The impact of biomarkers in multivariate algorithms for bladder cancer diagnosis in patients with hematuria

Stratifying risk of disease in haematuria patients using machine learning techniques to improve diagnostics

Background

Detailed and invasive clinical investigations are required to identify the causes of haematuria. Highly unbalanced patient population (predominantly male) and a wide range of potential causes make the ability to correctly classify patients and identify patient-specific biomarkers a major challenge. Studies have shown that it is possible to improve the diagnosis using multi-marker analysis, even in unbalanced datasets, by applying advanced analytical methods. Here, we applied several machine learning algorithms to classify patients from the haematuria patient cohort (HaBio) by analysing multiple biomarkers and to identify the most relevant ones.

Materials and methods

We applied several classification and feature selection methods (k-means clustering, decision trees, random forest with LIME explainer and CACTUS algorithm) to stratify patients into two groups: healthy (with no clear cause of haematuria) or sick (with an identified cause of haematuria e.g., bladder cancer, or infection). The classification performance of the models was compared. Biomarkers identified as important by the algorithms were also analysed in relation to their involvement in the pathological processes.

Results

Results showed that a high unbalance in the datasets significantly affected the classification by random forest and decision trees, leading to the overestimation of the sick class and low model performance. CACTUS algorithm was more robust to the unbalance in the dataset. CACTUS obtained a balanced accuracy of 0.747 for both genders, 0.718 for females and 0.803 for males. The analysis showed that in the classification process for the whole dataset: microalbumin, male gender, and tPSA emerged as the most informative biomarkers. For males: age, microalbumin, tPSA, cystatin C, BTA, HAD and S100A4 were the most significant biomarkers while for females microalbumin, IL-8, pERK, and CXCL16.

Conclusions

CACTUS algorithm demonstrated improved performance compared with other methods such as decision trees and random forest. Additionally, we identified the most relevant biomarkers for the specific patient group, which could be considered in the future as novel biomarkers for diagnosis. Our results have the potential to inform future research and provide new personalised diagnostic approaches tailored directly to the needs of the individuals.

Deciphering Urogenital Cancers through Proteomic Biomarkers: A Systematic Review and Meta-Analysis

Urogenital cancers, which include prostate, bladder, and kidney malignancies, exert a substantial impact on global cancer-related morbidity and mortality. Proteomic biomarkers, emerging as valuable tools, aim to enhance early detection, prognostic accuracy, and the development of personalized therapeutic strategies. This study undertook a comprehensive systematic review and meta-analysis of the existing literature investigating the role and potential of proteomic biomarkers in plasma, tissue, and urine samples in urogenital cancers. Our extensive search across several databases identified 1879 differentially expressed proteins from 37 studies, signifying their potential as unique biomarkers for these cancers. A meta-analysis of the significantly differentially expressed proteins was executed, accentuating the findings through visually intuitive volcano plots. A functional enrichment analysis unveiled their significant involvement in diverse biological processes, including signal transduction, immune response, cell communication, and cell growth. A pathway analysis highlighted the participation of key pathways such as the nectin adhesion pathway, TRAIL signaling pathway, and integrin signaling pathways. These findings not only pave the way for future investigations into early detection and targeted therapeutic approaches but also underscore the fundamental role of proteomics in advancing our understanding of the molecular mechanisms underpinning urogenital cancer pathogenesis. Ultimately, these findings hold remarkable potential to significantly enhance patient care and improve clinical outcomes.

Urine biomarkers in bladder cancer - current status and future perspectives

Urine markers to detect bladder cancer have been the subject of research for decades. The idea that urine - being in continuous contact with tumour tissue - should provide a vector of tumour information remains an attractive concept. Research on this topic has resulted in a complex landscape of many different urine markers with varying degrees of clinical validation. These markers range from cell-based assays to proteins, transcriptomic markers and genomic signatures, with a clear trend towards multiplex assays. Unfortunately, the number of different urine markers and the efforts in research and development of clinical grade assays are not reflected in the use of these markers in clinical practice, which is currently limited. Numerous prospective trials are in progress with the aim of increasing the quality of evidence about urinary biomarkers in bladder cancer to achieve guideline implementation. The current research landscape suggests a division of testing approaches. Some efforts are directed towards addressing the limitations of current assays to improve the performance of urine markers for a straightforward detection of bladder cancer. Additionally, comprehensive genetic analyses are emerging based on advances in next-generation sequencing and are expected to substantially affect the potential application of urine markers in bladder cancer.

Urinary biomarkers for bladder cancer diagnosis and NMIBC follow-up: a systematic review

BACKGROUND

Bladder cancer detection and follow-up is based on cystoscopy and/or cytology, but it remains imperfect and invasive. Current research focuses on diagnostic biomarkers that could improve bladder cancer detection and follow-up by discriminating patients at risk of aggressive cancer who need confirmatory TURBT (Transurethral Resection of Bladder Tumour) from patients at no risk of aggressive cancer who could be spared from useless explorations.

OBJECTIVE

To perform a systematic review of data on the clinical validity and clinical utility of eleven urinary biomarkers (VisioCyt^®, Xpert^®Bladder, BTA stat^®, BTA TRAK™, NMP22 BC^®, NMP22^® BladderChek^® Test, ImmunoCyt™/uCyt1+™, UroVysion Bladder Cancer Kit^®, Cxbladder, ADXBLADDER, Urodiag^®) for bladder cancer diagnosis and for non-muscle invasive bladder cancer (NMIBC) follow-up.

