New Biomarkers For Prostate Cancer Research Articles

Wrinkled MXene-modified screen-printed electrodes for highly efficient sarcosine detection

MXenes are gaining immense attention owing to their robust conductivity, presence of favorable surface-functional groups and excellent hydrophilicity. Herein, a simple solution-based approach was adopted to functionalize few-layer thick MXene-Ti3C2Tx with chitosan (Chi) molecules, creating a stable electro-active screen-printed electrode (SPE) platform for the detection of sarcosine (SAR), a new biomarker for prostate cancer. In comparison to pristine MXene, the chitosan-functionalized Ti3C2Tx (MX-Chi/SPE) offered favorable surface functionalization for easy immobilization of sarcosine oxidase (SOx) enzymes, which led to the improved enzymatic oxidation of SAR. The detection mechanism relied upon the efficient reduction of enzymatically produced H2O2 over MX-Chi/SPE, enabling selective detection of SAR both in low (0.1–0.3 µM) and high (1.5–3.5 µM) concentration ranges, with an estimated limit of detection (LOD) values of 0.012 µM and 0.14 µM (S/N = 3), respectively. Due to its robust enzymatic configuration, the biosensor enabled selective detection of SAR even in the presence of interfering species like ascorbic acid, uric acid, and glucose. Furthermore, the biosensor demonstrated excellent signal repeatability and stability and effectively recovered spiked SAR levels (98–106%) from artificial urine samples. This approach demonstrated the successful integration of MXenes as redox-active materials in clinical biosensors with a simple electrode preparation procedure, which has the potential to be extended to other MXene compositions.

Integrated analysis of mRNA-single nucleotide polymorphism-microRNA interaction network to identify biomarkers associated with prostate cancer.

Background: Prostate cancer is one of the most common malignancies among men worldwide currently. However, specific mechanisms of prostate cancer were still not fully understood due to lack of integrated molecular analyses. We performed this study to establish an mRNA-single nucleotide polymorphism (SNP)-microRNA (miRNA) interaction network by comprehensive bioinformatics analysis, and search for novel biomarkers for prostate cancer. Materials and methods: mRNA, miRNA, and SNP data were acquired from Gene Expression Omnibus (GEO) database. Differential expression analysis was performed to identify differentially expressed genes (DEGs) and miRNAs (DEMs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, protein-protein interaction (PPI) analysis and expression quantitative trait loci (eQTL) analysis of DEGs were conducted. SNPs related to DEMs (miRSNPs) were downloaded from the open-source website MirSNP and PolymiRTS 3.0. TargetScan and miRDB databases were used for the target mRNA prediction of miRNA. The mRNA-SNP-miRNA interaction network was then constructed and visualized by Cytoscape 3.9.0. Selected key biomarkers were further validated using the Cancer Genome Atlas (TCGA) database. A nomogram model was constructed to predict the risk of prostate cancer. Results: In our study, 266 DEGs and 11 DEMs were identified. KEGG pathway analysis showed that DEGs were strikingly enriched in focal adhesion and PI3K-Akt signaling pathway. A total of 60 mRNA-SNP-miRNAs trios were identified to establish the mRNA-SNP-miRNA interaction network. Seven mRNAs in mRNA-SNP-miRNA network were consistent with the predicted target mRNAs of miRNA. These results were largely validated by the TCGA database analysis. A nomogram was constructed that contained four variables (ITGB8, hsa-miR-21, hsa-miR-30b and prostate-specific antigen (PSA) value) for predicting the risk of prostate cancer. Conclusion: Our study established the mRNA-SNP-miRNA interaction network in prostate cancer. The interaction network showed that hsa-miR-21, hsa-miR-30b, and ITGB8 may be utilized as new biomarkers for prostate cancer.

Template-Independent Poly(A)-Tail Decay and RNASEL as Potential Cellular Biomarkers for Prostate Cancer Development.

