Quantitative Extracellular Vesicle Proteomics by Multiplexed Data-Independent Acquisition

This study established an optimized dimethyl labeling-based multiplexed DIA (mDIA) pipeline for quantitative proteomics of extracellular vesicles (EVs). Benchmarking different library generation strategies and software suites demonstrated superior performance of mDIA using project-specific libraries generated from small-scale StageTip fractionation. This approach enabled robust profiling of low-abundance EV proteins and successfully revealed proteomic changes associated with IDH1 mutation and inhibitor treatment in intrahepatic cholangiocarcinoma (iCCA) cell-derived EVs.