Proteomics

Dataset Information

0

Standard operating procedure combined with comprehensive quality control system to enable large-scale urinary proteomics across multiple LC-MS platforms for precision medicine


ABSTRACT: In this study, we carried out a comprehensive evaluation of multiple LC-MS platforms in urinary proteomics including 756 proteome measurements. A series of interrelated studies was designed to assess the intra- and inter-platform consistency and reproducibility. First, we optimized the method for urinary proteome, including sample loading amount, chromatography, and DIA method. Second, a uniformly prepared urine sample is distributed to 20 LC-MS platforms, where a total of 160 data are generated to analyze the consistency and reproducibility across different LC-MS platforms. Third, benchmarking samples, which consist of tryptic digests of human, yeast, and E. coli proteins mixed in defined proportions, are generated to mimic differential expressed biological samples and provide proof of the robustness and reproducibility of the different LC-MS platforms. Finally, the above SOP are applied to actual clinical CRC cohort urinary proteome datasets derived from 3 LC-MS platforms to further demonstrate the performance of urinary proteomics cohorts from multi-platform in biomarker discovery.

ORGANISM(S): Homo Sapiens Escherichia Coli Saccharomyces Cerevisiae

SUBMITTER: Wei Sun  

PROVIDER: PXD050291 | iProX | Mon Oct 28 00:00:00 GMT 2024

REPOSITORIES: iProX

altmetric image

Publications

Standard operating procedure combined with comprehensive quality control system for multiple LC-MS platforms urinary proteomics.

Liu Xiang X   Sun Haidan H   Hou Xinhang X   Sun Jiameng J   Tang Min M   Zhang Yong-Biao YB   Zhang Yongqian Y   Sun Wei W   Liu Chao C  

Nature communications 20250126 1


Urinary proteomics is emerging as a potent tool for detecting sensitive and non-invasive biomarkers. At present, the comparability of urinary proteomics data across diverse liquid chromatography-mass spectrometry (LC-MS) platforms remains an area that requires investigation. In this study, we conduct a comprehensive evaluation of urinary proteome across multiple LC-MS platforms. To systematically analyze and assess the quality of large-scale urinary proteomics data, we develop a comprehensive qu  ...[more]

Similar Datasets

2023-06-22 | E-PROT-106 | ExpressionAtlas
2025-10-31 | PXD070173 | panorama
2005-04-21 | GSE2458 | GEO
2010-06-10 | E-GEOD-2458 | biostudies-arrayexpress
2006-06-01 | GSE4833 | GEO
2006-06-01 | GSE4832 | GEO
2006-06-01 | GSE4831 | GEO
2006-06-01 | GSE4834 | GEO
2006-06-01 | GSE4830 | GEO
2006-06-01 | GSE4829 | GEO