Innovative Diagnostic Methods for Early Prostate Cancer Detection through Urine Analysis: A Review

Cellulose nanofibers/polyacrylic acid hydrogels integrated with a 3D printed strip: A platform for screening prostate cancer via sarcosine detection

Cellulose nanofiber/polyacrylic acid (CNF/PAA) hydrogel-based colorimetric sensor was fabricated for non-invasive screening of prostate cancer (PCa) via selective detection of sarcosine. The hydrogel was synthesized by photo-crosslinking of acrylic acid in the presence of CNF which acted as mechanical reinforcement and as color enhancer. The hydrogel exhibited a high aqueous absorption and high mechanical strength. A homogeneous distribution of CNF in the hydrogel was confirmed by TEM. A significant improvement in the compressive modulus and stress in the hydrogel were obtained after the incorporation of 0.25%wt CNF. The hydrogel sensor was integrated within a 3D printing strip on a diaper, and it offered a vivid color change from light yellow to blue for detecting sarcosine for PCa indication with a detection limit starting from 10 μM. The colorimetric results were semi-quantitatively evaluated by a spectrophotometer offering a linear range of 0-100 μM with R2 of 0.9901. Furthermore, the increase in CNF content significantly enhanced the sensor's sensitivity toward sarcosine. This sensor could open new avenues for non-invasive screening of prostate cancer in the future.

Volatile Organic Metabolites as Potential Biomarkers for Genitourinary Cancers: Review of the Applications and Detection Methods

Cancer is one of the leading causes of death globally, and is ranked second in the United States. Early detection is crucial for more effective treatment and a higher chance of survival rates, reducing burdens on individuals and societies. Genitourinary cancers, in particular, face significant challenges in early detection. Finding new and cost-effective diagnostic methods is of clinical need. Metabolomic-based approaches, notably volatile organic compound (VOC) analysis, have shown promise in detecting cancer. VOCs are small organic metabolites involved in biological processes and disease development. They can be detected in urine, breath, and blood samples, making them potential candidates for sensitive and non-invasive alternatives for early cancer detection. However, developing robust VOC detection methods remains a hurdle. This review outlines the current landscape of major genitourinary cancers (kidney, prostate, bladder, and testicular), including epidemiology, risk factors, and current diagnostic tools. Furthermore, it explores the applications of using VOCs as cancer biomarkers, various analytical techniques, and comparisons of extraction and detection methods across different biospecimens. The potential use of VOCs in detection, monitoring disease progression, and treatment responses in the field of genitourinary oncology is examined.

SynNotch-Programmed Macrophages for Cancerous Cell Detection and Sensing

Synthetic Notch (synNotch) receptors have enabled mammalian cells to sense extracellular ligands and respond by activating user-prescribed transcriptional programs. Based on the synNotch system, we describe a cell-based in vivo sensor for cancerous cell detection. We attempted to engineer synNotch-programmed macrophages to sense cancer cells via urinary analysis of human chorionic gonadotropin (HCGB5). Principally, when the synNotch receptors of macrophages bind to the ligands of cancer cells, Notch is activated and undergoes intramembrane proteolysis to release the transcriptional activator into the nucleus. The transcriptional activator targets and activates downstream gene expression, such as human chorionic gonadotropin (HCGB5) in macrophages. When HCGB5 is secreted extracellularly into urine, it can be detected with commercial HCGB5 colloidal gold test strips. As a proof of principle, we demonstrated the feasibility of synNotch-programmed macrophages in detecting breast cancer cells engineered with artificial EGFP ligands. We demonstrated that HCGB5 expression was only induced when the cancer cell expressing EGFP ligands is present; thereby, extracellular HCGB5 expression is directly proportional to the number of cancer cells. Further optimizations of the synNotch system can realize the ultimate goal of establishing cell-based in vivo sensors as the paragon of cancer diagnostics for point-of-care testing and home self-test.

Detection and Validation of Organic Metabolites in Urine for Clear Cell Renal Cell Carcinoma Diagnosis

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) comprises the majority, approximately 70-80%, of renal cancer cases and often remains asymptomatic until incidentally detected during unrelated abdominal imaging or at advanced stages. Currently, standardized screening tests for renal cancer are lacking, which presents challenges in disease management and improving patient outcomes. This study aimed to identify ccRCC-specific volatile organic compounds (VOCs) in the urine of ccRCC-positive patients and develop a urinary VOC-based diagnostic model.

METHODS

This study involved 233 pretreatment ccRCC patients and 43 healthy individuals. VOC analysis utilized stir-bar sorptive extraction coupled with thermal desorption gas chromatography/mass spectrometry (SBSE-TD-GC/MS). A ccRCC diagnostic model was established via logistic regression, trained on 163 ccRCC cases versus 31 controls, and validated with 70 ccRCC cases versus 12 controls, resulting in a ccRCC diagnostic model involving 24 VOC markers.

RESULTS

The findings demonstrated promising diagnostic efficacy, with an Area Under the Curve (AUC) of 0.94, 86% sensitivity, and 92% specificity.

CONCLUSIONS

This study highlights the feasibility of using urine as a reliable biospecimen for identifying VOC biomarkers in ccRCC. While further validation in larger cohorts is necessary, this study's capability to differentiate between ccRCC and control groups, despite sample size limitations, holds significant promise.

Overcoming the Limits of Cross-Sensitivity: Pattern Recognition Methods for Chemiresistive Gas Sensor Array

As information acquisition terminals for artificial olfaction, chemiresistive gas sensors are often troubled by their cross-sensitivity, and reducing their cross-response to ambient gases has always been a difficult and important point in the gas sensing area. Pattern recognition based on sensor array is the most conspicuous way to overcome the cross-sensitivity of gas sensors. It is crucial to choose an appropriate pattern recognition method for enhancing data analysis, reducing errors and improving system reliability, obtaining better classification or gas concentration prediction results. In this review, we analyze the sensing mechanism of cross-sensitivity for chemiresistive gas sensors. We further examine the types, working principles, characteristics, and applicable gas detection range of pattern recognition algorithms utilized in gas-sensing arrays. Additionally, we report, summarize, and evaluate the outstanding and novel advancements in pattern recognition methods for gas identification. At the same time, this work showcases the recent advancements in utilizing these methods for gas identification, particularly within three crucial domains: ensuring food safety, monitoring the environment, and aiding in medical diagnosis. In conclusion, this study anticipates future research prospects by considering the existing landscape and challenges. It is hoped that this work will make a positive contribution towards mitigating cross-sensitivity in gas-sensitive devices and offer valuable insights for algorithm selection in gas recognition applications.

Investigating the effects of storage conditions on urinary volatilomes for their reliability in disease diagnosis

BACKGROUND

Cancer detection presents challenges regarding invasiveness, cost, and reliability. As a result, exploring alternative diagnostic methods holds significant clinical importance. Urinary metabolomic profiling has emerged as a promising avenue; however, its application for cancer diagnosis may be influenced by sample preparation or storage conditions.

OBJECTIVE

This study aimed to assess the impact of sample storage and processing conditions on urinary volatile organic compounds (VOCs) profiles and establish a robust standard operating procedure (SOP) for such diagnostic applications.

