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. 2021 Sep 20;12:739768. doi: 10.3389/fimmu.2021.739768

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Copyright © 2021 Sun, Xie, Zhang, Wang, Huang and Xia

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Identification of m⁶A methylation modification subtypes. (A) Heat map of sample clustering under k = 2 in 5 independent PC cohorts. (B) Consensus clustering cumulative distribution function (CDF) with the number of subtypes k = 2 to 9. (C) The relative change of the area under the CDF curve of k = 2 to 9. (D) Principal component analysis of the expression profiles of 23 m⁶A regulators to distinguish two determined m⁶A clusters. (E) Unsupervised clustering of 23 m⁶A regulators in two m⁶A clusters. (F) Differences in the expression of 23 m⁶A regulators between distinct m⁶A clusters. (G) TME immune-infiltrating characteristics and transcriptome traits of two m⁶A clusters. (H) GO enrichment pathway of differentially expressed genes between two m⁶A clusters. (I) KEGG enrichment pathway of differentially expressed genes between two m⁶A clusters. ***P < 0.001; **P < 0.01; *P < 0.05.