A microRNA biomarker panel for the non-invasive detection of bladder cancer.

The development of accurate, non-invasive urinary assays for bladder cancer would greatly facilitate the detection and management of a disease that has a high rate of recurrence and progression. In this study, we employed a discovery and validation strategy to identify microRNA signatures that can perform as a non-invasive bladder cancer diagnostic assay. Expression profiling of 754 human microRNAs (TaqMan low density arrays) was performed on naturally voided urine samples from a cohort of 85 subjects of known bladder disease status (27 with active BCa). A panel of 46 microRNAs significantly associated with bladder cancer were subsequently monitored in an independent cohort of 121 subjects (61 with active BCa) using quantitative real-time PCR (RT-PCR). Multivariable modeling identified a 25-target diagnostic signature that predicted the presence of BCa with an estimated sensitivity of 87% at a specificity of 100% (AUC 0.982). With additional validation, the monitoring of a urinary microRNA biomarker panel could facilitate the non-invasive evaluation of patients under investigation for BCa.

Urinary mRNA biomarker panel for the detection of urothelial carcinoma.

The early detection of bladder cancer is important as the disease has a high rate of recurrence and progression. The development of accurate, non-invasive urinary assays would greatly facilitate detection. In previous studies, we have reported the discovery and initial validation of mRNA biomarkers that may be applicable in this context. In this study, we evaluated the diagnostic performance of proposed molecular signatures in an independent cohort.Forty-four mRNA transcripts were monitored blindly in urine samples obtained from a cohort of 196 subjects with known bladder disease status (89 with active BCa) using quantitative real-time PCR (RT-PCR). Statistical analyses defined associations of individual biomarkers with clinical data and the performance of predictive multivariate models was assessed using ROC curves. The majority of the candidate mRNA targets were confirmed as being associated with the presence of BCa over other clinical variables. Multivariate models identified an optimal 18-gene diagnostic signature that predicted the presence of BCa with a sensitivity of 85% and a specificity of 88% (AUC 0.935). Analysis of mRNA signatures in naturally micturated urine samples can provide valuable information for the evaluation of patients under investigation for BCa. Additional refinement and validation of promising multi-target signatures will support the development of accurate assays for the non-invasive detection and monitoring of BCa.

External validation of a multiplex urinary protein panel for the detection of bladder cancer in a multicenter cohort.

BACKGROUND: Because of the faltering sensitivity and/or specificity, urine-based assays currently have a limited role in the management of patients with bladder cancer. The aim of this study was to externally validate our previously reported protein biomarker panel from multiple sites in the United States and Europe. METHODS: This multicenter external validation study included a total of 320 subjects (bladder cancer = 183). The 10 biomarkers (IL8, MMP9, MMP10, SERPINA1, VEGFA, ANG, CA9, APOE, SDC1, and SERPINE1) were measured using commercial ELISA assays in an external laboratory. The diagnostic performance of the biomarker panel was assessed using receiver operator curves (ROC) and descriptive statistical values. RESULTS: Utilizing the combination of all 10 biomarkers, the area under the ROC for the diagnostic panel was noted to be 0.847 (95% confidence interval, 0.796-0.899), outperforming any single biomarker. The multiplex assay at optimal cutoff value achieved an overall sensitivity of 0.79, specificity of 0.79, positive prediction value of 0.73, and negative prediction value of 0.84 for bladder cancer classification. Sensitivity values of the diagnostic panel for high-grade bladder cancer, low-grade bladder cancer, muscle invasive bladder cancer, and non-muscle invasive bladder cancer were 0.81, 0.90, 0.95, and 0.77, respectively. CONCLUSIONS: Urinary levels of the biomarker panel enabled discrimination of patients with bladder cancer and controls, and the levels of biomarker subsets were associated with advancing tumor grade and stage. IMPACT: If proven to be reliable, urinary diagnostic biomarker assays can detect bladder cancer in a timely manner such that the patient can expect improvements in overall survival and quality of life.

Chemokine (C-X-C motif) ligand 1 (CXCL1) protein expression is increased in high-grade prostate cancer.