Simple SummaryThe ultimate need in cancer tissue is to adapt translation machinery to accelerated protein synthesis in a rapidly proliferating environment. Our study was designed with the aim of integrating fundamental and clinical research to find new biomarkers for prostate cancer (PC) with clinical usefulness for the stratification prediction of healthy tissue transition into malignant phenotype. This study revealed: (i) an entirely novel mechanism of the regulatory influence of Poly(A) deadenylase in mRNAs translational activity and the 3′ mRNA untranslated region (3′UTR) length in cancer tissue and its regulation by the poly(A) decay; (ii) the RNASEL interrelationship with the inflammatory pattern of PC and corresponding tumor-adjacent and healthy tissue; and (iii) the sensitivity, specificity, and predictive value of these enzymes. The proposed manuscript is based on the use of specific biochemical and immunoassay methods with the principal research adapted for the use of tissue specimens.The post-transcriptional messenger RNA (mRNA) decay and turnover rate of the template-independent poly(A) tail, localized at the 3′-untranslated region (3′UTR) of mRNA, have been documented among subtle mechanisms of uncontrolled cancer tissue growth. The activity of Poly(A) deadenylase and the expression pattern of RNASEL have been examined. A total of 138 prostate tissue specimens from 46 PC patients (cancer specimens, corresponding adjacent surgically healthy tissues, and in their normal counterparts, at least 2 cm from carcinoma) were used. For the stratification prediction of healthy tissue transition into malignant phenotype, the enzyme activity of tumor-adjacent tissue was considered in relation to the presence of microfocal carcinoma. More than a four-times increase in specific enzyme activity (U/L g.prot) was registered in PC on account of both the dissociation of its inhibitor and genome reprogramming. The obtained ROC curve and Youden index showed that Poly(A) deadenylase identified PC with a sensitivity of 93.5% and a specificity of 94.6%. The RNASEL expression profile was raised significantly in PC, but the sensitivity was 40.5% and specificity was 86.9%. A significantly negative correlation between PC and control tissue counterparts with a higher expression pattern in lymphocyte-infiltrated samples were reported. In conclusion, significantly upregulated Poly(A) deadenylase activity may be a checkpoint for the transition of precancerous lesion to malignancy, while RNASEL may predict chronic inflammation.

Sarcosine Biosensor Based on Pt/g-C3N4 Nanocomposites with High Electrocatalytic Activity

Sarcosine has been shown to be a new biomarker for prostate cancer that is superior to prostate-specific antigen (PSA). By detecting the concentration of sarcosine in the human body, accurate screening and diagnosis of prostate cancer can be achieved in clinical practice. However, the sarcosine level is extremely low in human serum or urine, and accurate detection of sarcosine concentration is difficult. More work is needed to prepare sarcosine biosensors with good anti-interference performance. In this work, we prepared a sarcosine biosensor using a highly electrocatalytically active nanocomposite comprising platinum/carbon nitride (Pt/g-C3N4) as the electrode modification material. The porous lamellar graphite phase carbon nitride (g-C3N4) prevents the agglomeration of Pt nanoparticles and keeps the Pt nanoparticles in a highly dispersed state. The constructed sarcosine biosensor achieves high sensitivity and can selectively detect low concentrations of sarcosine. Its linear detection range is 2–70 μM, and the limit of detection (LOD) is 0.8 μM (S/N = 3). The prepared sarcosine biosensor shows relatively good performance in terms of resistance to interference caused by electroactive substances and provides the potential to be applied in serum for accurate detection of sarcosine.

MiR-30b-3p and miR-126-3p of urinary extracellular vesicles could be new biomarkers for prostate cancer.

BackgroundExtracellular vesicles (EVs) including exosomes are present in blood, urine, and saliva and contain proteins, microRNAs, and messenger RNAs. We investigated microRNAs in urinary EVs to discover new biomarkers of prostate cancer (PCa).MethodsWe isolated EVs from urine obtained following digital rectal examination (DRE) of 14 men with elevated levels of serum prostate-specific antigen (PSA) [negative biopsy (n=4) and PCa with Gleason scores of 6 (n=3), 7 (n=3), and 8–9 (n=4)]. MicroRNAs extracted from EVs were analyzed by microRNA microarray.ResultsMicroRNAs miR-30b-3p and miR-126-3p were identified as being overexpressed in urinary EVs of the PCa patients versus the biopsy-negative men, but no microRNAs were associated with the Gleason score. In the independent cohort as well, these two microRNAs were overexpressed in urinary EVs from the PCa patients versus the negative-biopsy men. Logistic regression analysis adjusted by age and PSA showed that these two microRNAs were significantly associated with the prediction of PCa in biopsy specimens. Sensitivity and specificity of miR-30b-3p and miR-126-3p for the prediction of PCa were 46.4% and 88.0% and 60.7% and 80.0%, respectively, which were better than those of serum PSA (53.5% and 64.0%, respectively).ConclusionsMiR-30b-3p and miR-126-3p in urinary EVs could be potential biomarkers of PCa.

