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. 2024 Nov 14;16(12):3089–3112. doi: 10.1038/s44321-024-00169-0

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© The Author(s) 2024

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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the data associated with this article, unless otherwise stated in a credit line to the data, but does not extend to the graphical or creative elements of illustrations, charts, or figures. This waiver removes legal barriers to the re-use and mining of research data. According to standard scholarly practice, it is recommended to provide appropriate citation and attribution whenever technically possible.

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(A) Workflow for the building and validation of GCPS. (B) Patient subgrouping based on the lipids associated with prognosis (P < 0.05 for univariable variant cox analysis and spearman’s correlation coefficients less than 0.5 between lipids). Samples and lipid metabolites are displayed as columns and rows, respectively, and the color of each cell shows the z-score of the relative abundance of the lipids (logarithmic scale in base 2). (C) Kaplan‒Meier curves for OS based on the GCPS for the exploration, external validation, and predictive cohorts. (D) Prognostic analysis of the GCPS in GC patients with different stages in the exploration, external validation, and predictive cohorts. P values were determined by log-rank test (C, D). CI confidence interval, GC gastric cancer, GCPS gastric cancer prognostic subtype, HR Hazard ratio, OS overall survival.