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. 2023 Jul 25;21:499. doi: 10.1186/s12967-023-04331-z

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© The Author(s) 2023

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/. 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. 6 — Characterization of immunogenomic features in LPRI subgroups. A Comparisons of the Purity, ImmuneScores, and StromalScores from the ESTIMATE software between low- and high-risk subgroups. B Pearson’s correlation between LPRI and TME signatures in the TCGA-LUAD and GEO-meta dataset. C, D Differences in immune genes between and GEO-meta dataset. E Altered CNV between low- and high-risk subgroups in the TCGA-LUAD in immunogenomics. F Comparison of risk subgroups in the current study with immune subtypes from previous studies. ‘ns’ means no statistical significance, ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001 and ∗∗∗∗P < 0.0001