Abstract

Abstract Mass Spectrometry based proteomics profiling has become a powerful tool for broad quantification of proteins and their post-translational modifications for cancer research. Due to extensive efforts in the field to benchmark and standardize complex workflows, particularly those of the Clinical Proteomics Tumor Analysis Consortium (CPTAC), proteomics is now moving into clinical research. Reliable and reproducible quantification of > 10,000 proteins and >30,000 phosphosites is now routinely attainable from mammalian tissue samples. Integration of deep-scale proteomics analysis of human tumors with genomic data has been shown to improve specificity for identifying pathway alterations caused by tumor associated mutations. Furthermore, phosphoproteome measurements provide information on pathway activation not discernible from genetic measurements and thus provides unique insights for potential therapeutic targets. A substantial challenge in the field of clinical proteomics is obtaining the sufficiently large clinical specimens necessary for deep coverage of the proteome. This challenge is particularly acute in the case of phosphoproteomics, which requires 100-fold more material than global profiling due to the low stoichiometry of the modification. The current gold standard approach for clinical proteomics employs a tandem mass tags (TMT) isobaric labeling approach to achieve deep quantitative proteomic and phosphoproteomic measurements. In this approach, 10 or 11 patient samples are labeled with unique isobaric labels, mixed in equal proportion, and fractionated prior to liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. This creates a second challenge since very often due to external variables, differing quantities of protein are obtainable for patients within the same study. In these cases, the analysts need to decide whether to exclude sample-limited patients, reduce the protein loading per patient for the study, or to include that individual patient at reduced protein loading. In this study, we set out to interrogate the impact of differential channel loading on global and phosphoproteomics results using an established clinical workflow. First, we determined protein yields from patient samples of decreasing cell count. We then used these results to design a 2 TMT plex experiment to explore a range of peptide loadings that we expect to encounter in executing a clinical proteomics experiment. The results were examined for protein/phosphosite coverage and various aspects of quantitative reproducibility. Our results provide a thorough examination of the impacts of differential channel loading and provide researchers with a resource to make informed decisions concerning their study design. Citation Format: Paul D. Piehowski, Yang Wang, James A. Sanford, Joshua R. Hansen, Marina A. Gritsenko, Vladislav A. Petyuk, Karl K. Weitz, Cristina Tognon, Wei-Jun Qian, Tao Liu, Brian J. Druker, Karin D. Rodland. Evaluation of differential peptide loading on TMT-based proteomic on phosphoproteomic data quality in an AML model [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5125.

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