A predictive model for prostate cancer incorporating PSA molecular forms and age

Development and validation of a clinical-radiomics model for prediction of prostate cancer: a multicenter study

PURPOSE

To develop an early diagnosis model of prostate cancer based on clinical-radiomics to improve the accuracy of imaging diagnosis of prostate cancer.

METHODS

The multicenter study enrolled a total of 449 patients with prostate cancer from December 2017 to January 2022. We retrospectively collected information from 342 patients who underwent prostate biopsy at Minhang Hospital. We extracted T2WI images through 3D-Slice, and used mask tools to mark the prostate area manually. The radiomics features were extracted by Python using the "Pyradiomics" module. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for data dimensionality reduction and feature selection, and the radiomics score was calculated according to the correlation coefficients. Multivariate logistic regression analysis was used to develop predictive models. We incorporated the radiomics score, PI-RADS, and clinical features, and this was presented as a nomogram. The model was validated using a cohort of 107 patients from the Xuhui Hospital.

RESULTS

In total, 110 effective radiomics features were extracted. Finally, 9 features were significantly associated with the diagnosis of prostate cancer, from which we calculated the radiomics score. The predictors contained in the individualized prediction nomogram included age, fPSA/tPSA, PI-RADS, and radiomics score. The clinical-radiomics model showed good discrimination in the validation cohort (C-index = 0.88).

CONCLUSION

This study presents a clinical-radiomics model that incorporates age, fPSA/PSA, PI-RADS, and radiomics score, which can be conveniently used to facilitate individualized prediction of prostate cancer before prostate biopsy.

Non-Invasive Diagnosis of Prostate Cancer and High-Grade Prostate Cancer Using Multiparametric Ultrasonography and Serological Examination

OBJECTIVES

This study aimed to assess the efficacy of multiparametric ultrasonography (mpUS) combined with serological examination, as a non-invasive method, in detecting prostate cancer (PCa) or high-grade prostate cancer (HGPCa) respectively.

METHODS

A cohort of 245 individuals with clinically suspected PCa were enrolled. All subjects underwent a comprehensive evaluation, including basic data collection, serological testing, mpUS and prostate biopsy. Random Forest (RF) models were developed, and the mean area under the curve (AUC) in 100 cross-validations was used to assess the performance in distinguishing PCa from HGPCa.

RESULTS

mpUS features showed significant differences (p < 0.001) between the PCa and non-PCa groups, as well as between the HGPCa and low-grade prostate cancer (LGPCa) groups including prostate-specific antigen density (PSAD), transrectal real-time elastography (TRTE) and intensity difference (ID). The RF model, based on these features, demonstrated an excellent discriminative ability for PCa with a mean area under the curve (AUC) of 0.896. Additionally, another model incorporating free prostate-specific antigen (FPSA) and color Doppler flow imaging (CDFI) achieved a high accuracy in predicting HGPCa with a mean AUC of 0.830. The nomogram derived from these models exhibited excellent individualized prediction of PCa and HGPCa.

CONCLUSION

The RF models incorporating mpUS and serological variables achieved satisfactory accuracies in predicting PCa and HGPCa.

Decoding the Influence of Obesity on Prostate Cancer and Its Transgenerational Impact

In recent decades, the escalating prevalence of metabolic disorders, notably obesity and being overweight, has emerged as a pressing concern in public health. Projections for the future indicate a continual upward trajectory in obesity rates, primarily attributable to unhealthy dietary patterns and sedentary lifestyles. The ramifications of obesity extend beyond its visible manifestations, intricately weaving a web of hormonal dysregulation, chronic inflammation, and oxidative stress. This nexus of factors holds particular significance in the context of carcinogenesis, notably in the case of prostate cancer (PCa), which is a pervasive malignancy and a leading cause of mortality among men. A compelling hypothesis arises from the perspective of transgenerational inheritance, wherein genetic and epigenetic imprints associated with obesity may wield influence over the development of PCa. This review proposes a comprehensive exploration of the nuanced mechanisms through which obesity disrupts prostate homeostasis and serves as a catalyst for PCa initiation. Additionally, it delves into the intriguing interplay between the transgenerational transmission of both obesity-related traits and the predisposition to PCa. Drawing insights from a spectrum of sources, ranging from in vitro and animal model research to human studies, this review endeavors to discuss the intricate connections between obesity and PCa. However, the landscape remains partially obscured as the current state of knowledge unveils only fragments of the complex mechanisms linking these phenomena. As research advances, unraveling the associated factors and underlying mechanisms promises to unveil novel avenues for understanding and potentially mitigating the nexus between obesity and the development of PCa.

