Fig. 1: Identification of TAM-specific genes in young-onset THCA through scRNA-seq analysis and validation in bulk RNA-seq datasets. | npj Aging

Fig. 1: Identification of TAM-specific genes in young-onset THCA through scRNA-seq analysis and validation in bulk RNA-seq datasets.

From: Age-specific tumor-associated macrophage biomarkers underlie metastasis and immune dysregulation in thyroid cancer

Fig. 1: Identification of TAM-specific genes in young-onset THCA through scRNA-seq analysis and validation in bulk RNA-seq datasets.

A UMAP visualization of 9 major cell types in the GSE193581 dataset. B UMAP visualization of two age groups. C Dotplot of marker genes. D Box plot of the cell type percentage in two age groups. All boxes are centered at the median and bounded by the first (Q1) and third (Q3) quartiles. Upper whiskers indicate the minimum (maximum, Q3 + 1.5 IQR), and lower whiskers indicate the maximum (minimum, Q1—1.5 IQR). E Filter criteria to obtain age-specific and macrophage-specific genes. F Bar plot exhibiting enrichment results of upregulated and downregulated genes on GOBP terms. Bar length represents the −log10(q-value) of enrichment, reflecting correlation strength. G Gene expression heatmap in the Young and Old groups from GSE153659, based on Z-scores of normalized gene expression levels. H Boxplot of significant DEGs in GSE153659, based on FPKM values. I Gene expression heatmap in the Young and Old groups from GSE53157, based on Z-scores of normalized gene expression levels. J Boxplot of significant DEGs in GSE53157, based on signal intensity. Asterisks indicate the level of statistical significance: ns, non-significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

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