Technical Evaluation of Plasma Proteomics Technologies

Area of Science:

• Biomedical research
• Proteomics
• Analytical chemistry

Background:

• Plasma proteomics technologies are crucial for biomedical research and rapidly advancing.
• Evaluating these technologies is essential for selecting appropriate methods for various applications.

Purpose of the Study:

• To conduct a technical evaluation of six prominent plasma proteomics technologies.
• To compare their performance based on proteomic depth, reproducibility, linearity, lipid interference tolerance, and limit of detection/quantification.
• To assess their applicability in distinguishing between healthy and non-small cell lung cancer (NSCLC) patient samples.

Main Methods:

• Six plasma proteomics technologies were evaluated: unenriched (Neat), acid depletion, PreOmics ENRICHplus, Mag-Net, Seer Proteograph XT, and Olink Explore HT.
• Performance metrics included proteomic depth, reproducibility, linearity, lipid interference tolerance, and limit of detection/quantification (LOD/LOQ).
• A total of 618 liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments and 93 Olink Explore HT assays were performed. A non-small cell lung cancer (NSCLC) cohort was used to test clinical applicability.

Main Results:

• Seer Proteograph XT achieved the highest proteomic depth (∼4500 proteins) and number of quantifiable proteins (LOD: 4407, LOQ: 2696).
• Olink Explore HT detected ∼2600 proteins, with 2002 having an LOD and 1883 an LOQ.
• Neat, Mag-Net, Seer, and Olink demonstrated good reproducibility, while PreOmics and Acid showed higher variability. All MS methods exhibited good linearity with spiked C-reactive protein (CRP).
• All six methods detected differentially abundant proteins between healthy and NSCLC samples, but significant discrepancies were observed in the specific proteins identified.

Conclusions:

• Seer Proteograph XT and Olink Explore HT offer superior proteomic depth and quantification capabilities among the evaluated methods.
• While all tested technologies can detect differential protein abundance in NSCLC, method-specific biases exist, impacting the identification of significant biomarkers.
• The choice of plasma proteomics technology significantly influences the outcomes of proteomic studies, particularly in biomarker discovery for diseases like NSCLC.