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      A multiplex immunoassay for the non-invasive detection of bladder cancer

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          Abstract

          Background

          Urine based assays that can non-invasively detect bladder cancer (BCa) have the potential to reduce unnecessary and invasive procedures. The purpose of this study was to develop a multiplex immunoassay that can accurately and simultaneously monitor ten diagnostic urinary protein biomarkers for application as a non-invasive test for BCa detection.

          Methods

          A custom electrochemiluminescent multiplex assay was constructed (Meso Scale Diagnostics, LLC, Rockville, MD, USA) to detect the following urinary proteins; IL8, MMP9, MMP10, ANG, APOE, SDC1, A1AT, PAI1, CA9 and VEGFA. Voided urine samples from two cohorts were collected prior to cystoscopy and samples were analyzed blinded to the clinical status of the participants. Means (±SD) and receiver operating characteristic (ROC) curve analysis were used to compare assay performance and to assess the diagnostic accuracy of the diagnostic signature.

          Results

          Comparative diagnostic performance analyses revealed an AUROC value of 0.9258 for the multiplex assay and 0.9467 for the combination of the single-target ELISA assays ( p = 0.625), so there was no loss of diagnostic utility for the MSD multiplex assay. Analysis of the independent 200-sample cohort using the multiplex assay achieved an overall diagnostic sensitivity of 0.85, specificity of 0.81, positive predictive value 0.82 and negative predictive value 0.84.

          Conclusions

          It is technically feasible to simultaneously monitor complex urinary diagnostic signatures in a single assay without loss of performance. The described protein-based assay has the potential to be developed for the non-invasive detection of BCa.

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          Most cited references27

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          Estimation of the Youden Index and its associated cutoff point.

          The Youden Index is a frequently used summary measure of the ROC (Receiver Operating Characteristic) curve. It both, measures the effectiveness of a diagnostic marker and enables the selection of an optimal threshold value (cutoff point) for the marker. In this paper we compare several estimation procedures for the Youden Index and its associated cutoff point. These are based on (1) normal assumptions; (2) transformations to normality; (3) the empirical distribution function; (4) kernel smoothing. These are compared in terms of bias and root mean square error in a large variety of scenarios by means of an extensive simulation study. We find that the empirical method which is the most commonly used has the overall worst performance. In the estimation of the Youden Index the kernel is generally the best unless the data can be well transformed to achieve normality whereas in estimation of the optimal threshold value results are more variable.
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            Detection of bladder cancer using a point-of-care proteomic assay.

            A combination of methods is used for diagnosis of bladder cancer because no single procedure detects all malignancies. Urine tests are frequently part of an evaluation, but have either been nonspecific for cancer or required specialized analysis at a laboratory. To investigate whether a point-of-care proteomic test that measures the nuclear matrix protein NMP22 in voided urine could enhance detection of malignancy in patients with risk factors or symptoms of bladder cancer. Twenty-three academic, private practice, and veterans' facilities in 10 states prospectively enrolled consecutive patients from September 2001 to May 2002. Participants included 1331 patients at elevated risk for bladder cancer due to factors such as history of smoking or symptoms including hematuria and dysuria. Patients at risk for malignancy of the urinary tract provided a voided urine sample for analysis of NMP22 protein and cytology prior to cystoscopy. The diagnosis of bladder cancer, based on cystoscopy with biopsy, was accepted as the reference standard. The performance of the NMP22 test was compared with voided urine cytology as an aid to cancer detection. Testing for the NMP22 tumor marker was conducted in a blinded manner. Bladder cancer was diagnosed in 79 patients. The NMP22 assay was positive in 44 of 79 patients with cancer (sensitivity, 55.7%; 95% confidence interval [CI], 44.1%-66.7%), whereas cytology test results were positive in 12 of 76 patients (sensitivity, 15.8%; 95% CI, 7.6%-24.0%). The specificity of the NMP22 assay was 85.7% (95% CI, 83.8%-87.6%) compared with 99.2% (95% CI, 98.7%-99.7%) for cytology. The proteomic marker detected 4 cancers that were not visualized during initial endoscopy, including 3 that were muscle invasive and 1 carcinoma in situ. The noninvasive point-of-care assay for elevated urinary NMP22 protein can increase the accuracy of cystoscopy, with test results available during the patient visit.
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              The failure of protein cancer biomarkers to reach the clinic: why, and what can be done to address the problem?

              There is a plethora of published cancer biomarkers but the reality is that very few, if any, new circulating cancer biomarkers have entered the clinic in the last 30 years. I here try to explain this apparent oxymoron by classifying circulating cancer biomarkers into three categories: fraudulent reports (rare); true discoveries of biomarkers, that then fail to meet the demands of the clinic; and false discoveries, which represent artifactual biomarkers. I further provide examples of combinations of some known cancer biomarkers that can perform well in niche clinical applications, despite individually being not useful.
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                Author and article information

                Contributors
                yoshikos@hawaii.edu
                hfuruya@cc.hawaii.edu
                pgreenwood@queens.org
                ochan@cc.hawaii.edu
                ydai@ichp.ufl.edu
                mthornqu@fredhutch.org
                goodison.steven@mayo.edu
                808-564-3812 , cjrosser@hawaii.edu
                Journal
                J Transl Med
                J Transl Med
                Journal of Translational Medicine
                BioMed Central (London )
                1479-5876
                30 January 2016
                30 January 2016
                2016
                : 14
                : 31
                Affiliations
                [ ]University of Hawaii Cancer Center, 701 Ilalo St, Rm 327, Honolulu, HI 96813 USA
                [ ]Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, HI USA
                [ ]Department of Biostatistics, University of Florida, Gainesville, FL USA
                [ ]Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA USA
                [ ]Nonagen BioScience Corp, Jacksonville, FL USA
                [ ]Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL USA
                Article
                783
                10.1186/s12967-016-0783-2
                4736707
                26830497
                5540d4c2-8b42-4b0d-9a30-0e715582d3ec
                © Shimizu et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 13 June 2015
                : 12 August 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2016

                Medicine
                biomarkers,bladder cancer,multiplex,protein,urine
                Medicine
                biomarkers, bladder cancer, multiplex, protein, urine

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