Approaches to urinary detection of prostate cancer

Is prostatic adenocarcinoma detectable by urine cytology-A multicenter retrospective review

INTRODUCTION

Urine cytology is robust for the diagnosis of urothelial lesions, but data on the detection rates of prostatic adenocarcinoma in urine cytology is limited. In this study, a multicenter review was performed to define the clinical role of urine cytology in diagnosis of prostatic adenocarcinoma.

METHODS

Cytologic diagnoses of lower tract urine cytology specimens with histology-proven prostatic adenocarcinoma from three institutions, from a period of over two decades, were reviewed. Clinicopathological parameters-tumor grade, stage, histologic features, and preanalytical factors-prostate-specific antigen (PSA) level and lesion size, were retrieved and compared with cytologic diagnoses.

RESULTS

In total, 2115 urine cytology specimens from 1119 patients were retrieved. The atypia (or above/C3+) and suspicious (or above/C4+) rates were 19.48% and 3.36%. Bilobar and extracapsular involvement, lymphovascular invasion, Gleason score, and International Society of Urological Pathology grade were associated with a positive urine diagnosis (p < 0.05). The atypia (C3+) and suspicious (C4+) rates of urine cytology in patients with a PSA level of ≤4.0 ng/mL was paradoxically higher (p < 0.01), but PSA levels correlated positively with urine diagnosis at higher cutoffs (>10, >20, >50, >100 ng/mL). All these factors remained significant on multivariate analysis (p < 0.05), including a negative correlation with low-PSA (≤4.0 ng/mL, p = 0.001) and positive correlation with high-PSA (>20 ng/mL, p = 0.020). Lesion size and multifocality were not associated with urine cytology diagnosis (p > 0.05).

CONCLUSION

Urine cytology showed low sensitivity in detection of prostatic adenocarcinoma. Detection rates were largely positively correlated with PSA levels but not for lesion size nor multifocality, limiting its clinical utility.

Preadsorbed Particles with Cross-Shaped DNA Scaffolds Enable Spherical Nucleic Acid to Directly Respond to Protein in Complex Matrices

Spherical nucleic acids (SNAs) usually suffer from an undesired protein corona and disrupt the function of nucleic acids (e.g., aptamer), thereby compromising recognition and response to proteins in the biological environment. To overcome the unexpected protein interference, specific proteins were initially adsorbed onto magnetic particles (MPs) as a customized protein corona "shield" with fabricated nucleic acid scaffolds, forming a preadsorbed particle-based spherical nucleic acid (pap-SNA). By comparing with AuNPs-SNA or COOH-MPs, it was found that such a protein corona "shield" of pap-SNA significantly eliminated the adsorption of nonspecific proteins or other biomolecules onto the MPs' interface, thereby enabling the SNA to directly respond to proteins in complex matrices. To further reduce the interference of protein on SNA performance, a series of nucleic acid scaffolds (Z-type, dsDNA type, circle type, T-type, and cross-shaped type) were designed by changing the rigidity and thermal stability of functional nucleic acids on the MPs. As a consequence, the pap-SNA with a cross-shaped scaffold improved the sensitivity of the pap-SNA-based detection platform in that the orderly arrangement of functional nucleic acids provides a steric hindrance to interferents. Moreover, the presence of the cross-shaped scaffold not only enables pap-SNA to exhibit a proportional response to varied protein concentrations but also enhances the detection sensitivity of pap-SNA by 160% in serum and by 190% in urine. Therefore, incorporating optimized DNA scaffolds maintained and facilitated the function of a probe (aptamer) on the surface of SNA. This approach offers a pathway for creating SNA with direct response and anti-interference capability applicable to detecting diverse biomolecules such as nucleic acids and proteins in biological matrices.

Prostate cancer theragnostics biomarkers: An update

Biomarkers are molecules such as proteins, genes, or other substances that may be tested to determine the stage of the tumor in a patient. The role of prostate cancer biomarkers is pivotal and the combination of prostate cancer immunotherapy with efficient biomarkers has emerged as a beneficial treatment strategy and its use has increased rapidly. The two primary objectives of this current prostate cancer early detection programs were recognizing non-symptomatic individuals with prostate cancer requiring prostatic core biopsy and identifying men with prostate cancer who might benefit from definitive medical treatment. The progress that has been made so far in the identification of the biomarkers that can be used for the classification, prediction and prognostication of prostate cancer, and as major targets for its clinical intervention has been well summarized in this review.

Discrimination of serum samples of prostate cancer and benign prostatic hyperplasia with 1H-NMR metabolomics

Prostate cancer continues to be a prominent health concern for men globally. Current screening techniques, primarily the prostate-specific antigen (PSA) test and digital rectal examination (DRE), possess inherent limitations, with prostate biopsy being the definitive diagnostic procedure. The invasive nature of the biopsy and other drawbacks of current screening tests create the need for non-invasive and more accurate diagnostic methods. This study utilized 1H-NMR (Proton Nuclear Magnetic Resonance) based serum metabolomics to differentiate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH). Serum samples from 40 PCa and 41 BPH patients were analysed using 1H-NMR spectroscopy. PepsNMR was utilized for preprocessing the raw NMR data, and the binned spectra were examined for patterns distinguishing PCa and BPH. Principal component analysis (PCA) showed a moderate separation between PCa and BPH, highlighting the distinct metabolic profiles of both conditions. A logistic regression model was then developed, which demonstrated good performance in distinguishing between the two conditions. The results showed significant variance in multiple metabolites between PCa and BPH, such as isovaleric acid, ethylmalonic acid, formate, and glutamic acid. This research underlines the potential of 1H-NMR-based serum metabolomics as a promising tool for improved prostate cancer screening, offering an alternative to the limitations of current screening methods.

Recent Electrochemical Advancements for Liquid-Biopsy Nucleic Acid Detection for Point-of-Care Prostate Cancer Diagnostics and Prognostics

Current diagnostic and prognostic tests for prostate cancer require specialised laboratories and have low specificity for prostate cancer detection. As such, recent advancements in electrochemical devices for point of care (PoC) prostate cancer detection have seen significant interest. Liquid-biopsy detection of relevant circulating and exosomal nucleic acid markers presents the potential for minimally invasive testing. In combination, electrochemical devices and circulating DNA and RNA detection present an innovative approach for novel prostate cancer diagnostics, potentially directly within the clinic. Recent research in electrochemical impedance spectroscopy, voltammetry, chronoamperometry and potentiometric sensing using field-effect transistors will be discussed. Evaluation of the PoC relevance of these techniques and their fulfilment of the WHO's REASSURED criteria for medical diagnostics is described. Further areas for exploration within electrochemical PoC testing and progression to clinical implementation for prostate cancer are assessed.

Computer-assisted urine cytology: Faster, cheaper, better?

Recent advancements in computer-assisted diagnosis (CAD) have catalysed significant progress in pathology, particularly in the realm of urine cytopathology. This review synthesizes the latest developments and challenges in CAD for diagnosing urothelial carcinomas, addressing the limitations of traditional urinary cytology. Through a literature review, we identify and analyse CAD models and algorithms developed for urine cytopathology, highlighting their methodologies and performance metrics. We discuss the potential of CAD to improve diagnostic accuracy, efficiency and patient outcomes, emphasizing its role in streamlining workflow and reducing errors. Furthermore, CAD tools have shown potential in exploring pathological conditions, uncovering novel biomarkers and prognostic/predictive features previously unknown or unseen. Finally, we examine the practical issues surrounding the integration of CAD into clinical practice, including regulatory approval, validation and training for pathologists. Despite the promising results, challenges remain, necessitating further research and validation efforts. Overall, CAD presents a transformative opportunity to revolutionize diagnostic practices in urine cytopathology, paving the way for enhanced patient care and outcomes.

