Urine markers and prostate cancer

Unveiling the potential of SLURP1 protein as a biomarker for prostate cancer screening

Background

Prostate cancer (PCa) develops slowly and lacks obvious symptoms in the early stage, which makes early screening and diagnosis difficult. Urine collection is simple and is an ideal source of biomarkers. In this study, we performed urinary proteomic studies in PCa patients to screen proteins and apply them to the non-invasive early diagnosis of PCa.

Method

Urine samples from PCa patients, benign prostatic hyperplasia (BPH) patients and normal control group were collected. Mass spectrometry was used for proteomic analysis and screening target proteins. Western blot and enzyme-linked immunosorbent assay (ELISA) were used to verify the results. Correlations with clinical indicators were explored, and receiver operating characteristic (ROC) curves were drawn to evaluate the value of target proteins in PCa.

Result

A total of 1065 proteins were identified. Urinary SLURP1 protein was significantly elevated in patients with PCa compared with normal controls and patients with BPH patients. Western blot and ELISA further verified the expression changes of SLURP1. The immunohistochemical staining results revealed a substantial increase in positive SLURP1 expression within PCa tumor tissue. Correlation analysis showed a positive correlation between the expression level of urine SLURP1 protein and serum PSA. ROC curve analysis of the SLURP1 protein in the urine of both normal individuals and PCa patients is determined to be 0.853 (95% CI=0.754 to 0.954).

Conclusion

The concentration of SLURP1 protein in urine of PCa patients is increased, which can serve as a biomarker for screening PCa.

Hollow Core-Shell Metal Oxide Heterojunctions for the Urinary Metabolic Fingerprint-Based Noninvasive Diagnostic Strategy

Urine is a preferred object for noninvasive diagnostic strategies. Urinary metabolic analysis is speculatively regarded as an ideal tool for screening diseases closely related to the genitourinary system in view of the intimate relationship between metabolomics and phenotype. Herein, we propose a urinary metabolic fingerprint-based noninvasive diagnostic strategy by designing hollow core-shell metal oxide heterojunctions (denoted as MOHs). With outstanding light absorption and electron-hole separation ability, MOHs aid in the extraction of high-performance urine metabolic fingerprints. Coupled with optimized machine learning algorithms, we establish a metabolic marker panel for accurate diagnosis of prostate cancer (PCa), which is the most common malignant tumor of the male genitourinary system, achieving accuracies of 84.72 and 83.33% in the discovery and validation sets, respectively. Furthermore, metabolite variations and related pathway analyses confirm the credibility and change correlation of key metabolic features in PCa. This work tends to advance the noninvasive diagnostic strategy toward clinical realities.

Noninvasive urine metabolomics of prostate cancer and its therapeutic approaches: a current scenario and future perspective

INTRODUCTION

The sensitive, specific, fast, robust and noninvasive biomarkers for the evaluation of prostate cancer (PC) remain elusive in medical research. However, efforts are in full sway to investigate and resolve these puzzles for clinical practice. Advances in modern analytical techniques, sample processing, and the emergence of multiple omics approaches have created a great hope for the development of better detection modalities for PC. The objective of the present review is to provide a concise overview of the PC metabolomics-based potential discriminating molecules in urine samples using nuclear magnetic resonance spectroscopy and mass spectrometry.

AREA COVERED

A literature search was executed to find the studies reporting the noninvasive urine-based biomarkers for the diagnosis and prognosis of underlying disease. Most studies have extensivelyreported PC discriminating molecules with their respective controls. Additionally, pathophysiology and the treatment paradigm of PC are summarized and related to the insights underpinning the therapeutic intervention of PC.

EXPERT OPINION

With multi-centric, global, comprehensive omics approaches via either a non- or least-invasive bio-matrix may open new avenues of research for PC biomarker discovery, backed by a molecular mechanistic outline.