Cancer Associated Macrophage-like Cells Are Prognostic for Highly Aggressive Prostate Cancer in Both the Non-Metastatic and Metastatic Settings

Despite advancements in the early-stage detection and expansion of treatments for prostate cancer (PCa), patient mortality rates remain high in patients with aggressive disease and the overtreatment of indolent disease remains a major issue. Prostate-specific antigen (PSA), a standard PCa blood biomarker, is limited in its ability to differentiate disease subtypes resulting in the overtreatment of non-aggressive indolent disease. Here we assess engorged cancer-associated macrophage-like cells (CAMLs), a ≥50 µm, cancer-specific, polynucleated circulating cell type found in the blood of patients with PCa as a potential companion biomarker to PSA for patient risk stratification. We found that rising PSA is positively correlated with increasing CAML size (r = 0.307, p = 0.004) and number of CAMLs in circulation (r = 0.399, p < 0.001). Over a 2-year period, the presence of a single engorged CAML was associated with 20.9 times increased likelihood of progression (p = 0.016) in non-metastatic PCa, and 2.4 times likelihood of progression (p = 0.031) with 5.4 times likelihood of death (p < 0.001) in metastatic PCa. These preliminary data suggest that CAML cell monitoring, in combination with PSA, may aid in differentiating non-aggressive from aggressive PCas by adding biological information that complements traditional clinical biomarkers, thereby helping guide treatment strategies.

A sensitive label-free biosensor based on Ag2S-sensitived Bi2WO6/BiOBr heterojunction for photoelectrochemical immunoassay of prostate specific antigen

Prostate cancer is one of the most common cancers in the world, and its early diagnosis can effectively reduce mortality. A new label-free photoelectrochemical (PEC) immunosensor on the basis of Bi₂WO₆/BiOBr nanocomposite materials has been successfully prepared for the test of prostate-specific antigen (PSA) in human serum in this work. The Ag₂S-sensitized Bi₂WO₆/BiOBr heterojunction was used as a photosensitive material, which effectively improved the photocurrent response. On Bi₂WO₆/BiOBr surface, dopamine immobilized PSA antibody by self-polymerizing to form polydopamine membrane. Antigen and antibody are specifically combined to achieve quantitative detection of PSA according to the current changes at different concentrations of antigen. Under the optimal experimental conditions, the PEC immunosensor has an ideal linear relationship between 1 pg/mL - 50 ng/mL, and the detection limit is 0.084 pg/mL. In addition, the prepared immunosensor has good stability, reproducibility and selectivity, providing a new method for the detection of PSA in actual sample analysis.

Aberrant protein glycosylation: Implications on diagnosis and Immunotherapy

Glycosylation-mediated post-translational modification is critical for regulating many fundamental processes like cell division, differentiation, immune response, and cell-to-cell interaction. Alterations in the N-linked or O-linked glycosylation pattern of regulatory proteins like transcription factors or cellular receptors lead to many diseases, including cancer. These alterations give rise to micro- and macro-heterogeneity in tumor cells. Here, we review the role of O- and N-linked glycosylation and its regulatory function in autoimmunity and aberrant glycosylation in cancer. The change in cellular glycome could result from a change in the expression of glycosidases or glycosyltransferases like N-acetyl-glucosaminyl transferase V, FUT8, ST6Gal-I, DPAGT1, etc., impact the glycosylation of target proteins leading to transformation. Moreover, the mutations in glycogenes affect glycosylation patterns on immune cells leading to other related manifestations like pro- or anti-inflammatory effects. In recent years, understanding the glycome to cancer indicates that it can be utilized for both diagnosis/prognosis as well as immunotherapy. Studies involving mass spectrometry of proteome, site- and structure-specific glycoproteomics, or transcriptomics/genomics of patient samples and cancer models revealed the importance of glycosylation homeostasis in cancer biology. The development of emerging technologies, such as the lectin microarray, has facilitated research on the structure and function of glycans and glycosylation. Newly developed devices allow for high-throughput, high-speed, and precise research on aberrant glycosylation. This paper also discusses emerging technologies and clinical applications of glycosylation.