Urine biomarkers can predict prostate cancer and PI-RADS score prior to biopsy

Prostate-Specific Antigen (PSA) based screening of prostate cancer (PCa) needs refinement. The aim of this study was the identification of urinary biomarkers to predict the Prostate Imaging-Reporting and Data System (PI-RADS) score and the presence of PCa prior to prostate biopsy. Urine samples from patients with elevated PSA were collected prior to prostate biopsy (cohort = 99). The re-analysis of mass spectrometry data from 45 samples was performed to identify urinary biomarkers to predict the PI-RADS score and the presence of PCa. The most promising candidates, i.e. SPARC-like protein 1 (SPARCL1), Lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1), Alpha-1-microglobulin/bikunin precursor (AMBP), keratin 13 (KRT13), cluster of differentiation 99 (CD99) and hornerin (HRNR), were quantified by ELISA and validated in an independent cohort of 54 samples. Various biomarker combinations showed the ability to predict the PI-RADS score (AUC = 0.79). In combination with the PI-RADS score, the biomarkers improve the detection of prostate carcinoma-free men (AUC = 0.89) and of those with clinically significant PCa (AUC = 0.93). We have uncovered the potential of urinary biomarkers for a test that allows a more stringent prioritization of mpMRI use and improves the decision criteria for prostate biopsy, minimizing patient burden by decreasing the number of unnecessary prostate biopsies.

Clinical value of ultrasound-guided full-needle path anesthesia in transperineal prostate biopsy: An observational study

BACKGROUND

The pain sensation in a transperineal prostate biopsy was obvious. This study explored the clinical value of ultrasound-guided full-needle path anesthesia in transperineal prostate biopsy.

METHODS

Two hundred patients who underwent ultrasound-guided transperineal prostate biopsy at our department were randomly divided into 2 groups. The control group received routine local infiltration anesthesia, and the experimental group received ultrasound-guided full-needle path anesthesia. Immediately after biopsy, visual analog scoring was used to evaluate pain during the biopsy process. Seven days postbiopsy, telephone follow-up revealed symptoms, such as hematuria and discomfort during urination. The measured data were expressed as x ± s. The 2 groups were compared using the t test, and the differences were statistically significant (P < .05).

RESULTS

There were no significant differences in age, prostate-specific antigen (PSA) level, or prostate volume between the 2 groups, and all patients underwent prostate biopsy. The pain score of visual analog score was (2.55 ± 0.88), urination discomfort was (1.86 ± 0.67) days and hematuria time was (2.87 ± 0.91) days in the experimental group after biopsy. In the control group, the pain score of visual analog scale was (4.32 ± 0.94), the urination discomfort was (2.3 ± 0.77) days, and the hematuria time was (2.85 ± 0.83) days. Pain scores and urination discomfort were compared between the 2 groups (P < .01). Pain and urination discomfort associated with prostate biopsy in the experimental group were significantly lower than those in the control group.

CONCLUSION

Ultrasound-guided full needle path anesthesia can alleviate pain sensation in patients undergoing transperineal prostate biopsy and has high clinical value.

Diagnosis and classification of intestinal diseases with urine by surface-enhanced Raman spectroscopy

Intestinal Disease (ID) is often characterized by clinical symptoms such as malabsorption, intestinal dysfunction, and injury. If treatment is not timely, it will increase the risk of cancer. Early diagnosis of ID is the key to cure it. There are certain limitations of the conventional diagnostic methods, such as low sensitivity and specificity. Therefore, development of a highly sensitive, non-invasive diagnostic method for ID is extremely important. Urine samples are easier to collect and more sensitive to changes in biomolecules than other pathological diagnostic samples such as tissue and blood. In this paper, a diagnostic method of ID with urine by surface-enhanced Raman spectroscopy (SERS) is proposed. A classification model between ID patients and healthy controls (HC) and a classification model between different pathological types of ID (i.e., benign intestinal disease (BID) and colorectal cancer (CRC)) are established. Here, 830 urine samples, including 100 HC, 443 BID, and 287 CRC, were investigated by SERS. The ID/HC classification model was developed by analyzing the SERS spectra of 150 ID and 100 HC, while BID/CRC classification model was built with 300 BID and 150 CRC patients by principal component analysis (PCA)-support vector machines (SVM). The two established models were internally verified by leave-one-out-cross-validation (LOOCV). Finally, the BID/CRC classification model was further evaluated by 143 BID and 137 CRC patients as an external test set. It shows that the accuracy of the classification model validated by the LOOCV for ID/HC and BID/CRC is 86.4% and 85.56%, respectively. And the accuracy of the BID/CRC classification model with external test set is 82.14%. It shows that high accuracy can be achieved with these two established classification models. It indicates that ID patients in the general population can be identified and BID and CRC patients can be further classified with measuring urine by SERS. It shows that the proposed diagnostic method and established classification models provide valuable information for clinicians to early diagnose ID patients and analyze different stages of ID.

Rapid Near-Patient Impedimetric Sensing Platform for Prostate Cancer Diagnosis

With the global escalation of concerns surrounding prostate cancer (PCa) diagnosis, reliance on the serologic prostate-specific antigen (PSA) test remains the primary approach. However, the imperative for early PCa diagnosis necessitates more effective, accurate, and rapid diagnostic point-of-care (POC) devices to enhance the result reliability and minimize disease-related complications. Among POC approaches, electrochemical biosensors, known for their amenability and miniaturization capabilities, have emerged as promising candidates. In this study, we developed an impedimetric sensing platform to detect urinary zinc (UZn) in both artificial and clinical urine samples. Our approach lies in integrating label-free impedimetric sensing and the introduction of porosity through surface modification techniques. Leveraging a cellulose acetate/reduced graphene oxide composite, our sensor's recognition layer is engineered to exhibit enhanced porosity, critical for improving the sensitivity, capture, and interaction with UZn. The sensitivity is further amplified by incorporating zincon as an external dopant, establishing highly effective recognition sites. Our sensor demonstrates a limit of detection of 7.33 ng/mL in the 0.1-1000 ng/mL dynamic range, which aligns with the reference benchmark samples from clinical biochemistry. Our sensor results are comparable with the results of inductively coupled plasma mass spectrometry (ICP-MS) where a notable correlation of 0.991 is achieved. To validate our sensor in a real-life scenario, tests were performed on human urine samples from patients being investigated for prostate cancer. Testing clinical urine samples using our sensing platform and ICP-MS produced highly comparable results. A linear correlation with R2 = 0.964 with no significant difference between two groups (p-value = 0.936) was found, thus confirming the reliability of our sensing platform.

Advancements in MRI-Based Radiomics and Artificial Intelligence for Prostate Cancer: A Comprehensive Review and Future Prospects

The use of multiparametric magnetic resonance imaging (mpMRI) has become a common technique used in guiding biopsy and developing treatment plans for prostate lesions. While this technique is effective, non-invasive methods such as radiomics have gained popularity for extracting imaging features to develop predictive models for clinical tasks. The aim is to minimize invasive processes for improved management of prostate cancer (PCa). This study reviews recent research progress in MRI-based radiomics for PCa, including the radiomics pipeline and potential factors affecting personalized diagnosis. The integration of artificial intelligence (AI) with medical imaging is also discussed, in line with the development trend of radiogenomics and multi-omics. The survey highlights the need for more data from multiple institutions to avoid bias and generalize the predictive model. The AI-based radiomics model is considered a promising clinical tool with good prospects for application.

Exosome Analysis in Prostate Cancer: How They Can Improve Biomarkers' Performance

Exosomes are extracellular nanovesicles (EV), that is, carriers of different biomolecules such as lipids, proteins, nucleic acids. Their composition and the fact that their release dramatically increases in cases of tumorigenesis open up different scenarios on their possible application to research into new biomarkers. The first purpose of the present review was to specifically analyze and compare different methodologies available for the use of exosomes in prostate cancer (PC). The most widely applied methodologies include ultracentrifugation techniques, size-based techniques, immunoaffinity capture-based techniques (mainly ELISA), and precipitation. To optimize the acquisition of exosomes from the reference sample, more techniques can be applied in sequence for a single extraction, thereby determining an increase in labor time and costs. The second purpose was to describe clinical results obtained with the analysis of PSA-expressing exosomes in PC; this provides an incredibly accurate method of discriminating between healthy patients and those with prostate disease. Specifically, the IC-ELISA alone method achieved 98.57% sensitivity and 80.28% specificity in discriminating prostate cancer (PC) from benign prostatic hyperplasia (BPH). An immunocapture-based ELISA assay was performed to quantify and characterize carbonic anhydrase (CA) IX expression in exosomes. The results revealed that CA IX positive exosomes were 25-fold higher in plasma samples from PC patients than in those from healthy controls. The analysis of PC-linked exosomes represents a promising diagnostic model that can effectively distinguish patients with PC from those with non-malignant prostatic disease. However, the use of exosome analysis in clinical practice is currently limited by several issues, including a lack of standardization in the analytical process and high costs, which are still too high for large-scale use.

