Biomarker For Diagnosis Of Prostate Cancer Research Articles

PSA, an outdated biomarker for prostate cancer: In search of a more specific biomarker, citrate takes the spotlight

The prevailing biomarker employed for prostate cancer (PCa) screening and diagnosis is the prostate-specific antigen (PSA). Despite excellent sensitivity, PSA lacks specificity, leading to false positives, unnecessary biopsies and overdiagnosis. Consequently, PSA is increasingly less used by clinicians, thus underscoring the imperative for the identification of new biomarkers. An emerging biomarker in this context is citrate, a molecule secreted by the normal prostate, which has been shown to be inversely correlated with PCa. Here, we discuss about PSA and its usage for PCa diagnosis, its lack of specificity, and the various conditions that can affect its levels. We then provide our vision about what we think would be a valuable addition to our PCa diagnosis toolkit, citrate. We describe the unique citrate metabolic program in the prostate and how this profile is reprogrammed during carcinogenesis. Finally, we summarize the evidence that supports the usage of citrate as a biomarker for PCa diagnosis, as it can be measured in various patient samples and be analyzed by several methods. The unique relationship between citrate and PCa, combined with the stability of citrate levels in other prostate-related conditions and the simplicity of its detection, further accentuates its potential as a biomarker.

A Synergistic Strategy Combining Chemotherapy and Photodynamic Therapy to Eradicate Prostate Cancer.

Prostate cancer is the most prevalent cancer among men in the United States and is a leading cause of cancer-related death. Prostate specific membrane antigen (PSMA) has been established as a biomarker for prostate cancer diagnosis and treatment. This study aimed to develop a novel theranostic agent, PSMA-1-MMAE-Pc413, which integrates a PSMA-targeting ligand, the photosensitizer Pc413, and the microtubular inhibitor monomethyl auristatin E (MMAE) for synergistic therapeutic efficacy. In vitro uptake studies revealed that PSMA-1-MMAE-Pc413 demonstrated selective and specific uptake in PSMA-positive PC3pip cells but not in PSMA-negative PC3flu cells, with the uptake in PC3pip cells being approximately three times higher. In vitro cytotoxicity assays showed that, when exposed to light, PSMA-1-MMAE-Pc413 had a synergistic effect, leading to significantly greater cytotoxicity in PSMA-positive cells (IC50 = 2.2 nM) compared to PSMA-1-Pc413 with light irradiation (IC50 = 164.9 nM) or PSMA-1-MMAE-Pc413 without light irradiation (IC50 = 12.6 nM). In vivo imaging studies further demonstrated the selective uptake of PSMA-1-MMAE-Pc413 in PC3pip tumors. In in vivo studies, PSMA-1-MMAE-Pc413 dramatically improves the therapeutic outcome for prostate cancer by providing a synergistic effect that surpasses the efficacy of each treatment modality alone in PC3pip tumors. These findings suggest that PSMA-1-MMAE-Pc413 has strong potential for clinical application in improving prostate cancer treatment.

Urinary volatile organic compounds (VOCs) based prostate cancer diagnosis via high-dimensional classification

Early detection of prostate cancer is critical for successful treatment and survival. However, current diagnostic methods such as prostate-specific antigen (PSA) testing and digital rectal examination (DRE) have limitations in accuracy, specificity, and sensitivity. Recent research suggests that urinary volatile organic compounds (VOCs) could serve as potential biomarkers for prostate cancer diagnosis. In this study, urine samples from 337 PCa-positive and 233 PCa-negative patients were collected to develop a diagnosis model. The study involves a high dimensional (HD) classification problem due to the vast number of measured VOCs. Our findings reveal that regularized logistic regression outperforms numerous other classifiers when analyzing the collected data. In particular, we have selected a regularized logistic model with the SCAD (smoothly clipped absolute deviation) penalty as the final model, which attains an AUC (area under the ROC curve) of 0.748, in contrast to a PSA-based AUC of 0.540. These results underscore the potential of VOC-based diagnosis as a clinically feasible approach for PCa screening.

