Proteomic Workflows for High-Quality Quantitative Proteome and Post-Translational Modification Analysis of Clinically Relevant Samples from Formalin-Fixed Paraffin-Embedded Archives

乙酰化 蛋白质组学 等压标记 蛋白质组 定量蛋白质组学 生物标志物发现 赖氨酸 计算生物学 生物 化学 生物化学 氨基酸 基因
作者
Magdalena Kuras,Nicole Woldmar,Yonghyo Kim,Max Hefner,Johan Malm,Judit Moldvay,Balázs Döme,János Fillinger,Luciana Pizzatti,Jeovanis Gil,György Marko‐Varga,Melinda Rezeli
出处
期刊:Journal of Proteome Research [American Chemical Society]
卷期号:20 (1): 1027-1039 被引量:27
标识
DOI:10.1021/acs.jproteome.0c00850
摘要

Well-characterized archival formalin-fixed paraffin-embedded (FFPE) tissues are of much value for prospective biomarker discovery studies, and protocols that offer high throughput and good reproducibility are essential in proteomics. Therefore, we implemented efficient paraffin removal and protein extraction from FFPE tissues followed by an optimized two-enzyme digestion using suspension trapping (S-Trap). The protocol was then combined with TMTpro 16plex labeling and applied to lung adenocarcinoma patient samples. In total, 9585 proteins were identified, and proteins related to the clinical outcome were detected. Because acetylation is known to play a major role in cancer development, a fast on-trap acetylation protocol was developed for studying endogenous lysine acetylation, which allows identification and localization of the lysine acetylation together with quantitative comparison between samples. We demonstrated that FFPE tissues are equivalent to frozen tissues to study the degree of acetylation between patients. In summary, we present a reproducible sample preparation workflow optimized for FFPE tissues that resolves known proteomic-related challenges. We demonstrate compatibility of the S-Trap with isobaric labeling and for the first time, we prove that it is feasible to study endogenous lysine acetylation stoichiometry in FFPE tissues, contributing to better utility of the existing global tissue archives. The MS proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers PXD020157, PXD021986, and PXD021964.
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