRBx for PC diagnosis were enrolled. Among them, 50 were diagnosed with PC. Significant differences in age and NKA level were observed between the PC and no-PC groups. Receiver operating characteristic (ROC) curve analysis showed that the optimal cut-off of NKA level for the prediction of PC was 500pg/dL, with a sensitivity of 68.0% and a specificity of 73.1%. In addition, NKA level (0.630) had the greatest area under the ROC curve compared to those for the ratio of total PSA to free PSA (0.597) and PSA density (0.578).

Conclusions

The results of this pilot study revealed that low NKA and high PSA levels were likely to be associated with a positive TRBx outcome. NKA detection was easy and improved the diagnostic accuracy of PC.

Cost-Effectiveness Analysis of Prostate-Specific Antigen Screening Among Chinese Men

OBJECTIVES

To analyze the cost-effectiveness of prostate cancer screening among Chinese men.

METHODS

A cost-effectiveness analysis was performed from a societal perspective using a Markov model to compare 2 strategies: the population-based screening strategy and the current clinical diagnostic strategy. Relevant parameters were retrieved from published literature data and surveys, and univariate sensitivity analysis was used to assess the robustness of the model. We simulated the health outcomes for the next 25 years for 100 000 men and calculated the incremental cost-effectiveness ratio (ICER).

RESULTS

This study found that the population-based screening strategy, compared with the clinical diagnostic strategy, could save 756.61 quality-adjusted life-years (QALYs) for the hypothetical population. The ICER for the population-based screening strategy was ¥14 747.11/QALY, and this value was less than the willingness-to-pay threshold of ¥64 520. With life-year gains (LYGs) as the model output, the population-based screening strategy yielded an ICER of ¥16 470.45/LYG. The univariate sensitivity analyses showed that the ICER was sensitive to the prostate-specific antigen (PSA) test fee, the proportion diagnosed with low-grade prostate cancer (PC) in the population-based strategy, and the proportion diagnosed with intermediate-grade PC in the population-based strategy.

CONCLUSIONS

Prostate cancer screening based on PSA test results appears to be cost-effective for Chinese men who are in good health and have a life expectancy of more than 10 years. Nevertheless, this finding needs to be further studied with more treatment cost parameters (treatment costs related to impotence and urinary incontinence) and using local utility value information.

Development and Psychometric Properties of a Prostate Cancer Knowledge Scale for African American Men

African American men have the highest prostate cancer-related mortality nationally. In response to this disparity, targeted interventions are emerging to enhance African American men's prostate cancer (PrCA) knowledge to ensure they are equipped to make informed decisions about PrCA screening with health-care providers. African American men's PrCA knowledge has been measured inconsistently over time with limited psychometric evidence. The factor structure of this construct in African American men is relatively unknown. This study describes the development and psychometric evaluation of an 18-item Prostate Cancer Knowledge Scale among 352 African American men. Exploratory factor analysis (EFA) was conducted using weighted least square mean and variance estimation with Geomin rotation. EFA yielded three factors: PrCA Anatomy and Screening (6 items), Risk Factors (5 items), Warning Signs (7 items) with good internal consistency reliability at KR-20 = .80 for the total scale and .64, .66, and .75, respectively, for each subscale. Factor loadings ranged from .31 to .86. The standardized root mean square residual (0.08) indicated that the factor structure explained most of the correlations. The three-factor, 18-item Prostate Cancer Knowledge Scale demonstrates that PrCA knowledge is a multidimensional construct and has utility for reliably measuring PrCA knowledge among African American men. Future research is required to confirm this factor structure among socio-demographically diverse African Americans.

