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. 2022 Mar;10(6):281. doi: 10.21037/atm-22-764

Figure 4.

Figure 4

Performance of CIBERSORT across immune cells in NSCLC samples. (A) Barplot showing the proportion of 22 types of immune cells in NSCLC tumor samples. (B) Heatmap shows the correlation between 22 kinds of immune cell proportions in TCGA datasets. Red represents a positive correlation and blue represents a negative correlation; the darker the color, the stronger the correlation. (C) Violin plot showing the ratio differentiation of 22 types of immune cells between NSCLC tumor samples with low or high Siglec15 expression relative to the median of Siglec15 expression level. (D) Scatter plot showing the correlation of eight kinds of infiltrated immune cells with the Siglec15 expression (P<0.05). (E) Venn plot displaying eight kinds of immune cells correlated with Siglec15 expression co-determined by difference and correlation tests displayed in the violin and scatter plots, respectively. (F) The results showed that the expression of previously discovered immune checkpoints was significantly higher in the high Siglec15 expression group. ***, P<0.001. CIBERSORT, Cell-type Identification by Estimating Relative Subsets of RNA Transcripts; NSCLC, non-small cell lung cancer; NK, natural killer cells; PD-1, programmed cell death 1; PD-L1, programmed cell death-ligand 1; TIM-3, T cell immunoglobulin mucin; TIGIT, T cell immunoreceptor with Ig and ITIM domains.