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. 2022 Oct 20;13:990594. doi: 10.3389/fgene.2022.990594

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Copyright © 2022 Lu, Liu, Wang, Zhang and Li.

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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Estimating the correlation between m5C-related lncRNAs and immune infiltration and mutation analysis. (A) The correlation analysis of risk score and tumor-infiltrating immune cells by TIMER, XCELL, QUANTISEQ, MCPcounter, EPIC, CIBERSORT-ABS, and CIBERSORT software. (B) A heatmap indicating the differential immune responses between the high- and low-risk groups based on the above seven software. (C) The differential scores of 13 immune-related functions in high- and low-risk groups. (D) Comparison of the risk score in different immune infiltration subtypes. *p < 0.05, **p < 0.01, and ***p < 0.001; ns, non-significant. (E,F) Waterfall plot of the 20 top mutated genes with high mutation frequency in the high-risk group (E) and low-risk group. (F,G) The different mutation event between two groups. (H) KM analysis between high/low TMB groups. (I) Comparative analysis of prognosis combining risk score and TMB.