PURPOSE: A major difficulty in treating brain tumors is the lack of effective methods of identifying novel or recurrent disease. In this study, we have evaluated the efficacy of urinary matrix metalloproteinases (MMP) as diagnostic biomarkers for brain tumors. EXPERIMENTAL DESIGN: Urine, cerebrospinal fluid, and tissue specimens were collected from patients with brain tumors. Zymography, ELISA, and immunohistochemistry were used to characterize the presence of MMP-2, MMP-9, MMP-9/neutrophil gelatinase-associated lipocalin (NGAL), and vascular endothelial growth factor (VEGF). Results were compared between age- and sex-matched controls and subjected to univariate and multivariate statistical analyses. RESULTS: Evaluation of a specific panel of urinary biomarkers by ELISA showed significant elevations of MMP-2, MMP-9, MMP-9/NGAL, and VEGF (all P < 0.001) in samples from brain tumor patients compared with controls. Multiplexing MMP-2 and VEGF provided superior accuracy compared with any other combination or individual biomarker. Receiver-operating characteristics curves for MMP-2 and VEGF showed excellent discrimination. Immunohistochemistry identified these same proteins in the source tumor tissue. A subset of patients with longitudinal follow-up revealed subsequent clearing of biomarkers after tumor resection. CONCLUSION: We report, for the first time, the identification of a panel of urinary biomarkers that predicts the presence of brain tumors. These biomarkers correlate with presence of disease, decrease with treatment, and can be tracked from source tissue to urine. These data support the hypothesis that urinary MMPs and associated proteins are useful predictors of the presence of brain tumors and may provide a basis for a novel, noninvasive method to identify new brain tumors and monitor known tumors after treatment.
PURPOSE: A major difficulty in treating brain tumors is the lack of effective methods of identifying novel or recurrent disease. In this study, we have evaluated the efficacy of urinary matrix metalloproteinases (MMP) as diagnostic biomarkers for brain tumors. EXPERIMENTAL DESIGN: Urine, cerebrospinal fluid, and tissue specimens were collected from patients with brain tumors. Zymography, ELISA, and immunohistochemistry were used to characterize the presence of MMP-2, MMP-9, MMP-9/neutrophil gelatinase-associated lipocalin (NGAL), and vascular endothelial growth factor (VEGF). Results were compared between age- and sex-matched controls and subjected to univariate and multivariate statistical analyses. RESULTS: Evaluation of a specific panel of urinary biomarkers by ELISA showed significant elevations of MMP-2, MMP-9, MMP-9/NGAL, and VEGF (all P < 0.001) in samples from brain tumorpatients compared with controls. Multiplexing MMP-2 and VEGF provided superior accuracy compared with any other combination or individual biomarker. Receiver-operating characteristics curves for MMP-2 and VEGF showed excellent discrimination. Immunohistochemistry identified these same proteins in the source tumor tissue. A subset of patients with longitudinal follow-up revealed subsequent clearing of biomarkers after tumor resection. CONCLUSION: We report, for the first time, the identification of a panel of urinary biomarkers that predicts the presence of brain tumors. These biomarkers correlate with presence of disease, decrease with treatment, and can be tracked from source tissue to urine. These data support the hypothesis that urinary MMPs and associated proteins are useful predictors of the presence of brain tumors and may provide a basis for a novel, noninvasive method to identify new brain tumors and monitor known tumors after treatment.
Authors: Tracy T Batchelor; Dan G Duda; Emmanuelle di Tomaso; Marek Ancukiewicz; Scott R Plotkin; Elizabeth Gerstner; April F Eichler; Jan Drappatz; Fred H Hochberg; Thomas Benner; David N Louis; Kenneth S Cohen; Houng Chea; Alexis Exarhopoulos; Jay S Loeffler; Marsha A Moses; Percy Ivy; A Gregory Sorensen; Patrick Y Wen; Rakesh K Jain Journal: J Clin Oncol Date: 2010-05-10 Impact factor: 44.544
Authors: Adelle Dagher; Adam Curatolo; Monisha Sachdev; Alisa J Stephens; Chris Mullins; J Richard Landis; Adrie van Bokhoven; Andrew El-Hayek; John W Froehlich; Andrew C Briscoe; Roopali Roy; Jiang Yang; Michel A Pontari; David Zurakowski; Richard S Lee; Marsha A Moses Journal: BJU Int Date: 2017-04-11 Impact factor: 5.588
Authors: Tomoshige Akino; Xuezhe Han; Hironao Nakayama; Brendan McNeish; David Zurakowski; Akiko Mammoto; Michael Klagsbrun; Edward Smith Journal: Cancer Res Date: 2014-05-08 Impact factor: 12.701
Authors: Natalie Gasterich; Sophie Wetz; Stefan Tillmann; Lena Fein; Anke Seifert; Alexander Slowik; Ralf Weiskirchen; Adib Zendedel; Andreas Ludwig; Steffen Koschmieder; Cordian Beyer; Tim Clarner Journal: J Mol Neurosci Date: 2020-09-21 Impact factor: 3.444
Authors: William H Chappell; Stephen L Abrams; Richard A Franklin; Michelle M LaHair; Giuseppe Montalto; Melchiorre Cervello; Alberto M Martelli; Ferdinando Nicoletti; Saverio Candido; Massimo Libra; Jerry Polesel; Renato Talamini; Michele Milella; Agostino Tafuri; Linda S Steelman; James A McCubrey Journal: Cell Cycle Date: 2012-11-16 Impact factor: 4.534