Biomarker For Prostate Cancer Research Articles

Highly specific colorimetric detection of sarcosine using surface molecular imprinted Zn/Ce-ZIF

Despite significant progress in nanozyme research and the advancement of analytical techniques, the inherent lack of specificity for target analytes often limits their utility in analysis. Integrating specific recognition capabilities into inorganic nanomaterials, independent of biological catalysts or adaptors, represents a crucial breakthrough in the field. Detecting Sarcosine (Sar) in human urine has recently emerged as a non-invasive biomarker for prostate cancer (PCa), presenting a valuable diagnostic tool. This study introduces a novel method for embedding molecular imprinting sites directly onto the surface of a Zn/Ce-based zeolitic imidazolate framework (Zn/Ce-ZIF) nanozyme, facilitating the development of a highly specific colorimetric assay for precise Sar measurement. By utilizing the lanthanide metal cerium as the catalytic element and ZIF-8 as the structural scaffold, we synthesized spherical Zn/Ce-ZIF nanozymes with exceptional oxidase-like catalytic efficiency. The efficiency of molecular imprinting experiments and the ability of molecularly imprinted polymers (MIPs) to identify target molecules were significantly enhanced by using theortical calculations to screen suitable functional monomers. The molecularly imprinted nanozyme (Zn/Ce-ZIF@MIP) initiates a colorimetric oxidation reaction of 3,3′,5,5′-tetramethylbenzidine (TMB), wherein the presence of Sar facilitates selective recognition and capture by the MIP shell, modulating the colorimetric response by hindering TMB’s access to the catalytic site. An intelligent color extraction detection device has been developed for the rapid perception of Sar. This colorimetric sensing platform has been validated through the detection of Sar in simulated urine samples. Overall, the application of surface molecular imprinting enhances the functionality of nanozymes in analytical fields.

Combining tissue biomarkers with mpMRI to diagnose clinically significant prostate cancer. Analysis of 21 biomarkers in the PICTURE study.

Serum PSA and digital rectal examination remain the key diagnostic tools for detecting prostate cancer. However, due to the limited specificity of serum PSA, the applicability of this marker continues to be controversial. Recent use of image-guided biopsy along with pathological assessment and the use of biomarkers has dramatically improved the diagnosis of clinically significant cancer. Despite the two modalities working together for diagnosis biomarker research often fails to correlate findings with imaging. We looked at 21 prostate cancer biomarkers correlating our results with mpMRI data to investigate the hypothesis that biomarkers along with mpMRI data make a powerful tool to detect clinically significant prostate cancer. Biomarkers were selected based on the existing literature. Using a tissue microarray comprised of samples from the PICTURE study, with biopsies at 5 mm intervals and mpMRI data we analysed which biomarkers could differentiate benign and malignant tissue. Biomarker data were also correlated with pathological grading, mpMRI, serum PSA, age and family history. AGR2, CD10 and EGR protein expression was significantly different in both matched malignant and benign tissues. AMACR, ANPEP, GDF15, MSMB, PSMA, PTEN, TBL1XR1, TP63, VPS13A and VPS28 showed significantly different expression between Gleason grades in malignant tissue. The majority of the biomarkers tested did not correlate with mpMRI data. However, CD10, KHDRBS3, PCLAF, PSMA, SIK2 and GDF15 were differentially expressed with prostate cancer progression. AMACR and PTEN were identified in both pathological and image data evaluation. There is a high demand to develop biomarkers that would help the diagnosis and prognosis of prostate cancer. Tissue biomarkers are of particular interest since immunohistochemistry remains a cheap, reliable method that is widely available in pathology departments. These results demonstrate that testing biomarkers in a cohort consistent with the current diagnostic pathway is crucial to identifying biomarker with potential clinical utility.

Exosomal PSM-E inhibits macrophage M2 polarization to suppress prostate cancer metastasis through the RACK1 signaling axis