Evaluation of miR-130b-3p and miR-375 levels and telomere length with telomerase activity in prostate cancer

Prostate cancer (PC) is the most frequent cancer in males, as well as the second highest cause of cancer-related deaths in men. Differences in expression levels of miRNAs were linked with prostat cancer pathogenesis. qPCR was used to evaluate the expression of miR-130b-3p and miR-375 in Benign Prostate Hyperplasia (BPH (n = 20) and PC (n = 22, pre- and post-operative) patients plasma. Relative telomere lengths (RLTs) in genomic DNA isolated from plasma were measured with qPCR, and telomerase activity analyzed by the ELISA method. PSA levels of PC patients were greater than of BPH patients (p = 0.0473). miR-130b-3p and miR-375 levels were significantly lower in pre-operative specimens of PC patients according to BPH (p = 0,0362, p = 0.0168, respectively). Similarly, post-operative miR-375 levels were lower in PC patients than in BPH patients (p = 0.1866). BPH patients had shorter RTLs than PC patients in both pre- (p=0.0438) and post-operative (p=0.0297) specimens. Telomerase activity was higher in PC patients than BPH(p = 0.0129). Interestingly, telomerase activity was further increased after surgery (p = 0.0003). We aim to identify the levels of miR-130b-3p and miR-375 expression and their relationship with telomerase activity in PC patients. Our data suggest that miRNAs and telomere length (TL) with telomerase activity may play a role in regulating prostate tumorgenesis and may be used as biomarkers for PC diagnosis.

Lipidomic profiling as a biomarker for prostate cancer diagnosis and response to enzalutamide (Enza).

217 Background: Metabolic rewiring, particularly reprogramming of lipid metabolism, is a hallmark of prostate cancer (PC). Upregulated lipogenesis plays a paramount role in PC pathogenesis, progression, and treatment resistance, especially in therapies targeting the androgen receptor (AR) pathway. Thus, we aimed to study whether lipidomic profiling can distinguish men with PC from those with benign prostate lesions (BL), as well as predict the response to Enza in metastatic castration-resistant PC (mCRPC). Methods: Plasma samples were collected from 14 men with BL and 13 pts with localized hormone-sensitive PC prior to the tissue biopsy, and 54 with mCRPC prior to Enza as first-line treatment. Plasma lipidomic profiling was performed by liquid chromatography and electrospray ionization-tandem mass spectrometry (LC-MS/MS). Lipids were analyzed with an untargeted approach using MultiQuantTM 3.0.3. Multiple comparisons were made by two-way ANOVA with Tukey’s multiple comparison test. A machine learning approach was used to assess the correlation between the lipid profile and the prediction of radiographic progression-free survival (rPFS) defined based on RECIST 1.1/PCWG-3 criteria. Kaplan-Meier survival curves were generated for each selected lipid species independently associated with rPFS adjusting for clinicopathological factors by a multivariate Cox regression analysis. Results: LC-MS/MS quantified a total of 1839 plasma lipids species comprising 17 classes. Ten lipid classes showed a higher expression in PC compared to BL, and only Phosphatidylethanolamine (PE) was significantly different between the two groups (p < 0.05). At the level of lipid species, 69 were found to be significantly dysregulated in pts with PC compared to pts with BL: 26 species belonging to Ceramides, Phosphatidylethanolamine, Phosphatidylglycerol, Phosphatidylinositol were upregulated, whereas 43 belonging to Cholesterol esters, Diacylglycerides, Phosphatidylcholine, and Triacylglycerides were downregulated. After a median follow-up time of 27.9 months, 24/54 (44%) pts with mCRPC progressed on Enza. Median progression-free survival was 44.1 months (95% CI, 41.1 -NA months). The baseline levels of 10 lipids were individually significantly associated with rPFS. Two lipids belonging to the phosphatidylinositol (PI) class, PI.14.0_16.0 and PI.20.3_20.3, were independent predictors of rPFS (p < 0.05) when they were modeled with PS ECOG score, BMI, baseline PSA levels, Gleason score, and the number of metastatic sites in a multivariable Cox regression. The results highlight the potential role of the PI class in modulating the AR pathway. Conclusions: Lipidomic profiling can differentiate between BL and PC. Furthermore, lipidomic profiling correlates with response to Enza in men with mCRPC. Further studies are needed to externally validate the diagnostic and predictive role of lipid signatures in PC.