METHODS

All available studies on the 11 biomarkers published between May 2010 and March 2021 and present in MEDLINE^® were reviewed. The main endpoints were clinical performance for bladder cancer detection, recurrence or progression during NMIBC monitoring, and additional value compared to cytology and/or cystoscopy.

RESULTS

Most studies on urinary biomarkers had a prospective design and high level of evidence. However, their results should be interpreted with caution given the heterogeneity among studies. Most of the biomarkers under study displayed higher detection sensitivity compared with cytology, but lower specificity. Some biomarkers may have clinical utility for NMIBC surveillance in patients with negative or equivocal cystoscopy or negative or atypical urinary cytology findings, and also for recurrence prediction.

CONCLUSION

Urinary biomarkers might have a complementary place in bladder cancer diagnosis and NMIBC surveillance. However, their clinical benefit remains to be confirmed.

Biomarkers to assess the risk of bladder cancer in patients presenting with haematuria are gender-specific

Introduction

Haematuria is a common red flag symptom of urinary tract cancer. Bladder cancer (BC) is the most common cancer to present with haematuria. Women presenting with haematuria are often underdiagnosed. Currently, no gender-specific tests are utilized in clinical practice. Considerable healthcare resources are needed to investigate causes of haematuria and this study was set up to help identify markers of BC. The aim of the study was to define biomarker algorithms in haematuria patients using an expanded panel of biomarkers to diagnose BC and investigate if the algorithms are gender-specific.

Materials and Methods

A total of n=675 patients with a history of haematuria were recruited from Northern Ireland hospitals. Patients were collected on a 2:1 ratio, non-BC (control) n=474: BC n=201. A detailed clinical history, urine and blood samples were collected. Biomarkers, known to be involved in the pathobiology underlying bladder carcinogenesis were investigated. Biomarkers differentially expressed between groups were investigated using Wilcoxon rank sum and linear regression.

Results

Biomarkers were gender specific. Two biomarker-algorithms were identified to triage haematuria patients; male - u_NSE, s_PAI-1/tPA, u_midkine, u_NGAL, u_MMP-9/TIMP-1 and s_prolactin (u=urine; s=serum); sensitivity 71.8%, specificity 72.8%; AUROC 0.795; and female urine biomarkers - IL-12p70, IL-13, midkine and clusterin; sensitivity 83.7%, specificity 79.7%; AUROC 0.865. Addition of the clinical variable infection to both algorithms increased both AUROC to 0.822 (DeLong p=0.014) and to 0.923 (DeLong p=0.004) for males and females, respectively. Combining clinical risk factors with biomarker algorithms would enable application of the algorithms to triage haematuria patients.

Conclusion

Using gender-specific biomarker algorithms in combination with clinical risks that are associated with BC would allow clinicians to better manage haematuria patients and potentially reduce underdiagnosis in females. In this study, we demonstrate, for the first time, that blood and urine biomarkers are gender-specific when assessing risk of BC in patients who present with blood in their urine. Combining biomarker data with clinical factors could improve triage when referring patients for further investigations.

Utility of urinary biomarkers in primary haematuria: Systematic review and meta-analysis

Objectives

To evaluate the diagnostic performance of FDA-approved urinary biomarkers in the evaluation of primary haematuria for investigation of bladder cancer.

Methods

The scientific databases MEDLINE, EMBASE, Pubmed and Web of Science were searched to collect studies. Studies that evaluated the diagnostic performance of FDA-approved urinary biomarkers in investigating patients with primary haematuria without a prior history of bladder cancer were included. Quality of studies was assessed using the JBI Criteria. Bivariate mixed-effects regression model was used to calculate pooled sensitivities and specificities for each biomarker.

Results

Eighteen studies were included in the analysis. The biomarkers assessed in these studies were CxBladder, AssureMDx, Bladder Tumour Antigen (BTA), NMP22, UroVysion and Immunocyt/uCyt+. Several biomarkers, such as AssureMDx, CxBladder and Immunocyt, were shown to have better diagnostic performance based on their sensitivity, specificity and diagnostic odds ratio, as well as positive and negative likelihood ratios. Across the six biomarkers, sensitivity ranged from 0.659 to 0.973, and the specificity ranged between 0.577 and 0.833.

Conclusion

Despite certain biomarkers demonstrated better performance, current diagnostic abilities of the FDA-approved biomarkers remain insufficient for their general application as a rule out test for bladder cancer diagnosis and as a triage test for cystoscopy in patients with primary haematuria. High-quality prospective studies are required to further analyse this and also analyse the correct scenario in which urinary biomarkers may be best utilised.