BackgroundIt is well-established that understanding the mechanism of prostate cancer (PCa)-associated metastasis is paramount for improving its prognosis. Metastasis is known to involve the communication between tumor-associated macrophages (TAMs) and tumor cells. Exosomes are crucial in mediating this intercellular communication within the tumor microenvironment. Nonetheless, the role of exosomal proteins in PCa metastasis is not yet fully understood. Here, we investigated the mechanisms of prostate cancer-derived exosomal PSM-E on regulating macrophage M2 polarization to suppress tumor invasion and metastasis.MethodsPSM-E levels in exosomes were detected by transmission electron microscopy and Western blotting analysis. The diagnostic value of urine-derived exosomal PSM-E in PCa were evaluated by LC-MS/MS, correlation analysis, and ROC curves analysis. The mechanisms underlying the inhibitory effect of exosomal PSM-E on the M2 polarization of macrophages was investigated by co-IP, IHC staining, and PCa tumorigenesis model, etc.ResultsWe revealed that exosomal PSM-E is upregulated in exosomes derived from the serum and urine of PCa patients. Clinically, an elevated exosomal PSM-E expression in urine is significantly correlated with an advanced pathological tumor stage and a high Gleason score. Our research also revealed that exosomal PSM-E inhibits prostate cancer cell proliferation, invasion, and metastasis by suppressing macrophage polarization in vitro and in vivo. Furthermore, we provided compelling evidence that exosomal PSM-E inhibits M2 polarization of macrophages by recruiting RACK1 and suppressing the FAK and ERK signaling pathways, consequently suppressing PCa invasion and metastasis. Furthermore, we found that the protease-associated domain of PSM-E and the fourth tryptophan-aspartate repeat of RACK1 are crucial for the interaction between PSM-E and RACK1.ConclusionsNotably, exosomes carrying PSM-E from PCa urine could potentially serve as a biomarker for PCa, and targeting exosomal PSM-E may represent a strategy for preventing tumor progression in this patient population.

Abstract A007: Characterization of miR-141 and miR-145 expression in cancer stem cells of metastatic prostate cancer patients

Abstract Background: Prostate cancer (PCA) is the second most prevalent cancer globally and the fifth leading cause of cancer-related mortality. However, effective prognostic biomarkers for metastatic PCA remain lacking. Recent research highlights the role of microRNAs (miRNAs) in regulating cancer stem cells (CSCs) and influencing tumour progression across various cancers. Therefore, in this we investigated the effects of miR-141 and miR-145 expression on the metastatic PCA of CSCs and assessed their potential role as biomarkers for metastatic PCA prognosis. Methods: The expression levels of miR-141 and miR-145 were quantified using real-time qPCR. Flow cytometry was employed to assess the levels of prostate cancer stem cells (PCSCs) in tissue samples from patients with localized (non-metastatic) and metastatic PCA. Results: Our findings revealed a significant increase in miR-141 expression, accompanied by elevated levels of CD44^high/CD24^low and CD133^high, in metastatic PCA compared to localized PCA. Conversely, reduced miR-145 expression was associated with enhanced stemness characteristics, as indicated by increased CD44^high/CD24^low and CD133^high levels, in metastatic PCA compared to localized PCA. Additionally, prostate-specific antigen (PSA) and testosterone levels exhibited a significant rise (p<0.001), while apoptosis rates decreased in both localized and metastatic PCA compared to localized PCA. Conclusions: The collective findings of this study suggest that miR-141 and miR-145, in conjunction with CSC markers, hold promise as diagnostic and prognostic tools for PCA. They may also be valuable for detecting minimal residual disease and improving therapeutic strategies for managing metastatic PCA. Citation Format: Kamla Kant Shukla, Gautam Ram Choudhary. Characterization of miR-141 and miR-145 expression in cancer stem cells of metastatic prostate cancer patients [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr A007.

Abstract A003: CD45 positive circulating tumor cells as a prognostic marker in prostate cancer