Chemokines, including chemokine (C-X-C motif) ligand 1 (CXCL1), may enhance tumor epithelial-stromal interactions facilitating tumor growth and invasion. Studies have linked CXCL1 expression to gastric, colon and skin cancers, however, no study to date has been reported describing CXCL1 in human prostate tumors. Herein, we set out to describe the expression pattern of CXCL1 in human prostate tumors. Utilizing a commercial tissue microarray, immunohistochemical staining was used to monitor CXCL1 protein expression in 90 primary prostate tumors and 20 benign prostate tissues. CXCL1 protein expression was noted to be predominantly in the cytoplasm of both the benign epithelia glands and cancerous epithelia glands) with >75% of benign or cancerous glands demonstrating immunoreactivity. However, staining intensity was noted to be significantly different between benign and cancerous tissue with 84% of cancerous tissue staining moderate (++) to strong (+++) compared to only 30% of benign prostate samples staining moderate (++) to strong (+++) (p<0.0001). Increased CXCL1 protein levels were associated with higher-grade tumors (Gleason≤6 vs. Gleason score 7-10, p=0.038). An increase in CXCL1 protein was present in of high-grade malignancy. Further studies are warranted to clearly define the role of CXCL1 in prostate cancer.

Urinary biomarkers of bladder cancer: an update and future perspectives.

Bladder cancer is one of the most prevalent cancers worldwide. Early detection of bladder tumors is critical for improved patient outcomes. The standard method for detection and surveillance of bladder tumors is cystoscopy with urinary cytology. Limitations of cystoscopy and urinary cytology have brought to light the need for more robust diagnostic assays. Ideally, such assays would be applicable to noninvasively obtained, voided urine, and be designed not only for diagnosis, but also for monitoring disease recurrence and response to therapy. Consequently, the development of a noninvasive urine-based assay would be of tremendous benefit to both patients and healthcare systems. This article reports some of the more prominent urine-based biomarkers reported in the literature. In addition, some new technologies that have been used to identify novel urinary biomarkers are highlighted.

Chemokine (C-X-C) ligand 1 (CXCL1) protein expression is increased in aggressive bladder cancers.

BACKGROUND: Chemokines, including chemokine (C-X-C motif) ligand 1 (CXCL1), may regulate tumor epithelial-stromal interactions that facilitate tumor growth and invasion. Studies have linked CXCL1 expression to gastric, colon and skin cancers, but limited studies to date have described CXCL1 protein expression in human bladder cancer (BCa). METHODS: CXCL1 protein expression was examined in 152 bladder tissue specimens (142 BCa) by immunohistochemical staining. The expression of CXCL1 was scored by assigning a combined score based on the proportion of cells staining and intensity of staining. CXCL1 expression patterns were correlated with clinicopathological features and follow-up data. RESULTS: CXCL1 protein expression was present in cancerous tissues, but was entirely absent in benign tissue. CXCL1 combined immunostaining score was significantly higher in high-grade tumors relative to low-grade tumors (p = 0.012). Similarly, CXCL1 combined immunostaining score was higher in high stage tumors (T2-T4) than in low stage tumors (Ta-T1) (p < 0.0001). An increase in the combined immunostaining score of CXCL1 was also associated with reduced disease-specific survival. CONCLUSION: To date, this is the largest study describing increased CXCL1 protein expression in more aggressive phenotypes in human BCa. Further studies are warranted to define the role CXCL1 plays in bladder carcinogenesis and progression.

Multiplex protein signature for the detection of bladder cancer in voided urine samples.

PURPOSE: Accurate urine assays for bladder cancer detection would benefit patients and health care systems. Through extensive genomic and proteomic profiling of urine components we previously identified a panel of 8 biomarkers that can facilitate the detection of bladder cancer in voided urine samples. In this study we confirmed this diagnostic molecular signature in a diverse multicenter cohort. MATERIALS AND METHODS: We performed a case-control, phase II study in which we analyzed voided urine from 102 subjects with bladder cancer and 206 with varying urological disorders. The urinary concentration of 8 biomarkers (IL-8, MMP-9 and 10, PAI-1, VEGF, ANG, CA9 and APOE) was assessed by enzyme-linked immunosorbent assay. Diagnostic performance of the panel of tested biomarkers was evaluated using ROCs and descriptive statistical values, eg sensitivity and specificity. RESULTS: Seven of the 8 urine biomarkers were increased in subjects with bladder cancer relative to those without bladder cancer. The 7 biomarkers were assessed in a new model, which had an AUROC of 0.88 (95% CI 0.84-0.93), and 74% sensitivity and 90% specificity. In contrast, the sensitivity of voided urine cytology and the UroVysion® cytogenetic test in this cohort was 39% and 54%, respectively. Study limitations include analysis performed on banked urine samples and the lack of voided urine cytology and cytogenetic test data on controls. CONCLUSIONS: The study provides further evidence that the reported panel of diagnostic biomarkers can reliably achieve the noninvasive detection of bladder cancer with higher sensitivity than currently available urine based assays.

