Shingo Hatakeyama1, Maho Amano2, Yuki Tobisawa1, Tohru Yoneyama3, Norihiko Tsuchiya4, Tomonori Habuchi4, Shin-Ichiro Nishimura2, Chikara Ohyama5. 1. Department of Urology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan. 2. Faculty of Advanced Life Science and Frontier Research Center for Post-Genome Science and Technology, Hokkaido University, Sapporo, Japan. 3. Department of Advanced Transplant and Regenerative Medicine, Hirosaki University Graduate School of Medicine, Hirosaki, Japan. 4. Department of Urology, Akita University Graduate School of Medicine, Akita, Japan. 5. Department of Urology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan. Electronic address: coyama@cc.hirosaki-u.ac.jp.
Abstract
PURPOSE: Biomarkers for the early detection and prediction of survival in patients with renal cell carcinoma have not been established. We developed what is to our knowledge a novel glycoblotting method that allows high throughput, comprehensive, quantitative analysis of glycans in human serum. In this study we identified alterations in serum N-glycans associated with renal cell carcinoma. MATERIALS AND METHODS: We performed a comprehensive N-glycan structural analysis of serum from 64 patients with renal cell carcinoma and 34 age matched, healthy volunteers using glycoblotting methods and matrix-assisted laser desorption/ionization-time of flight mass spectrometry. The peak intensity of N-glycan was analyzed using logistic regression analysis and ROCs were used to select candidate N-glycans. Candidate N-glycans with a statistically significant relationship to renal cell carcinoma or overall survival were independently evaluated using a Cox regression model to determine superiority compared to other conventional renal cell carcinoma biomarkers. RESULTS: We identified 56 types of N-glycans in serum from healthy volunteers and patients with renal cell carcinoma. Peaks 40 and 43 were significantly more intense in patients than in volunteers. Peak 19 intensity was significantly higher and peak 49 intensity was significantly lower in patients with renal cell carcinoma who survived for a longer period. Multivariate analysis revealed that peaks 19 and 49 were independent predictors of overall survival. CONCLUSIONS: Serum N-glycan analysis is a promising approach to discovering new biomarkers for renal cell carcinoma. Further study is warranted to validate our results.
PURPOSE: Biomarkers for the early detection and prediction of survival in patients with renal cell carcinoma have not been established. We developed what is to our knowledge a novel glycoblotting method that allows high throughput, comprehensive, quantitative analysis of glycans in human serum. In this study we identified alterations in serum N-glycans associated with renal cell carcinoma. MATERIALS AND METHODS: We performed a comprehensive N-glycan structural analysis of serum from 64 patients with renal cell carcinoma and 34 age matched, healthy volunteers using glycoblotting methods and matrix-assisted laser desorption/ionization-time of flight mass spectrometry. The peak intensity of N-glycan was analyzed using logistic regression analysis and ROCs were used to select candidate N-glycans. Candidate N-glycans with a statistically significant relationship to renal cell carcinoma or overall survival were independently evaluated using a Cox regression model to determine superiority compared to other conventional renal cell carcinoma biomarkers. RESULTS: We identified 56 types of N-glycans in serum from healthy volunteers and patients with renal cell carcinoma. Peaks 40 and 43 were significantly more intense in patients than in volunteers. Peak 19 intensity was significantly higher and peak 49 intensity was significantly lower in patients with renal cell carcinoma who survived for a longer period. Multivariate analysis revealed that peaks 19 and 49 were independent predictors of overall survival. CONCLUSIONS: Serum N-glycan analysis is a promising approach to discovering new biomarkers for renal cell carcinoma. Further study is warranted to validate our results.
Authors: Calvin R K Blaschke; Colin T McDowell; Alyson P Black; Anand S Mehta; Peggi M Angel; Richard R Drake Journal: Clin Lab Med Date: 2021-04-24 Impact factor: 2.172
Authors: Andréia Vasconcelos-Dos-Santos; Isadora A Oliveira; Miguel Clodomiro Lucena; Natalia Rodrigues Mantuano; Stephen A Whelan; Wagner Barbosa Dias; Adriane Regina Todeschini Journal: Front Oncol Date: 2015-06-25 Impact factor: 6.244