Abstract Prostate cancer is one of the most common types of cancer among male patients worldwide, making early diagnosis and effective treatment crucial for improving patient survival rates. In this regard, circulating tumor cells (CTCs) have garnered attention as an important biomarker for cancer staging and monitoring treatment response. In prostate cancer, CTCs are typically identified as keratin+/CD45- cells, with additional markers such as PSA or PSMA also being used. The conventional CTC identification way have dismissed CD45+/keratin+ double-positive cells as artifacts by nonspecific binding during the staining process. However, recent studies have reported the presence of CD45+/keratin+ CTCs in various types of cancers, highlighting metastatic potential and their ability to evade the immune system. These findings require re- examination of the role for the double positive CTCs. Therefore, this study aimed to identify the presence of CD45+ CTCs in prostate cancer and to assess their clinical significance. Blood samples were collected from 80 prostate cancer patients, followed by unbiased isolation of CTCs, which were stained using PSA, keratin, and CD45. The detected CTCs were categorized based on CD45 expression, and the clinical relevance of each group was validated using patient information. Through this study, we aimed to confirm whether the CD45+ CTCs can be a clinical indicator in prostate cancer. The results revealed that CD45+ CTCs accounted for 90% of all detected CTCs, likely due to their high immune evasion capabilities. Additionally, in 17% of the patients, only CD45+ CTCs were detected, indicating the potential to expand CTC detection even in patients where CTCs were previously undetected using conventional criteria. The number of CD45+ CTCs was significantly higher in patients with progressive disease compared to those with complete or partial response, showing greater statistical significance than analyses using CD45- CTCs. Furthermore, the number of PSA+ CTCs was closely linked to changes in plasma PSA levels, suggesting they could be used as a supporting marker to enhance the accuracy of current plasma PSA tests. These findings indicate that CD45+ CTCs in prostate cancer are not merely artifacts of nonspecific binding but are indeed meaningful cells closely related to cancer progression. This study suggests that CD45+ CTCs have the potential to be utilized as a prognostic biomarker in prostate cancer. By including CD45+ CTCs, which were previously overlooked in conventional CTC analysis methods, more sensitive and accurate cancer monitoring could be achieved. In-depth future studies on the clinical applicability of CD45+ CTCs could significantly contribute to predicting prognosis and developing personalized treatment strategies for prostate cancer patients. Citation Format: Hyeongjung Woo, Woon-Hae Kim, Hyun Young Shin, Hyerin Jung, Hyung Ho Lee, Minseok S. Kim, Jae Young Joung. CD45 positive circulating tumor cells as a prognostic marker in prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A003.

AR (CAG)n Microsatellite and APEX1 c.444T>G (p.Asp148Glu) Polymorphisms as Independent Prognostic Biomarkers in Prostate Cancer: Insights from an Argentinian Cohort.

Prostate cancer (PCa) is the leading malignancy and the third most common cause of cancer-related death in Argentinian men. Predicting outcomes in localized PCa remains difficult due to tumor heterogeneity. In this study, we assessed the impact of AR (CAG)n and APEX1 c.444T>G polymorphisms on biochemical relapse in Argentine patients with localized PCa. We genotyped blood samples from 123 PCa patients for AR (CAG)n and APEX1 p.Asp148Glu (c.444T>G) polymorphisms. Associations with clinicopathological parameters and biochemical relapse-free survival (BRFS) were assessed. AR (CAG)20-23 was associated with a family history of breast/ovarian cancer (p = 0.0469). The combination of AR (CAG)20-23 and APEX1 c.444TT/GG correlated with a 2.89 times higher risk of biochemical relapse (log-rank p = 0.006). Multivariable analysis confirmed AR and APEX1 polymorphisms as independent predictors of biochemical relapse (HR = 3.95, p = 0.002). In patients with PSA levels <10 ng/mL, combined AR (CAG)20-23 and APEX1 c.444TT/GG genotypes were significantly associated with an increased risk of biochemical relapse (HR = 2.61, p = 0.044). Multivariable analysis confirmed the prognostic significance of these genotypes (HR = 3.44, p = 0.02). This study has identified AR (CAG)n and APEX1 c.444T>G polymorphisms as independent predictors of PCa relapse in Argentinian patients, suggesting their potential use in improving prognostic models.

Spatial transcriptomics reveals strong association between SFRP4 and extracellular matrix remodeling in prostate cancer

Prostate tumor heterogeneity is a major obstacle when studying the biological mechanisms of molecular markers. Increased gene expression levels of secreted frizzled-related protein 4 (SFRP4) is a biomarker in aggressive prostate cancer. To understand how SFRP4 relates to prostate cancer we performed comprehensive spatial and multiomics analysis of the same prostate cancer tissue samples. The experimental workflow included spatial transcriptomics, bulk transcriptomics, proteomics, DNA methylomics and tissue staining. SFRP4 mRNA was predominantly located in cancer stroma, produced by fibroblasts and smooth muscle cells, and co-expressed with extracellular matrix components. We also confirmed that higher SFRP4 gene expression is associated with cancer aggressiveness. Gene expression of SFRP4 was affected by gene promotor methylation. Surprisingly, the high mRNA levels did not reflect SFRP4 protein levels, which was much lower. This study contributes previously unknown insights of SFRP4 mRNA in the prostate tumor environment that potentially can improve diagnosis and treatment.

Discovery of RNA Biomarkers for Prostate Cancer Using Cross-Platform Transcriptomics.