ZBTB46, SPDEF, and ETV6: Novel Potential Biomarkers and Therapeutic Targets in Castration-Resistant Prostate Cancer

Prostate cancer (PCa) is the second most common killer among men in Western countries. Targeting androgen receptor (AR) signaling by androgen deprivation therapy (ADT) is the current therapeutic regime for patients newly diagnosed with metastatic PCa. However, most patients relapse and become resistant to ADT, leading to metastatic castration-resistant PCa (CRPC) and eventually death. Several proposed mechanisms have been proposed for CRPC; however, the exact mechanism through which CRPC develops is still unclear. One possible pathway is that the AR remains active in CRPC cases. Therefore, understanding AR signaling networks as primary PCa changes into metastatic CRPC is key to developing future biomarkers and therapeutic strategies for PCa and CRPC. In the current review, we focused on three novel biomarkers (ZBTB46, SPDEF, and ETV6) that were demonstrated to play critical roles in CRPC progression, epidermal growth factor receptor tyrosine kinase inhibitor (EGFR TKI) drug resistance, and the epithelial-to-mesenchymal transition (EMT) for patients treated with ADT or AR inhibition. In addition, we summarize how these potential biomarkers can be used in the clinic for diagnosis and as therapeutic targets of PCa.

Retrospective analysis of glycan-related biomarkers based on clinical laboratory data in two medical centers during the past 6 years

Most of clinically used cancer biomarkers are either specific glycan structures or glycoproteins. Although the high serum levels of the cancer biomarkers are also present in certain patients suffering noncancer diseases, systematic measurement and comparison of the serum levels of all cancer biomarkers among cancer and noncancer patients have not been reported. In this study, the serum levels of 17 glucose and glycan-related biomarkers including 10 cancer biomarkers SCCA, CA724, CA50, CA242, CA125, CA199, CA153, AFP, CEA, and PSA were retrospectively investigated based on clinical laboratory data in two medical centers during the past 6 years (2012-2018). The data included a total of 1,477,309 clinical lab test results of 17 biomarkers from healthy controls and patients suffering 64 different types of cancer and noncancer diseases. We found that the median serum levels of CA724, CEA, CA153, SCCA, and CA125 were highest not in cancer patients but in patients suffering gout, lung fibrosis, nephrotic syndrome, uremia, and cirrhosis, respectively. Consistently, the classical ovarian cancer biomarker CA125 had better overall sensitivity and specificity as biomarker for cirrhosis (67% and 92%, respectively) than that for ovarian cancer (41% and 97%, respectively). Furthermore, the information shown as heatmap or waterfall built on the -Log₁₀p values of the 17 glycan-related biomarkers in different clinically defined diseases suggested that all glycan-related biomarkers had cancer-, aging-, and disease-relevant characteristics and cancers were systems disease. The detailed presentation of the data for each of the 17 biomarkers will be deliberated in chapters 6-23 in this book series.

Discovery of Metabolic Biomarkers Predicting Radiation Therapy Late Effects in Prostate Cancer Patients

Patients presenting with prostate cancers undergo clinical staging evaluations to determine the extent of disease to guide therapeutic recommendations. Management options may include watchful waiting, surgery, or radiation therapy. Thus, initial risk stratification of prostate cancer patients is important for achieving optimal therapeutic results or cancer cure and preservation of quality of life. Predictive biomarkers for risks of complications or late effects of treatment are needed to inform clinical decisions for treatment selection. Here, we analyzed pre-treatment plasma metabolites in a cohort of prostate cancer patients (N = 99) treated with Stereotactic Body Radiation Therapy (SBRT) at Medstar-Georgetown University Hospital in a longitudinal, quality-of-life study to determine if individuals experiencing radiation toxicities can be identified by a molecular profile in plasma prior to treatment. We used a multiple reaction mass spectrometry-based molecular phenotyping of clinically annotated plasma samples in a retrospective outcome analysis to identify candidate biomarker panels correlating with adverse clinical outcomes following radiation therapy. We describe the discovery of candidate biomarkers, based on small molecule metabolite panels, showing high correlations (AUCs ≥ 95%) with radiation toxicities, suitable for validation studies in an expanded cohort of patients.

