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. 2023 Jan 16;23:7. doi: 10.1186/s12935-022-02836-z

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© The Author(s) 2023

Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 8 — Correlations of the cuproptosis score with biological characteristics and immune checkpoints between the two score groups. A GSEA results showing differential enrichment of genes in KEGG between the two groups. B Heatmap for immune responses based on the TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCP-COUNTER, XCELL and EPIC algorithms in the two groups. C Boxplots showing the results for immune function scores using ssGSEA between the two groups. D Violin plot of immune cell infiltration between the low and high cuproptosis score groups. E Expression of immune checkpoints between the two groups. F–I The relationship between the IPS and two cuproptosis score groups in TCGA-PAAD patients. *P < 0.05, **P < 0.01, ***P < 0.001