Expression of CXCL1 in human endothelial cells induces angiogenesis through the CXCR2 receptor and the ERK1/2 and EGF pathways.

Endothelial cell growth and proliferation are critical for angiogenesis; thus, greater insight into the regulation of pathological angiogenesis is greatly needed. Previous studies have reported on chemokine (C-X-C motif) ligand 1 (CXCL1) expression in epithelial cells and that secretion of CXCL1 from these epithelial cells induces angiogenesis. However, limited reports have demonstrated CXCL1 expression in endothelial cells. In this report, we present data that expand on the role of CXCL1 in human endothelial cells inducing angiogenesis. Specifically, CXCL1 is expressed and secreted from human endothelial cells. Interference of CXCL1 function using neutralizing antibodies resulted in a reduction in endothelial cell migration and viability/proliferation, the latter associated with a decrease in levels of cyclin D and cdk4. In vitro studies revealed that CXCL1 influenced neoangiogenesis through the regulation of epidermal growth factor and ERK1/2. In a xenograft angiogenesis model, interference of CXCL1 function resulted in inhibition of angiogenesis. A better understanding of the role of CXCL1 in the interactions between the endothelial and epithelial components will provide insight into how human tissues use CXCL1 to survive and thrive in a hostile environment.

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.

Complete Genome Sequence of Mycoplasma hyorhinis Strain SK76.

Mycoplasma hyorhinis is a eubacterium belonging to the Mollicutes class and is responsible for porcine respiratory and arthritic diseases. It is also the major contaminant of mammalian tissue cultures in laboratories worldwide. Here, we report the complete genome sequence of M. hyorhinis strain SK76.

MULTIPLEX URINARY TESTS FOR BLADDER CANCER DIAGNOSIS.

The development of accurate and reliable molecular assays that could diagnose bladder cancer would be of significant benefit to both patients and the healthcare system. Non-invasive assays that have utility not only for diagnosis, but also for monitoring disease recurrence and response to treatment, are needed. Current urinary tests lack sufficient sensitivity or specificity, often because of a reliance on single biomarkers, but high-throughput technologies are enabling the derivation of more accurate panels of biomarkers. In this article, we review some of the promising investigational studies that are revealing multiplex biomarker signatures that may augment current bladder cancer detection strategies.

A multi-analyte assay for the non-invasive detection of bladder cancer.

Accurate urinary assays for bladder cancer (BCa) detection would benefit both patients and healthcare systems. Through genomic and proteomic profiling of urine components, we have previously identified a panel of biomarkers that can outperform current urine-based biomarkers for the non-invasive detection of BCa. Herein, we report the diagnostic utility of various multivariate combinations of these biomarkers. We performed a case-controlled validation study in which voided urines from 127 patients (64 tumor bearing subjects) were analyzed. The urinary concentrations of 14 biomarkers (IL-8, MMP-9, MMP-10, SDC1, CCL18, PAI-1, CD44, VEGF, ANG, CA9, A1AT, OPN, PTX3, and APOE) were assessed by enzyme-linked immunosorbent assay (ELISA). Diagnostic performance of each biomarker and multivariate models were compared using receiver operating characteristic curves and the chi-square test. An 8-biomarker model achieved the most accurate BCa diagnosis (sensitivity 92%, specificity 97%), but a combination of 3 of the 8 biomarkers (IL-8, VEGF, and APOE) was also highly accurate (sensitivity 90%, specificity 97%). For comparison, the commercial BTA-Trak ELISA test achieved a sensitivity of 79% and a specificity of 83%, and voided urine cytology detected only 33% of BCa cases in the same cohort. These data show that a multivariate urine-based assay can markedly improve the accuracy of non-invasive BCa detection. Further validation studies are under way to investigate the clinical utility of this panel of biomarkers for BCa diagnosis and disease monitoring.

A candidate molecular biomarker panel for the detection of bladder cancer.