Urinary markers aiding in the detection and risk stratification of prostate cancer

The purpose of this review is to highlight the role of existing and promising urinary biomarkers for the detection and prognostication of prostate cancer (PCa). A number of novel urinary biomarkers have been introduced into the clinical space, which in combination with clinical variables, have demonstrated an increased ability to select patients for biopsy and identify men at risk of harboring clinically significant PCa. Though a number of assays require further validation, initial data is promising and forthcoming results will ultimately determine their clinical utility and commercial availability. For the past 30 years, first-line screening for PCa has relied on measurement of serum prostate-specific antigen (PSA) levels and the results from a digital rectal exam (DRE). A large body of evidence from the last 3 decades indicates that these screening methods are problematic, and often inadequate for detecting clinically significant PCa. Extensive efforts have recently been made to identify and commercialize novel PCa biomarkers for more effective detection of PCa, either alone or in combination with current screening methods. This review article highlights problems with current screening standards, and discusses 6 urinary biomarker assays in terms of their ability to detect and risk-stratify PCa: prostate cancer antigen 3 (PCA3), TMPRSS2-ERG, second chromosome locus associated with prostate-1 (SChLAP1), ExoDx, SelectMDx, and Michigan Prostate Score (MiPS).

Optimizing patient's selection for prostate biopsy: A single institution experience with multi-parametric MRI and the 4Kscore test for the detection of aggressive prostate cancer

Objectives

To evaluate the performance of mpMRI and the 4Kscore test together for the detection of significant prostate cancer.

Material and methods

We selected a consecutive series of men who were referred for evaluation of prostate cancer at an academic institution and underwent mpMRI and the 4Kscore test. The primary outcome was the presence of Gleason 7 or higher cancer on biopsy of the prostate. We used logistic regression and Decision Curve Analysis to report the discrimination and clinical utility of using mpMRI and the 4Kscore test for prostate cancer detection. We modeled the probability of harboring a Gleason 7 or higher prostate cancer based on the 4Kscore test and mpMRI findings. Finally, we examined various combinations and sequences of mpMRI and the 4Kscore test and assessed the impact on biopsies avoided and cancers missed.

Results

Among 300 men who underwent a 4Kscore test and mpMRI, 149 (49%) underwent a biopsy. Among those, 73 (49%) had cancer, and 49 (33%) had Gleason 7 cancer. The area under the curve (AUC) for using the 4Kscore test and mpMRI together 0.82 (0.75–0.89) was superior to using the 4Kscore 0.70 (0.62–0.79) or mpMRI 0.74 (0.66–0.81) individually (p = 0.001). Similarly, decision analysis revealed the highest net benefit was achieved using both tests.

Conclusions

The 4Kscore test and mpMRI results provide independent, but complementary, information that enhances the prediction of higher-grade prostate cancer and improves patient’s selection for a prostate biopsy. Prospective trials are required to confirm these findings.

Detecting Novel Urine Biomarkers for the Early Diagnosis of Prostate Cancer: Platelet Derived Growth Factor-BB as a Possible New Target

Introduction

Although the prostate specific antigen revolutionized the diagnosis of prostate cancer (PCa), it has its limitations. We prospectively examined the potential use of the platelet-derived growth factor-BB (PDGF-BB) as a urine biomarker for the early diagnosis of PCa.

Materials and Methods

The urine samples of 118 patients were collected after a prostatic massage and all the patients subsequently underwent ultrasound-guided transrectal biopsy. PDGF-BB was detected in the urine by enzyme-linked immunosorbent assay.

Results

Patients with PCa had greater levels of prostate specific antigen and PDGF-BB. Receiver operating characteristic curve analysis showed that the optimal cut-of of PDGF-BB for the prediction of PCa was 1,504.9 with a sensitivity of 60% and a specificity of 51.3%. For a 100 unit increase in PDGF-BB, the likelihood for PCa increased about 4%.

Conclusion

PDGF-BB showed a significant predictive ability for PCa. Detection of PDGF-BB in urine with Elisa was easy and improved our diagnostic accuracy in the diagnosis of PCa.

Regulation of prostate cancer by hormone-responsive G protein-coupled receptors

Regulation of prostate cancer by androgen and androgen receptor (AR), and blockade of AR signaling by AR antagonists and steroidogenic enzyme inhibitors have been extensively studied. G protein-coupled receptors (GPCRs) are a family of membrane receptors that regulate almost all physiological processes. Nearly 40% of FDA-approved drugs in the market target GPCRs. A variety of GPCRs that mediate reproductive function have been demonstrated to be involved in the regulation of prostate cancer. These GPCRs include gonadotropin-releasing hormone receptor, luteinizing hormone receptor, follicle-stimulating hormone receptor, relaxin receptor, ghrelin receptor, and kisspeptin receptor. We highlight here GPCR regulation of prostate cancer by these GPCRs. Further therapeutic approaches targeting these GPCRs for the treatment of prostate cancer are summarized.

