A Rich Array of Prostate Cancer Molecular Biomarkers: Opportunities and Challenges

LGALS3 cfDNA methylation in seminal fluid as a novel prostate cancer biomarker outperforming PSA

BACKGROUND

The unmet challenge in prostate cancer (PCa) management is to discriminate it from benign prostate hyperplasia (BPH) due to the lack of specific diagnostic biomarkers. Contemporary research on potential PCa biomarkers is directed toward methylated cell-free DNA (cfDNA) from liquid biopsies since epigenetic mechanisms are strongly involved in PCa development.

METHODS

In the present research, cfDNA methylation of the LGALS3 gene in blood and seminal plasma of PCa and BPH patients was assessed using pyrosequencing, as well as LGALS3 DNA methylation in tissue biopsies. Liquid biopsy samples were taken from patients with clinical suspicion of PCa, who were subsequently divided into two groups, that is, 42 with PCa and 55 with BPH, according to the histopathological analysis.

RESULTS

Statistically significant higher cfDNA methylation of LGALS3 in seminal plasma of BPH than in PCa patients was detected by pyrosequencing. ROC curve analysis showed that it could distinguish PCa and BPH patients with 56.4% sensitivity and 70.4% specificity, while PSA did not differ between the two patient groups. In contrast, there was no statistically significant difference in LGALS3 cfDNA methylation in blood plasma between the two patient groups. In prostate tumor tissue, there was a statistically significant DNA hypermethylation of LGALS3 compared to surrounding nontumor tissue and BPH tissue.

CONCLUSIONS

The DNA hypermethylation of the LGALS3 gene represents an event specific to PCa development. In conclusion, LGALS3 cfDNA methylation in seminal fluid discriminates early PCa and BPH presenting itself as a powerful novel PCa biomarker highly outperforming PSA.

Upregulation of shelterin and CST genes and longer telomeres are associated with unfavorable prognostic characteristics in prostate cancer

INTRODUCTION

Search for new clinical biomarkers targets in prostate cancer (PC) is urgent. Telomeres might be one of these targets. Telomeres are the extremities of linear chromosomes, essential for genome stability and control of cell divisions. Telomere homeostasis relies on the proper functioning of shelterin and CST complexes. Telomeric dysfunction and abnormal expression of its components are reported in most cancers and are associated with PC. Despite this, there are only a few studies about the expression of the main telomere complexes and their relationship with PC progression. We aimed to evaluate the role of shelterin (POT1, TRF2, TPP1, TIN2, and RAP1) and CST (CTC1, STN1, and TEN1) genes and telomere length in the progression of PC.

METHODS

We evaluated genetic alterations of shelterin and CST by bioinformatics in samples of localized (n = 499) and metastatic castration-resistant PC (n = 444). We also analyzed the expression of the genes using TCGA (localized PC n = 497 and control n = 152) and experimental approaches, with surgical specimens (localized PC n = 81 and BPH n = 10) and metastatic cell lines (LNCaP, DU145, PC3 and PNT2 as control) by real-time PCR. Real-time PCR also determined the telomere length in the same experimental samples. All acquired data were associated with clinical parameters.

RESULTS

Genetic alterations are uncommon in PC, but POT1, TIN2, and TEN1 showed significantly more amplifications in the metastatic cancer. Except for CTC1 and TEN1, which are differentially expressed in localized PC samples, we did not detect an expression pattern relative to control and cell lines. Nevertheless, except for TEN1, the upregulation of all genes is associated with a worse prognosis in localized PC. We also found that increased telomere length is associated with disease aggressiveness in localized PC.

CONCLUSION

The upregulation of shelterin and CST genes creates an environment that favors telomere elongation, giving selective advantages for localized PC cells to progress to more aggressive stages of the disease.

Development of a multigenomic liquid biopsy (PROSTest) for prostate cancer in whole blood

INTRODUCTION

We describe the development of a molecular assay from publicly available tumor tissue mRNA databases using machine learning and present preliminary evidence of functionality as a diagnostic and monitoring tool for prostate cancer (PCa) in whole blood.

MATERIALS AND METHODS

We assessed 1055 PCas (public microarray data sets) to identify putative mRNA biomarkers. Specificity was confirmed against 32 different solid and hematological cancers from The Cancer Genome Atlas (n = 10,990). This defined a 27-gene panel which was validated by qPCR in 50 histologically confirmed PCa surgical specimens and matched blood. An ensemble classifier (Random Forest, Support Vector Machines, XGBoost) was trained in age-matched PCas (n = 294), and in 72 controls and 64 BPH. Classifier performance was validated in two independent sets (n = 263 PCas; n = 99 controls). We assessed the panel as a postoperative disease monitor in a radical prostatectomy cohort (RPC: n = 47).

RESULTS

A PCa-specific 27-gene panel was identified. Matched blood and tumor gene expression levels were concordant (r = 0.72, p < 0.0001). The ensemble classifier ("PROSTest") was scaled 0%-100% and the industry-standard operating point of ≥50% used to define a PCa. Using this, the PROSTest exhibited an 85% sensitivity and 95% specificity for PCa versus controls. In two independent sets, the metrics were 92%-95% sensitivity and 100% specificity. In the RPCs (n = 47), PROSTest scores decreased from 72% ± 7% to 33% ± 16% (p < 0.0001, Mann-Whitney test). PROSTest was 26% ± 8% in 37 with normal postoperative PSA levels (<0.1 ng/mL). In 10 with elevated postoperative PSA, PROSTest was 60% ± 4%.

CONCLUSION

A 27-gene whole blood signature for PCa is concordant with tissue mRNA levels. Measuring blood expression provides a minimally invasive genomic tool that may facilitate prostate cancer management.

JMJD2A promotes the development of castration-resistant prostate cancer by activating androgen receptor enhancer and inhibiting the cGAS-STING pathway

Exploring targets for inhibiting androgen receptor (AR) activity is an effective strategy for suppressing the development of castration-resistant prostate cancer (CRPC). Upregulation of histone demethylase JMJD2A activity is an important factor in increasing AR expression in CRPC. Based on our research, we found that the binding affinity between JMJD2A and AR increases in CRPC, while the level of AR histone methylation decreases and the H3K27ac level increases in the AR enhancer region. Further investigations revealed that overexpression of the histone demethylase JMJD2A increased the binding affinity between JMJD2A and AR, decreased AR histone methylation levels, upregulated H3K27ac in the AR enhancer region, and increased AR activity. Conversely, knocking down JMJD2A effectively reversed these effects. Additionally, in CRPC, JMJD2A expression was upregulated, the tumor-intrinsic immune cGAS-STING signaling pathway was suppressed, the tumor microenvironment was altered, and AR expression was upregulated. However, both knocking down JMJD2A and inhibiting the cyclic GMP-AMP synthase/stimulator of interferon genes (cGAS-STING) signaling pathway reversed these effects. In summary, our study indicates that in CRPC, JMJD2A can directly bind to AR and activate residual AR enhancers through its demethylation activity, thereby promoting AR expression. Furthermore, upregulation of JMJD2A expression inhibits the innate immune cGAS-STING signaling pathway of the tumor, leading to a decrease in antitumor immune function, and further promoting AR expression.

Fibroblast growth factor pathway promotes glycolysis by activating LDHA and suppressing LDHB in a STAT1-dependent manner in prostate cancer

BACKGROUND

The initiation of fibroblast growth factor 1 (FGF1) expression coincident with the decrease of FGF2 expression is a well-documented event in prostate cancer (PCa) progression. Lactate dehydrogenase A (LDHA) and LDHB are essential metabolic products that promote tumor growth. However, the relationship between FGF1/FGF2 and LDHA/B-mediated glycolysis in PCa progression is not reported. Thus, we aimed to explore whether FGF1/2 could regulate LDHA and LDHB to promote glycolysis and explored the involved signaling pathway in PCa progression.

METHODS

In vitro studies used RT‒qPCR, Western blot, CCK-8 assays, and flow cytometry to analyze gene and protein expression, cell viability, apoptosis, and cell cycle in PCa cell lines. Glycolysis was assessed by measuring glucose consumption, lactate production, and extracellular acidification rate (ECAR). For in vivo studies, a xenograft mouse model of PCa was established and treated with an FGF pathway inhibitor, and tumor growth was monitored.

RESULTS

FGF1, FGF2, and LDHA were expressed at high levels in PCa cells, while LDHB expression was low. FGF1/2 positively modulated LDHA and negatively modulated LDHB in PCa cells. The depletion of FGF1, FGF2, or LDHA reduced cell proliferation, induced cell cycle arrest, and inhibited glycolysis. LDHB overexpression showed similar inhibitory effect on PCa cells. Mechanistically, we found that FGF1/2 positively regulated STAT1 and STAT1 transcriptionally activated LDHA expression while suppressed LDHB expression. Furthermore, the treatment of an FGF pathway inhibitor suppressed PCa tumor growth in mice.

CONCLUSION

The FGF pathway facilitates glycolysis by activating LDHA and suppressing LDHB in a STAT1-dependent manner in PCa.