Immune-checkpoint inhibitor therapy response evaluation using oncophysics-based mathematical models

The field of oncology has transformed with the advent of immunotherapies. The standard of care for multiple cancers now includes novel drugs that target key checkpoints that function to modulate immune responses, enabling the patient's immune system to elicit an effective anti-tumor response. While these immune-based approaches can have dramatic effects in terms of significantly reducing tumor burden and prolonging survival for patients, the therapeutic approach remains active only in a minority of patients and is often not durable. Multiple biological investigations have identified key markers that predict response to the most common form of immunotherapy-immune checkpoint inhibitors (ICI). These biomarkers help enrich patients for ICI but are not 100% predictive. Understanding the complex interactions of these biomarkers with other pathways and factors that lead to ICI resistance remains a major goal. Principles of oncophysics-the idea that cancer can be described as a multiscale physical aberration-have shown promise in recent years in terms of capturing the essence of the complexities of ICI interactions. Here, we review the biological knowledge of mechanisms of ICI action and how these are incorporated into modern oncophysics-based mathematical models. Building on the success of oncophysics-based mathematical models may help to discover new, rational methods to engineer immunotherapy for patients in the future. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

A tissue miRNA expression pattern is associated with disease aggressiveness of localized prostate cancer

BACKGROUND

Prostate cancer (PCa) is a heterogeneous malignancy with high variability in clinical course. Insufficient stratification according to the aggressiveness at the time of diagnosis causes unnecessary or delayed treatment. Current stratification systems are not effective enough because they are based on clinical, surgical or biochemical parameters, but do not take into account molecular factors driving PCa cancerogenesis. MicroRNAs (miRNAs) are important players in molecular pathogenesis of PCa and could serve as valuable biomarkers for the assessment of disease aggressiveness and its prognosis.

METHODS

In the study, in total, 280 PCa patients were enrolled. The miRNA expression profiles were analyzed in FFPE PCa tissue using the miRCURY LNA miRNA PCR System. The expression levels of candidate miRNAs were further verified by two-level validation using the RT-qPCR method and evaluated in relation to PCa stratification reflecting the disease aggressiveness.

RESULTS

MiRNA profiling revealed 172 miRNAs dysregulated between aggressive (ISUP 3-5) and indolent PCa (ISUP 1) (p < 0.05). In the training and validation cohort, miR-15b-5p and miR-106b-5p were confirmed to be significantly upregulated in tissue of aggressive PCa when their level was associated with disease aggressiveness. Furthermore, we established a prognostic score combining the level of miR-15b-5p and miR-106b-5p with serum PSA level, which discriminated indolent PCa from an aggressive form with even higher analytical parameters (AUC being 0.9338 in the training set and 0.8014 in the validation set, respectively). The score was also associated with 5-year biochemical progression-free survival (bPFS) of PCa patients.

CONCLUSIONS

We identified a miRNA expression pattern associated with disease aggressiveness in prostate cancer patients. These miRNAs may be of biological interest as the focus can be also set on their specific role within the molecular pathology and the molecular mechanism that underlies the aggressivity of prostate cancer.

Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis: a cohort study in the UK Biobank

BACKGROUND

Prostate cancer is highly heritable, with >250 common variants associated in genome-wide association studies. It commonly presents with non-specific lower urinary tract symptoms that are frequently associated with benign conditions.

METHODS

Cohort study using UK Biobank data linked to primary care records. Participants were men with a record showing a general practice consultation for a lower urinary tract symptom. The outcome measure was prostate cancer diagnosis within 2 years of consultation. The predictor was a genetic risk score of 269 genetic variants for prostate cancer.

RESULTS

A genetic risk score (GRS) is associated with prostate cancer in symptomatic men (OR per SD increase = 2.12 [1.86-2.41] P = 3.5e-30). An integrated risk model including age and GRS applied to symptomatic men predicted prostate cancer (AUC 0.768 [0.739-0.796]). Prostate cancer incidence was 8.1% (6.7-9.7) in the highest risk quintile. In the lowest quintile, prostate cancer incidence was <1%.

CONCLUSIONS

This study is the first to apply GRS in primary care to improve the triage of symptomatic patients. Men with the lowest genetic risk of developing prostate cancer could safely avoid invasive investigation, whilst those identified with the greatest risk could be fast-tracked for further investigation. These results show that a GRS has potential application to improve the diagnostic pathway of symptomatic patients in primary care.