Hyaluronic acid and hyaluronidase as possible novel urine biomarkers for the diagnosis of prostate cancer

The goal of the study is to examine the possible use of HA (hyaluronic acid) and HAase (hyaluronidase) as novel urine biomarkers for the early diagnosis for prostate cancer (Pca). After a prostatic massage, the urine of 118 high-risk patients for Pca was collected, and the patients were submitted to ultrasound-guided transrectal biopsy. HA and HAase were detected and analyzed with Enzyme-Linked Immunosorbent Assay, and a statistical analysis of the urine levels of the two biomarkers according to the histology results was performed. HAase and HA were independently associated with Pca, and both HAase and HA showed significant predictive ability for prostate cancer. With an optimal cut-off point of 183.71 HAase had 70% sensitivity maintaining at the same time a 55.2% specificity, while the optimal cut-off point for HA was 50.13 with 65% sensitivity and 53.9% specificity. Patients with HAase more than 183.71 ng/ml had 3.67 times greater likelihood for prostate cancer and Patients with HA more than 50.13 ng/ml had 2.31 times greater likelihood for prostate cancer. The need of novel biomarkers that will improve the efficacy of PSA is urgent. HAase and HA showed significant predictive ability for prostate cancer and were independently associated with Pca, and greater levels were associated with greater odds for prostate cancer. To Our Knowledge, this is the first study referring to the detection of HAase and HA as potential urine biomarkers for the early diagnosis of Pca.

Hyaluronic acid and hyaluronidase as possible novel urine biomarkers for the diagnosis of prostate cancer

The goal of the study is to examine the possible use of HA (hyaluronic acid) and HAase (hyaluronidase) as novel urine biomarkers for the early diagnosis for prostate cancer (Pca). After a prostatic massage, the urine of 118 high-risk patients for Pca was collected, and the patients were submitted to ultrasound-guided transrectal biopsy. HA and HAase were detected and analyzed with Enzyme-Linked Immunosorbent Assay, and a statistical analysis of the urine levels of the two biomarkers according to the histology results was performed. HAase and HA were independently associated with Pca, and both HAase and HA showed significant predictive ability for prostate cancer. With an optimal cut-off point of 183.71 HAase had 70% sensitivity maintaining at the same time a 55.2% specificity, while the optimal cut-off point for HA was 50.13 with 65% sensitivity and 53.9% specificity. Patients with HAase more than 183.71 ng/ml had 3.67 times greater likelihood for prostate cancer and Patients with HA more than 50.13 ng/ml had 2.31 times greater likelihood for prostate cancer. The need of novel biomarkers that will improve the efficacy of PSA is urgent. HAase and HA showed significant predictive ability for prostate cancer and were independently associated with Pca, and greater levels were associated with greater odds for prostate cancer. To Our Knowledge, this is the first study referring to the detection of HAase and HA as potential urine biomarkers for the early diagnosis of Pca.

Development of sarcosine quantification in urine based on enzyme-coupled colorimetric method for prostate cancer diagnosis

An enzyme-coupled colorimetric assay for quantification of urinary sarcosine was developed. The proposed method is a specific reaction based on hydrogen peroxide (H₂O₂) formation via sarcosine oxidase (SOX). The liberated H₂O₂ reacts with Amplex Red in the presence of horseradish peroxidase (HRP) to produce the red-fluorescent oxidation product, resorufin, which can be measured spectrophotometrically (OD570). The method was performed in the 96-well microtiter plate. Reaction conditions, such as pH and reaction time were optimized. At the optimum conditions, the limit of detection (LOD) and quantification (LOQ) were found to be 0.7 and 1 µM, respectively. A good linearity was revealed with a coefficient of 0.990. The assay showed no significant interference from ascorbic acid, glucose and bilirubin. In addition, it is extremely specific for sarcosine rather than other amino acids. The determination of sarcosine in human urine displayed high accuracy and good reproducibility. This method is promising to differentiate prostate cancer patients from healthy subjects according to urinary sarcosine level. Altogether, this study provides a rapid, simple and specific tool to determine urinary sarcosine which could be useful for prostate cancer diagnosis.