Prostate cancer biomarkers: from early diagnosis to precision treatment

Prostate cancer (PCa) is the second most prevalent cancer in men. In 2020, approximately 1,414,259 new cases were reported that accounted for 3,75,324 deaths (Sung et al. in CA 71:209-249, 2021). PCa is often asymptomatic at early stages; hence, routine screening and monitoring based on reliable biomarkers is crucial for early detection and assessment of cancer progression. Early diagnosis of disease is key step in reducing PCa-induced mortality. Biomarkers such as PSA have played vital role in reducing recent PCa deaths. Recent research has identified many other biomarkers and also refined PSA-based tests for non-invasive diagnosis of PCa in patients. Despite progress in screening methods, an important issue that influences treatment is heterogeneity of the cancer in different individuals, necessitating personalized treatment. Currently, focus is to identify biomarkers that can accurately diagnose PCa at early stage, indicate the stage of the disease, metastatic nature and chances of survival based on individual patient profile (Fig. 1). Fig. 1 Graphical abstract.

A Prognostic Model for Prostate Cancer Patients Based on Two DNA Damage Response Mutation-Related Immune Genes

Background: DNA damage response (DDR) mutation-related genes and composition of immune cells are core factors affecting the effectiveness of immune checkpoint inhibitor therapy. The aim of this study is to combine DDR with immune-related genes to screen the prognostic signature for prostate cancer (PCa). Methods: Gene expression profile and somatic mutation were downloaded from The Cancer Genome Atlas (TCGA). DDR-related genes were obtained from published study. After identification of prognostic-related DDR genes, samples were divided into mutation and nonmutation groups. Differentially expressed genes between these two groups were screened, followed by selection of immune-related DDR genes. Univariate and multivariate Cox analyses were performed to screen genes for constructing prognostic model. Nomogram model was also developed. The expression level of signature was detected by quantitative real-time PCR (qPCR). Results: Two genes (MYBBP1A and PCDHA9) were screened to construct the prognostic model, and it showed good risk prediction of PCa prognosis. Survival analysis showed that patients in high-risk group had worse overall survival than those in low-risk group. Cox analyses indicated that risk score could be used as an independent prognostic factor for PCa. qPCR results indicated that MYBBP1A was upregulated, whereas PCDHA9 was downregulated in PCa cell lines. Conclusions: A prognostic model based on DDR mutation-related genes for PCa was established, which serves as an effective tool for prognostic differentiation in patients with PCa.

Applications of Urinary Extracellular Vesicles in the Diagnosis and Active Surveillance of Prostate Cancer

Prostate cancer is the most common non-cutaneous cancer among men in the UK, causing significant health and economic burdens. Diagnosis and risk prognostication can be challenging due to the genetic and clinical heterogeneity of prostate cancer as well as uncertainties in our knowledge of the underlying biology and natural history of disease development. Urinary extracellular vesicles (EVs) are microscopic, lipid bilayer defined particles released by cells that carry a variety of molecular cargoes including nucleic acids, proteins and other molecules. Urine is a plentiful source of prostate-derived EVs. In this narrative review, we summarise the evidence on the function of urinary EVs and their applications in the evolving field of prostate cancer diagnostics and active surveillance. EVs are implicated in the development of all hallmarks of prostate cancer, and this knowledge has been applied to the development of multiple diagnostic tests, which are largely based on RNA and miRNA. Common gene probes included in multi-probe tests include PCA3 and ERG, and the miRNAs miR-21 and miR-141. The next decade will likely bring further improvements in the diagnostic accuracy of biomarkers as well as insights into molecular biological mechanisms of action that can be translated into opportunities in precision uro-oncology.

The Current Therapeutic Landscape for Metastatic Prostate Cancer

In 2024, there will be an estimated 1,466,718 cases of prostate cancer (PC) diagnosed globally, of which 299,010 cases are estimated to be from the US. The typical clinical approach for PC involves routine screening, diagnosis, and standard lines of treatment. However, not all patients respond to therapy and are subsequently diagnosed with treatment emergent neuroendocrine prostate cancer (NEPC). There are currently no approved treatments for this form of aggressive PC. In this review, a compilation of the clinical trials regimen to treat late-stage NEPC using novel targets and/or a combination approach is presented. The novel targets assessed include DLL3, EZH2, B7-H3, Aurora-kinase-A (AURKA), receptor tyrosine kinases, PD-L1, and PD-1. Among these, the trials administering drugs Alisertib or Cabozantinib, which target AURKA or receptor tyrosine kinases, respectively, appear to have promising results. The least effective trials appear to be ones that target the immune checkpoint pathways PD-1/PD-L1. Many promising clinical trials are currently in progress. Consequently, the landscape of successful treatment regimens for NEPC is extremely limited. These trial results and the literature on the topic emphasize the need for new preventative measures, diagnostics, disease specific biomarkers, and a thorough clinical understanding of NEPC.

Integrating the 40-Gene Expression Profile (40-GEP) Test Improves Metastatic Risk-Stratification Within Clinically Relevant Subgroups of High-Risk Cutaneous Squamous Cell Carcinoma (cSCC) Patients

INTRODUCTION

The validated 40-gene expression profile (40-GEP) test independently stratifies risk of regional or distant metastasis for cutaneous squamous cell carcinoma (cSCC) tumors with high-risk clinicopathologic features. This study evaluated the stratification of risk by the 40-GEP test in a large cohort of tumors with one or more high-risk factors and in clinically relevant subgroups, including tumors within National Comprehensive Cancer Network (NCCN) high- and very-high-risk groups, lower-stage BWH T1 and T2a tumors, and patients > 65 years old.

METHODS

This multicenter (n = 58) performance study of the 40-GEP included 897 patients. Kaplan-Meier analyses were performed to assess risk stratification profiles for 40-GEP Class 1 (low), Class 2A (higher) and Class 2B (highest) risk groups, while nested Cox regression models were used to compare risk prediction of clinicopathologic risk classification systems versus risk classification systems in combination with 40-GEP.

RESULTS

Patients classified as 40-GEP Class 1, Class 2A, or Class 2B had significantly different metastatic risk profiles (p < 0.0001). Integrating 40-GEP results into models with individual clinicopathologic risk factors or risk classification systems (Brigham and Women's Hospital, American Joint Committee on Cancer Staging Manual, 8th Edition) and NCCN demonstrated significant improvement in accuracy for prediction of metastatic events (ANOVA for model deviance, p < 0.0001 for all models).

CONCLUSION

The 40-GEP test demonstrates accurate, independent, clinically actionable stratification of metastatic risk and improves predictive accuracy when integrated into risk classification systems. The improved accuracy of risk assessment when including tumor biology via the 40-GEP test ensures more risk-aligned, personalized patient management decisions.

CircTHSD4 promotes the malignancy and docetaxel (DTX) resistance in prostate cancer by regulating miR-203/HMGA2 axis

Objective

Circular ribose nucleic acids (circRNAs) are implicated in tumor progression and drug resistance of prostate cancer (PCa). The current work explored the function of circ_0005203 (circTHSD4) in the malignancy and docetaxel (DTX) resistance of PCa.

Methods

circTHSD4 expression within PCa as well as matched non-carcinoma samples was measured through real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). In addition, a subcellular fraction assay was conducted to determine circTHSD4 subcellular localization within PCa cells. In addition, we performed a Western blot (WB) assay to detect high-mobility-group A2 protein (HMGA2) levels. Besides, functional associations of two molecules were investigated through dual luciferase reporter assay. Cell Counting Kit (CCK)-8, colony formation together with Transwell assay was conducted to assess malignant phenotypes of PCa cells, whereas flow cytometry was performed to determine cell apoptosis. Furthermore, a xenograft mouse model was constructed to verify the effect of circTHSD4 on the carcinogenesis of PCa cells.

Results

According to RT-qPCR results, circTHSD4 was up-regulated within PCa tissues and cells, which predicted the dismal prognostic outcome of PCa cases. circTHSD4 silencing within PCa cells markedly suppressed cell growth, migration, and colony formation. circTHSD4 silencing remarkably elevated PCa cell apoptosis and carcinogenesis within the xenograft model. Further, circTHSD4 silencing enhanced docetaxel (DTX) sensitivity in PCa cells. Furthermore, we demonstrated that circTHSD4 modulated the malignancy of PCa cells by regulating HMGA2 expression through sponging miR-203.

Conclusion

Together, our findings suggest that circTHSD4 overexpression could promote the malignant phenotype and DTX resistance in PCa through the regulation of the miR-203/HMGA2 axis.

Utility of noninvasive biomarker testing and MRI to predict a prostate cancer diagnosis

PURPOSE

To assess the diagnostic performance and utility of the ExoDx IntelliScore and an OPKO4K score to predict prostate cancer in men presenting with elevated PSA-both as independent predictors and in combination with clinical/MRI characteristics.

METHODS

Patients with elevated PSA were retrospectively reviewed. Abnormal tests were defined as an OPKO4K score ≥ 7.5% and an ExoDx IntelliScore ≥ 15.6. Four regression models and ROC curves were generated based on: (1) age, PSA, and DRE, (2) model 1 + OPKO4K 4Kscore ≥ 7.5%, (3) model 2 + ExoDx IntelliScore ≥ 15.6, and (4) model 3 + MRI PIRADS 4-5.