Volatilomics: An Emerging and Promising Avenue for the Detection of Potential Prostate Cancer Biomarkers

Simple Summary

The lack of highly specific and sensitive biomarkers for the early detection of prostate cancer (PCa) is a major barrier to its management. Volatilomics emerged as a non-invasive, simple, inexpensive, and easy-to-use approach for cancer screening, characterization of disease progression, and follow-up of the treatment’s success. We provide a brief overview of the potential of volatile organic metabolites (VOMs) for the establishment of PCa biomarkers from non-invasive matrices. Endogenous VOMs have been investigated as potential biomarkers since changes in these VOMs can be characteristic of specific disease processes. Recent studies have shown that the conjugation of the prostate-specific antigen (PSA) screening with other methodologies, such as risk calculators, biomarkers, and imaging tests, can attenuate overdiagnosis and under-detection issues. This means that the combination of volatilomics with other methodologies could be extremely valuable for the differentiation of clinical phenotypes in a group of patients, providing more personalized treatments.

Abstract

Despite the spectacular advances in molecular medicine, including genomics, proteomics, transcriptomics, lipidomics, and personalized medicine, supported by the discovery of the human genome, prostate cancer (PCa) remains the most frequent malignant tumor and a leading cause of oncological death in men. New methods for prognostic, diagnostic, and therapy evaluation are mainly based on the combination of imaging techniques with other methodologies, such as gene or protein profiling, aimed at improving PCa management and surveillance. However, the lack of highly specific and sensitive biomarkers for its early detection is a major hurdle to this goal. Apart from classical biomarkers, the study of endogenous volatile organic metabolites (VOMs) biosynthesized by different metabolic pathways and found in several biofluids is emerging as an innovative, efficient, accessible, and non-invasive approach to establish the volatilomic biosignature of PCa patients, unravelling potential biomarkers. This review provides a brief overview of the challenges of PCa screening methods and emergent biomarkers. We also focus on the potential of volatilomics for the establishment of PCa biomarkers from non-invasive matrices.

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

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

Alpha-1-antichymotrypsin as a novel biomarker for diagnosis, prognosis, and therapy prediction in human diseases

The glycoprotein alpha-1-antichymotrypsin (AACT), a serine protease inhibitor, is mainly synthesized in the liver and then secreted into the blood and is involved in the acute phase response, inflammation, and proteolysis. The dysregulation of AACT and its glycosylation levels are associated with tumor progression and recurrence, and could be used as a biomarker for tumor monitoring. In this review, we summarized the expression level, glycosylation modification, and biological characteristics of AACT during inflammation, neurodegenerative or other elderly diseases, and tumorigenesis, as well as, focused on the biological roles of AACT in cancer. The aberrant expression of AACT in cancer might be due to genetic alterations and/or immune by bioinformatics analysis. Moreover, AACT may serve as a diagnostic or prognostic biomarker or therapeutic target in tumors. Furthermore, we found that the expression of AACT was associated with the overall survival of patients with human cancers. Decreased AACT expression was associated with poor survival in patients with liver cancer, increased AACT expression was associated with shorter survival in patients with pancreatic cancer, and decreased AACT expression was associated with shorter survival in patients with early lung cancer. The review confirmed the key roles of AACT in tumorigenesis, suggesting that the glycoprotein AACT may serve as a biomarker for tumor diagnosis and prognosis, and could be a potential therapeutic target for human diseases.

Induction of IDO1 and Kynurenine by Serine Proteases Subtilisin, Prostate Specific Antigen, CD26 and HtrA: A New Form of Immunosuppression?

Several serine proteases have been linked to autoimmune disorders and tumour initiation although the mechanisms are not fully understood. Activation of the kynurenine pathway enzyme indoleamine-2,3-dioxygenase (IDO1) modulates cellular activity in the brain, tolerogenesis in the immune system and is a major checkpoint in cancer development. We now report that IDO1 mRNA and IDO1 protein expression (generating kynurenine) are induced in human monocyte-derived macrophages by several chymotryptic serine proteases with direct links to tumorigenesis, including Prostate Specific Antigen (PSA), CD26 (Dipeptidyl-peptidase-4, CD26/DPP-4), High Temperature Requirement protein-A (HtrA), and the bacterial virulence factor subtilisin. These proteases also induce expression of the pro-inflammatory cytokine genes IL1B and IL6. Other serine proteases tested: bacterial glu-C endopeptidase and mammalian Pro-protein Convertase Subtilase-Kexin-3 (PCSK3, furin), urokinase plasminogen activator (uPA), cathepsin G or neutrophil elastase, did not induce IDO1, indicating that the reported effects are not a general property of all serine proteases. The results represent a novel mechanism of activating immunosuppressive IDO1 and inducing kynurenine generation which, together with the production of inflammatory cytokines, would contribute to tumour initiation and progression, providing a new target for drug development. In addition, the proteasomal S20 serine protease inhibitor carfilzomib, used in the treatment of myeloma, prevented the induction of IDO1 and cytokine gene expression, potentially contributing to its clinical anti-cancer activity.