Microarray and Single-Molecule Molecular Inversion Probe (smMIP)-based targeted RNA sequencing are two RNA profiling platforms for identifying disease-associated biomarkers. The microarray uses a GeneChip array with oligonucleotide probes to measure expression levels across thousands of genes, while smMIPs capture and quantify RNA transcripts and transcript variants via next-generation sequencing. To evaluate the strengths and weaknesses of both platforms, a comparative gene expression profiling study was conducted using RNA samples from 52 prostate tissues (normal, benign prostatic hyperplasia (BPH) and various prostate cancer (PCa) grades). Of all genes covered by both platforms, only 35% of the expression levels aligned, with 45% showing discrepancies. Both platforms identified the same 17 genes as potential PCa biomarkers. Microarray analysis identified an additional 253 genes that were not covered or not identified by smMIP technology, while smMIP technology identified eight markers not covered or not identified in the microarray core gene analysis, including fusion genes and splice variants. For high-grade prostate cancer (HG-PCa), the smMIP-method identified 8 markers, and the microarray identified 17 markers, with FOLH1, FAP and CLDN3 being common across both platforms. The choice of RNA expression analysis technology depends on research objectives; microarray technology is useful for the evaluation of a wide range of genes but has low throughput. In contrast, smMIP-based RNA sequencing enables sensitive analysis with minimal RNA in a medium- to high-throughput setting.

Identifying causal relationships between 35 blood and urine biomarkers and urologic cancers: MR-meta combined with Bayesian colocalization Mendelian randomization analysis

BackgroundBlood and urine biomarkers have been associated with urologic tumors, but their causal relationship with urologic tumors is unclear.MethodsWe performed a bidirectional Mendelian randomization (MR) analysis of the association between 35 blood and urine biomarkers and urological tumors in our discovery cohort. A Bayesian weighting approach was used to validate the positive results identified in the discovery cohort, and steiger filtering analysis was used to distinguish causality from reverse causality. Bayesian colocalization analysis was used to analyze which single nucleotide polymorphisms (SNPs) specifically co-located between the positive blood and urine biomarkers and the disease phenotypes were driven, and MR-positive results from the discovery cohort and the validation cohort were combined using the MR-meta method.ResultsSeveral blood and urine biomarkers were found to be significantly and causally associated with urologic cancers. Notably, calcium (OR: 1.34, 95%CI 1.10–1.63, P = 0.0040) and sex hormone-binding globulin (SHBG) (OR: 0.81, 95%CI 0.70–0.95, P = 0.0092) were associated with bladder cancer; gamma glutamyl transferase (GGT) (OR: 0.91, 95%CI 0.83–0.99, P = 0.0209), lipoprotein A (Lp(a)) (OR: 1.12, 95%CI 1.01–1.24, P = 0.0399), and insulinlike growth factor 1 (IGF 1) (OR: 1.10, 95%CI 1.01–1.20, P = 0.0220) were linked to prostate cancer (PCa); non albumin protein (OR: 0.78, 95%CI 0.65–0.93, P = 0.0065) and total protein (OR: 0.80, 95%CI 0.64–0.99, P = 0.0380) were linked to renal cancer; and apolipoprotein A (Apo-A) (OR: 0.56, 95%CI 0.32–0.98, P = 0.0426) and urate (OR:1.89, 95%CI 1.03–3.47, P = 0.0399) were associated with renal pelvis cancer. These associations were validated in an independent cohort, with GGT, IGF 1, and Lp(a) being consistently linked to PCa.ConclusionThis study identified significant biomarkers associated with urological cancers in blood and urine. These include GGT, IGF 1, and Lp(a), which are strong biomarkers for PCa. In addition, the findings of this study provide evidence for a handful of risk and protective factors for the development of urologic cancers.

Comprehensive cataloging of miR-363 as a therapeutic & non-invasive biomarker of prostate cancer.