Identification and Validation of Hub Genes Associated with Bladder Cancer by Integrated Bioinformatics and Experimental Assays

Bladder cancer (BC) is the most common malignant tumor of the urinary system and is associated with high morbidity and mortality; however, the molecular mechanism underlying its occurrence is not clear. In this study, the gene expression profile and related clinical information of GSE13507 were downloaded from the Gene Expression Omnibus (GEO) database. RNA sequencing (RNA-seq) expression data and related clinical information were retrieved from The Cancer Genome Atlas (TCGA) database. Overlapping genes were identified by differential gene expression analysis and weighted gene co-expression network analysis (WGCNA). Then, we carried out functional enrichment analysis to understand the potential biological functions of these co-expressed genes. Finally, we performed a protein-protein interaction (PPI) analysis combined with survival analysis. Using the CytoHubba plug-in of Cytoscape, TROAP, CENPF, PRC1, AURKB, CCNB2, CDC20, TTK, CEP55, ASPM, and CDCA8 were identified as candidate central genes. According to the survival analysis, the high expression of TTK was related to the poor overall survival (OS) of patients with BC. TTK may also affect the bladder tumor microenvironment (TME) by affecting the number of immune cells. The expression level of TTK was verified by immunohistochemistry (IHC) and real-time quantitative polymerase chain reaction (RT-qPCR), and the tumor-promoting effect of TTK in BC cells was confirmed in vitro. Our results also identified the MSC-AS1/hsa-miR-664b-3p/TTK regulatory axis, which may also play an important role in the progression of BC, but further research is needed to verify this result. In summary, our results provide a new idea for accurate early diagnosis, clinical treatment, and prognosis of BC.

Biomarkers for Precision Urothelial Carcinoma Diagnosis: Current Approaches and the Application of Single-Cell Technologies

Simple Summary

Urothelial carcinoma (UC) is the most frequently diagnosed cancer of the urinary tract and is ranked the sixth most diagnosed cancer in men worldwide. About 70–75% of newly diagnosed UCs are non-invasive or low grade. Different tests such as urine cytology and cystoscopy are used to detect UC. If abnormal tissue is found during cystoscopy, then a biopsy will be performed. Cytology has low sensitivity for low-grade cancer while cystoscopy is invasive and costly. Detecting UC early improves the chances of treatment success. Therefore, many researchers have painstakingly identified urine biological markers for non-invasive UC diagnosis. In this review, we summarize some of the latest and most promising biological markers (including FDA-approved and investigational markers). We also discuss some new technologies that can aid research efforts in biological marker discovery for early UC detection.

Abstract

Urothelial carcinoma (UC) is the most frequent malignancy of the urinary system and is ranked the sixth most diagnosed cancer in men worldwide. Around 70–75% of newly diagnosed UC manifests as the non-muscle invasive bladder cancer (NMIBC) subtype, which can be treated by a transurethral resection of the tumor. However, patients require life-long monitoring due to its high rate of recurrence. The current gold standard for UC diagnosis, prognosis, and disease surveillance relies on a combination of cytology and cystoscopy, which is invasive, costly, and associated with comorbidities. Hence, there is considerable interest in the development of highly specific and sensitive urinary biomarkers for the non-invasive early detection of UC. In this review, we assess the performance of current diagnostic assays for UC and highlight some of the most promising biomarkers investigated to date. We also highlight some of the recent advances in single-cell technologies that may offer a paradigm shift in the field of UC biomarker discovery and precision diagnostics.

Thrombomodulin Expression in Bladder Cancer Tissue and Its Association with Prognosis and Patient Survival

Background

Decreased expression of thrombomodulin (TM) in bladder cancer tissue has been shown to be associated with cell proliferation, increased malignancy and a poor prognosis. The aim of this study was to investigate the immunoexpression of TM in bladder tissue cores by immunohistochemistry (IHC) and the relationship between TM score and patient survival for the following pathologies: transitional cell papillary carcinoma (TCPC), transitional cell carcinoma (non-papillary) (TCC), squamous cell carcinoma (SCC), adenocarcinoma, and sarcoma. TM immunoexpression was also evaluated in normal adjacent bladder tissue cores.

Methods

TM immunoexpression was assessed in n=185 formalin-fixed paraffin-embedded (FFPE) bladder tissue cores from n=98 patients by IHC. Tissue cores included TCPC (n=29), TCC (n=85), SCC (n=21), adenocarcinoma (n=12), sarcoma (n=4), and normal tissue cores (n=34).

Results

TM immunoexpression scores are stronger in TCPC, TCC and SCC bladder cancer tissue cores with respect to adenocarcinoma and sarcoma (mean TM immunoexpression scores: 3.04, 2.57, 2.55, 1.55 and 1.19, respectively) (Kruskal–Wallis p<0.001). TM immunoexpression scores significantly decreased in bladder cancer tissue cores across both stage (p<0.001) and grade (p<0.001) (Kruskal–Wallis). Survival data were available for n=45 bladder cancer patients (mean follow-up of 34 months). Applying a TM immunoexpression cut-off score of 3.0 demonstrated that patients with bladder cancer who had a TM immunoexpression score <3.0 had lower survival rates (median survival 23.5 months). In contrast, patients with TM immunoexpression scores ≥3.0 had longer survival rates (median survival 40 months) (log-rank; p=0.045).

Conclusion

TM immunoexpression in bladder cancer tissue may be a clinically relevant predictor of tumor progression and survival. Low expression of TM in bladder cancer biopsies or in recurrent bladder cancer may be indicative of a poor prognosis. TM immunoexpression could be used to guide clinical decision making.

Glomerular function in relation to circulating adhesion molecules and inflammation markers in a general population

Background

Inflammation is a hallmark of chronic kidney disease (CKD) and stimulates glomerular expression of vascular adhesion molecules (VCAMs). We investigated in a general population whether estimated glomerular filtration rate (eGFR) is associated with circulating adhesion molecules, inflammation markers or both.