METHODS

Five key variables were investigated: storage temperatures, durations, freeze-thaw cycles, sample collection conditions, and sample amounts. The analysis of VOCs involved stir bar sorptive extraction coupled with thermal desorption-gas chromatography/mass spectrometry (SBSE-TD-GC-MS), with compound identification facilitated by the National Institute of Standards and Technology Library (NIST). Extensive statistical analysis, including combined scatterplot and response surface (CSRS) plots, partial least squares-discriminant analysis (PLS-DA), and probability density function plots (PDFs), were employed to study the effects of the factors.

RESULTS

Our findings revealed that urine storage duration, sample amount, temperature, and fasting/non-fasting sample collection did not significantly impact urinary metabolite profiles. This suggests flexibility in urine sample collection conditions, enabling individuals to contribute samples under varying circumstances. However, the influence of freeze-thaw cycles was evident, as VOC profiles exhibited distinct clustering patterns based on the number of cycles. This emphasizes the effect of freeze-thaw cycles on the integrity of urinary profiles.

CONCLUSIONS

The developed SOP integrating SBSE-TD-GC-MS and statistical analyses can serve as a valuable tool for analyzing urinary organic compounds with minimal preparation and sensitive detection. The findings also support that urinary VOCs for cancer screening and diagnosis could be a feasible alternative offering a robust, non-invasive, and sensitive approach for cancer screening.

Advancing Healthcare: Synergizing Biosensors and Machine Learning for Early Cancer Diagnosis

Cancer is a fatal disease and a significant cause of millions of deaths. Traditional methods for cancer detection often have limitations in identifying the disease in its early stages, and they can be expensive and time-consuming. Since cancer typically lacks symptoms and is often only detected at advanced stages, it is crucial to use affordable technologies that can provide quick results at the point of care for early diagnosis. Biosensors that target specific biomarkers associated with different types of cancer offer an alternative diagnostic approach at the point of care. Recent advancements in manufacturing and design technologies have enabled the miniaturization and cost reduction of point-of-care devices, making them practical for diagnosing various cancer diseases. Furthermore, machine learning (ML) algorithms have been employed to analyze sensor data and extract valuable information through the use of statistical techniques. In this review paper, we provide details on how various machine learning algorithms contribute to the ongoing development of advanced data processing techniques for biosensors, which are continually emerging. We also provide information on the various technologies used in point-of-care cancer diagnostic biosensors, along with a comparison of the performance of different ML algorithms and sensing modalities in terms of classification accuracy.

Early Detection of Prostate Cancer: The Role of Scent

Prostate cancer (PCa) represents the cause of the second highest number of cancer-related deaths worldwide, and its clinical presentation can range from slow-growing to rapidly spreading metastatic disease. As the characteristics of most cases of PCa remains incompletely understood, it is crucial to identify new biomarkers that can aid in early detection. Despite the prostate-specific antigen serum (PSA) levels, prostate biopsy, and imaging representing the actual gold-standard for diagnosing PCa, analyzing volatile organic compounds (VOCs) has emerged as a promising new frontier. We and other authors have reported that highly trained dogs can recognize specific VOCs associated with PCa with high accuracy. However, using dogs in clinical practice has several limitations. To exploit the potential of VOCs, an electronic nose (eNose) that mimics the dog olfactory system and can potentially be used in clinical practice was designed. To explore the eNose as an alternative to dogs in diagnosing PCa, we conducted a systematic literature review and meta-analysis of available studies. PRISMA guidelines were used for the identification, screening, eligibility, and selection process. We included six studies that employed trained dogs and found that the pooled diagnostic sensitivity was 0.87 (95% CI 0.86–0.89; I2, 98.6%), the diagnostic specificity was 0.83 (95% CI 0.80–0.85; I2, 98.1%), and the area under the summary receiver operating characteristic curve (sROC) was 0.64 (standard error, 0.25). We also analyzed five studies that used an eNose to diagnose PCa and found that the pooled diagnostic sensitivity was 0.84 (95% CI, 0.80–0.88; I2, 57.1%), the diagnostic specificity was 0.88 (95% CI, 0.84–0.91; I2, 66%), and the area under the sROC was 0.93 (standard error, 0.03). These pooled results suggest that while highly trained dogs have the potentiality to diagnose PCa, the ability is primarily related to olfactory physiology and training methodology. The adoption of advanced analytical techniques, such as eNose, poses a significant challenge in the field of clinical practice due to their growing effectiveness. Nevertheless, the presence of limitations and the requirement for meticulous study design continue to present challenges when employing eNoses for the diagnosis of PCa.

Differences in the Volatilomic Urinary Biosignature of Prostate Cancer Patients as a Feasibility Study for the Detection of Potential Biomarkers

Prostate cancer (PCa) continues to be the second most common malignant tumour and the main cause of oncological death in men. Investigating endogenous volatile organic metabolites (VOMs) produced by various metabolic pathways is emerging as a novel, effective, and non-invasive source of information to establish the volatilomic biosignature of PCa. In this study, headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GC-MS) was used to establish the urine volatilomic profile of PCa and identify VOMs that can discriminate between the two investigated groups. This non-invasive approach was applied to oncological patients (PCa group, n = 26) and cancer-free individuals (control group, n = 30), retrieving a total of 147 VOMs from various chemical families. This included terpenes, norisoprenoid, sesquiterpenes, phenolic, sulphur and furanic compounds, ketones, alcohols, esters, aldehydes, carboxylic acid, benzene and naphthalene derivatives, hydrocarbons, and heterocyclic hydrocarbons. The data matrix was subjected to multivariate analysis, namely partial least-squares discriminant analysis (PLS-DA). Accordingly, this analysis showed that the group under study presented different volatomic profiles and suggested potential PCa biomarkers. Nevertheless, a larger cohort of samples is required to boost the predictability and accuracy of the statistical models developed.

Has the Landscape of Immunotherapy for Prostate Cancer Changed? A Systematic Review and Post Hoc Analysis

Prostate cancer (PCa) is the second leading cause of cancer-causing death in the United States. As the most common malignancy in men, it is pertinent to explore whether novel immunotherapies may improve the quality of life and overall survival (OS) of patient populations. This systematic review and post hoc analysis curates a patient-by-patient pool of evidence adhering to PRISMA Statement 2020 guidelines. In total, 24 patients were analyzed for treatment history and associated variables including prostate-specific antigen (PSA) levels at diagnosis and post-treatment, Gleason score, secondary tumor locations, success/failure of therapy, and post-immunotherapy outcomes including OS. In total, 10 types of immunotherapies were identified with Pembrolizumab (among 8 patients) followed by IMM-101 (among 6 patients) being the most commonly administered. The mean OS for all patients was 27.8 months (24 patients) with the relatively highest mean OS reported with IMM-101 (56 months) followed by tumor-infiltrating lymphocytes (30 months). This research article provides critical insights into the evolving landscape of immunotherapies being tested for PCa and addresses gaps in oncological research to advance the understanding of PCa.

