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. 2022 Nov 12;8:454. doi: 10.1038/s41420-022-01243-7

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© The Author(s) 2022

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — A Principal component analysis of RCCC cancer group and normal groups. B Volcano plot of differentially expressed genes between cancer and normal groups. C According to the combination of module dissimilarity, 11 sub modules were finally obtained in the cancer group. D The correlation between cancer network modules. E Cross analysis of cancer module and normal module, color block represents the number of overlapping genes. F Heat map showing correlation between the gene module and clinical traits. G The relevance of module membership in green and gene significance for PFI time. H The relevance of module membership in green and gene significance for OS time.