Methods

We measured serum levels of five adhesion molecules [VCAM-1, intracellular adhesion molecule-1 (ICAM-1), P-selectin, E-selectin and monocyte chemoattractant protein-1 (MCP-1)] and seven inflammation markers [C-reactive protein (CRP), neutrophil gelatinase-associated lipocalin (NGAL), tumour necrosis factor receptor 1 (TNF-R1), TNF-α, interleukin 6 (IL-6), IL-8 and vascular endothelial growth factor] in 1338 randomly recruited people (50.8% women, mean age 51.7 years, eGFR 79.9 mL/min/1.73 m²).

Results

In multivariable-adjusted analyses, eGFR decreased (P ≤ 0.004) with higher VCAM-1 (association size expressed in mL/min/1.73 m² for a doubling of the marker, −2.99), MCP-1 (−1.19), NGAL (−1.19), TNF receptor 1 (−2.78), TNF-α (−2.28) and IL-6 (−0.94). The odds ratios of having eGFR <60 versus ≥60 mL/min/1.73 m² (n = 138 versus 1200) were significant (P ≤ 0.001) for VCAM-1 (1.77), MCP-1 (1.32), NGAL (1.26), TNF-R1 (1.49), TNF-α (1.45) and IL-6 (1.20). Compared with 24-h albuminuria, VCAM-1 increased (P <0.0001) the area under the curve from 0.57 to 0.65, MCP-1 to 0.67 and TNF-R1 to 0.79, but TNF-R1 outperformed both adhesion molecules (P < 0.0001).

Conclusions

In a general population, eGFR is inversely associated with circulating adhesion molecules VCAM-1 and MCP-1 and several inflammation markers, but inflammation markers, in particular TNF-R1 and TNF-α, identify patients with eGFR <60 mL/min/1.73 m² more accurately.

An early analysis of the cost-effectiveness of a diagnostic classifier for risk stratification of haematuria patients (DCRSHP) compared to flexible cystoscopy in the diagnosis of bladder cancer

Background

Urothelial bladder cancer (UBC) is the 5^th most common cancer in Western societies. The most common symptom of UBC is haematuria. Cystoscopy the gold standard for UBC detection, allows direct observation of the bladder, but is expensive, invasive, and uncomfortable. This study examines whether an alternative new urine-based diagnostic test, the DCRSHP, is cost-effective as a triage diagnostic tool compared to flexible cystoscopy in the diagnosis of UBC in haematuria patients.

Methods

A model-based cost-utility analysis using cost per quality adjusted life year and life year gained, parameterised with secondary data sources.

Results

If the DCRSHP is targeted at haematuria patients at lower risk of having bladder cancer e.g. younger patients, non-smokers, then it can be priced as high as £620, and be both effective and cost-effective. Sensitivity analysis found that DCRSHP is approximately 80% likely to be cost-effective across all willingness to pay values (for a QALY) and prevalence estimates.

Conclusion

This analysis shows the potential for a non-invasive test to be added to the diagnostic pathway for haematuria patients suspected of having UBC. If the DCRSHP is applied targeting haematuria patients at low risk of UBC, then it has the potential to be both effective and cost-effective.

Biomarker profiling of plasma samples utilizing RANDOX biochip array technology

RANDOX Biochip Array Technology offers an efficient, cost-effective method of measuring multiple analytes on a large number of samples in biologic fluids. This innovative technology has proven extremely useful in the profiling of markers in a number of different disease states. Biochip arrays have also shown promise in clinical trials, offering rapid evaluation of multiple markers and circulating levels of the analyte with only a small sample. This biochip technology has broad applications in clinical, pharmaceutical, toxicological, immunologic and microbiologic areas. This technique offers parallel profiling and will have great value in personalized and precision medicine. The aim of this manuscript is to explore the recent and future utility of biochips for profiling marker levels in different diseased populations using RANDOX's Biochip Array Technology.

Overexpression of UHRF1 gene correlates with the major clinicopathological parameters in urinary bladder cancer

INTRODUCTION

Recently, expression of the UHRF1 gene was found to be up-regulated in numerous neoplasms, including the urinary bladder transitional cell carcinoma (TCC).

OBJECTIVE

The aim of our study was to determine if the expression levels of UHRF1 gene correlates with the major pathological characteristics of the tumor and patients' clinical outcome.

MATERIALS AND METHODS

In our study, we have analyzed the tissue samples derived from group of 70 patients with histologically confirmed TCC of the urinary bladder, while normal urinary bladder mucosa obtained from 40 patients with nonmalignant diseases was used as a negative control group. Expression of UHRF1 gene in each patient sample was determined using reverse transcriptase-polymerase chain reaction.

RESULTS

UHRF1 gene expression was found to be app. 2.5 times higher in samples from patients with TCC in comparison with normal epithelium derived from control group patients. Analysis show that gene expression correlates with the malignancy of the tumor. A highly significant differences were found between the expression values of samples from low and high grade TCC, as well as between the high grade and control group. UHRF1 expression was higher in patients with non-muscle invasive disease than in those with muscle invasive disease.

CONCLUSIONS

The result of this study indicates that UHRF1 gene expression levels correlates with the major pathological characteristics of TCC samples and with the clinical outcome of those patients. Determination of UHRF1 gene expression could have a potential to be used as a sensitive molecular marker in patients with urinary bladder cancer.