Urine biomarkers in cancer detection: A systematic review of preanalytical parameters and applied methods

The aim of this review was to explore the status of urine sampling as a liquid biopsy for noninvasive cancer research by reviewing used preanalytical parameters and protocols. We searched two main health sciences databases, PubMed and Web of Science. From all eligible publications (2010-2022), information was extracted regarding: (a) study population characteristics, (b) cancer type, (c) urine preanalytics, (d) analyte class, (e) isolation method, (f) detection method, (g) comparator used, (h) biomarker type, (i) conclusion and (j) sensitivity and specificity. The search query identified 7835 records, of which 924 unique publications remained after screening the title, abstract and full text. Our analysis demonstrated that many publications did not report information about the preanalytical parameters of their urine samples, even though several other studies have shown the importance of standardization of sample handling. Interestingly, it was noted that urine is used for many cancer types and not just cancers originating from the urogenital tract. Many different types of relevant analytes have been shown to be found in urine. Additionally, future considerations and recommendations are discussed: (a) the heterogeneous nature of urine, (b) the need for standardized practice protocols and (c) the road toward the clinic. Urine is an emerging liquid biopsy with broad applicability in different analytes and several cancer types. However, standard practice protocols for sample handling and processing would help to elaborate the clinical utility of urine in cancer research, detection and disease monitoring.

Urinary DNA as a Tool for Germline and Somatic Mutation Detection in Castration-Resistant Prostate Cancer Patients

(1) Background: DNA damage response (DDR) pathway gene mutations are detectable in a significant number of patients with metastatic castration-resistant prostate cancer (mCRPC). The study aimed at identification of germline and/or somatic DDR mutations in blood and urine samples from patients with mCRPC for correlation with responses to entire sequence of systemic treatment and survival outcomes. (2) Methods: DDR gene mutations were assessed prospectively in DNA samples from leukocytes and urine sediments from 149 mCRPC patients using five-gene panel targeted sequencing. The impact of DDR status on progression-free survival, as well as treatment-specific and overall survival, was evaluated using Kaplan–Meier curves and Cox regression. (3) Results: DDR mutations were detected in 16.6% of urine and 15.4% of blood samples. BRCA1, BRCA2, CHEK2, ATM and NBN mutations were associated with significantly shorter PFS in response to conventional androgen deprivation therapy and first-line mCRPC therapy with abiraterone acetate. Additionally, BRCA1 and BRCA2 mutation-bearing patients had a significantly worse response to radium-223. However, DDR mutation status was predictive for the favourable effect of second-line abiraterone acetate after previous taxane-based chemotherapy. (4) Conclusions: Our data confirm the benefit of non-invasive urine-based genetic testing for timely identification of high-risk prostate cancer cases for treatment personalization.

Nurturing the marriages of urinary liquid biopsies and nano-diagnostics for precision urinalysis of prostate cancer

Prostate cancer remains the second-most common cancer diagnosed in men, despite the increasingly widespread use of serum prostate-specific antigen (PSA) screening. The controversial clinical implications and cost benefits of PSA screening have been highlighted due to its poor specificity, resulting in a high rate of overdiagnosis and underdiagnosis. Thus, the development of novel biomarkers for prostate cancer detection remains an intriguing challenge. Urine is emerging as a source for prostate cancer biomarker discovery. Currently, new urine biomarkers already outperform serum PSA in clinical diagnosis. Meanwhile, the advances in nanotechnology have provided a suite of diagnostic tools to study prostate cancer in more detail, sparking a new era of biomarker discoveries. In this review, we envision that future prostate cancer diagnosis will probably integrate multiplex nano-diagnostic approaches to detect novel urinary biomarkers. However, challenges remain in differentiating indolent from aggressive cancers to better inform treatment decisions, and clinical translation still needs to be overcome.

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.

Accuracy of novel urinary biomarker tests in the diagnosis of prostate cancer: A systematic review and network meta-analysis

Objective

The purpose of this study was to conduct a network meta-analysis comparing the diagnostic value of different urinary markers for prostate cancer.

Methods

As of June 2022, the literature was retrieved by searching Pubmed, EMBASE, Web of Science databases and other databases. The methodological quality of included studies was assessed using the Cochrane Collaboration’s risk of bias tool, and publication bias was assessed using funnel plots. The surface under the cumulative ranking curve (SUCRA) values ​​was used to determine the most effective diagnostic method and the data were analyzed accordingly using data analysis software.

Results

A total of 16 articles was included including 9952 patients. The ranking results of network meta-analysis showed that the diagnostic performance of the four urine markers Selectmdx, MIPS, PCA3 and EPI was better than that of PSA. Among them, the specificity, positive predictive value and diagnostic accuracy of Selectmdx ranked first in the SUCRA ranking (SUCRA values: 85.2%, 88.3%, 97.1%), and the sensitivity ranked second in the SUCRA ranking (SUCRA value: 54.4%), and the negative predictive value ranked fourth in SUCRA (SUCRA value: 51.6%). The most sensitive screening tool was MIPS (SUCRA value: 67.1%), and it was also the second screening tool ranked higher in specificity, positive predictive value, negative predictive value and diagnostic accuracy (SUCRA value: 56.5%, respectively)., 57.1%, 67.9%, 74.3%). The high negative predictive value SUCRA ranking is EPI (SUCRA value: 68.0%), its sensitivity ranks third (SUCRA value: 45.6%), and its specificity, positive predictive value and diagnostic accuracy are ranked fourth (SUCRA values are: 45%, 38.2%, 35.8%).

Conclusion

According to the network ranking diagram, we finally concluded that Selectmdx and MIPS can be used as the most suitable urine markers for prostate cancer screening and diagnosis. To further explore the diagnostic value of different urinary markers in the screening of PCa patients.

Systematic Review Registration

https://inplasy.com/, identifier INPLASY202290094.

Detection of rare prostate cancer cells in human urine offers prospect of non-invasive diagnosis

Two molecular cytology approaches, (i) time-gated immunoluminescence assay (TGiA) and (ii) Raman-active immunolabeling assay (RiA), have been developed to detect prostate cancer (PCa) cells in urine from five prostate cancer patients. For TGiA, PCa cells stained by a biocompatible europium chelate antibody-conjugated probe were quantitated by automated time-gated microscopy (OSAM). For RiA, PCa cells labeled by antibody-conjugated Raman probe were detected by Raman spectrometer. TGiA and RiA were first optimized by the detection of PCa cultured cells (DU145) spiked into control urine, with TGiA-OSAM showing single-cell PCa detection sensitivity, while RiA had a limit of detection of 4-10 cells/mL. Blinded analysis of each patient urine sample, using MIL-38 antibody specific for PCa cells, was performed using both assays in parallel with control urine. Both assays detected very low abundance PCa cells in patient urine (3-20 PCa cells per mL by TGiA, 4-13 cells/mL by RiA). The normalized mean of the detected PCa cells per 1 ml of urine was plotted against the clinical data including prostate specific antigen (PSA) level and Clinical Risk Assessment for each patient. Both cell detection assays showed correlation with PSA in the high risk patients but aligned with the Clinical Assessment rather than with PSA levels of the low/intermediate risk patients. Despite the limited available urine samples of PCa patients, the data presented in this proof-of-principle work is promising for the development of highly sensitive diagnostic urine tests for PCa.