Small extracellular vesicles: Roles and clinical application in prostate cancer.

Prostate cancer is a significant health problem in the United States. It is remarkably heterogenous, ranging from slow growing disease amenable to active surveillance to highly aggressive forms requiring active treatments. Therefore, being able to precisely determine the nature of disease and appropriately match patients to available and/or novel therapeutics is crucial to improve patients' overall outcome and quality of life. Recently small extracellular vesicles (sEVs), a subset of nanoscale membranous vesicles secreted by various cells, have emerged as important analytes for liquid biopsy and promising vehicles for drug delivery. sEVs contain various biomolecules such as genetic material, proteins, and lipids that recapitulate the characteristics and state of their donor cells. The application of existing and newly developed technologies has resulted in an increased depth of knowledge about biophysical structures, biogenesis, and functions of sEVs. In prostate cancer patients, tumor-derived sEVs can be isolated from biofluids, commonly urine and blood. They mediate intercellular signaling within the tumor microenvironment and distal organ-specific sites, supporting cancer initiation, progression, and metastasis. A mounting body of evidence suggests that sEV components can be potent biomarkers for prostate cancer diagnosis, prognosis, and prediction of disease progression and treatment response. Due to enhanced circulation stability and bio-barrier permeability, sEVs can be also used as effective drug delivery carriers to improve the efficacy and specificity of anti-tumor therapies. This review discusses recent studies on sEVs in prostate cancer and is focused on their role as biomarkers and drug delivery vehicles in the clinical management of prostate cancer.

A novel circular RNA, circMAML3, promotes tumor progression of prostate cancer by regulating miR-665/MAPK8IP2 axis

Many studies have now demonstrated that circRNAs are aberrantly expressed in cancer and are involved in the regulation of malignant tumor progression. However, the role of circMAML3 (hsa_circ_0125392) in prostate cancer has not been reported. circMAML3 was selected from public data through screening. The circMAML3 circular characterization was performed using Sanger sequencing, agarose gel electrophoresis assay, RNase R assay and actinomycin D assay. The expression of circMAML3 in prostate cancer tissues and cells was detected by qRT-PCR. In vivo and in vitro experiments were conducted to investigate the biological functions of circMAML3 in prostate cancer. Finally, the underlying mechanism of circMAML3 was revealed by qRT-PCR, luciferase reporter assay, miRNA Pulldown, RNA immunoprecipitation, western blotting, and rescue assay. Compared to normal prostate tissue and prostate epithelial cells, circMAML3 is highly expressed in prostate cancer tissues and cell lines. CircMAML3 overexpression promotes prostate cancer proliferation and metastasis, while knockdown of circMAML3 exerts the opposite effect. Mechanistically, circMAML3 promotes prostate cancer progression by upregulating MAPK8IP2 expression through sponge miR-665. Our research indicates that circMAML3 promotes prostate cancer progression through the circMAML3/miR-665/MAPK8IP2 axis. circMAML3 and MAPK8IP2 are upregulated in prostate cancer expression and play an oncogenic role, whereas miR-665 is downregulated in prostate cancer and plays an oncogenic role. Therefore, CircMAML3 may be a potential biomarker for prostate cancer diagnosis, treatment and prognosis.

