• Poster presentation
  • P-II-0715

Unlocking biomarker discovery with novel high-throughput LC-MS workflows for translational research on an Orbitrap Astral mass spectrometer

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Clinical Proteomics

Topic

  • Clinical Proteomics

Abstract

Cancer claims millions of lives globally every year. Current tests, such as invasive biopsies or costly imaging scans, can lack sensitivity or selectivity and are not readily available. Thus, analyzing blood plasma is widely accepted as a promising technique for biomarker detection. Here, we demonstrate the performance of a high-throughput, in-depth plasma proteomics workflow using different sample preparation technologies coupled with a state-of-the-art Orbitrap Astral mass spectrometer in a small group of diverse cancer and non-cancer samples, which sets the stage for larger-scale cancer cohort studies and translational research. In the mini-cohort study, the plasma samples of various cancers, including melanoma, non-small cell lung cancer (NSCLC), B-cell lymphoma, ovarian, and pancreatic cancer were compared with age- and ethnicity-matched normal plasma.

Plasma samples were processed with Seer"s Proteograph XT Assay or Pierce"s Top 14 abundant protein depletion plate for enrichment and depletion, respectively. Different throughput needs were met by separating the resulting peptides using either EASY-Spray PepMap Neo HPLC column or IonOpticks Aurora Frontier UHPLC column on a Vanquish Neo UHPLC system. The separation was coupled to an Orbitrap Astral mass spectrometer operated in DIA mode at a rate of either 16 or 60 samples per day (SPD). Quantitation accuracy was accessed by comparing mixtures of chicken and human plasma at different ratios. Proteomics data was analyzed by Chimerys in Proteome Discoverer software and DIA-NN software. Protein group intensity was used for the unsupervised classification of patients.

In total, we were able to identify approximately 1500 protein groups from the depleted plasma samples using the high-throughput 60 SPD method. For enriched plasma samples, we identified approximately 10,000 [ND1] and 7000 protein groups from a throughput of 16 and 60 SPD, respectively. The results demonstrate the unprecedented plasma proteome coverage from Orbitrap Astral mass spectrometer. With in-depth proteome coverage and excellent quantitation, we further conducted principal component analysis. Our results indicate that we were able to classify the samples based on cancer types, highlighting the performance of the workflow in biomarker discovery.

Quantitation accuracy was further assessed by comparing the data of human and chicken plasma mixed at different ratios. The quantitative results of the observed ratio accurately reflected the expected ratio, which demonstrates excellent quantitation accuracy. Altogether, our LC-MS workflows on Orbitrap Astral offer extensive coverage along with excellent throughput and quantitation accuracy for proteomics, empowering enhanced classification and biomarker discovery. The mini cancer cohort results demonstrate the advancements in unprecedented depth of coverage and biomarker detection from the Orbitrap Astral mass spectrometer.