Sensitive Voltammetric Method for Rapid Determination of Sarcosine as a New Biomarker for Prostate Cancer Using a TiO2 Nanoparticle/Ionic Liquid Modified Carbon Paste Electrode

Sensitive Voltammetric Method for Rapid Determination of Sarcosine as a New Biomarker for Prostate Cancer Using a TiO2 Nanoparticle/Ionic Liquid Modified Carbon Paste Electrode

Bioinformatic analysis of dysregulated proteins in prostate cancer patients reveals putative urinary biomarkers and key biological pathways.

Prostate cancer (PCa) is one of the most common cancer types among men. The quantification of prostate-specific antigen used for PCa detection has revealed limited applicability. Thus, it is crucial to identify new minimally invasive biomarkers for PCa. It is believed that the integration of proteomics data from different studies is vital for identifying new biomarkers for PCa, but studies carried out in this regard have few converging results. Using a different approach, this study aimed to unveil molecular features consistently dysregulated in PCa and potential urinary biomarkers for PCa. The novelty of this analysis relies on the comparison of urinary and tissue proteomes from PCa patients and consequent exclusion of kidney and bladder cancer interference. The conducted bioinformatic analysis revealed molecular processes dysregulated in urine from PCa patients that mirror the alterations in prostate tumor tissue. To identify putative urinary biomarkers, proteins previously detected in kidney and bladder tissues were eliminated from the final list of potential urinary biomarkers for PCa. After a detailed analysis, MSMB, KLK3, ITIH4, ITIH2, HPX, GP2, APOA2 and AZU1 proteins stood out as candidate urinary biomarkers for PCa.

Diagnostic Utility Of Various Biomarkers For Prostate Cancer: A Review

Prostate carcinoma is one of the most widespread occurring cancers in males and is the second most common cause of cancer related mortality in men around the world. The therapeutic success rate for prostate cancer can be greatly improved if the disease is detected at an early stage. Therefore, a successful therapy depends immensely on the clinical indicators (biomarkers) for early diagnosis and progression of the disease, as well as the prognosis after the clinical intervention. Despite of its limitations, prostate biopsy is the “gold standard” for diagnosis of prostatic carcinoma. Beyond the shadow of doubt, the advent of PSA level has marked a new era for the efficient screening of prostatic lesions, but PSA alone cannot be considered as an authentic tool for diagnosis. Therefore, the use of new imaging techniques and molecular markers are of great importance for an accurate diagnosis of prostate cancer. Recent advances in molecular techniques have provided new tools facilitating the discovery of new biomarkers for prostate cancer. The aim of this review is to examine the current status of prostate cancer biomarkers, with special focus the on their diagnostic utility and therefore determine a panel of two or three markers for the prompt diagnosis of prostatic carcinoma.

Olfactomedin 4 deficiency promotes prostate neoplastic progression and is associated with upregulation of the hedgehog-signaling pathway.

Loss of olfactomedin 4 (OLFM4) gene expression is associated with the progression of human prostate cancer, but its role and the molecular mechanisms involved in this process have not been completely understood. In this study, we found that Olfm4-knockout mice developed prostatic intraepithelial neoplasia and prostatic adenocarcinoma. Importantly, we found that the hedgehog-signaling pathway was significantly upregulated in the Olfm4-knockout mouse model. We also found that restoration of OLFM4 in human prostate-cancer cells that lack OLFM4 expression significantly downregulated hedgehog signaling-pathway component expression. Furthermore, we demonstrated that the OLFM4 protein interacts with sonic hedgehog protein, as well as significantly inhibits GLI-reporter activity. Bioinformatic and immunohistochemistry analyses revealed that decreased OLFM4 and increased SHH expression was significantly associated with advanced human prostate cancer. Thus, olfactomedin 4 appears to play a critical role in regulating progression of prostate cancer, and has potential as a new biomarker for prostate cancer.