Cancer-Retina Antigens in the Urine of Bladder and Prostate Cancer Patients

It has recently been shown that combination of arrestin and recoverin can serve as an effective urinary biomarker for renal cell carcinoma with sensitivity and specificity of over 92%. In this work, we studied the possibility of detecting these antigens in the urine in other urological oncological diseases - bladder cancer (BC) and prostate cancer (PCa). Urine samples from 40 BC patients and 40 PCa patients were analyzed using an ultrasensitive microarray immunoassay with a detection limit of 0.1 pg/ml. It was shown that in BC the sensitivity of determining combination of arrestin with recoverin is 58% (AUC 0.76, 95% CI 0.66-0.86), while in PCa it is 60% (AUC 0.7, 95% CI 0.68-0.88). It has been established that in patients with bladder and prostate cancer who had a positive test, these antigens are not detected in 90% of cases after removal of the tumor. In the future, the obtained results could become the basis for developing new approaches for timely detection of relapses of such diseases and treatment control, as well as for the development of new diagnostic methods.

Current and future applications of biomarkers in samples collected through minimally invasive methods for cancer medicine and population-based research

Despite advances in cancer medicine and research, invasive and potentially risky procedures such as biopsies, venous blood tests, imaging, colonoscopy, and pap smear tests are still primarily used for screening, staging, and assessing response to therapy. The development and interdisciplinary use of biomarkers from urine, feces, saliva, scent, and capillary blood collected with minimally invasive methods represents a potential opportunity for integration with biomarker analysis for cancers, both in clinical practice (e.g., in screening, treatment, and disease monitoring, and improved quality of life for patients) and population-based research (e.g., in epidemiology/public health, studies of social and environmental determinants, and evolutionary medicine). In this article, we review the scientific rationale, benefits, challenges, and potential opportunities for measuring cancer-related biomarkers in samples collected through minimally invasive methods.

Urinary marker panels for aggressive prostate cancer detection

Majority of patients with indolent prostate cancer (PCa) can be managed with active surveillance. Therefore, finding biomarkers for classifying patients between indolent and aggressive PCa is essential. In this study, we investigated urinary marker panels composed of urinary glycopeptides and/or urinary prostate-specific antigen (PSA) for their clinical utility in distinguishing non-aggressive (Grade Group 1) from aggressive (Grade Group ≥ 2) PCa. Urinary glycopeptides acquired via data-independent acquisition mass spectrometry (DIA-MS) were quantitatively analyzed, where prostatic acid phosphatase (ACPP), clusterin (CLU), alpha-1-acid glycoprotein 1 (ORM1), and CD antigen 97 (CD97) were selected to be evaluated in various combinations with and without urinary PSA. Targeted parallel reaction monitoring (PRM) assays of the glycopeptides from urinary ACPP and CLU were investigated along with urinary PSA for the ability of aggressive PCa detection. The multi-urinary marker panels, combined via logistic regression, were statistically evaluated using bootstrap resampling and validated by an independent cohort. Majority of the multi-urinary marker panels (e.g., a panel consisted of ACPP, CLU, and Urinary PSA) achieved area under the curve (AUC) ranged from 0.70 to 0.85. Thus, multi-marker panels investigated in this study showed clinically meaningful results on aggressive PCa detection to separate Grade Group 1 from Grade Group 2 and above warranting further evaluation in clinical setting in future.

Automated Recognition of Cancer Tissues through Deep Learning Framework from the Photoacoustic Specimen

The fast advancement of biomedical research technology has expanded and enhanced the spectrum of diagnostic instruments. Various research groups have found optical imaging, ultrasonic imaging, and magnetic resonance imaging to create multifunctional devices that are critical for biomedical activities. Multispectral photoacoustic imaging that integrates the ideas of optical and ultrasonic technologies is one of the most essential instruments. At the same time, early cancer identification is becoming increasingly important in order to minimize fatality. Deep learning (DL) techniques have recently advanced to the point where they can be used to diagnose and classify cancer using biological images. This paper describes a hybrid optimization method that combines in-depth transfer learning-based cancer detection with multispectral photoacoustic imaging. The goal of the PS-ACO-RNN approach is to use ultrasound images to detect and classify the presence of cancer. Bilateral filtration (BF) is often used as a noise removal approach in image processing. In addition, lightweight LEDNet models are used to separate the biological images. A feature extractor with particle swarm with ant colony optimization (PS-ACO) paradigm can also be used. Finally, biological images assign appropriate class labels using a recurrent neural network (RNN) model. The effectiveness of the PS-ACO-RNN technique is verified using a benchmark database, and test results show that the PS-ACO-RNN approach works better than current approaches.

Correlation between stage of prostate cancer and tyrosine and tryptophan in urine samples measured electrochemically

Prostate cancer (PCa) is the second most common cancer in men and one of the leading causes of cancer-related deaths. Early detection is the key to successful treatment and provides the greatest chance to cure the patient. Currently, early detection involves screening for prostate-specific antigen levels in blood, which is not a tumor-specific biomarker. There is a critical need to develop clinically useful methods for screening for more reliable biomarkers. Here, we introduce an electrochemical biosensor that measures the concentrations of the amino acids tyrosine and tryptophan, and propose it as a possible diagnostic and prognostic tool for PCa. The limits of detection of tyrosine and tryptophan using the electrochemical sensors were 1.15 and 1.13 μmol/L in 1:10 urine: PBS, respectively. This study is the first to present electrochemical measurements of tyrosine and tryptophan directly in patient urine samples. We demonstrated an inverse correlation between the measured electrochemical signals and the severity of PCa. The most notable observation was a significant difference between controls and metastatic PCa patients (P ≤ 0.001). This observation was further validated using Liquid-Chromatography-Mass Spectrometry. Our data provides the basis for further research with electrochemical measurements of tyrosine and tryptophan as potential biomarkers for PCa.

Application of Proteogenomics to Urine Analysis towards the Identification of Novel Biomarkers of Prostate Cancer: An Exploratory Study

Simple Summary

Prostate cancer (PCa) is one of the most common cancers. Due to the limited and invasive approaches for PCa diagnosis, it is crucial to identify more accurate and non-invasive biomarkers for its detection. The aim of our study was to non-invasively uncover new protein targets for detecting PCa using a proteomics and proteogenomics approach. This work identified several dysregulated mutant protein isoforms in urine from PCa patients, some of them predicted to have a protective or an adverse role in these patients. These results are promising given urine’s non-invasive nature and offers an auspicious opportunity for research and development of PCa biomarkers.

Abstract

To identify new protein targets for PCa detection, first, a shotgun discovery experiment was performed to characterize the urinary proteome of PCa patients. This revealed 18 differentially abundant urinary proteins in PCa patients. Second, selected targets were clinically tested by immunoblot, and the soluble E-cadherin fragment was detected for the first time in the urine of PCa patients. Third, the proteogenome landscape of these PCa patients was characterized, revealing 1665 mutant protein isoforms. Statistical analysis revealed 6 differentially abundant mutant protein isoforms in PCa patients. Analysis of the likely effects of mutations on protein function and PPIs involving the dysregulated mutant protein isoforms suggests a protective role of mutations HSPG2*Q1062H and VASN*R161Q and an adverse role of AMBP*A286G and CD55*S162L in PCa patients. This work originally characterized the urinary proteome, focusing on the proteogenome profile of PCa patients, which is usually overlooked in the analysis of PCa and body fluids. Combined analysis of mass spectrometry data using two different software packages was performed for the first time in the context of PCa, which increased the robustness of the data analysis. The application of proteogenomics to urine proteomic analysis can be very enriching in mutation-related diseases such as cancer.

Emerging Technologies for the Detection of Cancer Micrometastasis

The most efficient way to treat tumors is through surgery. However, many cancer patients have a poor prognosis even when they undergo radical excision at an early stage. Micrometastasis is one of the most critical factors that induced this situation. Undetected micrometastasis can lead to the failure of initial treatment. Therefore, preoperative and intraoperative detection of micrometastasis could have a significant clinical influence on the prognosis and optimal therapy for cancer patients. Additionally, to achieve this goal, researchers have aimed to create more effective detection technologies. Herein, we classify the currently reported micrometastasis detection technologies, introduce some representative samples for each technology, including the limitations, and provide future directions to overcome the limitations.