Plasma and urine DNA levels are related to microscopic hematuria in patients with bladder urothelial carcinoma

a) Objective: An increase in cell-free DNA was observed in the plasma of many cancer patients. This major biomarker can be used to differentiate patients with malignant neoplasms from those with benign neoplasms or healthy patients. Depending on the characteristic of the tumor, there are qualitative variations in the circulating cell-free DNA. Today, studies on the concentration of fragments of circulating cell-free DNA and their respective sizes in patients with bladder cancer are not plentiful in the literature. A 100% effective plasma tumor marker, which would help in the diagnosis and follow-up of bladder cancer, is yet to be developed; therefore, cell-free DNA levels in the plasma may represent a valuable biomarker for the diagnosis, prognosis and follow-up of patients with this type of tumor. b) Design and methods: In this study we analyze the kinetics of plasma and urine DNA concentrations in patients with bladder cancer, relating them to the other clinical laboratory variables. c) Results: Patients with hematuria showed a positive correlation with urine DNA. d) Conclusion: An increase in plasma and urine DNA was unprecedentedly reported over time, a fact that may come in handy in the prognosis of patients. Furthermore, microscopic haematuria is correlated with plasma and urinary DNA levels.

A Systematic Review of the Diagnostic and Prognostic Value of Urinary Protein Biomarkers in Urothelial Bladder Cancer

For over 80 years, cystoscopy has remained the gold-standard for detecting tumours of the urinary bladder. Since bladder tumours have a tendency to recur and progress, many patients are subjected to repeated cystoscopies during long-term surveillance, with the procedure being both unpleasant for the patient and expensive for healthcare providers. The identification and validation of bladder tumour specific molecular markers in urine could enable tumour detection and reduce reliance on cystoscopy, and numerous classes of biomarkers have been studied. Proteins represent the most intensively studied class of biomolecule in this setting. As an aid to researchers searching for better urinary biomarkers, we report a comprehensive systematic review of the literature and a searchable database of proteins that have been investigated to date. Our objective was to classify these proteins as: 1) those with robustly characterised sensitivity and specificity for bladder cancer detection; 2) those that show potential but further investigation is required; 3) those unlikely to warrant further investigation; and 4) those investigated as prognostic markers. This work should help to prioritise certain biomarkers for rigorous validation, whilst preventing wasted effort on proteins that have shown no association whatsoever with the disease, or only modest biomarker performance despite large-scale efforts at validation.

A segregation index combining phenotypic (clinical characteristics) and genotypic (gene expression) biomarkers from a urine sample to triage out patients presenting with hematuria who have a low probability of urothelial carcinoma

Background

Hematuria can be symptomatic of urothelial carcinoma (UC) and ruling out patients with benign causes during primary evaluation is challenging. Patients with hematuria undergoing urological work-ups place significant clinical and financial burdens on healthcare systems. Current clinical evaluation involves processes that individually lack the sensitivity for accurate determination of UC. Algorithms and nomograms combining genotypic and phenotypic variables have largely focused on cancer detection and failed to improve performance. This study aimed to develop and validate a model incorporating both genotypic and phenotypic variables with high sensitivity and a high negative predictive value (NPV) combined to triage out patients with hematuria who have a low probability of having UC and may not require urological work-up.

Methods

Expression of IGFBP5, HOXA13, MDK, CDK1 and CXCR2 genes in a voided urine sample (genotypic) and age, gender, frequency of macrohematuria and smoking history (phenotypic) data were collected from 587 patients with macrohematuria. Logistic regression was used to develop predictive models for UC. A combined genotypic-phenotypic model (G + P INDEX) was compared with genotypic (G INDEX) and phenotypic (P INDEX) models. Area under receiver operating characteristic curves (AUC) defined the performance of each INDEX: high sensitivity, NPV >0.97 and a high test-negative rate was considered optimal for triaging out patients. The robustness of the G + P INDEX was tested in 40 microhematuria patients without UC.

Results

The G + P INDEX offered a bias-corrected AUC of 0.86 compared with 0.61 and 0.83, for the P and G INDEXs respectively. When the test-negative rate was 0.4, the G + P INDEX (sensitivity = 0.95; NPV = 0.98) offered improved performance compared with the G INDEX (sensitivity = 0.86; NPV = 0.96). 80% of patients with microhematuria who did not have UC were correctly triaged out using the G + P INDEX, therefore not requiring a full urological work-up.

Conclusion

The adoption of G + P INDEX enables a significant change in clinical utility. G + P INDEX can be used to segregate hematuria patients with a low probability of UC with a high degree of confidence in the primary evaluation. Triaging out low-probability patients early significantly reduces the need for expensive and invasive work-ups, thereby lowering diagnosis-related adverse events and costs.

Measuring midkine: the utility of midkine as a biomarker in cancer and other diseases

Midkine (MK) is a pleiotropic growth factor prominently expressed during embryogenesis but down-regulated to neglible levels in healthy adults. Many published studies have demonstrated striking MK overexpression compared with healthy controls in various pathologies, including ischaemia, inflammation, autoimmunity and, most notably, in many cancers. MK expression is detectable in biopsies of diseased, but not healthy, tissues. Significantly, because it is a soluble cytokine, elevated MK is readily apparent in the blood and other body fluids such as urine and CSF, making MK a relatively convenient, accessible, non-invasive and inexpensive biomarker for population screening and early disease detection. The first diagnostic tests that quantify MK are just now receiving regulatory clearance and entering the clinic. This review examines the current state of knowledge pertaining to MK as a biomarker and highlights promising indications and clinical settings where measuring MK could make a difference to patient treatment. I also raise outstanding questions about reported variants of MK as well as MK's bio-distribution in vivo. Answering these questions in future studies will enhance our understanding of the significance of measured MK levels in both patients and healthy subjects, and may reveal further opportunities for measuring MK to diagnose disease. MK has already proven to be a biomarker that can significantly improve detection, management and treatment of cancer, and there is significant promise for developing further MK-based diagnostics in the future.

