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Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer

BACKGROUND: Urine has evolved as a promising body fluids in clinical proteomics because it can be easily and noninvasively obtained and can reflect physiological and pathological status of the human body. Many efforts have been made to characterize more urinary proteins in recent years, but few have...

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Detalles Bibliográficos
Autores principales: Lin, Lin, Yu, Quan, Zheng, Jiaxin, Cai, Zonglong, Tian, Ruijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303996/
https://www.ncbi.nlm.nih.gov/pubmed/30607141
http://dx.doi.org/10.1186/s12014-018-9220-2
Descripción
Sumario:BACKGROUND: Urine has evolved as a promising body fluids in clinical proteomics because it can be easily and noninvasively obtained and can reflect physiological and pathological status of the human body. Many efforts have been made to characterize more urinary proteins in recent years, but few have focused on the analysis throughput and detection reproducibility. Increasing the urine proteomic profiling throughput and reproducibility is urgently needed for discovering potential biomarker in large cohorts. METHODS: In this study, we developed a fast and robust workflow for streamlined urinary proteome analysis. The workflow integrate highly efficient sample preparation technique and urinary specific data-independent acquisition (DIA) approach. The performance of the workflow was systematically evaluated and the workflow was subsequently applied in a proof-of-concept urine proteome study of 21 kidney cancer (KC) patients and 22 healthy controls. RESULTS: With this workflow, the entire sample preparation process takes less than 3 h and allows multiplexing on standard centrifuges. Without pre-fractionation, our newly developed DIA method allows quantitative analysis of ~ 1000 proteins within 80 min of MS time (~ 15 samples/day). The quantitation accuracy of the whole workflow was excellent with median CV of 9.1%. The preliminary study on KC identified 125 significantly changed proteins. CONCLUSIONS: The result suggested the feasibility of applying the high throughput workflow in extensive urinary proteome profiling and clinical relevant biomarker discovery. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12014-018-9220-2) contains supplementary material, which is available to authorized users.