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a multi-analyte assay for the non-invasive detection of bladder cancer一个multi-analyte试验的非侵入性检测膀胱癌.pdf

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a multi-analyte assay for the non-invasive detection of bladder cancer一个multi-analyte试验的非侵入性检测膀胱癌

A Multi-Analyte Assay for the Non-Invasive Detection of Bladder Cancer 1,4 2 2 1,4 3,4 Steve Goodison , Myron Chang , Yunfeng Dai , Virginia Urquidi , Charles J. Rosser * 1 Cancer Research Institute, M.D. Anderson Cancer Center Orlando, Orlando, Florida, United States of America, 2 Department of Biostatistics, The University of Florida, Gainesville, Florida, United States of America, 3 Section of Urologic Oncology, MD Anderson Cancer Center Orlando, Orlando, Florida, United States of America, 4 Nonagen Bioscience Corp, Orlando, Florida, United States of America Abstract 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 9