Preliminary evaluation of urinary soluble Met as a biomarker for urothelial carcinoma of the bladder

BACKGROUND

Among genitourinary malignancies, bladder cancer (BCa) ranks second in both prevalence and cause of death. Biomarkers of BCa for diagnosis, prognosis and disease surveillance could potentially help prevent progression, improve survival rates and reduce health care costs. Among several oncogenic signaling pathways implicated in BCa progression is that of hepatocyte growth factor (HGF) and its cell surface receptor, Met, now targeted by 25 experimental anti-cancer agents in human clinical trials. The involvement of this pathway in several cancers is likely to preclude the use of urinary soluble Met (sMet), which has been correlated with malignancy, for initial BCa screening. However, its potential utility as an aid to disease surveillance and to identify patients likely to benefit from HGF/Met-targeted therapies provide the rationale for this preliminary retrospective study comparing sMet levels between benign conditions and primary BCa, and in BCa cases, between different disease stages.

METHODS

Normally voided urine samples were collected from patients with BCa (Total: 183; pTa: 55, pTis: 62, pT1: 24, pT2: 42) and without BCa (Total: 83) on tissue-procurement protocols at three institutions and sMet was measured and normalized to urinary creatinine. Normalized sMet values grouped by pathologic stage were compared using non-parametric tests for correlation and significant difference. ROC analyses were used to derive classification models for patients with or without BCa and patients with or without muscle-invasive BCa (MIBCa or NMIBCa).

RESULTS

Urinary sMet levels accurately distinguished patients with BCa from those without (p<0.0001, area under the curve (AUC): 0.7008) with limited sensitivity (61%) and moderate specificity (76%), and patients with MIBCa (n=42) from those with NMIBCa (n=141; p<0.0001, AUC: 0.8002) with moderate sensitivity and specificity (76% and 77%, respectively) and low false negative rate (8%).

CONCLUSIONS

Urinary sMet levels distinguish patients with BCa from those without, and patients with or without MIBCa, suggesting the potential utility of urinary sMet as a BCa biomarker for surveillance following initial treatment. Further studies are warranted to determine its potential value for prognosis in advanced disease, predicting treatment response, or identifying patients likely to benefit from Met-targeted therapies.

Thrombomodulin expression regulates tumorigenesis in bladder cancer

Background

The identification of potential tumor markers will help improve therapeutic planning and patient management. Thrombomodulin (TM) is a sensitive urothelial marker. TM was reported to be one of the endogenous anti-metastatic factors and has diagnostic and prognostic values for the progression of carcinoma. In the present study, we examine the role of TM in bladder cancer.

Methods

We studied the role of TM in tumor behavior and related signaling pathways in vitro using the human bladder cancer cell lines HT1376, HT1197, J82 and T24, and in vivo using animal models. We also selected clinical specimens from 100 patients with bladder cancer for immunohistochemical staining to evaluate the predictive capacity of TM in tumor invasiveness.

Results

The data revealed that positive immunoreactivity for TM was inversely correlated with clinical stage and DNA methyltransferase 1 immunoreactivity. Decreased TM expression could predict the aggressive tumor growth and advanced clinical stage in bladder cancer. When TM was inhibited, tumor growth rate and invasion ability were augmented in vitro and in vivo. The underlying changes included increased cell proliferation, enhanced epithelial-mesenchymal transition (EMT) and angiogenesis. Moreover, inhibition of NF-κB activation significantly increased TM expression and attenuated tumor aggressiveness in bladder cancer.

Conclusions

TM plays an important role in bladder cancer tumor aggressiveness in vitro and in vivo and is a clinically significant predictor that may represent a suitable therapeutic target for bladder cancer.

Automated quantification of FISH signals in urinary cells enables the assessment of chromosomal aberration patterns characteristic for bladder cancer

Targeting the centromeres of chromosomes 3, 7, 17 (CEP3, 7, 17) and the 9p21-locus (LSI9p21) for diagnosing bladder cancer (BC) is time- and cost-intensive and requires a manual investigation of the sample by a well-trained investigator thus overall limiting its use in clinical diagnostics and large-scaled epidemiological studies. Here we introduce a new computer-assisted FISH spot analysis tool enabling an automated, objective and quantitative assessment of FISH patterns in the urinary sediment. Utilizing a controllable microscope workstation, the microscope software Scan^R was programmed to allow automatic batch-scanning of up to 32 samples and identifying quadruple FISH signals in DAPI-scanned nuclei of urinary sediments. The assay allowed a time- and cost-efficient, automated and objective assessment of CEP3, 7 and 17 FISH signals and facilitated the quantification of nuclei harboring specific FISH patterns in all cells of the urinary sediment. To explore the diagnostic capability of the developed tool, we analyzed the abundance of 51 different FISH patterns in a pilot set of urine specimens from 14 patients with BC and 21 population controls (PC). Herein, the results of the fully automated approach yielded a high degree of conformity when compared to those obtained by an expert-guided re-evaluation of archived scans. The best cancer-identifying pattern was characterized by a concurrent gain of CEP3, 7 and 17. Overall, our automated analysis refines current FISH protocols and encourages its use to establish reliable diagnostic cutoffs in future large-scale studies with well-characterized specimens-collectives.