Development of sarcosine quantification in urine based on enzyme-coupled colorimetric method for prostate cancer diagnosis

An enzyme-coupled colorimetric assay for quantification of urinary sarcosine was developed. The proposed method is a specific reaction based on hydrogen peroxide (H2O2) formation via sarcosine oxidase (SOX). The liberated H2O2 reacts with Amplex Red in the presence of horseradish peroxidase (HRP) to produce the red-fluorescent oxidation product, resorufin, which can be measured spectrophotometrically (OD570). The method was performed in the 96-well microtiter plate. Reaction conditions, such as pH and reaction time were optimized. At the optimum conditions, the limit of detection (LOD) and quantification (LOQ) were found to be 0.7 and 1 µM, respectively. A good linearity was revealed with a coefficient of 0.990. The assay showed no significant interference from ascorbic acid, glucose and bilirubin. In addition, it is extremely specific for sarcosine rather than other amino acids. The determination of sarcosine in human urine displayed high accuracy and good reproducibility. This method is promising to differentiate prostate cancer patients from healthy subjects according to urinary sarcosine level. Altogether, this study provides a rapid, simple and specific tool to determine urinary sarcosine which could be useful for prostate cancer diagnosis.

Emerging proteomics biomarkers and prostate cancer burden in Africa

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers.

Differential Expression Patterns of Eph Receptors and Ephrin Ligands in Human Cancers

Eph receptors constitute the largest family of receptor tyrosine kinases, which are activated by ephrin ligands that either are anchored to the membrane or contain a transmembrane domain. These molecules play important roles in the development of multicellular organisms, and the physiological functions of these receptor-ligand pairs have been extensively documented in axon guidance, neuronal development, vascular patterning, and inflammation during tissue injury. The recognition that aberrant regulation and expression of these molecules lead to alterations in proliferative, migratory, and invasive potential of a variety of human cancers has made them potential targets for cancer therapeutics. We present here the involvement of Eph receptors and ephrin ligands in lung carcinoma, breast carcinoma, prostate carcinoma, colorectal carcinoma, glioblastoma, and medulloblastoma. The aberrations in their abundances are described in the context of multiple signaling pathways, and differential expression is suggested as the mechanism underlying tumorigenesis.

Novel tumor suppressor microRNA at frequently deleted chromosomal region 8p21 regulates epidermal growth factor receptor in prostate cancer

Genomic loss of chromosome (chr) 8p21 region, containing prostate-specific NKX3.1 gene, is a frequent alteration of the prostate cancer (PCa) oncogenome. We propose a novel, paradigm shifting hypothesis that this frequently deleted locus is also associated with a cluster of microRNA genes- miR-3622a/b- that are lost in PCa and play an important mechanistic role in progression and metastasis. In this study, we demonstrate the role of miR-3622b in prostate cancer. Expression analyses in a cohort of PCa clinical specimens and cell lines show that miR-3622b expression is frequently lost in prostate cancer. Low miR-3622b expression was found to be associated with tumor progression and poor biochemical recurrence-free survival. Further, our analyses suggest that miR-3622b expression is a promising prostate cancer diagnostic biomarker that exhibits 100% specificity and 66% sensitivity. Restoration of miR-3622b expression in PCa cell lines led to reduced cellular viability, proliferation, invasiveness, migration and increased apoptosis. miR-3622b overexpression in vivo induced regression of established prostate tumor xenografts pointing to its therapeutic potential. Further, we found that miR-3622b directly represses Epidermal Growth Factor Receptor (EGFR). In conclusion, our study suggests that miR-3622b plays a tumor suppressive role and is frequently downregulated in prostate cancer, leading to EGFR upregulation. Importantly, miR-3622b has associated diagnostic, prognostic and therapeutic potential. Considering the association of chr8p21 loss with poor prognosis, our findings are highly significant and support a novel concept that associates a long standing observation of frequent loss of a chromosomal region with a novel miRNA in prostate cancer.

