Urinary Protein Markers for the Detection and Prognostication of Urothelial Carcinoma

A Diagnostic Gene Expression Signature for Bladder Cancer Can Stratify Cases into Prescribed Molecular Subtypes and Predict Outcome

Bladder cancer is a biologically heterogeneous disease with variable clinical presentations, outcomes and responses to therapy. Thus, the clinical utility of single biomarkers for the detection and prediction of biological behavior of bladder cancer is limited. We have previously identified and validated a bladder cancer diagnostic signature composed of 10 biomarkers, which has been incorporated into a multiplex immunoassay bladder cancer test, Oncuria™. In this study, we evaluate whether these 10 biomarkers can assist in the prediction of bladder cancer clinical outcomes. Tumor gene expression and patient survival data from bladder cancer cases from The Cancer Genome Atlas (TCGA) were analyzed. Alignment between the mRNA expression of 10 biomarkers and the TCGA 2017 subtype classification was assessed. Kaplan-Meier analysis of multiple gene expression datasets indicated that high expression of the combined 10 biomarkers correlated with a significant reduction in overall survival. The analysis of three independent, publicly available gene expression datasets confirmed that multiplex prognostic models outperformed single biomarkers. In total, 8 of the 10 biomarkers from the Oncuria™ test were significantly associated with either luminal or basal molecular subtypes, and thus, the test has the potential to assist in the prediction of clinical outcome.

Diagnostic panel of serum miR-125b-5p, miR-182-5p, and miR-200c-3p as non-invasive biomarkers for urothelial bladder cancer

PURPOSE

This study aimed to identify a diagnostic panel of serum microRNAs (miRNAs) for the early detection of bladder cancer (BC).

METHODS

Serum samples were collected from 112 BC patients and 112 normal controls (NCs). A three-stage selection was conducted to identify differentially expressed miRNAs as candidates to construct the diagnostic panel. Further, to explore their potential roles in urothelial BC, bioinformatics analyses, including target genes prediction and functional annotation, were used.

RESULTS

Six downregulated miRNAs (miR-1-3p, miR-30a-5p, miR-100-5p, miR-125b-5p, miR-143-3p, and miR-200c-3p) and one upregulated, miR-182-5p, in BC patients' serum were detected compared to NCs and were selected to establish the diagnostic panel. Based on a backward stepwise logistic regression analysis, miR-125b-5p, miR-182-5p, and miR-200c-3p comprehended the diagnostic panel [area under the curve (AUC) = 0.959, sensitivity = 91.67%, specificity = 92.5%].

CONCLUSION

The panel of three miRNAs had an excellent diagnostic capability, representing a potential non-invasive method for early BC detection.

Discovery of Novel Protein Biomarkers in Urine for Diagnosis of Urothelial Cancer Using iTRAQ Proteomics

Urothelial carcinoma (UC) is the ninth most prevalent malignancy worldwide. Noninvasive and efficient biomarkers with high accuracy are imperative for the surveillance and diagnosis of UC. CKD patients were enrolled as a control group in this study for the discovery of highly specific urinary protein markers of UC. An iTRAQ-labeled quantitative proteomic approach was used to discover novel potential markers. These markers were further validated with 501 samples by ELISA assay, and their diagnostic accuracies were compared to those of other reported UC markers. BRDT, CYBP, GARS, and HDGF were identified as novel urinary UC biomarkers with a high discrimination ability in a population comprising CKD and healthy subjects. The diagnostic values of the four novel UC markers were better than that of a panel of well-known or FDA-approved urinary protein markers CYFR21.1, Midkine, and NUMA1. Three of our discovered markers (BRDT, HDGF, GARS) and one well-known marker (CYFR21.1) were finally selected and combined as a marker panel having AUC values of 0.962 (95% CI, 0.94-0.98) and 0.860 (95% CI, 0.83-0.89) for the discrimination between UC and normal groups and UC and control (healthy + CKD) groups, respectively.

