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. 2023 Jul 24;13:11950. doi: 10.1038/s41598-023-37300-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/.

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The distinct TME characteristics between the three m5C modification phenotypes. (A) Heatmap of the different immune cells that infiltrated the TME between the phenotypes. The clinical characteristics and CRC cohort were distributed in distinct m5C clusters. Each column represents patients, and each row represents individual immune cells. (B) The different immune cells infiltrated in the TME of the three m5C clusters calculated by the CIBERSORT algorithm. The Kruskal–Wallis H test was used to statistically analyze the difference between distinct m5C clusters. (C) The difference in the enrichment score of each known biological process gene signature between the three m5C clusters. (D) The immune score, (E) stromal score, and (F) ESTIMATE score of the three gene clusters were analyzed and plotted. (G) The checkpoint gene PD-L1 expression in the distinct m5C clusters.