PURPOSE: Metastatic prostate cancer is a major cause of death of men in the United States. Expression of met, a receptor tyrosine kinase, has been associated with progression of prostate cancer. EXPERIMENTAL DESIGN: To investigate met as a biomarker of disease progression, urinary met was evaluated via ELISA in men with localized (n = 75) and metastatic (n = 81) prostate cancer. Boxplot analysis was used to compare the distribution of met values between each group. We estimated a receiver operating characteristic curve and the associated area under the curve to summarize the diagnostic accuracy of met for distinguishing between localized and metastatic disease. Protein-protein interaction networking via yeast two-hybrid technology supplemented by Ingenuity Pathway Analysis and Human Interactome was used to elucidate proteins and pathways related to met that may contribute to progression of disease. RESULTS: Met distribution was significantly different between the metastatic group and the group with localized prostate cancer and people with no evidence of cancer (P < 0.0001). The area under the curve for localized and metastatic disease was 0.90, with a 95% confidence interval of 0.84 to 0.95. Yeast two-hybrid technology, Ingenuity Pathway Analysis, and Human Interactome identified 89 proteins that interact with met, of which 40 have previously been associated with metastatic prostate cancer. CONCLUSION: Urinary met may provide a noninvasive biomarker indicative of metastatic prostate cancer and may be a central regulator of multiple pathways involved in prostate cancer progression.
PURPOSE:Metastatic prostate cancer is a major cause of death of men in the United States. Expression of met, a receptor tyrosine kinase, has been associated with progression of prostate cancer. EXPERIMENTAL DESIGN: To investigate met as a biomarker of disease progression, urinary met was evaluated via ELISA in men with localized (n = 75) and metastatic (n = 81) prostate cancer. Boxplot analysis was used to compare the distribution of met values between each group. We estimated a receiver operating characteristic curve and the associated area under the curve to summarize the diagnostic accuracy of met for distinguishing between localized and metastatic disease. Protein-protein interaction networking via yeast two-hybrid technology supplemented by Ingenuity Pathway Analysis and Human Interactome was used to elucidate proteins and pathways related to met that may contribute to progression of disease. RESULTS: Met distribution was significantly different between the metastatic group and the group with localized prostate cancer and people with no evidence of cancer (P < 0.0001). The area under the curve for localized and metastatic disease was 0.90, with a 95% confidence interval of 0.84 to 0.95. Yeast two-hybrid technology, Ingenuity Pathway Analysis, and Human Interactome identified 89 proteins that interact with met, of which 40 have previously been associated with metastatic prostate cancer. CONCLUSION: Urinary met may provide a noninvasive biomarker indicative of metastatic prostate cancer and may be a central regulator of multiple pathways involved in prostate cancer progression.
Authors: Jiaqi Mi; Erika Hooker; Steven Balog; Hong Zeng; Daniel T Johnson; Yongfeng He; Eun-Jeong Yu; Huiqing Wu; Vien Le; Dong-Hoon Lee; Joseph Aldahl; Mark L Gonzalgo; Zijie Sun Journal: J Biol Chem Date: 2018-11-06 Impact factor: 5.157
Authors: Andreas Varkaris; Paul G Corn; Sanchaika Gaur; Farshid Dayyani; Christopher J Logothetis; Gary E Gallick Journal: Expert Opin Investig Drugs Date: 2011-10-28 Impact factor: 6.206
Authors: John Thoms; Jayant S Goda; Alexender R Zlotta; Neil E Fleshner; Theodorus H van der Kwast; Stéphane Supiot; Padraig Warde; Robert G Bristow Journal: Nat Rev Clin Oncol Date: 2010-12-21 Impact factor: 66.675
Authors: Jinlu Dai; Honglai Zhang; Andreas Karatsinides; Jill M Keller; Kenneth M Kozloff; Dana T Aftab; Frauke Schimmoller; Evan T Keller Journal: Clin Cancer Res Date: 2013-10-04 Impact factor: 12.531
Authors: Alisa J Prager; Cynthia R Peng; Elena Lita; Debbie McNally; Aradhana Kaushal; Mary Sproull; Kathryn Compton; William L Dahut; William D Figg; Deborah Citrin; Kevin A Camphausen Journal: Biomark Med Date: 2013-12 Impact factor: 2.851