Underlying Features of Prostate Cancer-Statistics, Risk Factors, and Emerging Methods for Its Diagnosis

Prostate cancer (PCa) is the most frequently occurring type of malignant tumor and a leading cause of oncological death in men. PCa is very heterogeneous in terms of grade, phenotypes, and genetics, displaying complex features. This tumor often has indolent growth, not compromising the patient's quality of life, while its more aggressive forms can manifest rapid growth with progression to adjacent organs and spread to lymph nodes and bones. Nevertheless, the overtreatment of PCa patients leads to important physical, mental, and economic burdens, which can be avoided with careful monitoring. Early detection, even in the cases of locally advanced and metastatic tumors, provides a higher chance of cure, and patients can thus go through less aggressive treatments with fewer side effects. Furthermore, it is important to offer knowledge about how modifiable risk factors can be an effective method for reducing cancer risk. Innovations in PCa diagnostics and therapy are still required to overcome some of the limitations of the current screening techniques, in terms of specificity and sensitivity. In this context, this review provides a brief overview of PCa statistics, reporting its incidence and mortality rates worldwide, risk factors, and emerging screening strategies.

Non-Invasive Lung Cancer Diagnostics through Metabolites in Exhaled Breath: Influence of the Disease Variability and Comorbidities

Non-invasive, simple, and fast tests for lung cancer diagnostics are one of the urgent needs for clinical practice. The work describes the results of exhaled breath analysis of 112 lung cancer patients and 120 healthy individuals using gas chromatography-mass spectrometry (GC-MS). Volatile organic compound (VOC) peak areas and their ratios were considered for data analysis. VOC profiles of patients with various histological types, tumor localization, TNM stage, and treatment status were considered. The effect of non-pulmonary comorbidities (chronic heart failure, hypertension, anemia, acute cerebrovascular accident, obesity, diabetes) on exhaled breath composition of lung cancer patients was studied for the first time. Significant correlations between some VOC peak areas and their ratios and these factors were found. Diagnostic models were created using gradient boosted decision trees (GBDT) and artificial neural network (ANN). The performance of developed models was compared. ANN model was the most accurate: 82-88% sensitivity and 80-86% specificity on the test data.

A Road Map toward Field-Effect Transistor Biosensor Technology for Early Stage Cancer Detection

Field effect transistor (FET)-based nanoelectronic biosensor devices provide a viable route for specific and sensitive detection of cancer biomarkers, which can be used for early stage cancer detection, monitoring the progress of the disease, and evaluating the effectiveness of therapies. On the road to implementation of FET-based devices in cancer diagnostics, several key issues need to be addressed: sensitivity, selectivity, operational conditions, anti-interference, reusability, reproducibility, disposability, large-scale production, and economic viability. To address these well-known issues, significant research efforts have been made recently. An overview of these efforts is provided here, highlighting the approaches and strategies presently engaged at each developmental stage, from the design and fabrication of devices to performance evaluation and data analysis. Specifically, this review discusses the multistep fabrication of FETs, choice of bioreceptors for relevant biomarkers, operational conditions, measurement configuration, and outlines strategies to improve the sensing performance and reach the level required for clinical applications. Finally, this review outlines the expected progress to the future generation of FET-based diagnostic devices and discusses their potential for detection of cancer biomarkers as well as biomarkers of other noncommunicable and communicable diseases.

Current progress of nanomedicine for prostate cancer diagnosis and treatment

Prostate cancer (PCa) is the most common new cancer case and the second most fatal malignancy in men. Surgery, endocrine therapy, radiotherapy and chemotherapy are the main clinical treatment options for PCa. However, most prostate cancers can develop into castration-resistant prostate cancer (CRPC), and due to the invasiveness of prostate cancer cells, they become resistant to different treatments and activate tumor-promoting signaling pathways, thereby inducing chemoresistance, radioresistance, ADT resistance, and immune resistance. Nanotechnology, which can combine treatment with diagnostic imaging tools, is emerging as a promising treatment modality in prostate cancer therapy. Nanoparticles can not only promote their accumulation at the pathological site through passive targeting techniques for enhanced permeability and retention (EPR), but also provide additional advantages for active targeting using different ligands. This property results in a reduced drug dose to achieve the desired effect, a longer duration of action within the tumor and fewer side effects on healthy tissues. In addition, nanotechnology can create good synergy with radiotherapy, chemotherapy, thermotherapy, photodynamic therapy and gene therapy to enhance their therapeutic effects with greater scope, and reduce the resistance of prostate cancer. In this article, we intend to review and discuss the latest technologies regarding the use of nanomaterials as therapeutic and diagnostic tools for prostate cancer.

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.

MALDI-TOF/MS Analysis of Non-Invasive Human Urine and Saliva Samples for the Identification of New Cancer Biomarkers

Cancer represents a group of heterogeneous diseases that are a leading global cause of death. Even though mortality has decreased in the past thirty years for different reasons, most patients are still diagnosed at the advanced stage, with limited therapeutic choices and poor outcomes. Moreover, the majority of cancers are detected using invasive painful methods, such as endoscopic biopsy, making the development of non-invasive or minimally invasive methods for the discovery and fast detection of specific biomarkers a crucial need. Among body fluids, a valuable non-invasive alternative to tissue biopsy, the most accessible and least invasive are undoubtedly urine and saliva. They are easily retrievable complex fluids containing a large variety of endogenous compounds that may provide information on the physiological condition of the body. The combined analysis of these fluids with matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI-TOF/MS), a reliable and easy-to-use instrumentation that provides information with relatively simple sample pretreatments, could represent the ideal option to rapidly achieve fast early stage diagnosis of tumors and their real-time monitoring. On this basis, the present review summarizes the recently reported applications relevant to the MALDI analysis of human urine and saliva samples.

Diagnostic Value of 1H NMR-Based Metabolomics in Acute Lymphoblastic Leukemia, Acute Myeloid Leukemia, and Breast Cancer

Cancer refers to a massive number of diseases distinguished by the development of abnormal cells that divide uncontrollably and have the capability of infiltration and destroying the normal body tissue. It is critical to detect biomarkers that are early detectable and noninvasive to save millions of lives. The aim of the present work is to use NMR as a noninvasive diagnostic tool for cancer diseases. This study included 30 plasma and 21 urine samples of patients diagnosed with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), 25 plasma and 17 urine samples of patients diagnosed with breast cancer (BC), and 9 plasma and urine samples obtained from healthy individuals as controls. They were prepared for NMR measurements; then, the metabolites were identified and the data were analyzed using multivariate statistical procedures. The OPLS-DA score plots clearly discriminated ALL, AML, and BC from healthy controls. Plots of the PLS-DA loadings and S-line plots showed that all metabolites in plasma were greater in BC than in the healthy controls, whereas lactate, O-acetylcarnitine, pyruvate, trimethylamine-N-oxide (TMAO), and glucose were higher in healthy controls than in ALL and AML. On the other hand, urine samples showed lower amounts of lactate, melatonin, pyruvate, and succinate in all of the studied types of cancer when compared to those of healthy controls. 1H NMR can be a successful and noninvasive tool for the diagnosis of different types of cancer.

