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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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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
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author Lin, Lin
Yu, Quan
Zheng, Jiaxin
Cai, Zonglong
Tian, Ruijun
author_facet Lin, Lin
Yu, Quan
Zheng, Jiaxin
Cai, Zonglong
Tian, Ruijun
author_sort Lin, Lin
collection PubMed
description 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.
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spelling pubmed-63039962019-01-03 Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer Lin, Lin Yu, Quan Zheng, Jiaxin Cai, Zonglong Tian, Ruijun Clin Proteomics Research 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. BioMed Central 2018-12-22 /pmc/articles/PMC6303996/ /pubmed/30607141 http://dx.doi.org/10.1186/s12014-018-9220-2 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Lin, Lin
Yu, Quan
Zheng, Jiaxin
Cai, Zonglong
Tian, Ruijun
Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer
title Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer
title_full Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer
title_fullStr Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer
title_full_unstemmed Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer
title_short Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer
title_sort fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer
topic Research
url 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
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