Discovering hidden depths: high-throughput proteomics study for enhanced biomarker discovery on Orbitrap Astral Mass Spectrometer

Significance of the topic

The ability to detect cancer biomarkers in blood at early stages can revolutionize patient outcomes by enabling timely diagnosis and personalized treatment. Plasma proteomics offers a minimally invasive route to capture dynamic protein signatures linked to disease states. However, conventional workflows often trade depth of coverage for speed or require complex handling steps, limiting their adoption in large‐scale translational studies.

Objectives and study overview

This work evaluates a combined high‐throughput and in‐depth plasma proteomics workflow using the Orbitrap Astral mass spectrometer coupled with the Proteograph XT Assay. A pilot cohort comprising plasma from patients with B-cell lymphoma, colorectal, lung, ovarian and pancreatic cancer, alongside age-, gender- and ethnicity-matched healthy controls, was profiled using two LC-MS methods: a 60 samples-per-day (SPD) protocol for throughput and a 16 SPD protocol for maximal proteome coverage.

Instrumentation

• Orbitrap Astral Mass Spectrometer (Thermo Scientific)
• Vanquish Neo UHPLC System (Thermo Scientific)
• EASY-Spray PepMap Column (15 cm) and IonOpticks TS UHPLC Column (60 cm)
• Proteograph XT Assay Kit (Seer Inc.) with nanoparticles for plasma protein enrichment
• EasyPep Mini MS Sample Prep Kit (Thermo Scientific)

Methodology

Sample Preparation:
• Neat plasma digests processed with EasyPep Mini kit.
• Enrichment of proteins using the Proteograph XT nanoparticles.

LC-MS Workflows:
• 60 SPD method: trap-and-elute on 15-cm column for rapid analysis.
• 16 SPD method: direct injection on 60-cm column for deeper coverage.
• Data acquisition in narrow‐window DIA mode.

Data Analysis:
• DIA data processed with DIA-NN v1.8.1 and Proteome Discoverer with CHIMERYS algorithm.
• Downstream statistical analysis and visualization in Python.

Main results and discussion

Coverage and Sensitivity:
• Neat plasma (60 SPD): 1,162 protein groups, 9,796 peptides.
• Neat plasma (16 SPD): 2,516 protein groups, 18,800 peptides.
• Enriched plasma (60 SPD): 5,531 protein groups, 57,913 peptides.
• Enriched plasma (16 SPD): 8,049 protein groups, 119,880 peptides.
• Overall identification of nearly 10,000 protein groups across workflows.

Quantitative Performance:
• Coefficient of variation (CV) consistently below 10%, demonstrating high precision.
• PCA of cancer versus healthy samples showed clear separation, supporting robust classification.
• Identification of 67.5–72.8% of FDA-approved oncology biomarkers in single‐shot LFQ-DIA analyses.

Biological Insights:
• Volcano plot and KEGG pathway analysis in B-cell lymphoma cases highlighted dysregulated pathways including complement cascades, cytoskeletal regulation, and immune response.

Benefits and practical applications

• Combines throughput and depth in a single platform, enabling both large‐cohort screening and detailed proteome mapping.
• High reproducibility and sensitivity support detection of subtle disease‐related proteome shifts.
• Automation and simplified enrichment reduce sample handling variability.
• Readiness for translational studies aiming at early biomarker discovery, drug response monitoring, and personalized medicine.

Future trends and opportunities

• Expansion to larger, multi-center cohorts to validate candidate biomarkers across populations.
• Integration with other omics layers (genomics, metabolomics) and AI‐driven analytics for multi‐modal biomarker panels.
• Development of targeted assays on the Astral platform for verification of high-priority biomarker candidates.
• Further automation and miniaturization of sample preparation to increase accessibility in clinical laboratories.
• Real‐time data processing and cloud-based workflows to accelerate turnaround times.

Conclusion

This study demonstrates that the Orbitrap Astral mass spectrometer, when paired with the Proteograph XT Assay, achieves unprecedented plasma proteome coverage and quantitative precision at both high throughput and in-depth settings. The workflow supports robust classification of cancer versus healthy samples and identifies known clinical biomarkers, paving the way for extensive translational and population-scale proteomics research.

References

Yang K, Flora A, Patel B, Motamedchaboki K, Samra S, Hakimi A. Discovering hidden depths: high-throughput proteomics study for enhanced biomarker discovery on Orbitrap Astral Mass Spectrometer. Thermo Fisher Scientific white paper; 2024.