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. 2022 Dec 3;24:22. doi: 10.1186/s12575-022-00185-9

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© The Author(s) 2022

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. 10 — Tumor mutation and drug sensitivity analyses of patients at different risk statuses. A Genetic mutation landscape in the entire TCGA-LIHC cohort, with the top 30 genes displayed in the waterfall plot. B Waterfall plots showed the genetic mutation features both in the high- (left) and low-risk (right) groups. C Violin plot of the comparison of the TIDE scores between distinct risk groups (left) and their liner dependence (right). D Sensitivity prediction of chemotherapeutic regents in different groups. (***p < 0.001)