Electrical Cartridge Sensor Enables Reliable and Direct Identification of MicroRNAs in Urine of Patients

Urinary miRNAs are biomarkers that demonstrate considerable promise for the noninvasive diagnosis and prognosis of diseases. However, because of background noise resulting from complex physiological features of urine, instability of miRNAs, and their low concentration, accurate monitoring of miRNAs in urine is challenging. To address these limitations, we developed a urine-based disposable and switchable electrical sensor that enables reliable and direct identification of miRNAs in patient urine. The proposed sensing platform combining disposable sensor chips composed of a reduced graphene oxide nanosheet and peptide nucleic acid facilitates the label-free detection of urinary miRNAs with high specificity and sensitivity. Using real-time detection of miRNAs in patient urine without pretreatment or signal amplification, this sensor allows rapid, direct detection of target miRNAs in a broad dynamic range with a detection limit down to 10 fM in human urine specimens within 20 min and enables simultaneous quantification of multiple miRNAs. As confirmed using a blind comparison with the results of pathological examination of patients with prostate cancer, the sensor offers the potential to improve the accuracy of early diagnosis before a biopsy is taken. This study holds the usefulness of the practical sensor for the clinical diagnosis of urological diseases.

Novel Metabolic Signatures of Prostate Cancer Revealed by 1H-NMR Metabolomics of Urine

Prostate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Based on 1H nuclear magnetic resonance (1H-NMR) analysis, 20 metabolites were identified. Subsequently, principal component analysis (PCA), partial least squares-differential analysis (PLS-DA) and ortho-PLS-DA (OPLS-DA) were applied to find metabolites to distinguish PC from the control group. Furthermore, Wilcoxon test was used to find significant differences between the two groups in metabolite urine levels. Guanidinoacetate, phenylacetylglycine, and glycine were significantly increased in PC, while L-lactate and L-alanine were significantly decreased. The receiver operating characteristics (ROC) analysis revealed that the combination of guanidinoacetate, phenylacetylglycine, and glycine was able to accurately differentiate 77% of the PC patients with sensitivity = 80% and a specificity = 64%. In addition, those three metabolites showed significant differences in patients stratified for Gleason score 6 and Gleason score ≥7, indicating potential use to detect significant prostate cancer. Pathway enrichment analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and the SMPDB (The Small Molecule Pathway Database) revealed potential involvement of KEGG "Glycine, Serine, and Threonine metabolism" in PC. The present study highlights that guanidinoacetate, phenylacetylglycine, and glycine are potential candidate biomarkers of PC. To the best knowledge of the authors, this is the first study identifying guanidinoacetate, and phenylacetylglycine as potential novel biomarkers in PC.

Self-Normalized Detection of ANXA3 from Untreated Urine of Prostate Cancer Patients without Digital Rectal Examination

A noninvasive quantitative assay that is capable of identifying prostate cancer biomarkers in untreated urine is an attractive diagnosis tool, but this method is subject to various obstacles. Difficulties presented by untreated urine include varying salt concentrations, and pH levels that may be different even though they are from the same patient. Untreated urine also presents interference from other biomolecules and possesses a fewer number of cancer biomarkers than can be found in serum. As a result, urine preconditioning processes and digital rectal examination (DRE) to increase biomarker secretion are mandatory in current urine assays. To address these challenges, an ion-responsive urine sensor (IRUS) that measures differential electrical signals is proposed as a self-normalized detection method. The proposed IRUS is based on a FET biosensor with a disposable sensing gate and has the capability to detect the prostate cancer antigen ANXA3 in untreated patient urine. The IRUS can detect ANXA3 at <1 fg mL^-1 with high reliability. In addition, it is found that ANXA3 levels in urine show clinically significant correlation with real tumor volumes. This paper provides a guideline in developing a clinically ready accurate noninvasive platform, which is capable of predicting prostate cancer using untreated urine without DRE.