Current advances in prognostic and diagnostic biomarkers for solid cancers: Detection techniques and future challenges

Solid cancers are one of the leading causes of cancer related deaths, characterized by rapid growth of tumour, and local and distant metastases. Current advances on multimodality care have substantially improved local control and metastasis-free survival of patients by resection of primary tumour. The major concern in disease prognosis is the timely detection of resectable or metastatic tumour, thus reinforcing the need for identification of biomarkers for premalignant lesions of solid cancer. This ultimately improves the outcome for the patients. Therefore, the purpose of this review is to update the recent advancements on prognostic and diagnostic biomarkers to enhance early detection of common solid cancers including, breast, lung, colorectal, prostate and stomach cancer. We also provide an insight into Food and Drug Administration (FDA)-approved solid cancers biomarkers; various conventional techniques used for detection of prognostic and diagnostic biomarkers and discuss approaches to turn challenges in this field into opportunities.

Identification of the metabolic signatures of prostate cancer by mass spectrometry-based plasma and urine metabolomics analysis

OBJECTIVE

Prostate cancer (PCa) is one of the most commonly diagnosed cancers among men which is associated with profound metabolic changes. Systematic analysis of the metabolic alterations and identification of new biomarkers may benefit PCa diagnosis and a deep understanding of the pathological mechanism. The purpose of this study was to determine the metabolic features of PCa.

METHODS

Plasma and urine metabolites from 89 prostate cancer (PCa) patients, 84 benign prostatic hyperplasia (BPH) patients, and 70 healthy males were analyzed using LC-MS/MS and GC-MS. The Orthogonalised Partial Least Squares Discriminant Analysis (OPLS-DA) was used to find the significantly changed metabolites. The clinical value of the candidate markers was examined by receiver operating characteristic curve analysis and compared with prostate-specific antigen (PSA).

RESULTS

Multivariate statistical analyses found a series of altered metabolites, which related to the urea cycle, tricarboxylic acid cycle (TCA), fatty acid metabolism, and the glycine cleavage system. Plasma Glu/Gln showed the highest predictive value (AUC = 0.984) when differentiating PCa patients from healthy controls, with a higher sensitivity than PSA (96.6% vs. 94.4%). Both Glu/Gln and PSA displayed a low specificity when differentiating PCa patients from BPH patients (<53.2%), while the combination of Glu/Gln and PSA can further increase the diagnostic specificity to 66.9%.

CONCLUSIONS

The present study showed the metabolic features of PCa, provided strong evidence that the amide nitrogen and the energy metabolic pathways could be a valuable source of markers for PCa. Several candidate markers identified in this study were clinically valuable for further assessment.

A novel affinity peptide-antibody sandwich electrochemical biosensor for PSA based on the signal amplification of MnO2-functionalized covalent organic framework

This work describes a novel affinity peptide-antibody sandwich electrochemical strategy for the ultrasensitive detection of prostate-specific antigen (PSA). Herein, polydopamine-coated boron-doped carbon nitride (Au@PDA@BCN) was synthesized and used as a sensing platform to anchor gold nanoparticles and immobilize primary antibody. Meanwhile, AuPt metallic nanoparticle and manganese dioxide (MnO₂)-functionalized covalent organic frameworks (AuPt@MnO₂@COF) was facilely synthesized to serve as a nanocatalyst and ordered nanopore for the enrichment and amplification of signal molecules (methylene blue, MB). PSA affinity peptide was bound to AuPt@MnO₂@COF to form Pep/MB/AuPt@MnO₂@COF nanocomposites (probe). The peptide-PSA-antibody sandwich biosensor was constructed, and the redox signal of MB was measured with the existence of PSA. The fabricated sensor exhibited a linear response (0.00005-10 ng mL^-1) with a low detection limit of 16.7 fg mL^-1 under the optimum condition. Additionally, the sensor showed an excellent selectivity, ideal repeatability, and good stability for PSA detection in real samples. Furthermore, the porous structure of COF can enrich more MB molecules and increase the sensitivity of the biosensor. This study provides an efficient and ultrasensitive strategy for PSA detection and broadens the use of organic/inorganic porous nanocomposite in biosensing.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