RESULTS

359 men received an OPKO4K test, 307 had MRI and 113 had ExoDx tests. 163 men proceeded to prostate biopsy and 196 (55%) were saved from biopsy. Mean age was 65.0 ± 8.7 years and mean PSA was 7.1 ± 6.1 ng/mL. Positive biopsies were found in 84 (51.5%) men. The sensitivity and negative predictive value of an OPKO4K score were 86.7% and 72.3%; values for an ExoDx test were 76.5% and 77.1%, respectively. On regression analysis, clinical markers (Age, PSA, DRE) generated an AUC of 0.559. The addition of an OPKO4K score raised the AUC to 0.653. The stepwise addition of an ExoDx score raised the AUC to 0.766. The combined use of both biomarkers, patient characteristics, and MRI yielded an AUC of 0.825.

CONCLUSION

This analysis demonstrates the high negative predictive value of both the OPKO4K score and ExoDX IntelliScore independently while demonstrating that the combination of an OPKO4K score, an ExoDX IntelliScore, and MRI increases predictive capability for biopsy confirmed prostate cancer.

Incidence and risk factors of prostate cancer among the Northern and Eastern parts of the United Arab Emirates population

BACKGROUND

Prostate cancer (PCa) is a prevalent disease worldwide. However, the incidence and patient-specific risk factors of PCa in the Middle East, specifically in the United Arab Emirates, have not been previously reported.

METHODS

We conducted a retrospective cohort study on 2377 men diagnosed with either benign prostatic hyperplasia (BPH) or PCa in the Northern and Eastern regions of the United Arab Emirates, excluding the Western part, which includes Abu Dhabi. The study spanned from January 2012 and December 2021. To calculate the PCa incidence rate, we utilized the world age-standardized incidence rates (W-ASIR) categorized by age groups. Patient-specific risk factors of PCa were identified through a multivariate logistic regression analysis of clinical data.

RESULTS

A total of 247 cases of PCa and 2130 cases of BPH were included in the study. In our cohort, the W-ASIR for PCa was 21.3 per 100,000 men. The incidence of PCa showed an increasing trend with age, with the highest incidence observed among men aged 70 years and older. Accordingly, multivariate analysis revealed that age over 70 was associated with an increased risk of PCa (OR: 2.546, 95% confidence interval [CI]: 1.892-3.425, p < 0.01). On the other hand, preexisting conditions such as hypertension and diabetes mellitus were found to lower the risk of PCa (OR: 0.222, 95% CI: 0.163-0.302, p < 0.001) and (OR: 0.364, 95% CI: 0.205-0.648, p < 0.001), respectively. Additionally, metformin intake was associated with a reduced risk of PCa (OR: 0.385, 95% CI: 0.190-0.782, p = 0.008); while insulin usage increased the risk of PCa (OR: 2.586, 95% CI: 1.539-4.344, p < 0.001). Anti-BPH medications such as phosphodiesterase inhibitors (OR: 0.223, 95% CI: 0.069-0.723, p = 0.012) or 5-α reductase (OR: 0.206, 95% CI: 0.110-0.389, p < 0.000), were found to lower the risk of PCa.

CONCLUSION

The findings underscore the high incidence of PCa in the United Arab Emirates, with age being a significant factor. Furthermore, the study highlights the influence of certain comorbidities and medications on the risk of developing PCa within the United Arab Emirates population.

How to Integrate Prostate Cancer Biomarkers in Urology Clinical Practice: An Update

Nowadays, the management of prostate cancer has become more and more challenging due to the increasing number of available treatment options, therapeutic agents, and our understanding of its carcinogenesis and disease progression. Moreover, currently available risk stratification systems used to facilitate clinical decision-making have limitations, particularly in providing a personalized and patient-centered management strategy. Although prognosis and prostate cancer-specific survival have improved in recent years, the heterogenous behavior of the disease among patients included in the same risk prognostic group negatively impacts not only our clinical decision-making but also oncological outcomes, irrespective of the treatment strategy. Several biomarkers, along with available tests, have been developed to help clinicians in difficult decision-making scenarios and guide management strategies. In this review article, we focus on the scientific evidence that supports the clinical use of several biomarkers considered by professional urological societies (and included in uro-oncological guidelines) in the diagnosis process and specific difficult management strategies for clinically localized or advanced prostate cancer.

COL10A1 as a Prognostic Biomarker in Association with Immune Infiltration in Prostate Cancer

BACKGROUND

The collagen type X alpha 1 (COL10A1) has recently been found to play an important role in the development and progression of cancer. However, the link between COL10A1 and the tumor immune microenvironment remains understood scantily.

METHODS

In the current study, the pan-cancer data of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were used to investigate the expression mode, the clinical prognostic and diagnostic value of COL10A1 in different tumors. We used TCGA data to assess the correlations between COL10A1 and clinical symptoms of prostate cancer. The R packages "edgR" and "clusterProfiler" were used for differential expression gene and enrichment analysis of COL10A1. Immunohistochemistry was further employed to corroborate the expression of COL10A1 gene in prostate cancer. After that, we used TIMER to evaluate the pertinence of COL10A1 expression to immune infiltration level in prostate cancer.

RESULTS

On the whole, COL10A1 was expressed at significantly higher levels in a variety of tumor tissues than in the corresponding normal tissues. Besides, significant correlations with tumor prognosis and relative exactitude in predicting tumors show that COL10A1 may be a probable prognostic and diagnostic biomarker of prostate cancer. In addition, the evidence indicates a significant correlation between COL10A1 and clinical symptoms of prostate cancer. Furthermore, the main molecular functions of COL10A1 included humoral immune response, complement activation, immunoglobulin, regulation of complement activation, and regulation of humoral immune response. Finally, we found that COL10A1 expression is positively correlated with enhanced macrophage and M2 macrophage infiltration in prostate cancer.

CONCLUSION

The study indicates that COL10A1 might participate in M2 macrophage polarization in prostate cancer. COL10A1 might be an innovative biomarker to evaluate tumor microenvironment immune cell infiltration and prognosis in prostate cancer.

Gene methylation status in focus of advanced prostate cancer diagnostics and improved individual outcomes

Background

Prostate cancer (PCa) is the most prevalent type of male genitourinary tumor, remains the second leading cause of deaths due to cancer in the United States in men. The aim of this study was to perform an integrative epigenetic analysis to explore the epigenetic abnormalities involved in the development and progression of PCa, and present advanced diagnostics and improved individual outcomes.

Methods

Genome-wide DNA methylation profiles obtained from The Cancer Genome Atlas (TCGA) were analyzed and a diagnostic model was constructed. For validation, we employed profiles from the Gene Expression Omnibus (GEO) and methylation data derived from clinical samples. Gene set enrichment analysis (GSEA) and the Tumor Immune Estimation Resource (TIMER) were employed for GSEA and to assess immune cell infiltration, respectively.

Results

An accurate diagnostic method for PCa was established based on the methylation level of Cyclin-D2 (CCND2) and glutathione S-transferase pi-1 (GSTP1), with an impressive area under the curve (AUC) value of 0.937. The model's reliability was further confirmed through validation using four GEO datasets GSE76938 (AUC =0.930), GSE26126 (AUC =0.906), GSE112047 (AUC =1.000), GSE84749 (AUC =0.938) and clinical samples (AUC =0.980). Notably, the TIMER analysis indicated that hypermethylation of CCND2 and GSTP1 was associated with reduced immune cell infiltration, higher tumor purity, and an increased risk of tumor progression.

Conclusions

In conclusion, our study provides a robust and reliable methylation-based diagnostic model for PCa. This model holds promise as an improved approach for screening and diagnosing PCa, potentially enhancing early detection and patient outcomes, as well as for an advanced clinical management for PCa in the framework of predictive, preventive and personalised medicine.

SIGNIFICANCE OF OSTEOPONTIN FOR PREDICTING AGGRESSIVENESS OF PROSTATE CANCER

BACKGROUND

Effective prediction of the course of prostate cancer (PCa) and the stratification of treatment tactics largely depend on the use of prognostic markers that reflect the molecular and biological features of tumors. In view of the important role of matricellular proteins in the modulation of the growing tumor and metastasis of the hormone-dependent neoplasms, the aim of the work was to study the expression of osteopontin (OPN) at the protein and mRNA levels in the PCa tissue in order to assess the significance of this protein for predicting the aggressiveness of PCa.

MATERIALS AND METHODS

The work is based on the analysis of the results of the examination and treatment of 83 patients with PCa of stages II-IV. The study of OPN expression at the level of mRNA and protein in the PCa tissue was carried out using methods of the real time polymerase chain reaction and immunohistochemistry, respectively.

RESULTS

The OPN expression in the PCa tissue was 1.6 times (p < 0.05) higher in patients with regional lymph node metastases compared to patients without metastases. In patients with a Gleason score of < 7, the OPN expression in the tumor tissue was 1.4 times lower (p < 0.05) than in patients with poorly differentiated PCa. In patients with a high risk of tumor progression, the OPN expression level was 1.4 and 2.1 times higher (p < 0.05) compared to patients with a moderate and low risk of PCa progression. The patients with a high OPN expression level in the PCa tissue had significantly decreased 2-year recurrence-free survival rate (by 25%).

CONCLUSIONS

The obtained results indicate the expediency of using OPN expression indicators in the tumor tissue to predict the PCa aggressiveness and assess the risk of its recurrence.