The Effectiveness of Pelvic Floor Muscle Training in Men after Radical Prostatectomy Measured with the Insert Test

A commonly used physiotherapeutic method for the treatment of urinary incontinence (UI) after radical prostatectomy (RP) is pelvic floor muscle training (PFMT). The aim of this study was to evaluate the effectiveness of PFMT by enhanced biofeedback using the 1h pad-weighing test. The following factors were taken into consideration in the analysis of PFMT effectiveness: the relevance of the patients’ age, time from RP, BMI, mental health, functional state, and depression. A total of 60 post-RP patients who underwent 10-week PFMT were studied. They were divided into groups: A (n = 20) and B (n = 20) (random division, time from RP: 2−6 weeks) and group C (time from RP > 6 weeks). Group B had enhanced training using EMG biofeedback. UI improved in all groups: A, p = 0.0000; B, p = 0.0000; and C, p = 0.0001. After the completion of PFMT, complete control over miction was achieved by 60% of the patients in group A, 85% in group B, and 45% in group C. There was no correlation between the results of PFMT efficacy and patients’ age, BMI, time from RP, mental health, functional state, and depression. PFMT is highly effective in UI treatment. The enhancement of PFMT by EMG biofeedback seems to increase the effectiveness of the therapy.

Toilet-based continuous health monitoring using urine

Regular health monitoring can result in early detection of disease, accelerate the delivery of medical care and, therefore, considerably improve patient outcomes for countless medical conditions that affect public health. A substantial unmet need remains for technologies that can transform the status quo of reactive health care to preventive, evidence-based, person-centred care. With this goal in mind, platforms that can be easily integrated into people's daily lives and identify a range of biomarkers for health and disease are desirable. However, urine - a biological fluid that is produced in large volumes every day and can be obtained with zero pain, without affecting the daily routine of individuals, and has the most biologically rich content - is discarded into sewers on a regular basis without being processed or monitored. Toilet-based health-monitoring tools in the form of smart toilets could offer preventive home-based continuous health monitoring for early diagnosis of diseases while being connected to data servers (using the Internet of Things) to enable collection of the health status of users. In addition, machine learning methods can assist clinicians to classify, quantify and interpret collected data more rapidly and accurately than they were able to previously. Meanwhile, challenges associated with user acceptance, privacy and test frequency optimization should be considered to facilitate the acceptance of smart toilets in society.

Drift compensation on electronic nose data for non-invasive diagnosis of prostate cancer by urine analysis

Diagnostic protocol for prostate cancer (KP) is affected by poor accuracy and high false-positive rate. The most promising innovative approach is based on urine analysis by electronic noses (ENs), highlighting a specific correlation between urine alteration and KP presence. Although EN could be exploited to develop non-invasive KP diagnostic tools, no study has already introduced EN into clinical practice, most probably because of drift issues that hinder EN scaling up from research objects to large-scale diagnostic devices. This study, proposing an EN for non-invasive KP detection, describes the data processing protocol applied to a urine headspace dataset acquired over 9 months, comprising 81 patients with KP and 41 controls, for compensating the drift. It proved effective in mitigating drift on 1-year-old sensors by restoring accuracy from 55% up to 80%, achieved by new sensors not subjected to drift. The model achieved, on double-blind validation, a balanced accuracy of 76.2% (CI95% 51.9-92.3).

Extracellular Vesicle Proteome in Prostate Cancer: A Comparative Analysis of Mass Spectrometry Studies

Molecular diagnostics based on discovery research holds the promise of improving screening methods for prostate cancer (PCa). Furthermore, the congregated information prompts the question whether the urinary extracellular vesicles (uEV) proteome has been thoroughly explored, especially at the proteome level. In fact, most extracellular vesicles (EV) based biomarker studies have mainly targeted plasma or serum. Therefore, in this study, we aim to inquire about possible strategies for urinary biomarker discovery particularly focused on the proteome of urine EVs. Proteomics data deposited in the PRIDE archive were reanalyzed to target identifications of potential PCa markers. Network analysis of the markers proposed by different prostate cancer studies revealed moderate overlap. The recent throughput improvements in mass spectrometry together with the network analysis performed in this study, suggest that a larger standardized cohort may provide potential biomarkers that are able to fully characterize the heterogeneity of PCa. According to our analysis PCa studies based on urinary EV proteome presents higher protein coverage compared to plasma, plasma EV, and voided urine proteome. This together with a direct interaction of the prostate gland and urethra makes uEVs an attractive option for protein biomarker studies. In addition, urinary proteome based PCa studies must also evaluate samples from bladder and renal cancers to assess specificity for PCa.

Optimization of training and measurement protocol for eNose analysis of urine headspace aimed at prostate cancer diagnosis

More than one million new cases of prostate cancer (PCa) were reported worldwide in 2020, and a significant increase of PCa incidence up to 2040 is estimated. Despite potential treatability in early stages, PCa diagnosis is challenging because of late symptoms' onset and limits of current screening procedures. It has been now accepted that cell transformation leads to release of volatile organic compounds in biologic fluids, including urine. Thus, several studies proposed the possibility to develop new diagnostic tools based on urine analysis. Among these, electronic noses (eNoses) represent one of the most promising devices, because of their potential to provide a non-invasive diagnosis. Here we describe the approach aimed at defining the experimental protocol for eNose application for PCa diagnosis. Our research investigates effects of sample preparation and analysis on eNose responses and repeatability. The dependence of eNose diagnostic performance on urine portion analysed, techniques involved for extracting urine volatiles and conditioning temperature were analysed. 192 subjects (132 PCa patients and 60 controls) were involved. The developed experimental protocol has resulted in accuracy, sensitivity and specificity of 83% (CI95% 77-89), 82% (CI95% 73-88) and 87% (CI95% 75-94), respectively. Our findings define eNoses as valuable diagnostic tool allowing rapid and non-invasive PCa diagnosis.

Biomarkers for Gastric Cancer Screening and Early Diagnosis

Gastric cancer is one of the most common cancers worldwide, with a bad prognosis associated with late-stage diagnosis, significantly decreasing the overall survival. This highlights the importance of early detection to improve the clinical course of these patients. Although screening programs, based on endoscopic or radiologic approaches, have been useful in countries with high incidence, they are not cost-effective in low-incidence populations as a massive screening strategy. Additionally, current biomarkers used in daily routine are not specific and sensitive enough, and most of them are obtained invasively. Thus, it is imperative to discover new noninvasive biomarkers able to diagnose early-stage gastric cancer. In this context, liquid biopsy is a promising strategy. In this review, we briefly discuss some of the potential biomarkers for gastric cancer screening and diagnosis identified in blood, saliva, urine, stool, and gastric juice.

Gonadorelins adherence in prostate cancer: A time-series analysis of England's national prescriptions during the COVID-19 pandemic (from Jan 2019 to Oct 2020)

Objective

To examine the effect of the COVID‐19 pandemic on gonadorelin analogue prescription for community patients in England.

Materials and methods

We included data from all primary‐care patients who had relevant prescriptions dispensed in the community in England. Descriptive statistics and interrupted time series analysis over 22 months (15 months before and 7 months after lockdown) was evaluated.

