Transitioning biomarkers from discovery to validation at unprecedented scale with the Stellar mass spectrometer

Importance of the Topic

This white paper addresses the critical need to transition biomarker candidates from discovery to robust validation at large scale. High-throughput, sensitive, and specific targeted quantitation platforms enable translational research in proteomics, metabolomics, and lipidomics by reducing missing data, accelerating method development, and improving detection limits for low‐abundance analytes.

Objectives and Study Overview

The primary goal was to introduce and evaluate the Thermo Scientific Stellar mass spectrometer’s performance for large‐scale biomarker verification. Key objectives included demonstrating its extended target capacity, enhanced sensitivity, quantified specificity, and automated workflows compared to conventional triple quadrupole (QQQ) instruments.

Instrumentation Used

• OptaMax Plus ion source (analytical LC flows) and EASYSpray source (0.1–10 µL/min flows)
• Auto-Ready integrated calibration ion source
• QR5 Plus segmented quadrupole mass filter (0.4 Th isolation resolution)
• Ion Concentrating Routing Multipole (ICRM) collision cell with dynamic AGC
• Hyper-fast dual-pressure linear ion trap analyzer
• Extended scale dual-conversion dynode/PTM detector
• Thermo Scientific Vanquish Neo UHPLC system

Methodology

The Stellar platform merges triple quadrupole quantitation with rapid full-scan MSn acquisition. Precursor ions (30–2000 m/z) are isolated and fragmented in the ICRM, transferred through high- and low-pressure linear ion traps for MS2 or MS3, and detected at up to 140 Hz with single-ion sensitivity. Normalized collision energy enables direct transfer from discovery methods. The PRM Conductor software, integrated with Skyline, automates method creation by filtering discovery DIA data, defining acquisition parameters (scan rate, window, cycle time), and embedding targeted tables into the instrument method. Adaptive RT alignment uses repetitive 50 Th DIA windows to correct retention drift in real time without external standards.

Main Results and Discussion

• The Stellar spectrometer achieved ~10× lower LOQs and quantified ~5× more peptides than a leading QQQ in a 30-min plasma digest experiment (786 targets in 823 scan events vs 3,950 SRM transitions).
• Dynamic AGC and full-scan PRM reduced required acquisition time per peptide to 5–30 ms versus >10 ms dwell times per SRM transition.
• Adaptive RT maintained retention stability within ±12 s over 4 weeks, ensuring >97% data completeness.
• Fast polarity switching (165 ms) and MSn characterization enabled simultaneous profiling of amino acids in ±ESI with HCD/CID and evaluation of adduct forms.

Benefits and Practical Applications of the Method

• Unrivaled quantitative throughput for large‐scale verification studies
• Single‐ion sensitivity for low‐abundance targets and single‐cell analyses
• Automated, guided software workflows reduce method development time from weeks to hours
• Dynamic retention alignment improves data completeness without spiked standards
• Flexibility for proteomic, metabolomic, and lipidomic panels in a single system

Future Trends and Potential Applications

Emerging directions include expansion to true multi‐omic workflows, integration with real‐time decision engines, single‐cell and spatial omics applications, higher‐order multiplexing with novel tags, and further miniaturization for on‐site or clinical testing. Advances in AI‐driven method optimization and adaptive acquisition strategies will further enhance throughput and data quality.

Conclusion

The Stellar mass spectrometer establishes a new benchmark for targeted biomarker verification by combining triple quadrupole robustness with high‐speed, sensitive MSn acquisition and automated data‐driven workflows. Its extended dynamic range, adaptive retention alignment, and streamlined software support enable researchers to transition candidates from discovery to validation with unprecedented scale and confidence.

Reference

Heil LR. Reaction Monitoring. J Proteome Res. 2021;20(11):4435-4442.
Heil LR, et al. Building Spectral Libraries from Narrow-Window DIA. J Proteome Res. 2022;21(6):1382-1391.
Kiyonami RS, et al. Increased Selectivity and Throughput in Targeted Proteomics. Mol Cell Proteomics. 2011;10(1):e1-e10.
Remes PM, et al. Highly Multiplex Target Proteomics Enabled by Real‐Time Chromatographic Alignment. Anal Chem. 2020;92(17):11809-11817.