Unveiling the Dichotomy of Urinary Proteins: Diagnostic Insights into Breast and Prostate Cancer and Their Roles

This review covers the diagnostic potential of urinary biomarkers, shedding light on their linkage to cancer progression. Urinary biomarkers offer non-invasive avenues for detecting cancers, potentially bypassing the invasiveness of biopsies. The investigation focuses primarily on breast and prostate cancers due to their prevalence among women and men, respectively. The intricate interplay of urinary proteins is explored, revealing a landscape where proteins exhibit context-dependent behaviors. The review highlights the potential impact of physical activity on urinary proteins, suggesting its influence on tumorigenic behaviors. Exercise-conditioned urine may emerge as a potential diagnostic biomarker source. Furthermore, treatment effects, notably after lumpectomy and prostatectomy, induce shifts in the urinary proteome, indicating therapeutic impacts rather than activating oncogenic signaling. The review suggests further investigations into the double-sided, context-dependent nature of urinary proteins, the potential role of post-translational modifications (PTM), and the integration of non-protein markers like mRNA and metabolites. It also discusses a linkage of urinary proteomes with secretomes from induced tumor-suppressing cells (iTSCs). Despite challenges like cancer heterogeneity and sample variability due to age, diet, and comorbidities, harnessing urinary proteins and proteoforms may hold promise for advancing our understanding of cancer progressions, as well as the diagnostic and therapeutic role of urinary proteins.

CircTENM3 inhibites tumor progression via the miR-558/RUNX3 axis in prostate cancer

BACKGROUND

Prostate cancer (PCa) is currently acknowledged as the second most widespread cancer among men worldwide. Yet, the lack of dependable diagnostic biomarkers and therapeutic targets has presented considerable hurdles to the progression of prostate cancer treatment. Circular RNAs are implicated in the pathogenesis of numerous diseases, positioning them as promising biomarkers for diverse medical conditions. This study aims to uncover a specific circRNA that could serve as a diagnostic and therapeutic target for detecting and treating PCa.

METHODS

The change of circTENM3 expression levels in PCa was detected by qPCR. CCK8 assays, EdU assays, Scratch assay and Transwell migration assay conducted to detect the role of circTENM3 in PCa cells in vitro. RIP assay, RNA-pull down and luciferase reporter assay were performed to explore the mechanism of circTENM3. Gain-of-function analysis was performed to reveal the function of circTENM3 in PCa in vivo.

RESULTS

The results revealed that the expression level of circTENM3 was significantly down-regulated in PCa. CircTENM3 overexpression alleviated the progression of PCa in vitro. Mechanistically, circTENM3 enhanced RUNX3 levels via miR-558 sponge. Gain-of-function analysis determined that circTENM3 overexpression could inhibit PCa progression in vitro.

CONCLUSIONS

Our research offers profound insights into the protective role played by circTENM3 in PCa. CircTENM3 operates as a sponge for miR-558, thereby triggering the elevation of RUNX3 expression, which subsequently curbs the progression of PCa.

Associations of the Geriatric Nutritional Risk Index with high risk for prostate cancer: A cross-sectional study

OBJECTIVES

The geriatric Nutritional Risk Index (GNRI) is an effective tool to assess the nutritional status of the elderly. However, the relationship between the GNRI and the risk for prostate cancer (PCa) remains uncertain in middle-aged and older men. The aim of this study was to investigate the association between the GNRI and the risk for PCa by analyzing the serum total (tPSA) and free prostate-specific antigen (fPSA) levels (including percent fPSA [%fPSA]).

METHODS

Data for this study were obtained from 7396 men ≥40 y of age from the 2001-2010 National Health and Nutrition Survey (NHANES). We obtained the tPSA and fPSA and calculated the %fPSA and the GNRI. Participants with %fPSA >25% and tPSA <4 ng/mL were defined as high PCa risk. The relationship between the GNRI and serum PSA levels was investigated using a linear regression model. The odds ratios (ORs) and 95% confidence intervals (CIs) for the association between the GNRI and PCa risk were estimated by a logistic regression model. The non-linear relationship was also characterized by a restricted cubic spline regression model.

RESULTS

The median of tPSA, fPSA, and %fPSA was 0.90, 0.26, and 29%, respectively. The mean of the GNRI was 29. The proportion of participants in the low PCa- and high PCa-risk groups was 93% and 7%, respectively. There was a negative and linear correlation between the GNRI and serum tPSA and fPSA levels in all models. However, no association between the GNRI and the %fPSA was observed. In the adjusted model, lower GNRI was associated with higher PCa risk (OR, 0.570; 95% CI, 0.415-0.784; Ptrend = 0.001). The restricted cubic spline regression model showed a non-linear and negative association between the GNRI and PCa risk (Pnon-linearity = 0.020), with inflection points of 109.148.

CONCLUSION

The results of this study suggest that nutritional status, as represented by the GNRI, is associated with the risk for PCa.

Clinical characteristics analysis and prognostic nomogram for predicting survival in patients with second primary prostate cancer: a population study based on SEER database

BACKGROUND AND AIMS

Second primary prostate cancer (SPPCa) is a common type of secondary malignancy that negatively impacts patient prognosis. This study aimed to identify prognostic factors for SPPCa patients and develop nomograms to assess their prognosis.

METHODS

Patients diagnosed with SPPCa between 2010 and 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The study cohort was randomly divided into a training set and a validation set. Cox regression analysis, Kaplan‒Meier survival analysis, and least absolute shrinkage and selection operator regression analysis were used to identify independent prognostic factors and develop the nomogram. The nomograms were evaluated using the concordance index (C-index), calibration curve, area under the curve (AUC), and Kaplan-Meier analysis.

RESULTS

A total of 5342 SPPCa patients were included in the study. Independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS) were identified as age, interval between diagnoses, first primary tumor site, and AJCC stage, N stage, M stage, PSA, Gleason score, and SPPCa surgery. Nomograms were constructed based on these prognostic factors, and the performance was evaluated using the C-index (OS: 0.733, CSS: 0.838), AUC, calibration curve, and Kaplan-Meier analysis, which demonstrated excellent predictive accuracy.

CONCLUSION

We successfully established and validated nomograms to predict OS and CSS in SPPCa patients using the SEER database. These nomograms provide an effective tool for risk stratification and prognosis assessment in SPPCa patients, which will aid clinicians in optimizing treatment strategies for this patient population.

Dual targeting in prostate cancer with phytoconstituents as a potent lead: a computational approach for novel drug discovery

Prostate Cancer (PCa) is an abnormal cell growth within the prostate. This condition is the second most widespread malignancy in elderly males and one of the most frequently diagnosed life-threatening conditions. The Androgen receptor signaling pathway played a crucial role in the initiation and spread to increase the risk of PCa. Hence, targeting the AR receptor signaling pathway is a key strategy for a therapeutic plan for PCa. Our study focuses on recognizing potential inhibitors for dual targeting in PCa by using the in-silico approach. In this study, we target the two enzymes that are CYP17A1 (3RUK) and 5α-reductase (3G1R) responsible for PCa, with the help of phytoconstituents. The natural plant contains various phytochemical types produced from secondary metabolites and used as a medical treatment. The in-silico investigation of phytoconstituents and enzymes was done by approaching molecular docking, ADMET analysis, and high-level molecular dynamic simulation used to assess the stability and binding affinities of the protein-ligand complex. Some phytoconstituents, such as Peonidin, Pelargonidin, Malvidin and Berberine show complex has good molecular interaction with protein. The reliability of the docking scores was examined using a molecular dynamic simulation, which revealed that the complex remained stable throughout the simulation, which ranged from 0 to 200 ns. The selected hits may be effective against CYP17A1 (3RUK) and 5α-reductase (3G1R) (PCa) using a computer-aided drug design (CADD) method, which further enables researchers for upcoming in-vivo and in-vitro research, according to our in-silico approach.Communicated by Ramaswamy H. Sarma.

A Luminex Approach to Develop an Anti-Tumor-Associated Antigen Autoantibody Panel for the Detection of Prostate Cancer in Racially/Ethnically Diverse Populations

(1) Background: Autoantibodies to tumor-associated antigens (TAAs) have emerged as promising cancer biomarkers. Luminex technology offers a powerful approach for the simultaneous detection of multiple anti-TAA autoantibodies. (2) Methods: We aimed to utilize Luminex technology to evaluate and optimize a panel of anti-TAAs autoantibodies for detecting prostate cancer (PCa), which included autoantibodies to fourteen TAAs. A total of 163 serum samples (91 PCa, 72 normal controls) were screened to determine the levels of the autoantibodies using the Luminex assay. (3) Results: Twelve autoantibodies exhibited significantly high frequencies ranging from 19.8% to 51.6% in the PCa group. Receiver operating characteristic (ROC) curve analysis revealed area under the curve (AUC) values ranging from 0.609 to 0.868 for the twelve autoantibodies individually. We further confirmed the performance of the HSP60 autoantibody by using an enzyme-linked immunosorbent assay (ELISA) in a larger sample comprising 200 PCa sera, 20 benign prostatic hyperplasia (BPH) sera, and 137 normal control sera. The results obtained from the Luminex assay were consistent with the ELISA findings. We developed a panel consisting of three autoantibodies (p16, IMP2, and HSP60) which achieved an impressive AUC of 0.910 with a sensitivity of 71.4% and a specificity of 95.8%. The panel was also evaluated in PCa patients from different races/ethnicities with the best performance observed in distinguishing the Hispanic American patients with PCa from normal controls. (4) Conclusions: We developed an anti-TAA autoantibody panel for the detection of PCa that exhibits promising performance. This panel holds significant potential as a high-throughput tool to facilitate PCa detection.