MiR-187 Targets the Androgen-Regulated Gene ALDH1A3 in Prostate Cancer.

miRNAs are predicted to control the activity of approximately 60% of all protein-coding genes participating in the regulation of several cellular processes and diseases, including cancer. Recently, we have demonstrated that miR-187 is significantly downregulated in prostate cancer (PCa) and here we propose a proteomic approach to identify its potential targets. For this purpose, PC-3 cells were transiently transfected with miR-187 precursor and miRNA mimic negative control. Proteins were analyzed by a two-dimensional difference gel electrophoresis (2D-DIGE) and defined as differentially regulated if the observed fold change was ±1.06. Then, MALDI-TOF MS analysis was performed after protein digestion and low abundance proteins were identified by LC–MS/MS. Peptides were identified by searching against the Expasy SWISS PROT database, and target validation was performed both in vitro by western blot and qRT-PCR and in clinical samples by qRT-PCR, immunohistochemistry and ELISA. DIGE analysis showed 9 differentially expressed spots (p<0.05) and 7 showed a down-regulated expression upon miR-187 re-introduction. Among these targets we identified aldehyde dehydrogenase 1A3 (ALDH1A3). ALDH1A3 expression was significantly downregulated in PC3, LNCaP and DU-145 cells after miR-187 re-introduction. Supporting these data, the expression of ALDH1A3 was found significantly (p<0.0001) up-regulated in PCa samples and inversely correlated (p<0.0001) with miR-187 expression, its expression being directly associated with Gleason score (p = 0.05). The expression of ALDH1A3 was measured in urine samples to evaluate the predictive capability of this biomarker for the presence of PCa and, at a signification level of 10%, PSA and also ALDH1A3 were significantly associated with a positive biopsy of PCa. In conclusion, our data illustrate for the first time the role of ALDH1A3 as a miR-187 target in PCa and provide insights in the utility of using this protein as a new biomarker for PCa.

Identification and validation of potential new biomarkers for prostate cancer diagnosis and prognosis using 2D-DIGE and MS.

This study was designed to identify and validate potential new biomarkers for prostate cancer and to distinguish patients with and without biochemical relapse. Prostate tissue samples analyzed by 2D-DIGE (two-dimensional difference in gel electrophoresis) and mass spectrometry (MS) revealed downregulation of secernin-1 (P < 0.044) in prostate cancer, while vinculin showed significant upregulation (P < 0.001). Secernin-1 overexpression in prostate tissue was validated using Western blot and immunohistochemistry while vinculin expression was validated using immunohistochemistry. These findings indicate that secernin-1 and vinculin are potential new tissue biomarkers for prostate cancer diagnosis and prognosis, respectively. For validation, protein levels in urine were also examined by Western blot analysis. Urinary vinculin levels in prostate cancer patients were significantly higher than in urine from nontumor patients (P = 0.006). Using multiple reaction monitoring-MS (MRM-MS) analysis, prostatic acid phosphatase (PAP) showed significant higher levels in the urine of prostate cancer patients compared to controls (P = 0.012), while galectin-3 showed significant lower levels in the urine of prostate cancer patients with biochemical relapse, compared to those without relapse (P = 0.017). Three proteins were successfully differentiated between patients with and without prostate cancer and patients with and without relapse by using MRM. Thus, this technique shows promise for implementation as a noninvasive clinical diagnostic technique.