The use of molecular analyses in voided urine for the assessment of patients with hematuria

Introduction

Patients presenting with painless hematuria form a large part of the urological patient population. In many cases, especially in younger patients, the cause of hematuria is harmless. Nonetheless, hematuria could be a symptom of malignant disease and hence most patients will be subject to cystoscopy. In this study, we aimed to develop a prediction model based on methylation markers in combination with clinical variables, in order to stratify patients with high risk for bladder cancer.

Material and Methods

Patients (n=169) presenting with painless hematuria were included. 54 patients were diagnosed with bladder cancer. In the remaining 115 patients, the cause of hematuria was non-malignant. Urine samples were collected prior to cystoscopy. Urine DNA was analyzed for methylation of OSR1, SIM2, OTX1, MEIS1 and ONECUT2. Methylation percentages were calculated and were combined with clinical variables into a logistic regression model.

Results

Logistic regression analysis based on the five methylation markers, age, gender and type of hematuria resulted in an area under the curve (AUC) of 0.88 and an optimism corrected AUC of 0.84 after internal validation by bootstrapping. Using a cut-off value of 0.307 allowed stratification of patients in a low-risk and high-risk group, resulting in a sensitivity of 82% (44/54) and a specificity of 82% (94/115). Most aggressive tumors were found in patients in the high-risk group. The addition of cytology to the prediction model, improved the AUC from 0.88 to 0.89, with a sensitivity and specificity of 85% (39/46) and 87% (80/92), retrospectively.

Conclusions

This newly developed prediction model could be a helpful tool in risk stratification of patients presenting with painless hematuria. Accurate risk prediction might result in less extensive examination of low risk patients and thereby, reducing patient burden and costs. Further validation in a large prospective patient cohort is necessary to prove the true clinical value of this model.

Bladder cancer detection and monitoring: assessment of urine- and blood-based marker tests

Bladder cancer is one of the most prevalent cancers worldwide, but the treatment and management of this disease can be very successful if the disease is detected early. The development of molecular assays that could diagnose bladder cancer accurately, and at an early stage, would be a significant advance. Ideally, such molecular assays would be applicable to non-invasively obtained body fluids, and be designed not only for diagnosis but also for monitoring disease recurrence and response to treatment. In this article, we assess the performance of current diagnostic assays for bladder cancer and discuss some of the emerging biomarkers that could be developed to augment current bladder cancer detection strategies.

A pilot study combining a GC-sensor device with a statistical model for the identification of bladder cancer from urine headspace

There is a need to reduce the number of cystoscopies on patients with haematuria. Presently there are no reliable biomarkers to screen for bladder cancer. In this paper, we evaluate a new simple in–house fabricated, GC-sensor device in the diagnosis of bladder cancer based on volatiles. Sensor outputs from 98 urine samples were used to build and test diagnostic models. Samples were taken from 24 patients with transitional (urothelial) cell carcinoma (age 27-91 years, median 71 years) and 74 controls presenting with urological symptoms, but without a urological malignancy (age 29-86 years, median 64 years); results were analysed using two statistical approaches to assess the robustness of the methodology. A two-group linear discriminant analysis method using a total of 9 time points (which equates to 9 biomarkers) correctly assigned 24/24 (100%) of cancer cases and 70/74 (94.6%) controls. Under leave-one-out cross-validation 23/24 (95.8%) of cancer cases were correctly predicted with 69/74 (93.2%) of controls. For partial least squares discriminant analysis, the correct leave-one-out cross-validation prediction values were 95.8% (cancer cases) and 94.6% (controls). These data are an improvement on those reported by other groups studying headspace gases and also superior to current clinical techniques. This new device shows potential for the diagnosis of bladder cancer, but the data must be reproduced in a larger study.

Proteomic studies of urinary biomarkers for prostate, bladder and kidney cancers

Urine is an ideal body fluid for the detection of protein markers produced by urological cancers as it can be sampled noninvasively and contains secreted and directly shed proteins from the prostate, bladder and kidney. Major challenges of working with urine include high inter-individual and intra-individual variability, low protein concentration, the presence of salts and the dynamic range of protein expression. Despite these challenges, significant progress is being made using modern proteomic methods to identify and characterize protein-based markers for urological cancers. The development of robust, easy-to-use clinical tests based on novel biomarkers has the potential to impact upon diagnosis, prognosis and monitoring and could revolutionize the treatment and management of these cancers.

Collectives of diagnostic biomarkers identify high-risk subpopulations of hematuria patients: exploiting heterogeneity in large-scale biomarker data

BACKGROUND

Ineffective risk stratification can delay diagnosis of serious disease in patients with hematuria. We applied a systems biology approach to analyze clinical, demographic and biomarker measurements (n = 29) collected from 157 hematuric patients: 80 urothelial cancer (UC) and 77 controls with confounding pathologies.

METHODS

On the basis of biomarkers, we conducted agglomerative hierarchical clustering to identify patient and biomarker clusters. We then explored the relationship between the patient clusters and clinical characteristics using Chi-square analyses. We determined classification errors and areas under the receiver operating curve of Random Forest Classifiers (RFC) for patient subpopulations using the biomarker clusters to reduce the dimensionality of the data.