Risks of prostate cancer and mortality in the city of Sharjah, United Arab Emirates

Background

Prostatic hyperplasia (BPH) and prostate cancer (PCa) are common age-related diseases in men. According to World Health Organization (WHO), PCa is the second most common cancer among Emirati men. This study aimed to identify the risk factors associated with PCa and mortality in a cohort diagnosed with PCa between 2012 and 2021 in Sharjah, United Arab Emirates (UAE).

Methods

The data collected in this retrospective case-control study included patient demographics and comorbidities, as well as PCa markers such as prostate-specific antigen (PSA), prostate volume, prostate-specific antigen density (PSAD), and Gleason scores. Risk factors for PCa were assessed using multivariate logistic regression analysis, and factors associated with all-cause mortality in PCa patients were evaluated using Cox-proportional hazard analysis.

Results

Of the 192 cases analyzed in this study, 88 were diagnosed with PCa and 104 were diagnosed with BPH. Regarding risk factors for PCa, a higher risk of PCa was associated with age 65 or older (OR=2.76, 95% confidence interval (CI): 1.04-7.30; P=0.038) and serum PSAD greater than 0.1 ng/mL² (OR=3.48, 95% CI:1.66-7.32; P=0.001), whereas being of UAE nationals (OR=0.40, 95% CI:0.18-0.88; P=0.029) were associated with lower risk of PCa, after adjusting for patient demographics and comorbidities. Moreover, regarding cancer markers, higher serum PSA level (P=0.003) and smaller prostate volume (P=0.028) were associated with a higher risk of PCa, after adjusting with patients' age and BMI. Additionally, a high-grade Gleason score was associated with an increased risk of all-cause mortality after adjusting for patient's age and BMI (hazard ratio, aHR= 2.3, 95% CI:1.3-4.1; P= 0.016).

Conclusion

This study found that age 65 or older and serum PSAD greater than 0.1 ng/mL² are risk factors for PCa, while UAE nationality is associated with a lower risk. PSAD may be a better screening marker for PCa compared to traditional markers such as PSA and prostate volume.

Association of TP53 Single Nucleotide Polymorphisms with Prostate Cancer in a Racially Diverse Cohort of Men

Growing evidence indicates the involvement of a genetic component in prostate cancer (CaP) susceptibility and clinical severity. Studies have reported the role of germline mutations and single nucleotide polymorphisms (SNPs) of TP53 as possible risk factors for cancer development. In this single institutional retrospective study, we identified common SNPs in the TP53 gene in AA and CA men and performed association analyses for functional TP53 SNPs with the clinico-pathological features of CaP. The SNP genotyping analysis of the final cohort of 308 men (212 AA; 95 CA) identified 74 SNPs in the TP53 region, with a minor allele frequency (MAF) of at least 1%. Two SNPs were non-synonymous in the exonic region of TP53: rs1800371 (Pro47Ser) and rs1042522 (Arg72Pro). The Pro47Ser variant had an MAF of 0.01 in AA but was not detected in CA. Arg72Pro was the most common SNP, with an MAF of 0.50 (0.41 in AA; 0.68 in CA). Arg72Pro was associated with a shorter time to biochemical recurrence (BCR) (p = 0.046; HR = 1.52). The study demonstrated ancestral differences in the allele frequencies of the TP53 Arg72Pro and Pro47Ser SNPs, providing a valuable framework for evaluating CaP disparities among AA and CA men.

Diagnostic quality model (DQM): an integrated framework for the assessment of diagnostic quality when using AI/ML

BACKGROUND

Laboratory medicine has reached the era where promises of artificial intelligence and machine learning (AI/ML) seem palpable. Currently, the primary responsibility for risk-benefit assessment in clinical practice resides with the medical director. Unfortunately, there is no tool or concept that enables diagnostic quality assessment for the various potential AI/ML applications. Specifically, we noted that an operational definition of laboratory diagnostic quality - for the specific purpose of assessing AI/ML improvements - is currently missing.

METHODS

A session at the 3rd Strategic Conference of the European Federation of Laboratory Medicine in 2022 on "AI in the Laboratory of the Future" prompted an expert roundtable discussion. Here we present a conceptual diagnostic quality framework for the specific purpose of assessing AI/ML implementations.

RESULTS

The presented framework is termed diagnostic quality model (DQM) and distinguishes AI/ML improvements at the test, procedure, laboratory, or healthcare ecosystem level. The operational definition illustrates the nested relationship among these levels. The model can help to define relevant objectives for implementation and how levels come together to form coherent diagnostics. The affected levels are referred to as scope and we provide a rubric to quantify AI/ML improvements while complying with existing, mandated regulatory standards. We present 4 relevant clinical scenarios including multi-modal diagnostics and compare the model to existing quality management systems.

CONCLUSIONS

A diagnostic quality model is essential to navigate the complexities of clinical AI/ML implementations. The presented diagnostic quality framework can help to specify and communicate the key implications of AI/ML solutions in laboratory diagnostics.

The Severity of Pain in Prostate Biopsy Depends on the Biopsy Sector

BACKGROUND: The pain experienced by a patient during a prostate fusion biopsy is cumulative and can also be modulated by many factors. The aim of the study was to assess the association between the degree of pain intensity during prostate biopsy and the region of the biopted organ. MATERIALS AND METHODS: The study included a group of 143 patients who underwent prostate fusion biopsy under local analgesia followed by blockage of the periprostatic nerve. After a biopsy, the patients completed the original questionnaire about the pain experienced during the procedure. RESULTS: There was a statistically significant difference in pain score between cores taken in the apex (median 5 (IQR 2–5)), medium level (median 1 (IQR 1–2)), and prostate base (median 1 (IQR 1–3)) (p < 0.001). The malignancy scale ISUP ≥ 2 (p = 0.038) and lower PSA value (r = −0.17; p = 0.046) are associated with higher pain during procedure. Biopsy time was correlated with discomfort (r = 0.19; p = 0.04). Age (p = 0.65), lesion size (p = 0.29), PI-RADS score (p = 0.86), prostate volume (p = 0.22), and the number of cores (p = 0.56) did not correspond to the pain scale. CONCLUSIONS: The apex is the most sensitive sector of the prostate. ISUP ≥ 2 and patients with low PSA levels more often indicated higher values on the pain rating scale.

Biomarkers of Aggressive Prostate Cancer at Diagnosis

In the United States, prostate cancer (CaP) remains the second leading cause of cancer deaths in men. CaP is predominantly indolent at diagnosis, with a small fraction (25-30%) representing an aggressive subtype (Gleason score 7-10) that is prone to metastatic progression. This fact, coupled with the criticism surrounding the role of prostate specific antigen in prostate cancer screening, demonstrates the current need for a biomarker(s) that can identify clinically significant CaP and avoid unnecessary biopsy procedures and psychological implications of being diagnosed with low-risk prostate cancer. Although several diagnostic biomarkers are available to clinicians, very few comparative trials have been performed to assess the clinical effectiveness of these biomarkers. It is of note, however, that a majority of these clinical trials have been over-represented by men of Caucasian origin, despite the fact that African American men have a 1.7 times higher incidence and 2.1 times higher rate of mortality from prostate cancer. Biomarkers for CaP diagnosis based on the tissue of origin include urine-based gene expression assays (PCA3, Select MDx, ExoDx Prostate IntelliScore, Mi-Prostate Score, PCA3-PCGEM1 gene panel), blood-based protein biomarkers (4K, PHI), and tissue-based DNA biomarker (Confirm MDx). Another potential direction that has emerged to aid in the CaP diagnosis include multi-parametric magnetic resonance imaging (mpMRI) and bi-parametric magnetic resonance imaging (bpMRI), which in conjunction with clinically validated biomarkers may provide a better approach to predict clinically significant CaP at diagnosis. In this review, we discuss some of the adjunctive biomarker tests along with newer imaging modalities that are currently available to help clinicians decide which patients are at risk of having high-grade CaP on prostate biopsy with the emphasis on clinical utility of the tests across African American (AA) and Caucasian (CA) men.

METCAM Is a Potential Biomarker for Predicting the Malignant Propensity of and as a Therapeutic Target for Prostate Cancer

Prostate cancer is the second leading cause of cancer-related death worldwide. This is because it is still unknown why indolent prostate cancer becomes an aggressive one, though many risk factors for this type of cancer have been suggested. Currently, many diagnostic markers have been suggested for predicting malignant prostatic carcinoma cancer; however, only a few, such as PSA (prostate-specific antigen), Prostate Health Index (PHI), and PCA3, have been approved by the FDA. However, each biomarker has its merits as well as shortcomings. The serum PSA test is incapable of differentiating prostate cancer from BPH and also has an about 25% false-positive prediction rate for the malignant status of cancer. The PHI test has the potential to replace the PSA test for the discrimination of BPH from prostate cancer and for the prediction of high-grade cancer avoiding unnecessary biopsies; however, the free form of PSA is unstable and expensive. PCA3 is not associated with locally advanced disease and is limited in terms of its prediction of aggressive cancer. Currently, several urine biomarkers have shown high potential in terms of being used to replace circulating biomarkers, which require a more invasive method of sample collection, such as via serum. Currently, the combined multiple tumor biomarkers may turn out to be a major trend in the diagnosis and assessment of the treatment effectiveness of prostate cancer. Thus, there is still a need to search for more novel biomarkers to develop a perfect cocktail, which consists of multiple biomarkers, in order to predict malignant prostate cancer and follow the efficacy of the treatment. We have discovered that METCAM, a cell adhesion molecule in the Ig-like superfamily, has great potential regarding its use as a biomarker for differentiating prostate cancer from BPH, predicting the malignant propensity of prostate cancer at the early premalignant stage, and differentiating indolent prostate cancers from aggressive cancers. Since METCAM has also been shown to be able to initiate the spread of prostate cancer cell lines to multiple organs, we suggest that it may be used as a therapeutic target for the clinical treatment of patients with malignant prostate cancer.