Raman chemometric urinalysis (Rametrix) as a screen for bladder cancer

Bladder cancer (BCA) is relatively common and potentially recurrent/progressive disease. It is also costly to detect, treat, and control. Definitive diagnosis is made by examination of urine sediment, imaging, direct visualization (cystoscopy), and invasive biopsy of suspect bladder lesions. There are currently no widely-used BCA-specific biomarker urine screening tests for early BCA or for following patients during/after therapy. Urine metabolomic screening for biomarkers is costly and generally unavailable for clinical use. In response, we developed Raman spectroscopy-based chemometric urinalysis (Rametrix™) as a direct liquid urine screening method for detecting complex molecular signatures in urine associated with BCA and other genitourinary tract pathologies. In particular, the Rametrix^TM screen used principal components (PCs) of urine Raman spectra to build discriminant analysis models that indicate the presence/absence of disease. The number of PCs included was varied, and all models were cross-validated by leave-one-out analysis. In Study 1 reported here, we tested the Rametrix™ screen using urine specimens from 56 consented patients from a urology clinic. This proof-of-concept study contained 17 urine specimens with active BCA (BCA-positive), 32 urine specimens from patients with other genitourinary tract pathologies, seven specimens from healthy patients, and the urinalysis control Surine^TM. Using a model built with 22 PCs, BCA was detected with 80.4% accuracy, 82.4% sensitivity, 79.5% specificity, 63.6% positive predictive value (PPV), and 91.2% negative predictive value (NPV). Based on the number of PCs included, we found the Rametrix^TM screen could be fine-tuned for either high sensitivity or specificity. In other studies reported here, Rametrix^TM was also able to differentiate between urine specimens from patients with BCA and other genitourinary pathologies and those obtained from patients with end-stage kidney disease (ESKD). While larger studies are needed to improve Rametrix^TM models and demonstrate clinical relevance, this study demonstrates the ability of the Rametrix^TM screen to differentiate urine of BCA-positive patients. Molecular signature variances in the urine metabolome of BCA patients included changes in: phosphatidylinositol, nucleic acids, protein (particularly collagen), aromatic amino acids, and carotenoids.

Comparison of Commercial ELISA Kits, a Prototype Multiplex Electrochemoluminescent Assay, and a Multiplex Bead-Based Immunoassay for Detecting a Urine-Based Bladder-Cancer-Associated Diagnostic Signature

The ability to accurately measure multiple proteins simultaneously in a single assay has the potential to markedly improve the efficiency of clinical tests composed of multiple biomarkers. We investigated the diagnostic accuracy of the two multiplex protein array platforms for detecting a bladder-cancer-associated diagnostic signature in samples from a cohort of 80 subjects (40 with bladder cancer). Banked urine samples collected from Kyoto and Nara Universities were compared to histologically determined bladder cancer. The concentrations of the 10 proteins (A1AT; apolipoprotein E—APOE; angiogenin—ANG; carbonic anhydrase 9—CA9; interleukin 8—IL-8; matrix metalloproteinase 9—MMP-9; matrix metalloproteinase 10—MMP10; plasminogen activator inhibitor 1—PAI-1; syndecan—SDC1; and vascular endothelial growth factor—VEGF) were monitored using two prototype multiplex array platforms and an enzyme-linked immunosorbent assay (ELISA) according to the manufacturer’s technical specifications. The range for detecting each biomarker was improved in the multiplex assays, even though the lower limit of quantification (LLOQ) was typically lower in the commercial ELISA kits. The area under the receiver operating characteristics (AUROC) of the prototype multiplex assays was reported to be 0.97 for the multiplex bead-based immunoassay (MBA) and 0.86 for the multiplex electrochemoluminescent assay (MEA). The sensitivities and specificities for MBA were 0.93 and 0.95, respectively, and for MEA were 0.85 and 0.80, respectively. Accuracy, positive predictive values (PPV), and negative predictive values (NPV) for MBA were 0.94, 0.95, and 0.93, respectively, and for MEA were 0.83, 0.81, and 0.84, respectively. Based on these encouraging preliminary data, we believe that a multiplex protein array is a viable platform that can be utilized as an efficient and highly accurate tool to quantitate multiple proteins within biologic specimens.