Boronic Acid-Functionalized MOFs Enable Ultrasensitive Proteomic Profiling of Ultratrace Plasma for Triple-Negative Breast Cancer Diagnosis

Blood-based proteomics holds great promise for noninvasive disease diagnostics, yet remains constrained by large sample requirements, laborious preprocessing, and limited sensitivity. Here, we present a streamlined workflow for ultratrace plasma sample proteomics (UPSP) utilizing boronic acid-functionalized metal–organic frameworks (MOFs) that enable efficient protein enrichment from just 1 μL plasma through synergistic nitrogen–boronate complexation, cation−π interaction, and O–Eu coordination. UPSP eliminates the need for high-abundance protein depletion and peptide fractionation, achieving robust and reproducible quantification of over 500 proteins per microliter with high interassay precision ( R 2 = 0.986) and low variability (CV < 20% for >65% of proteins). We demonstrate the utility of UPSP in a clinical context by profiling plasma from triple-negative breast cancer (TNBC) and healthy controls. Integrated with machine learning, the platform achieved a diagnostic accuracy of 0.93 for TNBC. UPSP provides a versatile and scalable platform for deep proteome profiling of trace-volume biospecimens, with broad applicability in biomarker discovery, longitudinal monitoring, and scarce-sample scenarios.