Natural biomolecules and derivatives as anticancer immunomodulatory agents

Despite advancements in chemotherapy, the issue of resistance and non-responsiveness to many chemotherapeutic drugs that are currently in clinical use still remains. Recently, cancer immunotherapy has gathered attention as a novel treatment against select cancers. Immunomodulation is also emerging as an effective strategy to improve efficacy. Natural phytochemicals, with known anticancer properties, been reported to mediate their effects by modulating both traditional cancer pathways and immunity. The mechanism of phytochemical mediated-immunomodulatory activity may be attributed to the remodeling of the tumor immunosuppressive microenvironment and the sensitization of the immune system. This allows for improved recognition and targeting of cancer cells by the immune system and synergy with chemotherapeutics. In this review, we will discuss several well-known plant-derived biomolecules and examine their potential as immunomodulators, and therefore, as novel immunotherapies for cancer treatment.

Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4-20 ng/mL

Excessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve clinical detection efficiency. We retrospectively enrolled 394 patients with PSA levels of 4-20 ng/mL who underwent prebiopsy bpMRI during 2010-2021. Based on bpMRI and hematological indicators, six models and a nomogram were constructed to predict the outcomes of biopsy. Furthermore, we constructed and evaluated a risk scoring model based on the nomogram. Age, prostate-specific antigen (PSA) density (PSAD), systemic immune-inflammation index, cystatin C level, and the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 score were significant predictors of prostate cancer (PCa) on multivariable logistic regression analyses (P < 0.05) and the five parameters were used to construct the XYFY nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was 0.916. Based on the nomogram, a risk scoring model (XYFY risk model) was constructed and then we divided the patients into low-(XYFY score: < 95), medium-(XYFY score: 95-150), and, high-risk (XYFY score: > 150) groups. The predictive values for diagnosis of PCa and clinically-significant PCa among the three risk groups were 3.0%(6/201), 41.8%(51/122), 91.5%(65/71); 0.5%(1/201), 19.7%(24/122), 60.6%(43/71), respectively. In conclusion, in this study, we used hematological and bpMRI parameters to establish and internally validate a XYFY risk scoring model for predicting the biopsy outcomes for patients with PSA levels of 4-20 ng/mL and this risk model would support clinical decision-making and reduce excessive biopsies.

Differentially expressed glycoproteins in pre- and post-digital rectal examination urine samples for detecting aggressive prostate cancer

Urinary glycoproteins associated with aggressive prostate cancer (AG-PCa) were previously reported using post-digital rectal examination (DRE) urine specimens. To explore the potential of using pre-DRE urine specimens for detecting AG-PCa, we compared glycoproteins between pre- and post-DRE urine specimens, verified the previously identified post-DRE AG-PCa-associated urinary glycoproteins in pre-DRE urine specimens, and explored potential new glycoproteins for AG-PCa detection in pre-DRE urine specimens. Quantitative glycoproteomic data were acquired for 154 pre-DRE urine specimens from 41 patients with no cancer at biopsy, 48 patients with non-AG-PCa (Gleason score = 6), and 65 patients with AG-PCa (Gleason score 7 or above). Compared to glycopeptides from the post-DRE urine data, humoral immunity-related proteins were enriched in pre-DRE urine samples, whereas cell mediated immune response proteins were enriched in post-DRE urine samples. Analyses of AG-PCa-associated glycoproteins from pre-DRE urine revealed that the three urinary glycoproteins, prostate-specific antigen (PSA), prostatic acid phosphatase (ACPP), and CD97 antigen (CD97) that were previously identified in post-DRE urine samples, were also observed as AG-PCa associated glycoproteins in pre-DRE urine. In addition, we identified three new glycoproteins, fibrillin 1 (FBN1), vitronectin (VTN), and hemicentin 2 (HMCN2), to be potentially associated with AG-PCa in pre-DRE urine specimens. In summary, glycoprotein profiles differ between pre- and post-DRE urine specimens. The identified AG-PCa-associated glycoproteins may be further evaluated in large cohort of pre-DRE urine specimens for detecting clinically significant PCa.

Gold Nanoparticles-MWCNT Based Aptasensor for Early Diagnosis of Prostate Cancer

Prostate cancer is one of the most frequently diagnosed male malignancies and can be detected by prostate-specific antigen (PSA) as a biomarker. To detect PSA, several studies have proposed using antibodies, which are not economical and require a long reaction time. In this study, we propose to use self-assembled thiolated single-strand DNA on electrodes functionalized by multi-walled carbon nanotubes (MWCNT) modified with gold nanoparticles (AuNPs) to realize a low-cost label-free electrochemical biosensor. In this regard, the PSA aptamer was immobilized via electrostatic adsorption on the surface of a screen-printed MWCNT/AuNPs electrode. The immobilization process was enhanced due to the presence of Au nanoparticles on the surface of the electrode. Surface characterization of the electrode at different stages of modification was performed by electrochemical impedance spectroscopy (EIS), atomic force microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) and contact angle for surface tension properties. The results showed an increase in surface roughness due to the absorbance of the aptamer on the electrode surfaces. The developed sensor has an extended linear range of 1-100 ng/mL, and a very low limit of detection down to 1 pg/mL. In addition, the reaction has a binding time of only five minutes on the developed electrodes. Investigations of the biosensor selectivity against several substances revealed an efficient selectivity for PSA detection. With this approach, low-cost biosensors with high sensitivity can be realized which have a wide linearity range and a low limit of detection, which are necessary for the early detection of prostate cancer.

Recent Progress in Biosensors for Detection of Tumor Biomarkers

Cancer is a leading cause of death worldwide, with an increasing mortality rate over the past years. The early detection of cancer contributes to early diagnosis and subsequent treatment. How to detect early cancer has become one of the hot research directions of cancer. Tumor biomarkers, biochemical parameters for reflecting cancer occurrence and progression have caused much attention in cancer early detection. Due to high sensitivity, convenience and low cost, biosensors have been largely developed to detect tumor biomarkers. This review describes the application of various biosensors in detecting tumor markers. Firstly, several typical tumor makers, such as neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), prostate-specific antigen (PSA), squamous cell carcinoma antigen (SCCA), carbohydrate, antigen19-9 (CA19-9) and tumor suppressor p53 (TP53), which may be helpful for early cancer detection in the clinic, are briefly described. Then, various biosensors, mainly focusing on electrochemical biosensors, optical biosensors, photoelectrochemical biosensors, piezoelectric biosensors and aptamer sensors, are discussed. Specifically, the operation principles of biosensors, nanomaterials used in biosensors and the application of biosensors in tumor marker detection have been comprehensively reviewed and provided. Lastly, the challenges and prospects for developing effective biosensors for early cancer diagnosis are discussed.

Diagnostic role of plasma ORM2 in differentiating prostate cancer from benign prostatic hyperplasia

PURPOSE

Markers are needed to increase the diagnostic accuracy of prostate-specific antigen (PSA) in prostate cancer (PCa) screening. Mounting evidence has shown that plasma proteins can be hopeful biomarkers for cancer diagnosis.

METHODS

Tandem mass tag (TMT)-based proteomics and parallel reaction monitoring (PRM) analysis were used to screen the differential proteins and further validated in other independent studies (n = 539). Receiver-operating characteristic (ROC), decision curves and nomograms were applied to assess the diagnostic accuracy of biomarkers.

RESULTS

Three candidate proteins (DBP, LCAT and ORM2) were preliminarily screened. Subsequent validation studies revealed significant upregulation of ORM2 in PCa patients across other independent cohorts. ORM2 yielded excellent discriminative power for PCa from benign prostatic hyperplasia (BPH) patients (AUC = 0.861 and 0.814 in validation phases 2a and 2b, respectively). Importantly, the combination of ORM2 and PSA gave better predictive accuracy than PSA alone. We incorporated age, PSA and ORM2 into a nomogram, which yielded C-index of 0.883 in validation phase 2a. A similar C-index of 0.879 was obtained in external validation phase 2b.

CONCLUSIONS

In summary, our study suggests that ORM2 could be treated as a complementary biomarker for PSA in distinguishing PCa from BPH.

Identification of candidate hub genes correlated with the pathogenesis, diagnosis, and prognosis of prostate cancer by integrated bioinformatics analysis

Background

Prostate cancer (PCa) has the second highest morbidity and mortality rates in men. Concurrently, novel diagnostic and prognostic biomarkers of PCa remain crucial.