In1-Ghrelin Splicing Variant as a Key Element in the Pathophysiological Association Between Obesity and Prostate Cancer

CONTEXT

Recent studies emphasize the importance of considering the metabolic status to develop personalized medicine approaches. This is especially relevant in prostate cancer (PCa), wherein the diagnostic capability of prostate-specific antigen (PSA) dramatically drops when considering patients with PSA levels ranging from 3 to 10 ng/mL, the so-called grey zone. Hence, additional noninvasive diagnostic and/or prognostic PCa biomarkers are urgently needed, especially in the metabolic-status context.

OBJECTIVE

To assess the potential relation of urine In1-ghrelin (a ghrelin-splicing variant) levels with metabolic-related/pathological conditions (eg, obesity, diabetes, body mass index, insulin and glucose levels) and to define its potential clinical value in PCa (diagnostic/prognostic capacity) and relationship with PCa risk in patients with PSA in the grey zone.

METHODS

Urine In1-ghrelin levels were measured by radioimmunoassay in a clinically, metabolically, pathologically well-characterized cohort of patients without (n = 397) and with (n = 213) PCa with PSA in the grey zone.

RESULTS

Key obesity-related factors associated with PCa risk (BMI, diabetes, glucose and insulin levels) were strongly correlated to In1-ghrelin levels. Importantly, In1-ghrelin levels were higher in PCa patients compared to control patients with suspect of PCa but negative biopsy). Moreover, high In1-ghrelin levels were associated with increased PCa risk and linked to PCa aggressiveness (eg, tumor stage, lymphovascular invasion). In1-ghrelin levels added significant diagnostic value to a clinical model consisting of age, suspicious digital rectal exam, previous biopsy, and PSA levels. Furthermore, a multivariate model consisting of clinical and metabolic variables, including In1-ghrelin levels, showed high specificity and sensitivity to diagnose PCa (area under the receiver operating characteristic curve = 0.740).

CONCLUSIONS

Urine In1-ghrelin levels are associated with obesity-related factors and PCa risk and aggressiveness and could represent a novel and valuable noninvasive PCa biomarker, as well as a potential link in the pathophysiological relationship between obesity and PCa.

Voided urine test to diagnose prostate cancer: Preliminary report

Objectives

Prostate cancer (PCa) is a common malignancy affecting elderly male. At present, PCa is estimated using serum prostate-specific antigen (PSA). Prostate biopsy remains the gold standard to confirm the diagnosis of PCa. In this preliminary study, we have assessed the feasibility of detecting PCa using voided urine by targeting the genomic vasoactive intestinal peptide receptor (VPAC) expressed on malignant PCa cells.

Material and Methods

Patients ≥40 years old, with no lower urinary tract symptoms (LUTS) and serum PSA levels of <1.6 ng/mL formed the control group and patients ≥40 years old, with LUTS and serum PSA >2.6 ng/ mL formed the study group. Patients were advised to give the first 50 mL of voided urine sample for the detection of malignant markers by targeting the VPAC. The results of histopathological studies were then compared to the results of urine biomarker.

Results

The study revealed absence of malignant markers in 75 patients (control group). In the study group, all the 33 patients with adenocarcinoma were positive for malignant markers in the biomarker study and absence of malignant markers in the 32 patients with benign histology. The results of the biomarker studies and histopathology were consistent with each other.

Conclusion

This preliminary study validates our belief that patients with PCa do shed malignant cells in the urine which can be identified by targeting the VPAC. The investigation is easy and our data appear to be highly encouraging and further serve as a simple, reliable, and a non-invasive tool in the detection of PCa.

Development of Parallel Reaction Monitoring Assays for the Detection of Aggressive Prostate Cancer Using Urinary Glycoproteins

Recently, we have found that two urinary glycoproteins, prostatic acid phosphatase (ACPP) and clusterin (CLU), combined with serum prostate-specific antigen (PSA) can serve as a three-signature panel for detecting aggressive prostate cancer (PCa) based on a quantitative glycoproteomic study. To facilitate the translation of candidates into clinically applicable tests, robust and accurate targeted parallel reaction monitoring (PRM) assays that can be widely adopted in multiple labs were developed in this study. The developed PRM assays for the urinary glycopeptides, FLN*ESYK from ACPP and EDALN*ETR from CLU, demonstrated good repeatability and a sufficient working range covering three to four orders of magnitude, and their performance in differentiating aggressive PCa was assessed by the quantitative analysis of urine specimens collected from 69 nonaggressive (Gleason score = 6) and 73 aggressive (Gleason ≥ 8) PCa patients. When ACPP combined with CLU, the discrimination power was improved from an area under a curve (AUC) of 0.66 to 0.78. By combining ACPP, CLU, and serum PSA to form a three-signature panel, the AUC was further improved to 0.83 (sensitivity: 84.9%, specificity: 66.7%). Since the serum PSA test alone had an AUC of 0.68, our results demonstrated that the new urinary glycopeptide PRM assays can serve as an adjunct to the serum PSA test to achieve better predictive power toward aggressive PCa. In summary, our developed PRM assays for urinary glycopeptides were successfully applied to clinical PCa urine samples with a promising performance in aggressive PCa detection.

Biomarkers in Prostate Cancer Diagnosis: From Current Knowledge to the Role of Metabolomics and Exosomes

Early detection of prostate cancer (PC) is largely carried out using assessment of prostate-specific antigen (PSA) level; yet it cannot reliably discriminate between benign pathologies and clinically significant forms of PC. To overcome the current limitations of PSA, new urinary and serum biomarkers have been developed in recent years. Although several biomarkers have been explored in various scenarios and patient settings, to date, specific guidelines with a high level of evidence on the use of these markers are lacking. Recent advances in metabolomic, genomics, and proteomics have made new potential biomarkers available. A number of studies focused on the characterization of the specific PC metabolic phenotype using different experimental approaches has been recently reported; yet, to date, research on metabolomic application for PC has focused on a small group of metabolites that have been known to be related to the prostate gland. Exosomes are extracellular vesicles that are secreted from all mammalian cells and virtually detected in all bio-fluids, thus allowing their use as tumor biomarkers. Thanks to a general improvement of the technical equipment to analyze exosomes, we are able to obtain reliable quantitative and qualitative information useful for clinical application. Although some pilot clinical investigations have proposed potential PC biomarkers, data are still preliminary and non-conclusive.

A Comprehensive Urine Proteome Database Generated From Patients With Various Renal Conditions and Prostate Cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers in the literature-curated database. Forty-three percentage of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

Noninvasive Precision Screening of Prostate Cancer by Urinary Multimarker Sensor and Artificial Intelligence Analysis

Screening for prostate cancer relies on the serum prostate-specific antigen test, which provides a high rate of false positives (80%). This results in a large number of unnecessary biopsies and subsequent overtreatment. Considering the frequency of the test, there is a critical unmet need of precision screening for prostate cancer. Here, we introduced a urinary multimarker biosensor with a capacity to learn to achieve this goal. The correlation of clinical state with the sensing signals from urinary multimarkers was analyzed by two common machine learning algorithms. As the number of biomarkers was increased, both algorithms provided a monotonic increase in screening performance. Under the best combination of biomarkers, the machine learning algorithms screened prostate cancer patients with more than 99% accuracy using 76 urine specimens. Urinary multimarker biosensor leveraged by machine learning analysis can be an important strategy of precision screening for cancers using a drop of bodily fluid.

Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics

Prostate cancer (PCa) is the second most diagnosed cancer in men worldwide. For its screening, serum prostate specific antigen (PSA) test has been largely performed over the past decade, despite its lack of accuracy and inability to distinguish indolent from aggressive disease. Metabolomics has been widely applied in cancer biomarker discovery due to the well-known metabolic reprogramming characteristic of cancer cells. Most of the metabolomic studies have reported alterations in urine of PCa patients due its noninvasive collection, but the analysis of prostate tissue metabolome is an ideal approach to disclose specific modifications in PCa development. This review aims to summarize and discuss the most recent findings from tissue and urine metabolomic studies applied to PCa biomarker discovery. Eighteen metabolites were found consistently altered in PCa tissue among different studies, including alanine, arginine, uracil, glutamate, fumarate, and citrate. Urine metabolomic studies also showed consistency in the dysregulation of 15 metabolites and, interestingly, alterations in the levels of valine, taurine, leucine and citrate were found in common between urine and tissue studies. These findings unveil that the impact of PCa development in human metabolome may offer a promising strategy to find novel biomarkers for PCa diagnosis.

