A Single-Aliquot, Enrichment-Free Workflow for High-Throughput Plasma Proteome and N-Glycoproteome Profiling

Abstract

High cancer mortality rates highlight an urgent need for early detection. Plasma proteomics and glycoproteomics provide minimally invasive routes for biomarker discovery, yet achieving an optimal balance among profiling depth, throughput, and longitudinal reproducibility remains a major challenge for clinical application and translation. To overcome this bottleneck, we present a single-aliquot, enrichment-free, paired-run dual-omics pipeline that concurrently profiles the global plasma proteome and N-glycoproteome from unenriched plasma. Following depletion of top14 abundant plasma proteins, we implemented sequential 23-min narrow-window data-independent acquisition (DIA) and 42-min stepped-collision-energy data-dependent (SCE-DDA) runs from the same plasma digest, delivering a clinical throughput of [~]24 patients/day with deep proteome coverage of 3,756{+/-}413 protein groups (PGs) and 1,226{+/-}78 glycopeptides per sample, including 303 FDA-approved drug targets. Cross-platform benchmarking with a previous generation instrument demonstrated significantly faster (>10-20 fold) profiling speed to achieve 113 PGs/min and high protein abundance reproducibility (Pearson r > 0.9), confirming cross-instrument transferability. Application to a 300-participant lung cohort (cancer, LDCT-detected non-cancer nodules, and controls) revealed differential expression of S100 and annexin family proteins between cancer and nodules. Paired glycoproteomic analysis (n=30) identified site-specific N-glycosylation alterations in FN1, IGHG2, C3, and MET independent of total protein abundance, uncovering additional biomarker candidates for early lung cancer detection. Together, this dual-omics strategy enables deep, scalable, and reproducible plasma analysis, supporting longitudinal biomarker discovery and validation across instruments and laboratories.