Validation of potential RNA biomarkers for prostate cancer diagnosis and monitoring in plasma and urinary extracellular vesicles

Introduction: Prostate cancer (PCa), one of the most prevalent malignancies affecting men worldwide, presents significant challenges in terms of early detection, risk stratification, and active surveillance. In recent years, liquid biopsies have emerged as a promising non-invasive approach to complement or even replace traditional tissue biopsies. Extracellular vesicles (EVs), nanosized membranous structures released by various cells into body fluids, have gained substantial attention as a source of cancer biomarkers due to their ability to encapsulate and transport a wide range of biological molecules, including RNA. In this study, we aimed to validate 15 potential RNA biomarkers, identified in a previous EV RNA sequencing study, using droplet digital PCR.Methods: The candidate biomarkers were tested in plasma and urinary EVs collected before and after radical prostatectomy from 30 PCa patients and their diagnostic potential was evaluated in a test cohort consisting of 20 benign prostate hyperplasia (BPH) and 20 PCa patients’ plasma and urinary EVs. Next, the results were validated in an independent cohort of plasma EVs from 31 PCa and 31 BPH patients.Results: We found that the levels of NKX3-1 (p = 0.0008) in plasma EVs, and tRF-Phe-GAA-3b (p < 0.0001) tRF-Lys-CTT-5c (p < 0.0327), piR-28004 (p = 0.0081) and miR-375-3p (p < 0.0001) in urinary EVs significantly decreased after radical prostatectomy suggesting that the main tissue source of these RNAs is prostate and/or PCa. Two mRNA biomarkers—GLO1 and NKX3-1 showed promising diagnostic potential in distinguishing between PCa and BPH with AUC of 0.68 and 0.82, respectively, in the test cohort and AUC of 0.73 and 0.65, respectively, in the validation cohort, when tested in plasma EVs. Combining these markers in a biomarker model yielded AUC of 0.85 and 0.71 in the test and validation cohorts, respectively. Although the PSA levels in the blood could not distinguish PCa from BPH in our cohort, adding PSA to the mRNA biomarker model increased AUC from 0.71 to 0.76.Conclusion: This study identified two novel EV-enclosed RNA biomarkers–NKX3-1 and GLO1–for the detection of PCa, and highlights the complementary nature of GLO1, NKX3-1 and PSA as combined biomarkers in liquid biopsies of PCa.

Clinical performance of magnetic resonance imaging and biomarkers for prostate cancer diagnosis in men at high genetic risk.

To evaluate different scenarios for the management of early diagnosis of cancer (PCa) in men at high genetic risk, using recently developed blood and urinary molecular biomarkers in combination with clinical information alongside multiparametric magnetic resonance imaging (mpMRI). A total of 322 patients with a high genetic risk (familial or personal history of cancers or a predisposing germline variant) were included in this study. The primary outcome was the detection rates of PCa (positive biopsy) or clinically significant PCa (biopsy with International Society of Urological Pathology [ISUP] grade >1). Clinical parameters included age, body mass index, ancestry, and germline mutational status,mpMRI, prostate-specific antigen density (PSAD), Prostate Health Index and urinary markers (Prostate Cancer Associated 3, SelectMdx™ and T2:ERG score) were assessed. Sensitivity (Se) and specificity (Sp) for each marker at their recommended cut-off for clinical practice were calculated. Comparison between diagnoses accuracy of each procedure and scenario was computed using mutual information based and direct effect contribution using a supervised Bayesian network approach. A mpMRI Prostate Imaging-Reporting and Data System (PI-RADS) score ≥3 showed higher Se than mpMRI PI-RADS score ≥4 for detection of PCa (82% vs 61%) and for the detection of ISUP grade >1 lesions (96% vs 80%). mpMRI PI-RADS score ≥3 performed better than a PSA level of ≥3 ng/mL (Se 96%, Sp 53% vs Se 91%, Sp 8%) for detection of clinically significant PCa. In case of negative mpMRI results, the supervised Bayesian network approach showed that urinary markers (with the same accuracy for all) and PSAD of ≥0.10 ng/mL/mL were the most useful indicators of decision to biopsy. We found that screening men at high genetic risk of PCa must be based on mpMRI without pre-screening based on a PSA level of >3 ng/mL, to avoid missing too many ISUP grade >1 tumours and to significantly reduce the number of unnecessary biopsies. However, urinary markers or a PSAD of ≥0.10 ng/mL/mL when mpMRI was negative increased the detection of ISUP grade >1 cancers. We suggest that a baseline mpMRI be discussed for men at high genetic risk from the age of 40 years.