The role of the voltage-gated potassium channel, Kv2.1 in prostate cancer cell migration

Voltage-gated potassium (Kv) channels are involved in many important cellular functions and play pivotal roles in cancer progression. The expression level of Kv2.1 was observed to be higher in the highly metastatic prostate cancer cells (PC-3), specifically in their membrane, than in immortalized prostate cells (WPMY-1 cells) and comparatively less metastatic prostate cancer cells (LNCaP and DU145 cells). However, Kv2.1 expression was significantly decreased when the cells were treated with anti-oxidants, such as N-acetylcysteine or ascorbic acid, implying that the highly expressed Kv2.1 could detect reactive oxygen species (ROS) in malignant prostate cancer cells. In addition, the blockade of Kv2.1 with stromatoxin-1 or siRNA targeting Kv2.1 significantly inhibited the migration of malignant prostate cancer cells. Our results suggested that Kv2.1 plays an important role as a ROS sensor and that it is a promising therapeutic molecular target in metastasis of prostate cancer.

Altered glycosylation in cancer: A promising target for biomarkers and therapeutics

Glycosylation is a well-regulated cell and microenvironment specific post-translational modification. Several glycosyltransferases and glycosidases orchestrate the addition of defined glycan structures on the proteins and lipids. Recent advances and systemic approaches in glycomics have significantly contributed to a better understanding of instrumental roles of glycans in health and diseases. Emerging research evidence recognized aberrantly glycosylated proteins as the modulators of the malignant phenotype of cancer cells. The Cancer Genome Atlas has identified alterations in the expressions of glycosylation-specific genes that are correlated with cancer progression. However, the mechanistic basis remains poorly explored. Recent researches have shown that specific changes in the glycan structures are associated with 'stemness' and epithelial-to-mesenchymal transition of cancer cells. Moreover, epigenetic changes in the glycosylation pattern make the tumor cells capable of escaping immunosurveillance mechanisms. The deciphering roles of glycans in cancer emphasize that glycans can serve as a source for the development of novel clinical biomarkers. The ability of glycans in intervening various stages of tumor progression and the biosynthetic pathways involved in glycan structures constitute a promising target for cancer therapy. Advances in the knowledge of innovative strategies for identifying the mechanisms of glycan-binding proteins are hoped to hold great potential in cancer therapy. This review discusses the fundamental role of glycans in regulating tumorigenesis and tumor progression and provides insights into the influence of glycans in the current tactics of targeted therapies in the clinical setting.

Modern biomarkers in prostate cancer diagnosis

INTRODUCTION

The most common malignant neoplasm of the urinary tract is prostate cancer (PCa), which is a heterogeneous disease, ranging from very slowly developing and slightly benign to progressing, aggressive, metastatic and fatal, even when properly treated. Existing, imperfect diagnostic methods often lead to over-diagnosis and over-treatment of PCa. That is why new, better PCa biomarkers are being developed.

MATERIAL AND METHODS

This review summarizes the current results of the most promising and clinically used PCa biomarkers, as well as having the potential to create new diagnostic and prognostic tools, based on the Web of Science (www.apps.webofknowledge.com) and Scopus (www.scopus) databases. com).

RESULTS

Limited specificity of the prostate-specific antigen (PSA) test brings a need to develop new and better diagnostic tools. In the last few years, new approaches for providing significantly better biomarkers, an alternative to PSA, have been introduced. Modern biomarkers show improvement in being used as not only a diagnostic procedure, but also for staging, evaluating aggressiveness and managing the therapeutic process. We describe the methods recommended in the diagnosis of PCa and new PCa molecular diagnostics technologies. Individual biomarkers are used in various stages of the PCa diagnostic process, which was presented on the developed diagnostic flowchart describing the role of biomarkers in prostate cancer management.

CONCLUSIONS

Given the diverse nature of PCa, one diagnostic test will not answer all questions, so the use of several diagnostic methods will allow physicians to provide patients with better, personalized clinical advice.