Background & objectives Overcoming the challenge of early diagnosis of prostate cancer (PCa) by exploring molecular biomarkers is urgently needed. With this objective, this study was designed to explore the biomarker and therapeutic potential of miRNA (miR)-363-3p in PCa pathogenesis. Methods Total participants (n=188) were enrolled, and blood and tissue samples were collected from individuals categorized into the control group (n=55), benign prostate hyperplasia (BPH) group (n=60), PCa group (n=48), and castration-resistant PCa (CRPC) group (n=25). MiR expression profiling was carried out using quantitative polymerase chain reaction (qPCR), and biomarker analysis was conducted employing receiver operating characteristics (ROC) curve. The miR-363 target genes were predicted by in silico tools like Target Scan and starBasev 2.0 and its expression was validated by qPCR and association among them was established by using the STRING database. Results The results showed that the tumour-suppressive nature of miR-363-3p in both PCa tissues and serum were significantly higher than the control with a greater area under curve (AUC) was 0.969 (sensitivity: 85%; specificity 100%) and 0.988 (sensitivity: 97.5%; specificity: 87.5%), respectively. The targetome analysis of miR-363-3p revealed five target genes-NRAS, E2F3, PTEN, MDM2, and CCNE2 which were strongly associated with cell division and proliferation. The expression analysis of the target genes showed a significant tumour-suppression of PTEN gene and significant upregulation of oncogenic genes such as NRAS, E2F3, MDM2, and CCNE2. Interpretation & conclusions Collectively, the findings of this study suggest that miR-363-3p may be a potential biomarker in differentiating individuals with PCa and CRPC from healthy controls. The miR-363-3p triggers various oncogenic genes (MDM2, NRAS, E2F3, CCNE2) and tumour suppressor genes (PTEN) that are actively involved in PCa progression and development.

Blood Protein Ratios Reveal New Diagnostic Biomarkers for Prostate Cancer: A Study from the Perspective of Mendelian Randomization

Prostate cancer (PCa) is a leading malignancy affecting men globally, contributing significantly to cancer-related morbidity and mortality. Our study aims to explore causal relationships between blood protein ratios (BPR) and PCa using a Mendelian randomization (MR) approach, potentially identifying new diagnostic and therapeutic targets. Methods: A two-sample MR method was employed, utilizing genetic variants as instrumental variables (IVs) to infer causality between circulating BPR and PCa. Data on BPR were obtained from a proteomics study of the UK Biobank, while PCa data were sourced from FinnGen, the PRACTICLE Consortium, and the GWAS Catalog. Stringent criteria were applied for IV selection, and statistical analyses included the inverse-variance weighted (IVW) method with sensitivity analyses to address pleiotropy and heterogeneity. Results: Significant causal associations were identified between several BPR and PCa. Notably, the ratios of CEBPB/PXN, APBB1IP/NCF2, APP/EGF, and CRKL/ EGF were found to be protective against PCa, while the ratios of ARHGAP1/RAD23B, EGF/ TNFSF14, and GOLM2/STC1 were identified as risk factors. Reverse MR analysis suggested that PCa might act as a protective factor for the GOLM2/STC1 ratio. Sensitivity analyses confirmed the robustness of these findings. Conclusions: This study elucidates significant causal relationships between 7 BPR and PCa, offering new insights for diagnosis, treatment evaluation, and personalized therapeutic strategies. Future research should focus on validating these findings and exploring the underlying biological mechanisms to improve PCa management.

N-linked fucosylated glycans are biomarkers for prostate cancer with a neuroendocrine and metastatic phenotype.

Prostate cancer (PCa) is a heterogeneous disease with a spectrum of pathology and outcomes ranging from indolent to lethal. Although there have been recent advancements in prognostic tissue biomarkers, limitations still exist. We leveraged Matrix Assisted Laser Desorption Ionization (MALDI) imaging of formalin-fixed, paraffin embedded (FFPE) prostate cancer specimens to determine if N-linked glycans expressed in the extracellular matrix of lethal neuroendocrine prostate cancer were also expressed in conventional prostate adenocarcinomas that were associated with poor outcomes. We found that N-glycan fucosylation was abundant in neuroendocrine prostate cancer as well as adenocarcinomas at time of prostatectomy that eventually developed recurrent metastatic disease. Analysis of patient derived xenografts revealed that this fucosylation signature was enriched differently across metastatic disease organ sites, with the highest abundance in liver metastases. These data suggest that N-linked fucosylated glycans could be an early tissue biomarker for poor PCa outcomes. Implications: These studies identify that hyper-fucosylated N-linked glycans are enriched in neuroendocrine prostate cancer and conventional prostate adenocarcinomas that progress to metastatic disease, thus advancing biomarker discovery and providing insights into mechanisms underlying metastatic disease.