GOLM1 Promotes Epithelial-Mesenchymal Transition by Activating TGFβ1/Smad2 Signaling in Prostate Cancer.

Background: Prostate cancer (PC) is one of the most commonly diagnosed cancer in men worldwide. Epithelial-mesenchymal transition (EMT) is considered to play a crucial role in the development of the metastatic castration-resistant prostate cancer, which causes the majority of the death cases in PC. Golgi membrane protein 1 (GOLM1) is highly expressed in PC and has been identified as a driver factor for EMT in various cancers. However, its biological functions and underlying mechanisms remain ambiguous in PC. Method: GOLM1 expression level of PC was detected by Western blot and immunohistochemistry analyses. To investigate GOLM1 functions in cancer cells, we overexpressed and knocked down GOLM1 in different prostate cancer cell lines. Transwell assay and wound healing assay were used to determine the role of GOLM1 in cell EMT, such as migration and invasion abilities. TGF-β1/Smad2 signaling pathway downstream of GOLM1 was detected by Western blot and Transwell assay. Result: GOLM1 expression is up-regulated in PC and correlated with a worse prognosis. GOLM1 promotes the abilities of migration and invasion in PC cell lines (DU145 and LNCaP). Furthermore, TGF-β1/Smad2 signaling is positively regulated by GOLM1 to facilitate EMT in PC, whereas this role can be restored by TGF-β1 after GOLM1 knockdown or be abrogated by p-Smad inhibitor SB431542. Conclusion: GOLM1 is significantly upregulated in PC and acts as a critical oncogene by promoting PC cell EMT process by activating TGF-β1/Smad2 signaling pathway. Therefore, GOLM1 has the potential to be a biomarker for PC diagnosis and to predict the prognosis of PC patients. It is of great significance to seek effective and specific inhibitor of GOLM1 for PC treatment as well.

IL-8 Produced Via Bidirectional Communication Between Prostate Cancer and M2 Macrophages as a Potential Diagnostic and Prognostic Biomarker.

Owing to the mortality associated with metastatic prostate cancer and the shortcomings of the current parameters in predicting the disease prognosis, we require the identification of viable biomarkers, which would help in the diagnosis and prognosis of the disease. We aimed to determine whether the interleukin-8 level in the tumor microenvironment could serve as a potential clinical diagnostic marker and prognostic factor for prostate cancer. The migration assay of prostate cancer cells was performed in an in vitro co-culture model. Cell lines PC3 and DU145 were divided into two groups and co-cultured with M0 and M2 macrophages, respectively. We used reverse transcription-quantitative polymerase chain reaction to detect M2 macrophage marker expression levels. Immunohistochemistry analyses of tissue microarrays were performed to analyze the correlation between the increased expression of interleukin-8 and the prognosis of prostate cancer. A retrospective analysis based on 142 residual serum specimens was performed to analyze the level of interleukin-8. We observed that M2 macrophages promoted the migration of prostate cancer cells and significantly increased the concentrations of interleukin-8 in the co-culture supernatants. We observed increased expression of CD163 and interleukin-8 in prostate cancer tissues. Furthermore, the levels of interleukin-8 in the serum of prostate cancer patients were higher than those in healthy controls. Untreated patients had higher levels of interleukin-8, which could be a predictor of a higher metastasis rate. These results suggest that interleukin-8 produced via bidirectional communication between prostate cancer cells and M2 macrophages is a putative biomarker for prostate cancer diagnosis and treatment.

MAPK8IP2 is a potential prognostic biomarker and promote tumor progression in prostate cancer

