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. 2022 Nov 29;9:732. doi: 10.1038/s41597-022-01845-x

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — Workflow for the proteomic analysis of nine HCC cell lines and generation of the HCC spectral library. Nine HCC cell lines were protein extracted and trypsin digested. Peptides were pre-fractionated by Hp-RP and analysed by LC-MS/MS using DDA mode. The gained 162 raw files were searched again protein database by MaxQuant version 2.0.3.0. Gene Ontology (GO) and ssGSEA analysis were then implemented. For generation of the HCC spectral library, peptides of HCC cell line mixture or tumour tissue mixture were pre-fractionated, then analysed by LC-MS/MS using DDA mode. The gained 48 raw files were searched again protein database by MaxQuant version 2.0.3.0, and the search results were imported into Spectronaut^TM version 15.2 to generate the HCC spectral library. The HCC spectral library could be used in Spectronaut^TM version 15.2 and DIA-NN version 1.8 for DIA quantification.