Validating METCAM/MUC18 as a Novel Biomarker to Predict the Malignant Potential of Prostate Cancer at an Early Stage by Using a Modified Gold Nanoparticles-Based Lateral Flow Immunoassay

(1) Background: To further validate METCAM/MUC18 as a diagnostic biomarker for prostate cancer, a modified Lateral Flow Immune Assay (LFIA) with increased sensitivity and specificity was designed by taking advantage of the extremely high affinity between biotin and streptavidin and used. (2) Methods: The combination of a commercial biotinylated rabbit antibody (EPP11278), or the home-made biotinylated chicken antibody, and the nano-gold conjugated home-made chicken antibody or a commercial rabbit antibody (EPP11278), had the higher sensitivity and specificity in this modified LFIA to establish calibration curves from the two recombinant METCAM/MUC18 proteins and were used for determining METCAM/MUC18 concentrations in serum specimens from normal individuals, benign prostatic hyperplasia (BPH) patients, prostatic intraepithelial neoplasia (PIN) patients, prostate cancer patients with various Gleason scores, and treated patients. (3) Results: Data obtained by this modified LFIA were statistically better than traditional LFIA and prostate-specific antigen (PSA) test. Interestingly, serum METCAM/MUC18 concentrations were higher in pre-malignant PIN patients than prostate cancer patients and both were higher than normal individuals, BPH patients, and treated patients. Serum METCAM/MUC18 concentrations were directly proportional to most serum PSA. (4) Conclusions: Elevated serum METCAM/MUC18 concentrations may be used for predicting the malignant potential of prostate cancer at an early premalignant (PIN) stage, which is not achievable by the current PSA test.

Liquid Biopsy-Based Exo-oncomiRNAs Can Predict Prostate Cancer Aggressiveness

Liquid biopsy-based biomarkers, including microRNAs packaged within extracellular vesicles, are promising tools for patient management. The cytokine tumor necrosis factor-like weak inducer of apoptosis (TWEAK) is related to PCa progression and is found in the semen of patients with PCa. TWEAK can induce the transfer of exo-oncomiRNAs from tumor cells to body fluids, and this process might have utility in non-invasive PCa prognosis. We investigated TWEAK-regulated exo-microRNAs in semen and in post-digital rectal examination urine from patients with different degrees of PCa aggressiveness. We first identified 14 exo-oncomiRNAs regulated by TWEAK in PCa cells in vitro, and subsequently validated those using liquid biopsies from 97 patients with PCa. Exo-oncomiR-221-3p, -222-3p and -31-5p were significantly higher in the semen of high-risk patients than in low-risk peers, whereas exo-oncomiR-193-3p and -423-5p were significantly lower in paired samples of post-digital rectal examination urine. A panel of semen biomarkers comprising exo-oncomiR-221-3p, -222-3p and TWEAK was designed that could correctly classify 87.5% of patients with aggressive PCa, with 85.7% specificity and 76.9% sensitivity with an area under the curve of 0.857. We additionally found that TWEAK modulated two exo-oncomiR-221-3p targets, TCF12 and NLK. Overall, we show that liquid biopsy detection of TWEAK-regulated exo-oncomiRNAs can improve PCa prognosis prediction.

METCAM/MUC18 is a new early diagnostic biomarker for the malignant potential of prostate cancer: Validation with Western blot method, enzyme-linked immunosorbent assay and lateral flow immunoassay

BACKGROUND

METCAM/MUC18 expression was increased with the malignant progression of prostate cancer and also a bona fide metastatic gene, capable of initiating and driving the metastasis of a non-metastatic human prostate cancer cell line to multiple organs.

OBJECTIVE

We explored if METCAM/MUC18 was detectable in human serum and a novel biomarker to predict malignant propensity of prostate cancer.

MATERIALS AND METHODS

Two antibodies were identified by Western blot analysis having the highest sensitivity and specificity to establish calibration curves from the recombinant METCAM/MUC18 proteins. They were used in ELISA and LFIA to determine the METCAM/MUC18 concentrations in serum samples from 8 normal individuals, 4 BPH patients, 1 with PIN, 6 with high-grade prostate cancer, and 2 treated cancer patients.

RESULTS

Serum METCAM/MUC18 concentrations were statistically significantly higher in the patients with PIN and prostate cancer than those with BPH, the treated patients and normal individuals. The LFIA results were statistically better than ELISA and Western blot methods. Serum METCAM/MUC18 concentrations were in direct proportional to most of serum PSA concentrations.

Affinity Captured Urinary Extracellular Vesicles Provide mRNA and miRNA Biomarkers for Improved Accuracy of Prostate Cancer Detection: A Pilot Study

Serum prostate-specific antigen (sPSA) testing has helped to increase early detection of and decrease mortality from prostate cancer. However, since sPSA lacks specificity, an invasive prostate tissue biopsy is required to confirm cancer diagnosis. Using urinary extracellular vesicles (EVs) as a minimally invasive biomarker source, our goal was to develop a biomarker panel able to distinguish prostate cancer from benign conditions with high accuracy. We enrolled 56 patients in our study, 28 negative and 28 positive for cancer based on tissue biopsy results. Using our Vn96 peptide affinity method, we isolated EVs from post-digital rectal exam urines and used quantitative polymerase chain reaction to measure several mRNA and miRNA targets. We identified a panel of seven mRNA biomarkers whose expression ratio discriminated non-cancer from cancer with an area under the curve (AUC) of 0.825, sensitivity of 75% and specificity of 84%. We also identified two miRNAs whose combined score yielded an AUC of 0.744. A model pairing the seven mRNA and two miRNA panels yielded an AUC of 0.843, sensitivity of 79% and specificity of 89%. Addition of EV-derived PCA3 levels and clinical characteristics to the biomarker model further improved test accuracy. An AUC of 0.955, sensitivity of 86% and specificity of 93% were obtained. Hence, Vn96-isolated urinary EVs are a clinically applicable and minimally invasive source of mRNA and miRNA biomarkers with potential to improve on the accuracy of prostate cancer screening and diagnosis.

Targeted Mass Spectrometry of a Clinically Relevant PSA Variant from Post-DRE Urines for Quantitation and Genotype Determination

PURPOSE

The rs17632542 single nucleotide polymorphism (SNP) results in lower serum prostate specific antigen (PSA) levels which may further mitigate against its clinical utility as a prostate cancer biomarker. Post-digital rectal exam (post-DRE) urine is a minimally invasive fluid that is currently utilized in prostate cancer diagnosis. To detect and quantitate the variant protein in urine.

EXPERIMENTAL DESIGN

Fifty-three post-DRE urines from rs17632542 genotyped individuals processed and analyzed by liquid chromatography/mass spectrometry (LC-MS) in a double-blinded randomized study. The ability to distinguish between homozygous wild-type, heterozygous, or homozygous variant is examined before unblinding.

RESULTS

Stable-isotope labeled peptides are used in the detection and quantitation of three peptides of interest in each sample using parallel reaction monitoring (PRM). Using these data, groupings are predicted using hierarchical clustering in R. Accuracy of the predictions show 100% concordance across the 53 samples, including individuals homozygous and heterozygous for the SNP.

CONCLUSIONS AND CLINICAL RELEVANCE

The study demonstrates that MS based peptide variant quantitation in urine could be useful in determining patient genotype expression. This assay provides a tool to evaluate the utility of PSA variant (rs17632542) in parallel with current and forthcoming urine biomarker panels.

A novel method for detection of exfoliated prostate cancer cells in urine by RNA in situ hybridization

BACKGROUND

In the current study, we explore the feasibility of detecting exfoliated prostate cancer cells in urine using an RNA in situ hybridization (RISH) assay. We hypothesized that robust and specific labeling of prostate cancer cells could be achieved in post-digital rectal examination (DRE) urine samples using RISH.