BackgroundMAPK8IP2 is one of the JNK-interacting proteins (JIPs) family members, and is involved in the regulation of the JNK and P38 MAPK signaling pathways. MAPK8IP2 has been reported to be closely associated with several cancers. However, the biological function of MAPK8IP2 in prostate cancer (PCa) remains unclear.MethodsMAPK8IP2 expression in PCa and subgroups of PCa was analyzed by public databases. The prognostic role of MAPK8IP2 in prostate cancer was analyzed using the Cox regression method. The potential mechanism by which MAPK8IP2 affects PCa progression was investigated by utilizing public data, including genetic alteration, DNA methylation, m6A methylation, and immune infiltration data. We further performed in vitro assays to validate the effect of MAPK8IP2 on PCa cell proliferation, migration and invasion.ResultsMAPK8IP2 is highly expressed in PCa tissues. Overexpression of MAPK8IP2 is associated with adverse clinicopathological factors and a poor prognosis in PCa. Receiver operating curve analysis showed that MAPK8IP2 can distinguish PCa tissues from non-PCa tissues with a certain accuracy (AUC = 0.814). The MAPK8IP2 genetic alteration rate was 2.6% and MAPK8IP2 alterations correlated with a poor prognosis. We also found that CDK12 and TP53 mutations were associated with MAPK8IP2 expression. The DNA methylation level of MAPK8IP2 was higher in primary tumors than in normal tissues, and the high MAPK8IP2 DNA methylation group of PCa patients had poor survival. Enrichment analysis indicated that MAPK8IP2 was involved in the MAPK signaling pathway. In vitro, knockdown of MAPK8IP2 inhibited PCa cell proliferation, migration and invasion.ConclusionMAPK8IP2 is a potential target for PCa treatment and can serve as a novel biomarker for PCa diagnosis and prognosis evaluation.

Evaluation and multi-institutional validation of a novel urine biomarker lncRNA546 to improve the diagnostic specificity of prostate cancer in PSA gray-zone.

Background and objectivesProstate specific antigen (PSA) is currently the most commonly used biomarker for prostate cancer diagnosis. However, when PSA is in the gray area of 4-10 ng/ml, the diagnostic specificity of prostate cancer is extremely low, leading to overdiagnosis in many clinically false-positive patients. This study was trying to discover and evaluate a novel urine biomarker long non-coding RNA (lncRNA546) to improve the diagnostic accuracy of prostate cancer in PSA gray-zone.MethodsA cohort study including consecutive 440 participants with suspected prostate cancer was retrospectively conducted in multi-urology centers. LncRNA546 scores were calculated with quantitative real-time polymerase chain reaction. The area under the receiver operating characteristic curve (AUROC), decision curve analysis (DCA) and a biopsy-specific nomogram were utilized to evaluate the potential for clinical application. Logistic regression model was constructed to confirm the predictive power of lncRNA546.ResultsLncRNA546 scores were sufficient to discriminate positive and negative biopsies. ROC analysis showed a higher AUC for lncRNA546 scores than prostate cancer antigen 3 (PCA3) scores (0.78 vs. 0.66, p<0.01) in the overall cohort. More importantly, the AUC of lncRNA546 (0.80) was significantly higher than the AUCs of total PSA (0.57, p=0.02), percentage of free PSA (%fPSA) (0.64, p=0.04) and PCA3 (0.63, p<0.01) in the PSA 4-10 ng/ml cohort. A base model constructed by multiple logistic regression analysis plus lncRNA546 scores improved the predictive accuracy (PA) from 79.8% to 86.3% and improved AUC results from 0.862 to 0.915. DCA showed that the base model plus lncRNA546 displayed greater net benefit at threshold probabilities beyond 15% in the PSA 4-10 ng/ml cohort.ConclusionLncRNA546 is a promising novel biomarker for the early detection of prostate cancer, especially in the PSA 4-10 ng/ml cohort.

Upregulation of COPB2 Promotes Prostate Cancer Proliferation and Invasion Through the MAPK/TGF-β Signaling Pathway.