Non-enzymatic electrochemical detection of sarcosine in serum of prostate cancer patients by CoNiWBO/rGO nanocomposite

Selective and sensitive sarcosine detection is crucial due to its recent endorsement as a prostate cancer (PCa) biomarker in clinical diagnosis. The reduced graphene oxide-cobalt nickel tungsten boron oxides (CoNiWBO/rGO) nanocomposite is developed as a non-enzymatic electrochemical sensor for sarcosine detection in PCa patients’ serum. CoNiWBO/rGO is synthesized by the chemical reduction method via a one-pot reduction method followed by calcination at 500 °C under a nitrogen environment for 2 h and characterized by UV-Vis, XRD, TGA, and SEM. CoNiWBO/rGO is then deposited on a glassy carbon electrode, and sarcosine sensing parameters are optimized, including concentration and pH. This non-enzymatic sensor is employed to directly determine sarcosine in serum samples. Differential pulse voltammetry (DPV) and linear sweep voltammetry (LSV) are employed to monitor the electrochemical behavior where sarcosine binding leads to oxidation. Chronoamperometric studies show the stability of the developed sensor. The results demonstrate a wide linear range from 0.1 to 50 µM and low limits of detection, i.e., 0.04 µM and 0.07 µM using DPV and LSV respectivel. Moreover, the calculated recovery of sarcosine in human serum of prostate cancer patients is 78–96%. The developed electrochemical sensor for sarcosine detection can have potential applications in clinical diagnosis.

Prognostic Impact of H19/Cell Adhesion Molecules Circuitry on Prostate Cancer Biopsy.

Metastatic prostate cancer (PCa) presents a significant challenge in oncology due to its high mortality rate and the absence of effective biomarkers for predicting patient outcomes. Building on previous research that highlighted the critical role of the long noncoding RNA (lncRNA) H19 and cell adhesion molecules in promoting tumor progression under hypoxia and estrogen stimulation, this study aimed to assess the potential of these components as prognostic biomarkers for PCa at the biopsy stage. This research utilized immunohistochemistry and droplet digital PCR to analyze formalin-fixed paraffin-embedded (FFPE) biopsies, focusing on specific markers within the H19/cell adhesion molecules pathway. A novel multivariate analysis led to a "BioScore", a composite biomarker score to predict disease progression. This score is based on evaluating five key markers: the expression levels of Hypoxia-Inducible Factor 2 Alpha (HIF-2α), endothelial Nitric Oxide Synthase (eNOS), β4 integrin, E-cadherin transcript (CDH1), and lncRNA H19. The criteria for the "BioScore" involve identifying three out of these five markers, combining elevated levels of HIF-2α, eNOS, β4 integrin, and CDH1 with reduced H19 expression. This finding suggests the possibility of identifying, at the time of biopsy, PCa patients at higher risk of metastasis based on dysregulation in the H19/cell adhesion molecules circuitry. This study provides a valuable opportunity for early intervention in managing PCa, potentially contributing to personalized treatment strategies.

Single-cell sequencing analysis revealed that NEAT1 was a potential biomarker and therapeutic target of prostate cancer.

Prostate cancer (PCa) usually manifests atypical symptoms in the early stage, and once symptoms appear, most PCa patients have developed to the advanced stage, failing to undergo radical surgery. In this study, PCa occurrence-related biomarkers were explored based on single-cell RNA sequencing (scRNA-seq) data. scRNA-seq data of prostate normal (Normal), benign prostatic hyperplasia (BPH), and PCa (Tumor) samples were acquired from the Gene Expression Omnibus (GEO). Cellular subsets associated with PCa occurrence were obtained using cell annotation. Additionally, the mRNA expression of nuclear enriched abundant transcript 1 (NEAT1) was detected by quantitative real-time PCR (qRT-PCR). The effects of NEAT1 on cell proliferation and apoptosis were analyzed by 5-ethynyl-2-deoxyuridine (EdU) and flow cytometry. Subsequently, cell-derived xenograft (CDX) models were constructed and divided into the LV-NC and LV-shNEAT1 groups. After the tumor tissues of CDX model mice in each group were extracted, the cell growth and Ki67 expression were observed separately using hematoxylin-eosin (H&E) staining and immunohistochemistry (IHC). Ten cellular subsets were obtained via cell annotation, and significantly differential changes were observed between Basal intermediate and Luminal during the course of BPH to PCa. NEAT1-Luminal was highly recruited in the Tumor group with low stemness and high malignancy scores. Matrix metallopeptidase 7 (MMP7)- keratin 17 (KRT17)-Basal intermediate had high ratios in the Tumor group with low stemness and high malignancy scores. The results of pseudotime analysis revealed that NEAT1-Luminal in the Tumor group were consistently distributed with tumor stage cells. In vitro assays showed that NEAT1 expression was elevated in PCa cells, and NEAT1 knockdown could inhibit cell proliferation and induce apoptosis. CDX assays indicated that silencing NEAT1 could reduce the growth rate of PCa tumor volume in CDX model mice. H&E staining results showed that nuclei of tumor cells were reduced and exhibited lighter color in the LV-shNEAT1 group compared with the LV-NC group. IHC results showed that Ki67 positivity was significantly lower in the LV-shNEAT1 group than in the LV-NC group. NEAT1 expression is increased in PCa, and NEAT1 can be a potential biomarker and therapeutic target for PCa.

