ArticleClinical proteomics2018
Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer.
Article in Clinical proteomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 27 citations in OpenAlex.
- The Urinary Proteome Differs with the Presence and Type of Breast Cancer.Journal of proteome research · 2025Article
- Effect of dynamic exclusion and the use of FAIMS, DIA and MALDI-mass spectrometry imaging with ion mobility on amyloid protein identification.Clinical proteomics · 2024Article
- Development and validation of machine learning models for diagnosis and prognosis of cancer by urinary proteomics, based on the FLEMENGHO cohort.American journal of cancer research · 2024Article
- Urinary complement proteins and risk of end-stage renal disease: quantitative urinary proteomics in patients with type 2 diabetes and biopsy-proven diabetic nephropathy.Journal of endocrinological investigation · 2021Article
- Rapid structural discrimination of IgG antibodies by multicharge-state collision-induced unfolding.RSC advances · 2021Article
- HBFP: a new repository for human body fluid proteome.Database : the journal of biological databases and curation · 2021Article
- Human body-fluid proteome: quantitative profiling and computational prediction.Briefings in bioinformatics · 2021Review
- Proteomic approaches for characterizing renal cell carcinoma.Clinical proteomics · 2020Review
- Article
- Identification of pathogens from native urine samples by MALDI-TOF/TOF tandem mass spectrometry.Clinical proteomics · 2020Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUrine 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.
methodsIn 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.
resultsWith 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.
conclusionsThe result suggested the feasibility of applying the high throughput workflow in extensive urinary proteome profiling and clinical relevant biomarker discovery.
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