Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics
Year: 2022
Type: article
Abstract: With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. Compared to the classic SILAC method, spike-in-SILAC is not limited to cell culture analysis, making it suitable for quantitative analysis of tumor tissue samples. TMT offered the lowest accuracy and the highest precision and robustness toward different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics.
Source: Analytical Chemistry
Institutions: University Medical Center Groningen, University of Groningen, Universität Innsbruck, University Medical Center Hamburg-Eppendorf, German Cancer Research Center, Heidelberg University, University Hospital Heidelberg, National Center for Tumor Diseases, Deutsches Konsortium für Translationale Krebsforschung, Carl von Ossietzky Universität Oldenburg
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $5,000
Funders: European Respiratory Society, Deutsches Krebsforschungszentrum, Ministère de l'Économie, de la Science et de l'Innovation - Québec, European Commission, Deutsche Forschungsgemeinschaft, Rijksuniversiteit Groningen, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Universitair Medisch Centrum Groningen, Tiroler Wissenschaftsförderung, Universität Innsbruck, Deutschen Konsortium für Translationale Krebsforschung, Stichting TSC Fonds, HORIZON EUROPE Framework Programme, Universitätsklinikum Hamburg-Eppendorf, H2020 Marie Skłodowska-Curie Actions, H2020 Health
Awards: G103040316, G1280267364, G2083358075, G2188863825, G2389168419, Systems Medicine of Metabolic-Signaling Networks: A New Concept for Breast Cancer Patient Stratification, G3009962538, G3426420526, G3431118226, G434337789, G5131486538, Systems Medicine of Metabolic-Signaling Networks: A New Concept for Breast Cancer Patient Stratification, Polymers in the Liver: Metabolism and Regulation, G592703221, G6041802362, G642704625, G643302094, G6511575481, Polymers in the Liver: Metabolism and Regulation, G7109857494, G7505984611, Netherlands X-omics Initiative, Partnership for the Assessment of Risks from Chemicals, G8579141734, G873904766, G8849477942
OpenAlex ID: W4288010073