ArticleJournal of proteome research2024
Comprehensive Prostate Fluid-Based Spectral Libraries for Enhanced Protein Detection in Urine.
Article in Journal of proteome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Comparative evaluation of analytical methods for CSF proteomics.Clinical proteomics · 2025Article
- In Search of Ideal Solutions for Cancer Diagnosis: From Conventional Methods to Protein Biomarkers in Liquid Biopsy.Proteomes · 2025Review
- Molecular marker discovery and detection for blinding eye disease.Journal of nanobiotechnology · 2025Article
- Integration of proteomics profiling data to facilitate discovery of cancer neoantigens: a survey.Briefings in bioinformatics · 2025Review
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Authors and funding
11 authors.
Funding
Abstract
Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.
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