MicroRNAs and epithelial-mesenchymal transition in prostate cancer

Prostate cancer (PCa) is a leading cause of male cancer-related deaths. A significant fraction of prostate tumors are very aggressive, often metastasizing to bone, causing significant morbidity and mortality. Also, PCa is associated with high rates of recurrence, often attributed to the existence of cancer stem cells. Epithelial-mesenchymal transition (EMT), a process characterized by decreased expression of epithelial genes and increased expression of mesenchymal genes, plays a critical role in tumor invasion, metastasis and recurrence. In PCa, EMT has been implicated particularly in the context of metastatic disease and microRNAs have emerged as critical post-transcriptional regulators of PCa EMT. In this review, we summarize the role of miRNAs in PCa EMT that play a role in progression, metastasis and recurrence. Studies till date suggest that microRNAs mediate efficient and reversible control of PCa EMT via multiple mechanisms including either by (i) directly repressing single or multiple EMT-TFs or regulating cytoskeletal components (epithelial/mesenchymal genes) or (ii) regulating key signaling pathways involved in EMT. Oncogenic microRNAs often act as EMT promoters by repressing epithelial characteristics and tumor suppressive miRNAs act by inhibiting mesenchymal progression. Further, EMT is mechanistically linked to stem cell signatures in PCa and several miRNAs implicated in EMT have been reported to influence PCa stem cells. Loss of EMT-inhibiting miRNAs and/or gain of EMT promoting miRNAs lead to induction of PCa EMT, leading to tumor progression, metastasis and recurrence. Restoring expression of tumor suppressive miRNAs and inhibiting oncogenic miRNAs represent potential therapeutic opportunities to prevent disease metastasis and recurrence.

Potential use of chymotrypsin-like proteasomal activity as a biomarker for prostate cancer

Although it is the most widely used biomarker for prostate cancer, the use of prostate specific antigen (PSA) is controversial due to its limitations in specificity and sensitivity. The proteasome is a complex associated with cell proliferation and apoptosis, and the abnormity of these processes may lead to tumor occurrence. Previous studies have reported that proteasomal activity is associated with cancer progression and can be used in risk stratification. The purpose of the present study was thus to investigate the feasibility of proteasome activity as a biomarker for prostate cancer. Proteasome activity in vitro and in vivo was detected, along with the expression of the substrate proteins NF-κB inhibitor-α (IκB-α), Bcl-2-associated X (Bax) and p27. Chymotrypsin-like proteasomal activity was elevated by 70% in vitro and 23% in vivo, and the expression levels of the proteasome substrate proteins IκB-α, Bax and p27 were decreased in prostate cancer cells and prostate tumor xenografts compared with normal mouse prostate tissue. In conclusion, proteasomal chymotrypsin-like activity maybe a potential biomarker for prostate cancer, and may be suitable to supplement PSA in clinical application for prostate cancer diagnosis.

microRNA-1246 Is an Exosomal Biomarker for Aggressive Prostate Cancer

Because of high heterogeneity, molecular characterization of prostate cancer based on biopsy sampling is often challenging. Hence, a minimally invasive method to determine the molecular imprints of a patient's tumor for risk stratification would be advantageous. In this study, we employ a novel, digital amplification-free quantification method using the nCounter technology (NanoString Technologies) to profile exosomal serum miRNAs (ex-miRNA) from aggressive prostate cancer cases, benign prostatic hyperplasia, and disease-free controls. We identified several dysregulated miRNAs, one of which was the tumor suppressor miR-1246. miR-1246 was downregulated in prostate cancer clinical tissues and cell lines and was selectively released into exosomes. Overexpression of miR-1246 in a prostate cancer cell line significantly inhibited xenograft tumor growth in vivo and increased apoptosis and decreased proliferation, invasiveness, and migration in vitro miR-1246 inhibited N-cadherin and vimentin activities, thereby inhibiting epithelial-mesenchymal transition. Ex-miR-1246 expression correlated with increasing pathologic grade, positive metastasis, and poor prognosis. Our analyses suggest ex-miR-1246 as a promising prostate cancer biomarker with diagnostic potential that can predict disease aggressiveness.Significance: Dysregulation of exosomal miRNAs in aggressive prostate cancer leads to alteration of key signaling pathways associated with metastatic prostate cancer. Cancer Res; 78(7); 1833-44. ©2018 AACR.