METHODS

We focused on method development, optimization, and analytical evaluation of RISH-based detection of prostate cancer in urine. We optimized a sample collection, processing, and target detection workflow for urine cytology specimens in conjunction with RNA target detection by RISH. We screened a panel of 11 prostate-specific RNA targets, and selected NKX3-1 and PRAC1 as markers for cells of prostate origin and PCA3 as a marker of prostate malignancy. Following analytical validation of a multiplexed NKX3-1/PRAC1/PCA3 assay, we evaluated whether prostate cancer cells can be detected in a pilot cohort of 19 post-DRE specimens obtained from men diagnosed with prostate cancer.

RESULTS

Using cytology specimens prepared from spiked urine samples, we established the analytical validity of the RISH assay for detection and visualization of prostate cells in urine. Cells of prostate origin could be readily and specifically identified and separated into benign and malignant cell populations based on the multiplex test that consisted of markers specific for prostate cells (NKX3-1, PRAC1) and prostate cancer cells (PCA3). Upon evaluation of post-DRE urine from a pilot cohort of prostate cancer patients, we identified 11 samples in which prostate cells were present, 6 of which were also positive for prostate cancer cells.

CONCLUSIONS

Multiplex RISH enables the direct visualization and molecular characterization of individual exfoliated prostate cells in urine. This proof-of-principle study provides evidence supporting the application of RISH as a potential noninvasive tool for prostate cancer detection.

Electrochemical and optical detection and machine learning applied to images of genosensors for diagnosis of prostate cancer with the biomarker PCA3

The development of simple detection methods aimed at widespread screening and testing is crucial for many infections and diseases, including prostate cancer where early diagnosis increases the chances of cure considerably. In this paper, we report on genosensors with different detection principles for a prostate cancer specific DNA sequence (PCA3). The genosensors were made with carbon printed electrodes or quartz coated with layer-by-layer (LbL) films containing gold nanoparticles and chondroitin sulfate and a layer of a complementary DNA sequence (PCA3 probe). The highest sensitivity was reached with electrochemical impedance spectroscopy with the detection limit of 83 pM in solutions of PCA3, while the limits of detection were 2000 pM and 900 pM for cyclic voltammetry and UV–vis spectroscopy, respectively. That detection could be performed with an optical method is encouraging, as one may envisage extending it to colorimetric tests. Since the morphology of sensing units is known to be affected in detection experiments, we applied machine learning algorithms to classify scanning electron microscopy images of the genosensors and managed to distinguish those exposed to PCA3-containing solutions from control measurements with an accuracy of 99.9%. The performance in distinguishing each individual PCA3 concentration in a multiclass task was lower, with an accuracy of 88.3%, which means that further developments in image analysis are required for this innovative approach.

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Low-cost biosensors fabricated with gold nanoparticles and chondroitin sulfate used for detecting PCA3 biomarker.

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PCA3 detection from machine learning with accuracy of 99.9%.

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The highest sensitivity was reached with electrochemical impedance spectroscopy with the detection limit of 83 pM.

In-Vitro Identification and In-Vivo Confirmation of DNA Methylation Biomarkers for Urothelial Cancer

We identified DNA methylation targets specific for urothelial cancer (UC) by genome-wide methylation difference analysis of human urothelial (RT4, J82, 5637), prostate (LNCAP, DU-145, PC3) and renal (RCC-KP, CAKI-2, CAL-54) cancer cell lines with their respective primary epithelial cells. A large overlap of differentially methylated targets between all organs was observed and 40 Cytosine-phosphate-Guanine motifs (CpGs) were only specific for UC cells. Of those sites, two also showed high methylation differences (≥47%) in vivo when we further compared our data to those previously obtained in our array-based analyses of urine samples in 12 UC patients and 12 controls. Using mass spectrometry, we finally assessed seven CpG sites in this “bladder-specific” region of interest in urine samples of patients with urothelial (n = 293), prostate (n = 75) and renal (n = 23) cancer, and 143 controls. DNA methylation was significantly increased in UC compared to non-UC individuals. The differences were more pronounced for males rather than females. Male UC cases could be distinguished from non-UC individuals with >30% sensitivity at 95% specificity (Area under the curve (AUC) 0.85). In summary, methylation sites highly specific in UC cell lines were also specific in urine samples of UC patients showing that in-vitro data can be successfully used to identify biomarker candidates of in-vivo relevance.

Risk factors associated with pain in fusion prostate biopsy

Background

Multiparametric prostate magnetic resonance imaging (mpMRI)–guided fusion prostate biopsy is an emerging technique in the diagnosis of prostate cancer and provides extensive information on the prebiopsy anatomy of the prostate, anus, and rectum. We aimed to investigate the clinical and anatomical risk factors aggravating the pain experienced by patients undergoing mpMRI-guided fusion prostate biopsy.

Methods

The prospective study included 319 patients aged 45–75 years who had a prostate-specific antigen <10 ng/ml and a Prostate Imaging Reporting and Data System ≥3 lesion and underwent combined biopsy (targeted biopsy + 12-core standard prostate biopsy) under local anesthesia (intrarectal lidocaine gel + periprostatic nerve block). Immediately after the biopsy procedure, pain assessment was achieved using Visual Analog Scale (VAS). The relationship between the VAS and 13 clinical parameters was evaluated using ordinal logistic regression analysis.

Results

The 319 patients had a mean age of 62.39 ± 6.98 years and a median prostate-specific antigen level of 7.20 (range, 5.20–8.50) ng/ml. The VAS was found to be correlated with 4 of 13 parameters, including (i) a shorter prostate–anus surface distance (cutoff value, 55.5 mm), (ii) a narrower anorectal angle (cutoff value, 106.5°), (iii) a larger total prostate volume (cutoff, 61.6 mm³), and (iv) having no history of prior biopsy (biopsy-naive patients).

Conclusion

Anatomical measurements that can be achieved by using mpMRI images (TPV, PASD and ARA) may be useful in the identification of patients at an increased risk of pain during biopsy and also in taking analgesic precautions in such patients.

Plasma enabled devices for the selective capture and photodynamic identification of prostate cancer cells

Prostate cancer is the second most common cancer in men and the second leading cause of male cancer deaths. The current blood test for detecting prostate cancers measures prostate-specific antigen. It has many limitations including a very high rate of false positives. Herein, prostate-specific membrane antigen (PSMA) based immunocapture and hexaminolevulinate (HAL) based photodetection are integrated into a new diagnostic device designed to selectively identify whole prostate cancer cells from voided urine with the aim of providing an accurate noninvasive alternative to current diagnosis methods. Prestained, prostate cancer cells spiked in urine samples at concentrations ranging from 1500 to 2000 cells/ml were captured with 89% sensitivity and 95% specificity. HAL, a cancer specific photosensitizer, was then used to circumvent the need for prestaining. Optimum HAL incubation conditions were identified (50 μM at 37 °C for 2 h) where the mean HAL-induced fluorescence intensity of LNCaP cells was three times that of healthy PNT2 cells, thus providing an independent way to discriminate captured cancer cells from background metabolites. Combining anti-PSMA immunocapture with HAL-induced fluorescent detection, 86% sensitivity and 88% selectivity were achieved, thereby proving the validity of the dual-method for the selective photospecific detection of prostate cancer cells.

What is the ideal number of biopsy cores per lesion in targeted prostate biopsy?

Background

The number of cores to be obtained in targeted biopsy (TB) is important. This study aimed to evaluate the TB outcomes in suspicious prostate lesions classified according to the Prostate Imaging Reporting and Data System (PI-RADS) and to determine the ideal number of biopsy cores per lesion.

Methods

This retrospective study included patients who underwent multiparametric magnetic resonance imaging–guided fusion prostate biopsy owing to increased serum prostate-specific antigen (PSA) levels and suspicious digital rectal examination outcomes in our institute. Patients with PI-RADS <3 lesions, PSA levels >10 ng/ml, and a prior diagnosis of prostate cancer (PCa) (active surveillance) were excluded from the study. The number of biopsy cores to be obtained from each lesion was determined by the clinician.