Methods

This study utilized integrated bioinformatics method to identify and validate the potential hub genes with high diagnostic and prognostic value for PCa.

Results

Four Gene Expression Omnibus (GEO) datasets including 123 PCa samples and 76 normal samples were screened and a total of 368 differentially expressed genes (DEGs), including 120 up-regulated DEGs and 248 down-regulated DEGs, were identified. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the DEGs were majorly enriched in focal adhesion, chemical carcinogenesis, drug metabolism, and cytochrome P450 pathways. Then, 11 hub genes were identified from the protein-protein interaction (PPI) network of the DEGs; 7 of the 11 genes showed the ability of distinguishing PCa from normal prostate based on receiver operating characteristic (ROC) curve analysis. And 5 of the 11 genes were correlated with clinical attributes. Lower CAV1, KRT5, SNAI2 and MYLK expression level were associated with higer Gleason score, advanced pathological T stage and N stage. Lower KRT5 and MYLK expression level were significantly correlated with poor disease-free survival, and lower KRT5 and PTGS2 expression level were significantly related to biochemical recurrence (BCR) status of PCa patients.

Conclusions

In conclusion, CAV1, KRT5, SNAI2, and MYLK show potential clinical diagnostic and prognostic value and could be used as novel candidate biomarkers and therapeutic targets for PCa.

Prognostic significance of lncRNA AP004608.1 in prostate cancer

This study aimed to screen and determine the value of AP004608.1 expression as a biomarker for Prostate cancer (PCa) survival. We investigated the expression and prognosis of AP004608.1 through bioinformatics analysis. Low AP004608.1 expression predicted favorable Overall survival (OS) and Progression-free survival (PFS) in PCa patients, according to the Cancer Genome Atlas (TCGA) database. Cox regression demonstrated that low AP004608.1 expression were in-dependent biomarkers for OS. Moreover, Gene Expression Omnibus (GEO) database was utilized to verify the prognostic role of AP004608.1 in PCa, and the similar results were reached. A meta-analysis revealed that low AP004608.1 expression was closely relevant to better OS. AP004608.1 could constitute a promising prognostic biomarker, and probably plays an important role in PCa.

Cathepsin K: A Versatile Potential Biomarker and Therapeutic Target for Various Cancers

Cancer, a common malignant disease, is one of the predominant causes of diseases that lead to death. Additionally, cancer is often detected in advanced stages and cannot be radically cured. Consequently, there is an urgent need for reliable and easily detectable markers to identify and monitor cancer onset and progression as early as possible. Our aim was to systematically review the relevant roles of cathepsin K (CTSK) in various possible cancers in existing studies. CTSK, a well-known key enzyme in the bone resorption process and most studied for its roles in the effective degradation of the bone extracellular matrix, is expressed in various organs. Nowadays, CTSK has been involved in various cancers such as prostate cancer, breast cancer, bone cancer, renal carcinoma, lung cancer and other cancers. In addition, CTSK can promote tumor cells proliferation, invasion and migration, and its mechanism may be related to RANK/RANKL, TGF-β, mTOR and the Wnt/β-catenin signaling pathway. Clinically, some progress has been made with the use of cathepsin K inhibitors in the treatment of certain cancers. This paper reviewed our current understanding of the possible roles of CTSK in various cancers and discussed its potential as a biomarker and/or novel molecular target for various cancers.

Molecular and pathological subtypes related to prostate cancer disparities and disease outcomes in African American and European American patients

Prostate cancer (PCa) disproportionately affects African American (AA) men, yet present biomarkers do not address the observed racial disparity. The objective of this study was to identify biomarkers with potential benefits to AA PCa patients. Differentially expressed genes (DEG) analysis coupled with gene set enrichment analysis (GSEA) and leading-edge genes analysis showed that the keratin family of genes, including KRT8, KRT15, KRT19, KRT34, and KRT80, constituted the single most prominent family of genes enriched in AA compared to European American (EA) PCa cell lines. In PCa patients (TCGA and MSKCC patient cohorts), KRT8, KRT15, and KRT19 expression were relatively higher in AA than in EA patients. The differences in the expression of KRT15 and KRT19, but not KRT8, were enhanced by Gleason score and ERG fusion status; in low Gleason (Gleason ≤ 6 [TCGA cohort] and Gleason ≤ 7 [MSKCC cohort]), the expression of KRT15 and KRT19 was significantly (p ≤ 0.05) higher in AA than in EA patients. Survival analysis revealed that high expression of KRT15 and KRT19 was associated with increased risk of biochemical recurrence in low Gleason category patients in the TCGA patient cohort. Interestingly, KRT15 and KRT19 expression were also associated with an increased risk of death in the metastatic prostate adenocarcinoma cohort, suggesting the potential to predict the risks of disease recurrence and death in the low Gleason category and advanced disease conditions respectively. Gene set enrichment analysis revealed known oncogenic gene signatures, including KRAS and ERBB2, to be enriched in patients expressing high KRT15 and KRT19. Furthermore, high KRT15 and KRT19 were linked to the basal and LumA PCa subtypes, which are associated with poor postoperative androgen deprivation therapy (ADT) response compared to the LumB subtype. Taken together, the present study identifies genes with high expression in AA than in EA PCa. The identified genes are linked to oncogenic gene signatures, including KRAS and ERBB2, and to basal and LumA PCa subtypes that are associated with poor postoperative ADT response. This study, therefore, reveals biomarkers with the potential to address biomarker bias in PCa risk stratification and/or prognosis.

Aptamers as Theragnostic Tools in Prostate Cancer

Despite of the capacity that several drugs have for specific inhibition of the androgen receptor (AR), in most cases, PCa progresses to an androgen-independent stage. In this context, the development of new targeted therapies for prostate cancer (PCa) has remained as a challenge. To overcome this issue, new tools, based on nucleic acids technology, have been developed. Aptamers are small oligonucleotides with a three-dimensional structure capable of interacting with practically any desired target, even large targets such as mammalian cells or viruses. Recently, aptamers have been studied for treatment and detection of many diseases including cancer. In PCa, numerous works have reported their use in the development of new approaches in diagnostics and treatment strategies. Aptamers have been joined with drugs or other specific molecules such as silencing RNAs (aptamer–siRNA chimeras) to specifically reduce the expression of oncogenes in PCa cells. Even though these studies have shown good results in the early stages, more research is still needed to demonstrate the clinical value of aptamers in PCa. The aim of this review was to compile the existing scientific literature regarding the use of aptamers in PCa in both diagnosis and treatment studies. Since Prostate-Specific Membrane Antigen (PSMA) aptamers are the most studied type of aptamers in this field, special emphasis was given to these aptamers.

Prognostic Role of RNA Expression Molecular Biomarkers in Prostate and Bladder Cancers

Prostate cancer and bladder cancer are two of the most common urologic cancers. Cancer risk stratification and prediction of prognosis have always been challenging. Following recent advances in genomic and proteomic technologies, several genomic biomarkers have been developed and proposed as a noninvasive and nonexpansive approach that can supplement our current data to improve prediction and accuracy. Several biomarkers have shown efficacy in patient risk stratification and in predicting prognosis. Here we provide a mini-review of current RNA biomarkers approved by the US Food and Drug Administration, including the Decipher, Oncotype DX Prostate, and Prolaris tests. We also provide a summary of their approved clinical utility in prostate cancer and bladder cancer management. PATIENT SUMMARY: A number of tests are available for measuring expression levels of genes related to prostate or bladder cancer. We review the usefulness of these tests in stratifying risk for patients and predicting their prognosis.

Construction of a Comprehensive Diagnostic Scoring Model for Prostate Cancer Based on a Novel Six-Gene Panel

Accumulating evidence indicates that the N6-methyladenosine (m⁶A) modification plays a critical role in human cancers. Given the current understanding of m⁶A modification, this process is believed to be dynamically regulated by m⁶A regulators. Although the discovery of m⁶A regulators has greatly enhanced our understanding of the mechanism underlying m⁶A modification in cancers, the function and role of m⁶A in the context of prostate cancer (PCa) remain unclear. Here, we aimed to establish a comprehensive diagnostic scoring model that can act as a complement to prostate-specific antigen (PSA) screening. To achieve this, we first drew the landscape of m⁶A regulators and constructed a LASSO-Cox model using three risk genes (METTL14, HNRNP2AB1, and YTHDF2). Particularly, METTL14 expression was found to be significantly related to overall survival, tumor T stage, relapse rate, and tumor microenvironment of PCa patients, showing that it has important prognostic value. Furthermore, for the sake of improving the predictive ability, we presented a comprehensive diagnostic scoring model based on a novel 6-gene panel by combining with genes found in our previous study, and its application potential was further validated by the whole TCGA and ICGC cohorts. Our study provides additional clues and insights regarding the treatment and diagnosis of PCa patients.