Circulating Tumor Cell Count and Overall Survival in Patients With Metastatic Hormone-Sensitive Prostate Cancer

In metastatic hormone-sensitive prostate cancer (mHSPC), new first-line combination therapies have enhanced overall survival (OS), but clinical outcomes for individual patients vary greatly and are difficult to predict. Peripheral blood circulating tumor cell (CTC) count is the most extensively validated prognostic liquid biomarker in metastatic castration-resistant prostate cancer (mCRPC), and recent studies have suggested that it may also be informative in mHSPC. To examine the prognostic value of CTC count in men with mHSPC. In this prognostic study, peripheral blood was drawn at registration (baseline) and at progression to mCRPC in the S1216 study (March 1, 2013, to July 15, 2017), a phase 3, prospective, randomized clinical trial in men with mHSPC. The CTCs were enumerated using a US Food and Drug Administration-cleared isolation platform. Counts were categorized as 0, 1 to 4, or 5 or more CTCs per 7.5 mL based on the prognostic value of these cut points in prior studies. The data analysis was performed between October 28, 2022, and June 15, 2023. Metastatic hormone-sensitive prostate cancer. Circulating tumor cell count was evaluated for an association with 3 prespecified trial end points: OS, progression-free survival, and 7-month prostate-specific antigen, after adjusting for other baseline covariates using proportional hazards and logistic regression models. Of 1313 S1216 participants (median [IQR] age, 68 [44-92] years), evaluable samples from 503 (median [IQR] age, 69 [46-90] years) with newly diagnosed mHSPC were collected at baseline, and 93 samples were collected at progression. Baseline counts were 5 or more CTCs per 7.5 mL in 60 samples (11.9%), 1 to 4 CTCs per 7.5 mL in 107 samples (21.3%), and 0 CTCs per 7.5 mL in 336 samples (66.8%). Median OS for men with 5 or more CTCs per 7.5 mL was 27.9 months (95% CI, 24.1-31.2 months) compared with 56.2 months (95% CI, 45.7-69.8 months) for men with 1 to 4 CTCs per 7.5 mL and not reached at 78.0 months follow-up for men with 0 CTCs per 7.5 mL. After adjusting for baseline clinical covariates, men with 5 or more CTCs per 7.5 mL at baseline had a significantly higher hazard of death (hazard ratio, 3.22; 95% CI, 2.22-4.68) and disease progression (hazard ratio, 2.46; 95% CI, 1.76-3.43) and a lower likelihood of prostate-specific antigen complete response (odds ratio, 0.26; 95% CI, 0.12-0.54) compared with men with 0 CTCs per 7.5 mL at baseline. Adding baseline CTC count to other known prognostic factors (covariates only: area under the curve, 0.73; 95% CI, 0.67-0.79) resulted in an increased prognostic value for 3-year survival (area under the curve, 0.79; 95% CI, 0.73-0.84). In this prognostic study, the findings validate CTC count as a prognostic biomarker that improved upon existing prognostic factors and estimated vastly divergent survival outcomes regardless of subsequent lines of therapy. As such, baseline CTC count in mHSPC may serve as a valuable noninvasive biomarker to identify men likely to have poor survival who may benefit from clinical trials of intensified or novel regimens.

Development of transition metal oxide platforms for aptasensing of PSA in cell cultures.

In this study, a novel aptasensor based on a transition metal oxide-modified pencil graphite electrode (PGE) was developed for the diagnosis of early-stage prostate cancer (PCa) via monitoring the prostate-specific antigen (PSA), which is the main biomarker for PCa. Single-use PGEs modified with pulsed deposited manganese oxide (MnOx) film were used to attach the amino-terminated aptamer specific to the PSA via carbodiimide chemistry. The designed aptasensor was placed in an electrochemical cell containing ferri/ferrocyanide ions as a redox probe to measure the charge transfer resistances (Rct) of the electrode surface by electrochemical impedance spectroscopy (EIS) to follow the response of each modification step. The effect of the medium pH on the ionic structure of the aptamer molecule according to its pI value and, thus, the reversing of the direction of the response (ΔRct) by the pH change was also discussed. The level of PSA secreted from PCa cells was investigated using impedimetric transduction. The specificity of the aptasensor was validated through selectivity studies against non-specific tumor markers like VEGF and different cancer cell lines including breast cancer and androgen-insensitive prostate cancer. The developed system showcases a label-free, fast, specific, and cost-effective approach for PSA detection, highlighting the importance of medium pH and the electrostatic environment on the aptamer's response. Our work emphasizes the potential for such aptasensors in clinical diagnostics and paves the way for further exploration into using transition metal oxides in biosensing applications.