There is increasing evidence that coatomer protein complex subunit beta 2 (COPB2) plays an important role in various cancer types. This study explored the role and the downstream mediators of COPB2 in prostate cancer (PCa). The expression of COPB2 was determined by the Cancer Genome Atlas database and enzyme-linked immunosorbent assay. COPB2 expression was upregulated in PCa tissues and correlated with Gleason score, biochemical recurrence, and poor prognosis. The functional roles of COPB2 in PCa were verified through a series of experiments. Knocking down COPB2 expression inhibited the growth and clonogenesis of PCa cells, promoted cell apoptosis, and inhibited the ability of scratch repair, invasion of PCa cells, and tumor growth in Nude mice. To analyze downstream signaling pathways, ingenuity pathway analysis, GSEA, and whole-genome expression spectrum GeneChip analysis were used. Western blot revealed that COPB2 expression promoted the proliferation and invasion of PCa cells by regulating the MAPK/TGF-β signaling pathway. The interacting protein (nuclear protein 1, NUPR1) was identified via Co-IP, real-time PCR, Western blot, and TCGA database in sampled tissues. The expressions of the interaction proteins NUPR1 and COPB2 were negatively regulated by each other. COPB2 could be a new biomarker for PCa diagnosis and monitoring and to provide a theoretical basis for identifying effective drug intervention targets through in-depth mechanistic studies.

Copy number variation of urine exfoliated cells by low-coverage whole genome sequencing for diagnosis of prostate adenocarcinoma: a prospective cohort study.

BackgroundNon-invasive, especially the urine-based diagnosis of prostate cancer (PCa) remains challenging. Although prostate cancer antigen (PSA) is widely used in prostate cancer screening, the false positives may result in unnecessary invasive procedures. PSA elevated patients are triaged to further evaluation of free/total PSA ratio (f/t PSA), to find out potential clinically significant PCa before undergoing invasive procedures. Genomic instability, especially chromosomal copy number variations (CNVs) were proved much more tumor specific. Here we performed a prospective study to evaluate the diagnostic value of CNV via urine-exfoliated cell DNA analysis in PCa.MethodsWe enrolled 28 PSA elevated patients (≥ 4 ng/ml), including 16 PCa, 9 benign prostate hypertrophy (BPH) and 3 prostatic intraepithelial neoplasia (PIN). Fresh initial portion urine was collected after hospital admission. Urine exfoliated cell DNA was analyzed by low coverage Whole Genome Sequencing, followed by CNV genotyping by the prostate cancer chromosomal aneuploidy detector (ProCAD). CNVs were quantified in absolute z-score (|Z|). Serum free/total PSA ratio (f/t PSA) was reported altogether.ResultsIn patients with PCa, the most frequent CNV events were chr3q gain (n = 2), chr8q gain (n = 2), chr2q loss (n = 4), and chr18q loss (n = 3). CNVs were found in 81.2% (95% Confidence Interval (CI) 53.7–95.0%) PCa. No CNV was identified in BPH patients. A diagnosis model was established by incorporating all CNVs. At the optimal cutoff of |Z|≥ 2.50, the model reached an AUC of 0.91 (95% CI 0.83–0.99), a sensitivity of 81.2% and a specificity of 100%. The CNV approach significantly outperformed f/t PSA (AUC = 0.62, P = 0.012). Further analyses showed that the CNV positive rate was significantly correlated with tumor grade. CNVs were found in 90.9% (95% CI 57.1–99.5%) high grade tumors and 60.0% (95% CI 17.0–92.7%) low grade tumors. No statistical significance was found for patient age, BMI, disease history and family history.ConclusionsUrine exfoliated cells harbor enriched CNV features in PCa patients. Urine detection of CNV might be a biomarker for PCa diagnosis, especially in terms of the clinically significant high-grade tumors.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12920-022-01253-5.

A rationally designed triple-qualitative and double-quantitative high precision multi-signal readout sensing platform

Single mode sensing is more likely suffers from false positive or negative results than multi-signal readout assay. By using a layer-by-layer modified ITO/Au/BiOI electrode as the matrix and core/shell upconversion nanoparticles (UCNPs) as the signal labels, a triple-qualitative (smartphone based naked-eye readout, photoelectrochemical (PEC) and fluorescence (FL)) and double-quantitative (PEC and FL) multi-signal readout sensing platform was designed for high-precision assay of prostate-specific antigen (PSA), a biomarker for prostate cancer diagnosis. Based on the PSA bio-recognition events, the PEC mode sensing was achieved, while the specific enzymatically active of PSA for 5-Carboxyfluorescein (FAM) labeled helix peptide (CGHSSKLQK-FAM) enabled the FL sensing. Besides, under the excitation of 980 nm near-infrared (NIR) laser, the signal antibody@UCNPs bioconjugates can emit visible light for smartphone based naked-eye readout. Compared with the single-signal method, the accuracy of PSA serodiagnosis was obviously improved. Moreover, the above procedure could be extended to the single-molecule fluorescence counting method, the limit of detection for PSA can reach 0.005 ag/mL (S/N = 3). This work combined the advantages of different techniques, minimized the misdiagnose detection, and provides a rational design idea for multi-signal readout sensing platform.