Results

A total of 22 months’ worth of data were analyzed (or 1 041 638 total items, monthly average 47 347 items). Goserelin; leuprorelin, and triptorelin are the medicines most used by total quantity in the study period. Simple descriptive statistics show that mean values have declined during the pandemic. The Interrupted Time Series (ARIMA Modeling) shows declining trends.

After the pandemic's onset, we observe a statistically significant downward trend for goserelin (P = .017) and leuprorelin (P = .014). As these are the major constituents of the model, we interpret this overall data as showing a significant downward category trend. Aside from linearity, a significant step change was noted for leuprorelin (P = .029) showing an increase in prescription items with a similar effect that is close to being statistically significant for goserelin (P = .051).

The actual cost of medicines shows minimal variation suggesting that prices of individual medicines have remained stable. The regional data showed variation but this was not statistically significant. In all cases, the Oct‐20 figures are lower “year on year.” This novel work reports the impact of a global pandemic on prescription volumes of prostate cancer (PCa) medicines.

Conclusions

A worrying decrease in prescription medicines raises concerns for the care of PCa patients. We encourage diagnosed patients to discuss their planned care with their doctor.

LncRNA CCAT1 promotes prostate cancer cells proliferation, migration, and invasion through regulation of miR-490-3p/FRAT1 axis

Prostate cancer (PCa) is a prevalent cancer in males, with high incidence and mortality. Recent studies have shown the crucial role of long non-coding RNA (lncRNA) in PCa. Here, we aimed to explore the functional roles and inner mechanisms of lncRNA CCAT1 in PCa cells. qRT-PCR results showed that CCAT1 was upregulated in PCa tissues and cells. Functional assays demonstrated that CCAT1 knockdown suppressed cell proliferation, migration, invasion, yet promoted apoptosis, while CCAT1 promotion showed the opposite results. We also found that CCAT1 negatively regulated miR-490-3p expression and subsequently regulated FRAT1 expression. Inhibition of miR-490-3p or up-regulation of FRAT1 reversed the suppressive effects of CCAT1 knockdown on the PCa cells. In conclusion, CCAT1 regulated FRAT1 expression through miR-490-3p and then promote the PCa cells proliferation, migration, and invasion, which reveals the oncogenic function of CCAT1 in PCa progress.

Inkjet Printed ZnO Sensors for Early Prostate Cancer Detection by Means of Urine Odor Analysis

In the second half of the 20th century, inkjet printing has rapidly evolved from a mere digital image reproduction technique into a highly versatile materials deposition technology. Recently, inkjet production of metal oxide-based gas sensors (MOS) has emerged, and inkjet sensors have been proposed for different applications. In this context, this paper proposes the adoption of inkjet MOS sensors for urine analysis for the purpose of developing an innovative tool for the early prostate cancer (KP) diagnosis. Based on the results reported in the scientific literature, proving the correlation between urine color and odor alterations and cancer, the study focuses on the analysis by means of MOS sensor array of odors emanated from urine samples from prostate cancer patients versus healthy donors. The results achieved in terms of diagnostic accuracy, sensitivity, and specificity (i.e., about 80%) proved the potentialities of inkjet MOS sensor for the challenging purpose of detection of prostate cancer in its early stages. Resulting significantly more powerful than current KP diagnostic protocol, the approach here presented might become, after validation, a rapid, non-invasive and low-cost screening tool, capable to provide a solution to the problems of patients’ overtreatment and high health spending associated to procedures currently adopted.

Electrochemical Detection of Prostate Cancer Biomarker PCA3 Using Specific RNA-Based Aptamer Labelled with Ferrocene

This paper reports on a feasibility study of electrochemical in-vitro detection of prostate cancer biomarker PCA3 (prostate cancer antigen 3) in direct assay with specific RNA aptamer labelled with a redox group (ferrocene) and immobilized on a screen-printed gold electrode surface. The cyclic voltammograms and electrochemical impedance spectroscopy methods yield encouraging results on the detection of PCA3 in a range of concentrations from 1 μg/mL down to 0.1 ng/mL in buffer solutions. Both anodic and cathodic current values in cyclic voltammograms measurements and charge transfer resistance values in electrochemical impedance spectroscopy experiments correlate with the PCA3 concentration in the sample. Kinetics studies of the binding of the PCA3 to our aptamer demonstrated high specificity of the reaction with a characteristic affinity constant of approximately 4·10−10 molar. The results of this work provide a background for the future development of novel, highly sensitive and cost-effective diagnostic methodologies for prostate cancer detection.

Fluorescence photobleaching of urine for improved signal to noise ratio of the Raman signal - An exploratory study

Urine analysis is an important clinical test routinely performed in pathology labs for disease diagnosis and prognosis. In recent years, near-infrared Raman spectroscopy has drawn considerable attention for urine analysis as it can provide rapid, reliable, and reagent-free analysis of urine samples. However, one important practical problem encountered in such Raman measurements is the orders of magnitude stronger spectral background preventing one to utilize the full dynamic range of the detector which is required for the measurement of Raman signal with good signal-to-noise ratio (SNR). We report here the results of an exploratory study carried out on human urine samples to show that the photobleaching, which is a major disadvantage during the fluorescence measurement, could be utilized for suppressing the measured background to improve the SNR of the Raman peaks. It was found that once the photobleaching reached its plateau, there were improvements by ~67% and ~47% in the SNR and the signal to background ratio (SBR), respectively, of the Raman signals as compared to the spectra measured at the start of acquisition. Further, the reduced background also allowed us to utilize the full dynamic range of the detector at increased integration time without saturating the detector indicating the possibility of obtaining an improved detection limit.

Electronic nose to distinguish bladder cancer by urinary odour feature: A pilot study

BACKGROUND

No study has yet investigated the use of electronic nose (eNose) technology to reveal pattern recognition of urological diseases, including bladder cancer.

OBJECTIVE

We sought to determine the diagnostic performance of the eNose in recognizing urinary odour in patients with bladder cancer.

METHODS

The eNose is a commercially available model equipped with two sensors. The angle of the two sensors (θ) depends on the kinds of chemical substances, thus defining θ as the feature of odour. Quantity of odour is the number of θ detected during a measurement. Urine samples were from 36 untreated patients with bladder cancer, 29 with urolithiasis, 10 with urinary tract infection (UTI), and 27 healthy volunteers.

RESULTS

Based on ROC analysis of the quantity in patients with bladder cancer, an optimal cut-off value for θ of 49, 48, and 55 was applied to compare with samples from the healthy volunteer, urolithiasis and UTI groups, respectively. There were significantly differences between bladder cancer and the other conditions using these specific points (p< 0.0001, respectively). The resulting diagnostic sensitivity was 61.4%, 45.6%, and 60.8%, and specificity was 52.8%, 68.4%, and 90.2%, respectively. The AUC for bladder cancer was 0.565, 0.548, and 0.909, respectively.

CONCLUSION

The eNose is a small, portable, rapid, low cost, and noninvasive instrument for distinguishing bladder cancer from other benign conditions.

