Highly multiplex targeted proteomics assay in plasma using the Stellar mass spectrometer with adaptive RT

Importance of the Topic

Targeted proteomics is essential for translating biomarker discoveries into clinical assays. High-multiplex methods enable quantitation of hundreds of proteins in plasma, improving disease diagnosis and monitoring.

Objectives and Study Overview

This study aimed to develop a large-scale multiplexed targeted proteomics workflow using real-time adaptive retention time alignment on the Stellar mass spectrometer. The method employs PQ500 heavy peptide standards and was applied to plasma from healthy donors and colorectal cancer patients.

Methodology

Plasma samples were digested using an automated AccelerOme platform. Scheduled parallel reaction monitoring (PRM) assays with adaptive RT windows were designed in Skyline to target over 1600 peptide precursors. Two acquisition modes were used: MS2 for broad profiling and MS3 to enhance signal-to-noise for low-abundance peptides, all with a 30-minute chromatographic gradient.

Used Instrumentation

• Thermo Scientific Vanquish Neo UHPLC system
• Stellar mass spectrometer with adaptive RT function
• Thermo Scientific EASY-Spray ES906A column
• Skyline software for method development and data analysis

Key Results and Discussion

Using a 30-minute gradient, the MS2 and MS3 assays identified 292 endogenous proteins and 472 peptides across disease and healthy plasma. MS3 acquisition improved signal-to-noise, increasing protein identifications by 10.3%. More than 94% of peptides in disease samples showed CVs below 25%, and 90% exhibited linearity (R2 > 0.9). Adaptive RT successfully captured all 804 scheduled peptides without manual adjustments.

Benefits and Practical Applications

• High-throughput quantitation of potential colorectal cancer biomarkers directly in plasma
• Enhanced sensitivity and reproducibility for clinical cohort studies
• Simultaneous monitoring of FDA-approved biomarkers and novel targets

Future Trends and Opportunities

Advances in instrument speed and predictive retention time modeling may further scale assays to thousands of targets. Integration with machine learning for automated method optimization and real-time data curation could improve robustness. Extensive clinical validation will support translation into routine diagnostics.

Conclusion

This work demonstrates a robust, scalable targeted proteomics approach in plasma using adaptive RT on the Stellar platform. The combined MS2/MS3 strategy delivers high sensitivity, reproducibility, and throughput, paving the way for large-scale biomarker validation.

References

1. Juthamard Chantaraamporn et al. Proteomes 2020, 8(3), 26.
2. Bethany Geary et al. Cancers 2021, 13(10), 2443.