Correlation of NTRK1 Downregulation with Low Levels of Tumor-Infiltrating Immune Cells and Poor Prognosis of Prostate Cancer Revealed by Gene Network Analysis

Prostate cancer (PCa) is a life-threatening heterogeneous malignancy of the urinary tract. Due to the incidence of prostate cancer and the crucial need to elucidate its molecular mechanisms, we searched for possible prognosis impactful genes in PCa using bioinformatics analysis. A script in R language was used for the identification of Differentially Expressed Genes (DEGs) from the GSE69223 dataset. The gene ontology (GO) of the DEGs and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. A protein–protein interaction (PPI) network was constructed using the STRING online database to identify hub genes. GEPIA and UALCAN databases were utilized for survival analysis and expression validation, and 990 DEGs (316 upregulated and 674 downregulated) were identified. The GO analysis was enriched mainly in the “collagen-containing extracellular matrix”, and the KEGG pathway analysis was enriched mainly in “focal adhesion”. The downregulation of neurotrophic receptor tyrosine kinase 1 (NTRK1) was associated with a poor prognosis of PCa and had a significant positive correlation with infiltrating levels of immune cells. We acquired a collection of pathways related to primary PCa, and our findings invite the further exploration of NTRK1 as a biomarker for early diagnosis and prognosis, and as a future potential molecular therapeutic target for PCa.

Effective Diagnosis of Prostate Cancer Based on mRNAs From Urinary Exosomes

Background

Novel non-invasive biomarkers are urgently required to improve the diagnostic sensitivity and specificity of prostate cancer (PCa). Therefore, the diagnostic value of following candidate genes (ERG, PCA3, ARV7, PSMA, CK19, and EpCAM) were estimated by testing mRNAs from urinary exosomes of patients with primary PCa.

Methods

Exosomes were obtained using size-exclusion chromatography (SEC), out of which RNAs were extracted, then analyzed by quantitative reverse transcription-polymerase chain reaction according to manufacturer's protocol.

Results

The expression of urinary exosomal ERG, PCA3, PSMA, CK19, and EpCAM were significantly increased in patients with PCa compared with healthy males. In addition, the levels of urinary exosomal ERG, ARV7, and PSMA were intimately correlated with the Gleason score in PCa patients (P < 0.05). The receiver operating characteristic curves (ROCs) showed that urinary exosomal ERG, PCA3, PSMA, CK19, and EpCAM were able to distinguish patients with PCa from healthy individuals with the area under the curve (AUC) of 0.782, 0.783, 0.772, 0.731, and 0.739, respectively. Urinary exosomal PCA3 and PSMA distinguished PCa patients from healthy individuals with an AUC of 0.870. Combination of urinary exosomal PCA3, PSMA with serum PSA and PI-RADS achieved higher AUC compared with PSA alone (0.914 and 0.846, respectively). Kaplan-Meier curves demonstrated that PCA3, ARV7, and EpCAM were associated in androgen-deprivation therapy (ADT) failure time which is defined as from the initiation of ADT in hormone-sensitive stage to the development of castration-resistant prostate cancer.

Conclusion

These findings suggested that mRNAs from urinary exosomes have the potential in serving as novel and non-invasive indicators for PCa diagnosis and prediction.

Current Methods and Caveats to Risk Factor Assessment in Cutaneous Squamous Cell Carcinoma (cSCC): A Narrative Review

Cutaneous squamous cell carcinoma (cSCC) is the second most common form of skin cancer, and the number of deaths due to cSCC is estimated to be greater than the number attributed to melanoma. While the majority of cSCC tumors are resectable with clear margins by standard excision practices, some lesions exhibit high-risk factors for which there is evidence of their association with recurrence, metastasis, and disease-specific death. The most commonly used staging systems and guidelines in the USA for cSCC are based on these clinical and pathologic high-risk factors; however, these are limited in their ability to predict adverse events, thus posing a challenge for implementing risk-directed patient management. Since the development of local recurrence and/or metastasis has a profound impact on the survival of patients with cSCC, accurate identification of patients at high risk for poor outcomes is critical, potentially allowing for early and appropriate adjuvant therapy. This review summarizes the current cSCC literature with a focus on how differing clinical assessments within each of the five selected risk factors (perineural invasion, differentiation, depth of invasion, size, and location) can influence the evaluation of patient outcomes, along with summarizing the utility of staging and guidelines, and highlighting the potential for molecular tools to improve upon cSCC risk assessment.

Nonmetastatic Castration-Resistant Prostate Cancer: Current Challenges and Trends

Prostate carcinoma is a highly prevalent biologically and clinically diverse disease, generally associated with a consistent elevation of prostate-specific antigen levels. Castration-resistant prostate cancer represents a heterogeneous clinical setting that ranges from patients with an asymptomatic prostate-specific antigen elevation after hormone blockade failure and good performance status to patients with significant debilitating symptoms and rapidly progressive disease, leading to death. Nonmetastatic castration-resistant prostate cancer is a transient disease stage defined over specific criteria established within a sensitive time period. The majority of the patients with nonmetastatic castration-resistant prostate cancer will eventually develop metastatic lesions, associated with prostate cancer-specific morbidity and mortality. However, progression to metastatic disease is a heterogeneous process still not fully understood, with studies suggesting that younger age, high Gleason score (> 7), high prostate-specific antigen levels, reduced prostate-specific antigen doubling time (< 6 months), and a rapid alkaline phosphatase rise as potentially associated factors. Although the nonmetastatic castration-resistant prostate cancer treatment landscape has substantially evolved in recent years, the disease heterogeneity makes treatment decisions for this population challenging in the effort to achieve a balance between the risk of disease progression and the toxicity of new treatments in patients who often have associated comorbidities, yet are generally asymptomatic. The present article addresses the current main challenges in nonmetastatic castration-resistant prostate cancer management, including in diagnosis, owing to the development of new imaging modalities with a direct impact in disease detection, prognostic classification, as a result of the traditionally oversimplified definition of disease aggressiveness (mainly based on prostate-specific antigen doubling time), and patient selection for the most adequate treatment.

Prostate cancer specific mortality after 5α-reductase inhibitors medication in benign prostatic hyperplasia patients: systematic review and meta-analysis

BACKGROUND

Our study was conducted to investigate the effect of 5-ARI on the death rate from prostate cancer by means of an updated meta-analysis using related data.

METHODS

We did comprehensive literature searches using the PubMed, Embase, and Cochrane databases through July 2019. We evaluated the risk of bias in such studies using the ROBINS-I tool and analyzed deaths from cancer and deaths from all causes using HR.

RESULTS

The meta-analysis included 11 studies. The pooled overall HRs for cancer-specific deaths between 5-ARI treatment versus non-exposed groups were 0.937 (95% CI: 0.730, 1.201). In the subgroup moderator analysis, the number of patients and additional medication variables were significantly associated with deaths from all causes (p = 0.022 and p = 0.005, respectively). For detecting the publication bias or small-study effect in the included studies, we performed Begg and Mazumdar's correlation test (0.851 and 0.573) and Egger's regression coefficient test (0.035 and 0.245) and ​suggested that there was no evidence of publication bias or small-study effect in this meta-analysis.

CONCLUSIONS

Our study indicated that exposure to 5-ARI had no close association between the overall death rate or cancer-specific deaths. To confirm these results, well-designed prospective studies with large samples are required.

The Role and Significance of Bioumoral Markers in Prostate Cancer

The prostate is one of the most clinically accessible internal organs of the genitourinary tract in men. For decades, the only method of screening for prostate cancer (PCa) has been digital rectal examination of 1990s significantly increased the incidence and prevalence of PCa and consequently the morbidity and mortality associated with this disease. In addition, the different types of oncology treatment methods have been linked to specific complications and side effects, which would affect the patient's quality of life. In the first two decades of the 21st century, over-detection and over-treatment of PCa patients has generated enormous costs for health systems, especially in Europe and the United States. The Prostate Specific Antigen (PSA) is still the most common and accessible screening blood test for PCa, but with low sensibility and specificity at lower values (<10 ng/mL). Therefore, in order to avoid unnecessary biopsies, several screening tests (blood, urine, or genetic) have been developed. This review analyzes the most used bioumoral markers for PCa screening and also those that could predict the evolution of metastases of patients diagnosed with PCa.

Biomarkers for Treatment Response in Advanced Prostate Cancer

Simple Summary

Prostate cancer is a leading cause of cancer-related death among males. Many treatments are available to manage the disease, but despite this, ultimately advanced prostate cancer is incurable and fatal. In order to improve survival and minimize side effects from these various treatments, the treatments need to be given in an optimal sequence or combination. This optimal use of therapies must be individualized, and biomarkers can be used for these decisions. Biomarkers can be useful in predicting whether a patient will respond to a treatment option and may help avoid use of therapies that are not expected to be effective. Many biomarkers are already in clinical use while many others are currently being investigated and may become part of clinical practice in future. In this review, we discuss both established and novel biomarkers with a role in management of advanced prostate cancer.

Abstract

Multiple treatment options with different mechanisms of action are currently available for the management of metastatic prostate cancer. However, the optimal use of these therapies—specifically, the sequencing of therapies—is not well defined. In order to obtain the best clinical outcomes, patients need to be treated with the therapies that are most likely to provide benefit and avoid toxic therapies that are unlikely to be effective. Ideally, predictive biomarkers that allow for the selection of the therapies most likely to be of benefit would be employed for each treatment decision. In practice, biomarkers including tumor molecular sequencing, circulating tumor DNA, circulating tumor cell enumeration and androgen receptor characteristics, and tumor cell surface expression (PSMA), all may have a role in therapy selection. In this review, we define the established prognostic and predictive biomarkers for therapy in advanced prostate cancer and explore emerging biomarkers.