Chromatographic bioanalytical assays for targeted covalent kinase inhibitors and their metabolites

Deriving from targeted kinase inhibitors (TKIs), targeted covalent kinase inhibitors (TCKIs) are a new class of TKIs that are covalently bound to their target residue of kinase receptors. Currently, there are many new TCKIs under clinical development besides afatinib, ibrutinib, osimertinib, neratinib, acalabrutinib, dacomitinib, and zanubrutinib that are already approved by the FDA. Subsequently, there is an increasing demand for bioanalytical methods to qualitatively and quantitively investigate those compounds, leading to a number of papers reporting the development, validation, and use of bioanalytical methods for TCKIs. Most publications describe the technological set up of analytical methods that allow quantification of TCKIs in various biomatrices such as plasma, cerebrospinal fluid, urine, tissue, and liver microsomes. In addition, the identification of metabolites and biotransformation pathways of new TCKIs has gained more interest in recent years. We provide an overview of bioanalytical methods of this new class of TCKIs. The included issues are sample pretreatment, chromatographic separation, detection, and method validation. In the scope of bioanalysis of TCKIs, protein precipitation is mostly applied to treat the biological matrices sample. Liquid chromatographic in reversed-phase mode (RPLC) and mass detection with triple quadrupole (QqQ) are the most often utilized separation and quantitative detection modes, respectively. There may be a possibility of increased use of the high-resolution mass spectrometry (HRMS) for qualitative investigation purposes in the future. We also found that US FDA and EMA guidelines are the most common guidelines employed as validation framework for the bioanalytical methods of TCKIs.

Screening of Urinary Renal Cancer Metabolic Biomarkers with Gold Nanoparticles-assisted Laser Desorption/Ionization Mass Spectrometry

Renal cell carcinoma is a very aggressive and often fatal disease for which there are no specific biomarkers found to date. The purpose of this work was to find features that differentiate urine metabolic profiles of healthy people and cancer patients. Laser desorption/ionization mass spectrometry on gold nanostructures-based techniques were used for the metabolic analysis of urine of 50 patients with kidney cancer. Comparison with data from 50 healthy volunteers led to the discovery of several compounds that may be considered potential renal cell carcinoma (RCC) biomarkers. Statistical analysis of data allowed for the discovery of m/z values that had the greatest impact on group differentiation. A database search enabled the assignment of signals for the most promising 15 features among them: serine, heptanol, 3-methylene-indolenine, 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate, phosphodimethylethanolamine, 4-methoxyphenylacetic acid, N-acetylglutamine, 3,5-dihydroxyphenylvaleric acid, hydroxyhexanoylglycine, valyl-leucine, leucyl-histidine, oleamide, 9,12,13-trihydroxyoctadecenoic acid, stearidonyl carnitine and squalene. Differences of metabolite profiles of human urine could be identified by gold nanoparticle-enhanced target (AuNPET) LDI MS method and used for the detection of renal cancer.

Multiparametric MR imaging of the prostate at 1.5-T without endorectal coil using an 8 channel pelvic phased array: Is it still a viable option?

INTRODUCTION

The purpose of our work was to evaluate the feasibility of prostate multiparametric MR imaging at 1.5-T without endorectal coil using an 8 channel pelvic phased array coil.

MATERIAL AND METHODS

A total of 154 patients who underwent mp-MRI were retrospectively included. Patients received a standardized mp-MRI, compliant with 2012 European Society of Uro-Radiology guidelines, with 1·5 T magnetic field strength and an 8 channel pelvic phased-array coil. Two blinded readers graded the image quality of mp-MRI on a three-point scale and they scored the prostate lesions according to PI-RADS v2. All PI-RADS of 4 or 5 underwent biopsy. A third radiologist and a pathologist verified the correspondence between the MRI images and the results of the biopsy.

RESULTS

64 (41.6%) patients showed a Pi-rads of 4 or 5. At biopsy, 79.7% showed a Gleason score ≥7, 12.5% showed a Gleason score of 6 and 7.8% showed a negative biopsy. In the group of Pi-rads ≤ 3, 12 patients underwent a biopsy with the following results: negative biopsy in 33.3%, atypical Small Acinar Proliferation in 16.7%, prostatic intraepithelial neoplasia in 25% and indolent PCa 25%. Mp-MRI in the identification of clinically significant cancer provided a low percentage of false positive (7.8%) while in 79.7% of cases it was capable to detect clinically significant prostate cancer. In 92.2% of patients mp-MRI identified a prostate cancer with a Gleason score ≥6. The inter-reader agreement was excellent in defining both the quality of the examination and the PI-RADS category (k = 0.83 and k = 0.70, respectively).

CONCLUSIONS

mp-MRI at 1.5-T without endorectal coil using an 8 channel phased array is an appropriate tool for early detection of clinically significant prostate cancer.

IMPLICATIONS FOR PRACTICE

8 channel pelvic phased array is still an appropriate tool for early detection of clinically significant prostate cancer and for obtaining a reduction in overdiagnosis of indolent PCa.

Validating fPSA Glycoprofile as a Prostate Cancer Biomarker to Avoid Unnecessary Biopsies and Re-Biopsies

BACKGROUND

To compare the clinical performance of a new PCa serum biomarker based on fPSA glycoprofiling to fPSA% and PHI.

METHODS

Serum samples from men who underwent prostate biopsy due to increased PSA were used. A comparison between two equal groups (with histologically confirmed PCa or benign, non-cancer condition) was used for the clinical validation of a new glycan-based PCa oncomarker. SPSS and R software packages were used for the multiparametric analyses of the receiver operating curve (ROC) and for genetic algorithm metaheuristics.

RESULTS

When comparing the non-cancer and PCa cohorts, the combination of four fPSA glycoforms with two clinical parameters (PGI, prostate glycan index (PGI)) showed an area under receiver operating curve (AUC) value of 0.821 (95% CI 0.754-0.890). AUC values were 0.517 for PSA, 0.683 for fPSA%, and 0.737 for PHI. A glycan analysis was also applied to discriminate low-grade tumors (GS = 6) from significant tumors (GS ≥ 7).

CONCLUSIONS

Compared to PSA on its own, or fPSA% and the PHI, PGI showed improved discrimination between presence and absence of PCa and in predicting clinically significant PCa. In addition, the use of PGI would help practitioners avoid 63.5% of unnecessary biopsies, while the use of fPSA% and PHI would help avoid 17.5% and 33.3% of biopsies, respectively, while missing four significant tumors (9.5%).

Nanotreatment and Nanodiagnosis of Prostate Cancer: Recent Updates

The fabrication and development of nanomaterials for the treatment of prostate cancer have gained significant appraisal in recent years. Advancements in synthesis of organic and inorganic nanomaterials with charge, particle size, specified geometry, ligand attachment etc have resulted in greater biocompatibility and active targeting at cancer site. Despite all of the advances made over the years in discovering drugs, methods, and new biomarkers for cancer of the prostate (PCa), PCa remains one of the most troubling cancers among people. Early on, effective diagnosis is an essential part of treating prostate cancer. Prostate-specific antigen (PSA) or serum prostate-specific antigen is the best serum marker widely accessible for diagnosis of PCa. Numerous efforts have been made over the past decade to design new biosensor-based strategies for biomolecules detection and PSA miniaturization biomarkers. The growing nanotechnology is expected to have a significant effect in the immediate future on scientific research and healthcare. Nanotechnology is thus predicted to find a way to solve one of the most and long-standing problem, "early cancer detection". For early diagnosis of PCa biomarkers, different nanoparticles with different approaches have been used. In this review, we provide a brief description of the latest achievements and advances in the use of nanoparticles for PCa biomarker diagnosis.