Urine Biomarkers for Prostate Cancer Diagnosis and Progression

Prostate cancer (PCa) can be highly heterogeneous and multifocal, and accurate assessment of the volume, grade, and stage of PCa in situ is not a simple task. Urine has been investigated as a source of PCa biomarkers for over 70 years, and there is now strong evidence that analysis of urine could provide more accurate diagnosis and a better risk stratification that could aid clinical decisions regarding disease surveillance and treatment. Urine diagnostics is a developing area, moving towards multiomic biomarker integration for improved diagnostic performance. Urine tests developed by strong collaborations between scientists and clinicians have the potential to provide targeted and meaningful data that can guide treatment and improve men’s lives.

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.

Liquid biomarkers in active surveillance.

In the past two decades, new biomarkers for prostate cancer detection and risk prediction have become available for clinical use. While tissue-based gene expression assays offer molecular risk assessment after diagnoses, several serum- and urine-based 'liquid' biomarkers are available for the pre-biopsy setting which may also play a role for active surveillance (AS). The medical literature was queried utilizing PubMed (pubmed.ncbi.nlm.nih.gov) for all relevant original publications describing prostate cancer biomarkers that can be identified in the blood, urine, or semen. Referenced studies must have defined patient inclusion criteria and descriptions of the biomarkers. Included studies investigated the utility of liquid biomarkers for selection or monitoring of men with prostate cancer for active surveillance. PSA is the most common and readily available biomarker for prostate cancer diagnosis and treatment. Contemporary AS guidelines consider diagnostic PSA level in addition to other clinical factors when selecting men for this approach, with most recommending that initial PSA should be under 10 ng/ml. Serum PSA changes are associated with outcomes on AS but are not adequately sensitive so drive men to secondary treatment in isolation. PSA derivates including the Prostate Health Index (phi) and the 4K Score can predict higher grade cancer and may help tailor repeat prostate biopsy strategies, but further data are needed prior to routine clinic use. Several urine-based biomarkers including PCA3 and TMPRSS2:ERG levels have also been studied in the AS setting. Multiple serum- and urine-based liquid biomarkers are available for use in men with prostate cancer. For AS, serum PSA is utilized in part for patient selection as well as to monitor disease over time. Models that incorporate PSA kinetics with other clinical characteristics may help tailor surveillance strategies to reduce disease burden and health care costs over time. Several novel liquid biomarkers demonstrate promise and may eventually have applications for prostate cancer surveillance as well.

C-reactive protein and procalcitonin levels in prostate cancer.

Prostate cancer (PCa) is one of the most common cancers among men in the world. Prostate-specific antigen is the most used biomarker for PCa diagnosis. In this study, we aimed to measure the procalcitonin (PCT) and C-reactive protein (CRP) levels in patients with PCa. The patients who underwent transrectal prostate biopsy and transurethral prostate surgery in the last 4years were included in the study. The patients were divided into two groups according to the pathology reports, group1; benign prostate hyperplasia and group2; prostate cancer. MedCalc Statistical Software version 17.6 was used for statistical analyses. The current study includes 149 patients. There were 118 patients in group 1 and 31 patients in group 2. The mean age of the patients was 66.85 and 69.41years in groups respectively. Serum CRP and PCT levels were 3.33 and 0.01 in group 4.07 and 0.04 in group 2. Serum PCT levels were significantly higher in patients with PCa. We found that the elevated procalcitonin level was associated with prostate cancer. Further studies are needed to define the relationship between procalcitonin and prostate cancer.