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. 2023 Jan 7;16:5. doi: 10.1186/s13048-022-01088-9

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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. 7 — The immune infiltration landscape of the GT-based signature in OC. A Estimation of immune score, stromal score and ESTIMATE score between low- and high-risk patients using the ESTIMATE algorithm. B, C Evaluation of the proportions of immune cell subsets using the CIBERSORT and TIMER algorithms. (D, E) Boxplot and Heatmap of the infiltration levels of 28 immune cell subsets in the low- and high-risk groups calculated by ssGSEA, respectively. F Correlation heatmap between six hub genes and these 28 immune cell subdivisions. ***P < 0.001; **P < 0.01; *P < 0.05; -, not significant