BACKGROUND: Bladder cancer is among the five most common malignancies worldwide, and due to high rates of recurrence, one of the most prevalent. Improvements in noninvasive urine-based assays to detect bladder cancer would benefit both patients and health care systems. In this study, the goal was to identify urothelial cell transcriptomic signatures associated with bladder cancer. METHODS: Gene expression profiling (Affymetrix U133 Plus 2.0 arrays) was applied to exfoliated urothelia obtained from a cohort of 92 subjects with known bladder disease status. Computational analyses identified candidate biomarkers of bladder cancer and an optimal predictive model was derived. Selected targets from the profiling analyses were monitored in an independent cohort of 81 subjects using quantitative real-time PCR (RT-PCR). RESULTS: Transcriptome profiling data analysis identified 52 genes associated with bladder cancer (P ≤ 0.001) and gene models that optimally predicted class label were derived. RT-PCR analysis of 48 selected targets in an independent cohort identified a 14-gene diagnostic signature that predicted the presence of bladder cancer with high accuracy. CONCLUSIONS: Exfoliated urothelia sampling provides a robust analyte for the evaluation of patients with suspected bladder cancer. The refinement and validation of the multigene urothelial cell signatures identified in this preliminary study may lead to accurate, noninvasive assays for the detection of bladder cancer. IMPACT: The development of an accurate, noninvasive bladder cancer detection assay would benefit both the patient and health care systems through better detection, monitoring, and control of disease.

Diagnostic potential of urinary α1-antitrypsin and apolipoprotein E in the detection of bladder cancer.

PURPOSE: The ability to reliably diagnose bladder cancer in voided urine samples would be a major advance. Using high throughput technologies, we identified a panel of bladder cancer associated biomarkers with potential clinical usefulness. In this study we tested 4 potential biomarkers for the noninvasive detection of bladder cancer. MATERIALS AND METHODS: We examined voided urine specimens from 124 patients, including 63 newly diagnosed with bladder cancer and 61 controls. Concentrations of proteins were assessed by enzyme-linked immunosorbent assay, including α1-antitrypsin, apolipoprotein E, osteopontin and pentraxin 3. Data were compared to the results of urinary cytology and the BTA Trak® enzyme-linked immunosorbent assay based bladder cancer detection assay. We used the AUC of ROC curves to compare the usefulness of each biomarker to detect bladder cancer. RESULTS: Urinary levels of α1-antitrypsin, apolipoprotein E and bladder tumor antigen were significantly increased in subjects with bladder cancer. α1-Antitrypsin (AUC 0.9087, 95% CI 0.8555-0.9619) and apolipoprotein E (AUC 0.8987, 95% CI 0.8449-0.9525) were the most accurate biomarkers. The combination of α1-antitrypsin and apolipoprotein E (AUC 0.9399) achieved 91% sensitivity, 89% specificity, and a positive and negative predictive value of 89% and 90%, respectively. Multivariate regression analysis highlighted only apolipoprotein E as an independent predictor of bladder cancer (OR 24.9, 95% CI 4.22-146.7, p = 0.0004). CONCLUSIONS: Alone or in combination, α1-antitrypsin and apolipoprotein E show promise for the noninvasive detection of bladder cancer (OR 24.9, 95% CI 4.22-146.7, p = 0.0004). Larger, prospective studies including more low grade, low stage tumors are needed to confirm these results.

CCL18 in a multiplex urine-based assay for the detection of bladder cancer.

The early detection of bladder cancer (BCa) is pivotal for successful patient treatment and management. Through genomic and proteomic studies, we have identified a number of bladder cancer-associated biomarkers that have potential clinical utility. In a case-control study, we examined voided urines from 127 subjects: 64 tumor-bearing subjects and 63 controls. The urine concentrations of the following proteins were assessed by enzyme-linked immunosorbent assay (ELISA); C-C motif chemokine 18 (CCL18), Plasminogen Activator Inhibitor 1 (PAI-1) and CD44. Data were compared to a commercial ELISA-based BCa detection assay (BTA-Trak©) and voided urinary cytology. We used analysis of the area under the curve of receiver operating characteristic curves to compare the ability of CCL18, PAI-1, CD44, and BTA to detect BCa in voided urine samples. Urinary concentrations of CCL18, PAI-1, and BTA were significantly elevated in subjects with BCa. CCL18 was the most accurate biomarker (AUC; 0.919; 95% confidence interval [CI], 0.8704-0.9674). Multivariate regression analysis highlighted CCL18 (OR; 18.31; 95% CI, 4.95-67.70, p<0.0001) and BTA (OR; 6.43; 95% CI, 1.86-22.21, p = 0.0033) as independent predictors of BCa in voided urine samples. The combination of CCL18, PAI-1 and CD44 improved the area under the curve to 0.938. Preliminary results indicate that CCL18 was a highly accurate biomarker for BCa detection in this cohort. Monitoring CCL18 in voided urine samples has the potential to improve non-invasive tests for BCa diagnosis. Furthermore using the combination of CCL18, PAI-1 and CD44 may make the model more robust to errors to detect BCa over the individual biomarkers or BTA.

