Poster Presentation 24th Annual Lorne Proteomics Symposium 2019

Mass spectrometry-based large-cohort proteomics for precision medicine – An international Cancer Moonshot multiple site study (#87)

Andreas Huhmer 1 , Yue Xuan 1
  1. Thermo Fisher Scientific, SAN JOSE, CA, United States

To successfully elevate discovery proteomics to translational research in the pipeline of precision medicine, large-cohort studies are essential in discovery and verification of protein biomarkers. However, to reproducibly and reliably quantify large numbers of proteins across different laboratories remain challenging. To address this, we present a high-throughput and streamlined analytical workflow using high resolution MS1-based quantitative data-independent acquisition (HRMS1–DIA) mass spectrometry. HRMS1-DIA workflow is standardized with well-defined experimental steps and systematically applied to set of test samples. The study was benchmarked across multiple Cancer Moonshot sites utilizing identical instrument, methods and software, demonstrating stability in a 24/7 operation mode for 7 consecutive days.

Successful proteome profiling workflows must address highly complex samples. Our approach is to increase chromatographic and mass spectral resolution, utilize HRAM MS1 data for quantitation and interspersed DIA for qualitative analysis, spiking quality control peptides, and creating in-depth spectral libraries. Besides setting FDR at 1%, roll-up statistic strategy was applied to improve quantitation precision. Robust and straightforward SOPs are created for HRMS1-DIA workflow, to define instrumental aspects such as retention time stability, spray stability, and product ion distribution overlap with spectral library.


The workflow was transferred to multiple sites to perform similar measurements for assessment. Each laboratory was equipped with similar instruments, columns, methods, spectral libraries and software. To evaluate robustness of the workflow, the study was carried out in a 24/7 operation mode for 7 consecutive days. The resulting data were processed individually and combined to evaluate proteome coverage and quantitative capabilities. At 1% FDR, > 5,000 proteins from > 40,000 peptides of the QC sample, as well as > 7,000 proteins from > 50,000 peptides of the mixed proteome sample, are consistently detected and reliably quantified across sites. The ratios of the mixed three proteomes accurately reflect the expected values.