Yinghao Sun: leader of research on prostate cancer in China

Yinghao Sun: leader of research on prostate cancer in China

236P - Possible Use of Urinary Prostate Proteins Glycosylation Profile As a Diagnostic Biomarker for Prostate Cancer

ABSTRACT Aim: Serum Prostate Specific Antigen (sPSA) is widely used for screening and early diagnosis of prostate cancer (PCa). This analysis is associated with considerable sensitivity and specificity problems, especially in the diagnostic grey zone (sPSA between 4 and 10 ng/mL). Other biomarkers have emerged but only few have shown clinical significance. Because of aberrant glycosylation changes in tumorogenesis, we explored the use of urinary prostate proteins and its glycosylation profile as a new biomarker for PCa. Methods: We determined sPSA and urinary biomarkers in healthy volunteers (HV; n = 54), patients with benign prostate hyperplasia (BPH; n = 99) and PCa patients (n = 74). Urinary prostate protein N-glycans were determined by fluorophore-assisted carbohydrate electrophoresis. Results: N-glycan profile analyses have pointed out differences between the subject groups: a decrease in overall fucosylation was noticed in PCa patients compared to patients with BPH and HV (p = 0.001 and p Multivariate logistic regression Variables OR (95% CI) P-value Age 0.99 (0.94–1.04) n.s. SPSA 1.19 (1.09–1.30) 0.0001 UGM 1.50 (1.26–1.79) Conclusions: Our urinary marker was able to differentiate between BPH and PCa. These changes in N-glycosylation could lead to the discovery of a new biomarker for PCa, which seems particularly useful in the diagnostic gray zone of sPSA concentration between 4 and 10 ng/mL. Disclosure: All authors have declared no conflicts of interest.

Biomarkers in prostate cancer: new era and prospective.

Currently, most men are diagnosed with prostate cancer (PCa) after a prostate-specific antigen (PSA) test shows an elevated level of the PSA protein. An elevated level suggests cancer may be present. If an elevation is detected, a biopsy to detect cancer is followed. But the PSA test is controversial. An elevated level does not always mean there is cancer present. The test often leads men to having unnecessary biopsies and treatments. Even if cancer is found on biopsy, many of these cancers are slow growing and would not impact the lives of the men who have them. Current advances in molecular techniques have provided new tools facilitating the discovery of new biomarkers for PCa. The purpose of this review is to examine the advances in PCa biomarkers and implication for possible improving disease outcome. The future of cancer prognosis may rely on small panels of markers that can accurately predict PCa presence, stage, and metastasis and can serve as prognosticators, targets, and/or surrogate endpoints of disease progression and response to therapy.

A pattern recognition system for prostate mass spectra discrimination based on the CUDA parallel programming model

The aim of the present study was to implement a pattern recognition system for the discrimination of healthy from malignant prostate tumors from proteomic Mass Spectroscopy (MS) samples and to identify m/z intervals of potential biomarkers associated with prostate cancer. One hundred and six MS-spectra were studied in total. Sixty three spectra corresponded to healthy cases (PSA < 1) and forty three spectra were cancerous (PSA > 10). The MS-spectra are publicly available from the NCI Clinical Proteomics Database. The pre-processing comprised the steps: denoising, normalization, peak extraction and peak alignment. Due to the enormous number of features that rose from MS-spectra as informative peaks, and in order to secure optimum system design, the classification task was performed by programming in parallel the multiprocessors of an nVIDIA GPU card, using the CUDA framework. The proposed system achieved 98.1% accuracy. The identified m/z intervals displayed significant statistical differences between the two classes and were found to possess adequate discriminatory power in characterizing prostate samples, when employed in the design of the classification system. Those intervals should be further investigated since they might lead to the identification of potential new biomarkers for prostate cancer.

Capillary electrophoresis of urinary prostate glycoproteins assists in the diagnosis of prostate cancer