Urinary Polyamines: A Pilot Study on Their Roles as Prostate Cancer Detection Biomarkers

Current screening methods towards prostate cancer (PCa) are not without limitations. Research work has been on-going to assess if there are other better tests suitable for primary or secondary screening of PCa to supplement the serum prostate specific antigen (PSA) test, which fails to work accurately in a grey zone of 4-10ng/ml. In this pilot study, the potential roles of urinary polyamines as prostate cancer biomarkers were evaluated. PCa, benign prostatic hyperplasia (BPH) patients and healthy controls (HC) showing PSA>4.0ng/ml were enrolled in the study. Their urine samples were obtained, and the urinary levels of putrescine (Put), spermidine (Spd) and spermine (Spm) were determined by ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometer (UPLC-MS/MS). Receiver operating characteristics (ROC) curve and Student’s t-test were used to evaluate their diagnostic accuracies. Among the three biogenic polyamines, Spm had demonstrated a good diagnostic performance when comparing their levels in PCa patients with BPH patients (1.47 in PCa vs 5.87 in BPH; p<0.0001). Results are in accordance with transrectal ultrasound prostatic biopsy (TRUSPB) results, with an area under curve (AUC) value of 0.83±0.03. Therefore urinary Spm shows potential to serve as a novel PCa diagnostic biomarker, which in turn can help to address the limited sensitivity and specificity problem of serum PSA test.

Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

Construction and analysis of lncRNA-lncRNA synergistic networks to reveal clinically relevant lncRNAs in cancer

Long non-coding RNAs (lncRNAs) play key roles in diverse biological processes. Moreover, the development and progression of cancer often involves the combined actions of several lncRNAs. Here we propose a multi-step method for constructing lncRNA-lncRNA functional synergistic networks (LFSNs) through co-regulation of functional modules having three features: common coexpressed genes of lncRNA pairs, enrichment in the same functional category and close proximity within protein interaction networks. Applied to three cancers, we constructed cancer-specific LFSNs and found that they exhibit a scale free and modular architecture. In addition, cancer-associated lncRNAs tend to be hubs and are enriched within modules. Although there is little synergistic pairing of lncRNAs across cancers, lncRNA pairs involved in the same cancer hallmarks by regulating same or different biological processes. Finally, we identify prognostic biomarkers within cancer lncRNA expression datasets using modules derived from LFSNs. In summary, this proof-of-principle study indicates synergistic lncRNA pairs can be identified through integrative analysis of genome-wide expression data sets and functional information.

Urine--a waste or the future of regenerative medicine?

In recent years, urine has emerged as a source of urine cells. Two different types of cells can be isolated from urine: urine derived stem cells (USCs) and renal tubular cells called urine cells (UCs). USCs have great differentiation properties and can be potentially used in genitourinary tract regeneration. Within this paper, we attempt to demonstrate that such as easily accessible source of cells, collected during completely non-invasive procedures, can be better utilized. Cells derived from urine can be isolated, stored, and used for the creation of urine stem cell banks. In the future, urine holds great potential to become a main source of cells for tissue engineering and regenerative medicine.

Ciprofloxacin as a prophylactic agent against prostate cancer: a "two hit" hypothesis

More evidence indicate that prostate inflammation can lead to prostate cancer development. Prostate cancer affects elderly men. Prostate cancer prophylaxis is an important issue because life expectancy is very long now. Ciprofloxacin is an antibacterial agent used mainly in urinary tract infections and prostate inflammation. This drug acts also against cancer cells by the inhibition of topoisomerase II. These properties should allow it to inhibit the development of prostate cancer. Firstly, ciprofloxacin can stop the acute and chronic prostate inflammation which can lead to cancer development. Secondly, ciprofloxacin can potentially kill prostate cancer cells in their early stage of development. Ciprofloxacin accumulates mainly in the prostate after oral intake thus ciprofloxacin seems to be a perfect candidate as a prophylactic agent.