Results

The study included a total of 418 patients and 684 lesions. Among PI-RADS 3 lesions, clinically significant PCa (sPCa) detection rate was similar in the lesions from which 2 and 3 cores were obtained (9.1% and 10.0%, respectively), whereas it was relatively higher in the lesions from which 4 biopsy cores were obtained (18.5%). Among PI-RADS 4 lesions, sPCa detection rate was similar in the lesions from which 3 and 4 cores were obtained (35.6% and 32.3%, respectively), whereas it was relatively lower in the lesions from which 2 biopsy cores were obtained (17.9%). Among PI-RADS 5 lesions, however, sPCa detection rate was similar in the lesions from which 2, 3, or 4 cores were obtained (47.6%, 46.0%, 48.9%, respectively).

Conclusion

The results indicated that the ideal number of cores to be obtained from each suspicious lesion in TB depends on the characteristics of the lesions. Accordingly, while obtaining 2–3 biopsy cores could be adequate in PI-RADS 4 and 5 lesions, which have a serious risk of cancer, a minimum of 4 biopsy cores should be obtained from PI-RADS 3 lesions to ensure accurate histopathological results.

Clinical trial number (ClinicalTrials.gov)NCT03936296.

Unravelling the proteomic landscape of extracellular vesicles in prostate cancer by density-based fractionation of urine

Extracellular vesicles (EV) are increasingly being recognized as important vehicles of intercellular communication and promising diagnostic and prognostic biomarkers in cancer. Despite this enormous clinical potential, the plethora of methods to separate EV from biofluids, providing material of highly variable purity, and lacking knowledge regarding methodological repeatability pose a barrier to clinical translation. Urine is considered an ideal proximal fluid for the study of EV in urological cancers due to its direct contact with the urogenital system. We demonstrate that density-based fractionation of urine by bottom-up Optiprep density gradient centrifugation separates EV and soluble proteins with high specificity and repeatability. Mass spectrometry-based proteomic analysis of urinary EV (uEV) in men with benign and malignant prostate disease allowed us to significantly expand the known human uEV proteome with high specificity and identifies a unique biological profile in prostate cancer not uncovered by the analysis of soluble proteins. In addition, profiling the proteome of EV separated from prostate tumour conditioned medium and matched uEV confirms the specificity of the identified uEV proteome for prostate cancer. Finally, a comparative proteomic analysis with uEV from patients with bladder and renal cancer provided additional evidence of the selective enrichment of protein signatures in uEV reflecting their respective cancer tissues of origin. In conclusion, this study identifies hundreds of previously undetected proteins in uEV of prostate cancer patients and provides a powerful toolbox to map uEV content and contaminants ultimately allowing biomarker discovery in urological cancers.

Identification of Specific Long Non-Coding Ribonucleic Acid Signatures and Regulatory Networks in Prostate Cancer in Fine-Needle Aspiration Biopsies

Prostate cancer (PCa) is one of the most common tumors in men and can be lethal, especially if left untreated. A substantial majority of PCa patients not only are diagnosed based on fine needle aspiration (FNA) biopsies, but their treatment choices are also largely driven by the pathological findings obtained with these FNA specimens. It is widely believed that lncRNAs have strong biological significance, but their specific functions and regulatory networks have not been elucidated. LncRNAs may serve as key players and regulators of PCa carcinogenesis and could be novel biomarkers of this cancer. To identify potential markers for early detection of PCa, in this study, we employed a competing endogenous RNA (ceRNA) microarray to identify differentially expressed lncRNAs (DelncRNAs) in PCa tissue and quantitative real-time PCR (qRT-PCR) analysis to validate these DelncRNAs in FNA biopsies. We demonstrated that a total of 451 lncRNAs were differentially expressed in four pairs of PCa/adjacent tissues, and upregulation of the lncRNAs RP11-33A14.1, RP11-423H2.3, and LAMTOR5-AS1 was confirmed in FNA biopsies of PCa by qRT-PCR and was consistent with the ceRNA array data. The association between the expression of the lncRNA LAMTOR5-AS1 and aggressive cancer was also investigated. Regulatory network analysis of DelncRNAs showed that the lncRNAs RP11-33A14.1 and RP11-423H2.3 targeted miR-7, miR-24-3p, and miR-30 and interacted with the RNA binding protein FUS. Knockdown of these DelncRNAs in PCa cells also demonstrated the effects of RP11-423H2.3 on miR-7/miR-24/miR-30 or LAMTOR5-AS1 on miR-942-5p/miR-542-3p via direct interaction. The results of these studies indicate that these three specific lncRNA signatures and regulatory networks might serve as risk prediction and diagnostic biomarkers for prostate cancer, even in biopsies obtained by FNA.

Diagnostic Performance of PET/CT Using 18F-FACBC in Prostate Cancer: A Meta-Analysis

Background: Diagnostic performance of PET/CT using 18F-fluciclovine (18F-FACBC) in patients with prostate cancer (PCa) has been evaluated in only a few studies. There is no consensus on the diagnostic value of 18F-FACBC PET/CT in PCa recurrence or metastasis (except for bone metastasis), the primary diagnosis of the lesion. Hence, a meta-analysis was conducted to evaluate the performance of 18F-FACBC PET/CT. Methods: The literature published from June 2015 to June 2019 on using 18F-FACBC PET/CT for the diagnosis of PCa was retrieved from PubMed and EMBASE. Pooled sensitivity (Sen), specificity (Spe), positive and negative likelihood ratios (LR+ and LR-), area under the curve (AUC), and diagnostic odds ratio (DOR) of 18F-FACBC PET/CT in patients with PCa were calculated. An SROC map was made, and a meta-regression analysis was carried out. A Fagan plot and likelihood ratio dot plot were drawn. Sensitivity and funnel plot analysis were made. Meta-disc, Review Manager 5.3, and STATA 13 were used for the meta-analysis. Results: A total of nine articles met the strict criteria for diagnostic meta-analysis, which included 363 patients and 345 lesions. Pooled Sen, Spe, LR+, LR-, DOR were 0.88, 0.73, 3.3, 0.17, and 20, respectively. Lesions detected on the PET/CT image included primary lesions and metastases. For the lesion, the doctors considered the abnormal part as a lesion on the PET/CT image by their own experience and expertise, including primary lesions and metastases. For the patient, patients who participated in the trial can be diagnosed as PCa through 18F-FACBC. Conclusion: This study comprehensively evaluated the diagnostic value of 18F-FACBC PET/CT on PCa. Our analysis suggests that 18F-FACBC PET/CT is a valuable agent in diagnosing PCa. More studies are needed for further validation.

Assessment of men's risk thresholds to proceed with prostate biopsy for the early detection of prostate cancer

PURPOSE

To delineate the range of "risk thresholds" for prostate biopsy to determine how improved prostate cancer (CaP) risk prediction tools may impact shared decision-making (SDM).

METHODS

We conducted a cross-sectional survey study involving men 45-75 years old attending a multispecialty urology clinic. Data included demographics, personal and family prostate cancer history, and prostate biopsy history. Respondents were presented with a summary of the details, risks, and benefits of prostate biopsy, then asked to indicate the specific risk threshold (% chance) of high-grade CaP at which they would proceed with prostate biopsy.

RESULTS

Of a total of 103 respondents, 18 men (17%) had a personal history of CaP, and 31 (30%) had undergone prostate biopsy. The median risk threshold to proceed with prostate biopsy was 25% (interquartile range 10-50%). Risk thresholds did not vary by race, education, or employment. Personal history of CaP or prostate biopsy was significantly associated with lower mean risk thresholds (19% vs. 32% [P = 0.02] and 23% vs. 33% [P = 0.04], respectively). In the lowest versus highest risk threshold quartiles, there were significantly higher rates of CaP (36% vs. 1%, P = 0.01) and prior prostate biopsy (46% vs. 17%, P < 0.01).

CONCLUSIONS

Men have a wide range of risk thresholds for high-grade CaP to proceed with prostate biopsy. Men with a prior history of CaP or biopsy reported lower risk thresholds, which may reflect their greater concern for this disease. The extent to which refined risk prediction tools will improve SDM warrants further study.