A Panel of Urinary Volatile Biomarkers for Differential Diagnosis of Prostate Cancer from Other Urological Cancers

Our group recently developed a urinary 6-biomarker panel for the diagnosis of prostate cancer (PCa) which has a higher level of accuracy compared to the serum prostate specific antigen (PSA) test. Herein, urine from an independent cohort of PCa patients and cancer-free controls was analyzed to further validate the discriminative power of that panel. Additionally, urine from patients diagnosed with bladder cancer (BC) and renal cancer (RC) were included to evaluate the site-specificity of the panel. Results confirmed the ability of the 6-biomarker panel to discriminate PCa patients from controls, but not from other urological cancers. To overcome this limitation, an untargeted approach was performed to unveil discriminant metabolites among the three cancer types. A 10-biomarker panel comprising the original panel plus four new metabolites was established to discriminate PCa from controls, BC, and RC, with 76% sensitivity, 90% specificity, and 92% accuracy. This improved panel also disclosed better accuracy than serum PSA test and provides the basis for a new non-invasive early detection tool for PCa.

Examined and Positive Lymph Node Counts Are Associated with Mortality in Prostate Cancer: A Population-Based Analysis

BACKGROUND

Prostate cancer (PCa) is the third leading cause of death from cancer in the United States. We aimed to disclose the prognostic values of examined (dissected) lymph node (ELN), negative lymph node (NLN), and positive (metastatic) lymph node (PLN) counts and lymph node (LNs) ratio in PCa patients.

METHODS

We extracted data of PCa patients diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) program. We included patients with a histologically confirmed diagnosis having at least one ELN and with the PCa as the primary tumor only.

RESULTS

We have included 96,064 patients. Multivariable Cox proportional hazards regression modelsdisclosed that patients having more ELNs were associated with better survival. However, we demonstrated that patients having more PLNs were associated with worse survival. Additionally, older age, unmarried patients, with Gleason's score of 8-10, T4 and M1 stages and those who received chemotherapy and/or radiation but did not receive surgery were significantly associated with worse PCa survival.

CONCLUSIONS

We have disclosed several independent predictors affecting PCa patients including age, marital status, Gleason's score, T and N stages, having received therapy, surgery, and ELN and PLN counts. Moreover, we demonstrated that patients with lower ELN and higher PLN counts were a high-risk group. We strongly recommend adding the ELN and/or PLN counts into consideration during patient staging/treatment.

Spectral characteristics of urine from patients with end-stage kidney disease analyzed using Raman Chemometric Urinalysis (Rametrix)

Raman Chemometric Urinalysis (Rametrix^TM) was used to discern differences in Raman spectra from (i) 362 urine specimens from patients receiving peritoneal dialysis (PD) therapy for end-stage kidney disease (ESKD), (ii) 395 spent dialysate specimens from those PD therapies, and (iii) 235 urine specimens from healthy human volunteers. Rametrix^TM analysis includes spectral processing (e.g., truncation, baselining, and vector normalization); principal component analysis (PCA); statistical analyses (ANOVA and pairwise comparisons); discriminant analysis of principal components (DAPC); and testing DAPC models using a leave-one-out build/test validation procedure. Results showed distinct and statistically significant differences between the three types of specimens mentioned above. Further, when introducing “unknown” specimens, Rametrix^TM was able to identify the type of specimen (as PD patient urine or spent dialysate) with better than 98% accuracy, sensitivity, and specificity. Rametrix^TM was able to identify “unknown” urine specimens as from PD patients or healthy human volunteers with better than 96% accuracy (with better than 97% sensitivity and 94% specificity). This demonstrates that an entire Raman spectrum of a urine or spent dialysate specimen can be used to determine its identity or the presence of ESKD by the donor.

Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine

BACKGROUND

The lack of sensitive and specific biomarkers for the early detection of prostate cancer (PCa) is a major hurdle to improve patient management.

METHODS

A metabolomics approach based on GC-MS was used to investigate the performance of volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine as potential markers for PCa detection.

RESULTS

Results showed that PCa patients (n = 40) can be differentiated from cancer-free subjects (n = 42) based on their urinary volatile profile in both VOCs and VCCs models, unveiling significant differences in the levels of several metabolites. The models constructed were further validated using an external validation set (n = 18 PCa and n = 18 controls) to evaluate sensitivity, specificity and accuracy of the urinary volatile profile to discriminate PCa from controls. The VOCs model disclosed 78% sensitivity, 94% specificity and 86% accuracy, whereas the VCCs model achieved the same sensitivity, a specificity of 100% and an accuracy of 89%. Our findings unveil a panel of 6 volatile compounds significantly altered in PCa patients' urine samples that was able to identify PCa, with a sensitivity of 89%, specificity of 83%, and accuracy of 86%.

CONCLUSIONS

It is disclosed a biomarker panel with potential to be used as a non-invasive diagnostic tool for PCa.

Review and Comparison of Cancer Biomarker Trends in Urine as a Basis for New Diagnostic Pathways

Cancer is one of the major causes of mortality worldwide and its already large burden is projected to increase significantly in the near future with a predicted 22 million new cancer cases and 13 million cancer-related deaths occurring annually by 2030. Unfortunately, current procedures for diagnosis are characterized by low diagnostic accuracies. Given the proved correlation between cancer presence and alterations of biological fluid composition, many researchers suggested their characterization to improve cancer detection at early stages. This paper reviews the information that can be found in the scientific literature, regarding the correlation of different cancer forms with the presence of specific metabolites in human urine, in a schematic and easily interpretable form, because of the huge amount of relevant literature. The originality of this paper relies on the attempt to point out the odor properties of such metabolites, and thus to highlight the correlation between urine odor alterations and cancer presence, which is proven by recent literature suggesting the analysis of urine odor for diagnostic purposes. This investigation aims to evaluate the possibility to compare the results of studies based on different approaches to be able in the future to identify those compounds responsible for urine odor alteration.

The Advent of Salivary Breast Cancer Biomarker Detection Using Affinity Sensors

Breast Cancer is one of the world's most notorious diseases affecting two million women in 2018 worldwide. It is a highly heterogeneous disease, making it difficult to treat. However, its linear progression makes it a candidate for early screening programs, and the earlier its detection the higher the chance of recovery. However, one key hurdle for breast cancer screening is the fact that most screening techniques are expensive, time-consuming, and cumbersome, making them impractical for use in several parts of the world. One current trend in breast cancer detection has pointed to a possible solution, the use of salivary breast cancer biomarkers. Saliva is an attractive medium for diagnosis because it is readily available in large quantities, easy to obtain at low cost, and contains all the biomarkers present in blood, albeit in lower quantities. Affinity sensors are devices that detect molecules through their interactions with biological recognition molecules. Their low cost, high sensitivity, and selectivity, as well as rapid detection time make them an attractive alternative to traditional means of detection. In this review article, we discuss the current status of breast cancer diagnosis, its salivary biomarkers, as well as the current trends in the development of affinity sensors for their detection.