Serum levels of prostate specific antigen, free PSA, [-2]proPSA, fPSA/tPSA ratio, Prostate Health Index, and glycosylation patterns of free PSA in patients with benign prostatic hyperplasia pharmacotherapy.

The medication used to treat benign prostate hyperplasia (BPH), a common condition in men over 50 years of age, can alter the levels of biomarkers used in prostate cancer detection. Commonly used medications for BPH include alpha-blockers, 5-alpha reductase inhibitors (5-ARIs), and muscarinic antagonists. We studied the impact of these drugs on total prostate-specific antigen (tPSA), free PSA (fPSA), [-2]proPSA, fPSA/tPSA ratio, and the Prostate Health Index (PHI), as well as novel potential biomarkers in the form of glycan composition of fPSA. Serum samples were collected from 564 males with BPH, with a mean age of 68.5 years. The samples were used to measure levels of tPSA, fPSA, and [-2]proPSA. The fPSA/tPSA and PHI were then calculated. The glycan composition of fPSA was analyzed using lectin-based glycoprofiling. Pharmacotherapy data was collected from the patients' medical records. Alpha-blocker monotherapy was associated with higher fPSA and fPSA/tPSA ratio, and decreased PHI. Levels of tPSA were not impacted. Alpha-blocker and 5-ARI dual therapy was associated with reduced levels of fPSA, [-2]proPSA, and PHI. Therapy combining alpha-blockers and antimuscarinic agents did not significantly influence biomarker levels apart from an increase in a Maackia amurensis lectin-recognized glycan originating in fPSA. BPH pharmacotherapy notably affects prostate cancer biomarkers. Recognizing the impact of pharmacotherapy is crucial for achieving an accurate diagnosis of prostate cancer and for planning treatment.

Proteomic and phosphoproteomic landscape of localized prostate cancer unveils distinct molecular subtypes and insights into precision therapeutics

Building upon our previous investigation of genomic, epigenomic, and transcriptomic profiles of prostate cancer in China, we conducted a comprehensive analysis of proteomic and phosphoproteomic profiles of 82 tumor tissues and matched adjacent normal tissues from 41 Chinese patients with localized prostate cancer. We identified three distinct proteomic subtypes with significant difference in both molecular features and clinical prognosis. Notably, these proteomic subtypes exhibited a parallel degree of heterogeneity in the phosphoproteome, featuring unique metabolism, proliferation, and immune infiltration characteristics. We further demonstrated that a combination of proteins and phosphosites serves as the most effective biomarkers in prostate cancer to predict biochemical recurrence. Through an integrated multiomics analysis, we revealed mechanistic differences underlying different proteomic subtypes and highlighted the potential significance of Serine/arginine-rich splicing factor 1 (SRSF1) phosphorylation in promoting the malignant characteristics of prostate cancer cells. Our multiomics data provide valuable resources for understanding the molecular mechanisms of prostate cancer within the Chinese population, which have the potential to inform the development of personalized treatment strategies and enhance prognostic analyses for prostate cancer patients.

Contemporary Update on Clinical and Experimental Prostate Cancer Biomarkers: A Multi-Omics-Focused Approach to Detection and Risk Stratification.

Prostate cancer remains a significant health challenge, being the most prevalent non-cutaneous cancer in men worldwide. This review discusses the critical advancements in biomarker discovery using single-omics and multi-omics approaches. Multi-omics, integrating genomic, transcriptomic, proteomic, metabolomic, and epigenomic data, offers a comprehensive understanding of the molecular heterogeneity of prostate cancer, leading to the identification of novel biomarkers and therapeutic targets. This holistic approach not only enhances the specificity and sensitivity of prostate cancer detection but also supports the development of personalized treatment strategies. Key studies highlighted include the identification of novel genes, genetic mutations, peptides, metabolites, and potential biomarkers through multi-omics analyses, which have shown promise in improving prostate cancer management. The integration of multi-omics in clinical practice can potentially revolutionize prostate cancer prognosis and treatment, paving the way for precision medicine. This review underscores the importance of continued research and the application of multi-omics to overcome current challenges in prostate cancer diagnosis and therapy.