Prostate marker assays are widely used for detection of prostate cancer (PCa) but are associated with considerable sensitivity and specificity problems. Therefore, we investigated prostatic protein glycosylation profiles as a potential biomarker. We determined the urinary asparagine-linked glycan (N-glycan) profile of prostatic proteins of healthy volunteers (n = 25), patients with benign prostate hyperplasia (BPH; n = 62) and newly diagnosed PCa patients (n = 42) using DNA-sequencer-assisted fluorophore-assisted carbohydrate electrophoresis. Through squeezing of the prostate, a sufficient amount of prostatic proteins was obtained for direct structural analyses of N-glycan structures. N-glycans of PCa compared to BPH were characterized by a significant decrease in triantennary structures (p = 0.047) and overall fucosylation (p = 0.026). Prostate-specific antigen (PSA) and the urinary glycoprofile marker showed comparable overall receiver operating characteristic curve analysis as well as in the diagnostic gray zone with serum PSA values between 4 and 10 μg/L. However, when combining PSA and the urinary glycoprofile marker, the latter gave an additive diagnostic value to serum PSA (p ≤ 0.001). In conclusion, N-glycosylation profiling demonstrated differences between BPH and PCa. These changes could lead to the discovery of a new biomarker for PCa.

Prostate cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up

Prostate cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up

The role of microRNAs in prostate cancer progression.

Prostate cancer (PCa) is the most common male malignancy and the second highest cause of cancer-related mortality in United States. MicroRNAs (miRNAs) are small non-coding RNAs that represent a new mechanism to regulate mRNA post-transcriptionally. It is involved in diverse physiological and pathophysiological process. Dysregulation of miRNAs has been associated with the multistep progression of PCa from prostatic intraepithelial neoplasia (PIN), localized adenocarcinoma to metastatic castration-resistance PCa (CRPC). Identification of unique miRNA could provide new biomarkers for PCa and develop into therapeutic strategies. In this review, we will summarize a broad spectrum of both tumor suppressive and oncogenic miRNAs, and their mechanisms contribute to prostate carcinogenesis.

Profiling of circulating microRNAs for prostate cancer biomarker discovery

Prostate cancer (PC) is the most frequent cancer in men in the Western world. Currently, serum prostate-specific antigen levels and digital rectal examinations are used to indicate the need for diagnostic prostate biopsy, but lack in specificity and sensitivity. Thus, many men undergo unnecessary biopsy, and better and less invasive tools for PC detection are needed. Furthermore, whereas aggressive PC should be treated immediately to prevent dissemination, indolent PC often does not progress and overtreatment should be avoided. Currently, the best predictors of aggressiveness are Gleason score and T-stage of the primary PC. Better tools to assess PC aggressiveness could aid in treatment decisions. Recently, circulating miRNAs have been suggested as potential new biomarkers for PC with diagnostic and prognostic potential. Here, to identify new serum miRNA biomarker candidates for PC, we performed genome-wide miRNA profiling of serum samples from 13 benign prostatic hyperplasia (BPH) control patients and 31 PC patients. Furthermore, we carefully reviewed the literature on circulating miRNA biomarkers for PC. Our results confirmed the de-regulation of miR-141 and miR-375, two of the most well-documented candidate miRNA markers for PC. Moreover, we identified several new potential serum miRNA markers for PC and developed three novel and highly specific (100%) miRNA candidate marker panels able to identify 84% of all PC patients (miR-562/miR-210/miR-501-3p/miR-375/miR-551b), 80% of patients with disseminated PC when compared to BPH patients (let-7a*/miR-210/miR-562/miR-616), and 75% of disseminated PC patients when compared to localized PC patients (miR-375/miR-708/miR-1203/miR-200a), demonstrating high potential of serum miRNAs for diagnosing and staging of PC.

Circulating microRNAs as potential new biomarkers for prostate cancer

Since they were first described in the 1990s, circulating microRNAs (miRNAs) have provided an active and rapidly evolving area of current research that has the potential to transform cancer diagnostics and therapeutics. In particular, miRNAs could provide potential new biomarkers for prostate cancer, the most common cause of cancer in UK men. Current diagnostic tests for prostate cancer have low specificity and poor sensitivity. Further, although many prostate cancers are so slow growing as not to pose a major risk to health, there is currently no test to distinguish between these and cancers that will become aggressive and life threatening. Circulating miRNAs are highly stable and are both detectable and quantifiable in a range of accessible bio fluids, thus have the potential to be useful diagnostic, prognostic and predictive biomarkers. This review aims to summarise the current understanding of circulating miRNAs in prostate cancer patients and their potential role as biomarkers.