Early detection of prostate cancer using prostate-specific antigen testing: an empirical evaluation among general practitioners and urologists

Background: Prostate cancer (PCa) is the most frequent cancer and the third leading cause of cancer death among German men. One option for PCa early detection is prostate-specific antigen (PSA) testing, which is still under debate regarding its risk benefits. Besides recommendations on the early PCa detection, daily practice on PSA testing varies in, for example, information communication and usage of the test. This pilot study assessed potential differences between general practitioners (GPs) and urologists in handling PSA testing and guidelines on early detection of PCa. Methods: 172 GPs belonging to the teaching network of the University of Oldenburg in Lower Saxony and Bremen and 128 practicing urologists were included in the online survey focusing on PSA testing. The questionnaire covered 43 questions on topics as the usage of the test, information communication, handling of test results and handling of/knowledge about national and international guidelines on PCa. Wether PSA testing is used in accordance with guidelines was also explored in four standardized case scenarios. Statistical analysis was done at a descriptive level. Results: In total, 65 doctors participated in the survey (response proportion: 21.7%, n=65; 27.9%, n=48 [GPs]; 13.2%, n=17 [urologists]). Results of 41 GPs and 14 urologists were analyzed. The PSA test was judged as useful by all urologists, while almost half of the GPs valued the test as ambivalent or not useful. Urologists showed a more proactive approach of informing men on PSA testing. Regarding guidelines and recommendations on PSA testing, GPs were less familiar with them compared to the urologists. Doctors of both specialties did not always treat men in consistence with the guidelines. This was partially in contradiction to their self-appraisal. Conclusion: This pilot study is highlighting differences in PSA testing practices between GPs and urologists in Germany. Urologists showed a more proactive approach. For further verification, we plan a more comprehensive study covering several German states.

Towards precision medicine: advances in 5-hydroxymethylcytosine cancer biomarker discovery in liquid biopsy

Robust and clinically convenient biomarkers for cancer diagnosis, early detection, and prognosis have great potential to improve patient survival and are the key to precision medicine. The advent of next-generation sequencing technologies enables a more sensitive and comprehensive profiling of genetic and epigenetic information in tumor-derived materials. Researchers are now able to monitor the dynamics of tumorigenesis in new dimensions, such as using circulating cell-free DNA (cfDNA) and tumor DNA (ctDNA). Mutation-based assays in liquid biopsy cannot always provide consistent results across studies due partly to intra- and inter-tumoral heterogeneity as well as technical limitations. In contrast, epigenetic analysis of patient-derived cfDNA is a promising alternative, especially for early detection and disease surveillance, because epigenetic modifications are tissue-specific and reflect the dynamic process of cancer progression. Therefore, cfDNA-based epigenetic assays are emerging to be a highly sensitive, minimally invasive tool for cancer diagnosis and prognosis with great potential in future precise care of cancer patients. The major obstacle for applying epigenetic analysis of cfDNA, however, has been the lack of enabling techniques with high sensitivity and technical robustness. In this review, we summarized the advances in epigenome-wide profiling of 5-hydroxymethylcytosine (5hmC) in cfDNA, focusing on the detection approaches and potential role as biomarkers in different cancer types.

Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics

Background

Methylation plays a key role in the aetiology and pathogenesis of prostate cancer (PCa). This study aimed to identify aberrantly methylated differentially expressed genes (DEGs) and pathways in PCa and explore the underlying mechanisms of tumourigenesis.

Methods

Expression profile (GSE29079) and methylation profile (GSE76938) datasets were obtained from the Gene Expression Omnibus (GEO). We used R 3.4.4 software to assess aberrantly methylated DEGs. The Cancer Genome Atlas (TCGA) RNA sequencing and Illumina HumanMethylation450 DNA methylation data were utilized to validate screened genes. Functional enrichment analysis of the screened genes was performed, and a protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Gens (STRING). The results were visualized in Cytoscape. After confirmation using TCGA, cBioPortal was used to examine alterations in genes of interest. Then, protein localization in PCa cells was observed using immunohistochemistry.

Results

Overall, 536 hypomethylated upregulated genes were identified that were enriched in biological processes such as negative regulation of transcription, osteoblast differentiation, intracellular signal transduction, and the Wnt signalling pathway. Pathway enrichment showed significant changes in factors involved in AMPK signalling, cancer, and adherens junction pathways. The hub oncogenes were AKT1, PRDM10, and FASN. Additionally, 322 hypermethylated downregulated genes were identified that demonstrated enrichment in biological processes including positive regulation of the MAPK cascade, muscle contraction, ageing, and signal transduction. Pathway analysis indicated enrichment in arrhythmogenic right ventricular cardiomyopathy (ARVC), focal adhesion, dilated cardiomyopathy, and PI3K-AKT signalling. The hub tumour suppressor gene was FLNA. Immunohistochemistry showed that AKT1, FASN, and FLNA were mainly expressed in PCa cell cytoplasm, while PRDM10 was mainly expressed in nuclei.

Conclusions

Our results identify numerous novel genetic and epigenetic regulatory networks and offer molecular evidence crucial to understanding the pathogenesis of PCa. Aberrantly methylated hub genes, including AKT1, PRDM10, FASN, and FLNA, can be used as biomarkers for accurate PCa diagnosis and treatment. In conclusion, our study suggests that AKT1, PRDM10, and FASN may be tumour promoters and that FLNA may be a tumour suppressor in PCa. We hope these findings will draw more attention to these hub genes in future cancer studies.

Approaches to urinary detection of prostate cancer

Background:

Prostate cancer is the most common cancer in American men that ranges from low risk states amenable to active surveillance to high risk states that can be lethal especially if untreated. There is a critical need to develop relatively non-invasive and clinically useful methods for screening, detection, prognosis, disease monitoring, and prediction of treatment efficacy. In this review, we focus on important advances as well as future efforts needed to drive clinical innovation in this area of urine biomarker research for prostate cancer detection and prognostication.

Methods:

We provide a review of current literature on urinary biomarkers for prostate cancer. We evaluate the strengths and limitations of a variety of approaches that vary in sampling strategies and targets measured; discuss reported urine tests for prostate cancer with respect to their technical, analytical, and clinical parameters; and provide our perspectives on critical considerations in approaches to developing a urine-based test for prostate cancer.

Results:

There has been an extensive history of exploring urine as a source of biomarkers for prostate cancer that has resulted in a variety of urine tests that are in current clinical use. Importantly, at least three tests have demonstrated high sensitivity (~90%) and negative predictive value (~95%) for clinically significant tumors; however, there has not been widespread adoption of these tests.

Conclusions:

Conceptual and methodological advances in the field will help to drive the development of novel urinary tests that in turn may lead to a shift in the clinical paradigm for prostate cancer diagnosis and management.