Comprehensive Prostate Fluid-Based Spectral Libraries for Enhanced Protein Detection in Urine

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.