Plasma, the cell-free component of blood, offers a minimally invasive and rich source of biomolecular information, making it ideal for investigating systemic diseases. The advent of high-throughput proteomic technologies has revolutionized plasma analysis by enabling large-scale identification and quantification of circulating proteins. These advances have facilitated biomarker discovery for early diagnosis, prognosis, and therapeutic targeting of various disorders, including cancers and inflammatory diseases. However, the inherent complexity of plasma, along with inconsistent sample preparation and analysis methods, has historically limited proteome coverage and reproducibility. Early approaches relying on crude plasma analysis often suffered from poor consistency and significant batch effects, impeding reliable comparative studies across clinical cohorts. To overcome these limitations, the current study introduces a robust and scalable plasma proteomics workflow. The protocol integrates key preparatory steps such as immunodepletion, molecular weight cutoff filtration, lyophilization, protein quantification and normalization, enzymatic digestion, and LC-MS/MS profiling. This optimized strategy significantly enhances proteome depth and reduces variability, thereby enabling more accurate and reproducible differential protein expression analysis between disease cases and healthy controls. The workflow provides a valuable platform for researchers aiming to generate high-quality proteomic data from plasma, ultimately contributing to the advancement of biomarker-driven diagnostics and personalized medicine.
M et al. (Fri,) studied this question.