RESULTS

Agglomerative clustering identified five patient clusters and seven biomarker clusters. Final diagnoses categories were non-randomly distributed across the five patient clusters. In addition, two of the patient clusters were enriched with patients with 'low cancer-risk' characteristics. The biomarkers which contributed to the diagnostic classifiers for these two patient clusters were similar. In contrast, three of the patient clusters were significantly enriched with patients harboring 'high cancer-risk" characteristics including proteinuria, aggressive pathological stage and grade, and malignant cytology. Patients in these three clusters included controls, that is, patients with other serious disease and patients with cancers other than UC. Biomarkers which contributed to the diagnostic classifiers for the largest 'high cancer- risk' cluster were different than those contributing to the classifiers for the 'low cancer-risk' clusters. Biomarkers which contributed to subpopulations that were split according to smoking status, gender and medication were different.

CONCLUSIONS

The systems biology approach applied in this study allowed the hematuric patients to cluster naturally on the basis of the heterogeneity within their biomarker data, into five distinct risk subpopulations. Our findings highlight an approach with the promise to unlock the potential of biomarkers. This will be especially valuable in the field of diagnostic bladder cancer where biomarkers are urgently required. Clinicians could interpret risk classification scores in the context of clinical parameters at the time of triage. This could reduce cystoscopies and enable priority diagnosis of aggressive diseases, leading to improved patient outcomes at reduced costs.

Standardization of diagnostic biomarker concentrations in urine: the hematuria caveat

Sensitive and specific urinary biomarkers can improve patient outcomes in many diseases through informing early diagnosis. Unfortunately, to date, the accuracy and translation of diagnostic urinary biomarkers into clinical practice has been disappointing. We believe this may be due to inappropriate standardization of diagnostic urinary biomarkers. Our objective was therefore to characterize the effects of standardizing urinary levels of IL-6, IL-8, and VEGF using the commonly applied standards namely urinary creatinine, osmolarity and protein. First, we report results based on the biomarker levels measured in 120 hematuric patients, 80 with pathologically confirmed bladder cancer, 27 with confounding pathologies and 13 in whom no underlying cause for their hematuria was identified, designated "no diagnosis". Protein levels were related to final diagnostic categories (p = 0.022, ANOVA). Osmolarity (mean = 529 mOsm; median = 528 mOsm) was normally distributed, while creatinine (mean = 10163 µmol/l, median = 9350 µmol/l) and protein (0.3297, 0.1155 mg/ml) distributions were not. When we compared AUROCs for IL-6, IL-8 and VEGF levels, we found that protein standardized levels consistently resulted in the lowest AUROCs. The latter suggests that protein standardization attenuates the "true" differences in biomarker levels across controls and bladder cancer samples. Second, in 72 hematuric patients; 48 bladder cancer and 24 controls, in whom urine samples had been collected on recruitment and at follow-up (median = 11 (1 to 20 months)), we demonstrate that protein levels were approximately 24% lower at follow-up (Bland Altman plots). There was an association between differences in individual biomarkers and differences in protein levels over time, particularly in control patients. Collectively, our findings identify caveats intrinsic to the common practice of protein standardization in biomarker discovery studies conducted on urine, particularly in patients with hematuria.

Molecular diagnostic trends in urological cancer: biomarkers for non-invasive diagnosis

The early detection of urological cancers is pivotal for successful patient treatment and management. The development of molecular assays that can diagnose disease accurately, or that can augment current methods of evaluation, would be a significant advance. Ideally, such molecular assays would be applicable to non-invasively obtained body fluids, enabling not only diagnosis of at risk patients, but also asymptomatic screening, monitoring disease recurrence and response to treatment. The advent of advanced proteomics and genomics technologies and associated bioinformatics development is bringing these goals into focus. In this article we will discuss the promise of biomarkers in urinalysis for the detection and clinical evaluation of the major urological cancers, including bladder, kidney and prostate. The development of urine-based tests to detect urological cancers would be of tremendous benefit to both patients and the healthcare system.

Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers

Three common urological diseases are bladder cancer, urinary tract infection, and hematuria. Seventeen bladder cancer biomarkers were previously discovered using iTRAQ - these findings were verified by MRM-MS in this current study. Urine samples from 156 patients with hernia (n=57, control), bladder cancer (n=76), or urinary tract infection/hematuria (n=23) were collected and subjected to multiplexed LC-MRM/MS to determine the concentrations of 63 proteins that are normally considered to be plasma proteins, but which include proteins found in our earlier iTRAQ study. Sixty-five stable isotope-labeled standard proteotypic peptides were used as internal standards for 63 targeted proteins. Twelve proteins showed higher concentrations in the bladder cancer group than in the hernia and the urinary tract infection/hematuria groups, and thus represent potential urinary biomarkers for detection of bladder cancer. Prothrombin had the highest AUC (0.796), with 71.1% sensitivity and 75.0% specificity for differentiating bladder cancer (n=76) from non-cancerous (n=80) patients. The multiplexed MRM-MS data was used to generate a six-peptide marker panel. This six-peptide panel (afamin, adiponectin, complement C4 gamma chain, apolipoprotein A-II precursor, ceruloplasmin, and prothrombin) can discriminate bladder cancer subjects from non-cancerous subjects with an AUC of 0.814, with a 76.3% positive predictive value, and a 77.5% negative predictive value. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.