IL-8 as a urinary biomarker for the detection of bladder cancer.

BACKGROUND: Current urine-based assays for bladder cancer (BCa) diagnosis lack accuracy, so the search for improved biomarkers continues. Through genomic and proteomic profiling of urine, we have identified a panel of biomarkers associated with the presence of BCa. In this study, we evaluated the utility of three of these biomarkers, interleukin 8 (IL-8), Matrix metallopeptidase 9 (MMP-9) and Syndecan in the diagnosis of BCa through urinalysis. METHODS: Voided urines from 127 subjects, cancer subjects (n = 64), non-cancer subjects (n = 63) were analyzed. The protein concentrations of IL-8, MMP-9, and Syndecan were assessed by enzyme-linked immunosorbent assay (ELISA). Data were also compared to a commercial ELISA-based BCa detection assay (BTA-Trak©) and urinary cytology. We used the area under the curve of a receiver operating characteristic (AUROC) to compare the performance of each biomarker. RESULTS: Urinary protein concentrations of IL-8, MMP-9 and BTA were significantly elevated in BCa subjects. Of the experimental markers compared to BTA-Trak©, IL-8 was the most prominent marker (AUC; 0.79; 95% confidence interval [CI], 0.72-0.86). Multivariate regression analysis revealed that only IL-8 (OR; 1.51; 95% CI, 1.16-1.97, p = 0.002) was an independent factor for the detection of BCa. CONCLUSIONS: These results suggest that the measurement of IL-8 in voided urinary samples may have utility for urine-based detection of BCa. These findings need to be confirmed in a larger, prospective cohort.

Vascular endothelial growth factor, carbonic anhydrase 9, and angiogenin as urinary biomarkers for bladder cancer detection.

OBJECTIVE: To investigate whether elevated urinary levels of vascular endothelial growth factor (VEGF), carbonic anhydrase 9 (CA9), and angiogenin are associated with bladder cancer (BCa). METHODS: This was a case-control study in which voided urine samples from 127 patients (63 control subjects and 64 patients with BCa) were analyzed. The urinary concentrations of VEGF, CA9, angiogenin, and bladder tumor antigen (BTA) were assessed using enzyme-linked immunosorbent assays. We used the area under the curve of receiver operating characteristic curves to determine the ability of VEGF, CA9, and angiogenin to detect BCa in voided urine samples. Data were also compared with the findings from a commercial enzyme-linked immunosorbent assay-based BCa detection assay (BTA-Trak). The sensitivity, specificity, and positive and negative predictive values were calculated. RESULTS: The urinary concentrations of VEGF, CA9, angiogenin, and BTA were significantly elevated in those with BCa. VEGF was the most accurate urinary biomarker (area under the curve 0.886, 95% confidence interval 0.8301-0.9418). Furthermore, multivariate regression analysis highlighted VEGF (odds ratio 5.90, 95% confidence interval 2.60-13.40, P < .0001) as an independent variable. The sensitivity and specificity for VEGF (83% sensitivity and 87% specificity) outperformed those for BTA (80% sensitivity and 84% specificity). CONCLUSION: VEGF could be a valuable addition to voided urine sample analysis for the detection of BCa. Larger, prospective studies are needed to determine the clinical utility of urinary VEGF and angiogenin as biomarkers in the noninvasive evaluation of patients with BCa.

Derivation of cancer diagnostic and prognostic signatures from gene expression data.

The ability to compare genome-wide expression profiles in human tissue samples has the potential to add an invaluable molecular pathology aspect to the detection and evaluation of multiple diseases. Applications include initial diagnosis, evaluation of disease subtype, monitoring of response to therapy and the prediction of disease recurrence. The derivation of molecular signatures that can predict tumor recurrence in breast cancer has been a particularly intense area of investigation and a number of studies have shown that molecular signatures can outperform currently used clinicopathologic factors in predicting relapse in this disease. However, many of these predictive models have been derived using relatively simple computational algorithms and whether these models are at a stage of development worthy of large-cohort clinical trial validation is currently a subject of debate. In this review, we focus on the derivation of optimal molecular signatures from high-dimensional data and discuss some of the expected future developments in the field.