Fig. 4 | Scientific Reports

Fig. 4

From: Integrated single-cell and machine learning analysis identifies PMAIP1 as a novel biomarker for predicting prognosis and immunotherapy response in colorectal cancer

Fig. 4The alternative text for this image may have been generated using AI.

Differential Expression Analysis and Functional Enrichment Analysis. (A) Volcano plot illustrating the distribution of differentially expressed genes (DEGs), with the horizontal axis representing log2 FoldChange and the vertical axis representing -log10(FDR). Green indicates upregulated genes, orange indicates downregulated genes, and gray indicates genes with no significant differences. Significant genes such as CDH3, ETV4, FOXO1, etc., are labeled in the plot. (B) Heatmap displaying the expression levels of the top 100 differentially expressed genes in normal tissues (N) and tumor tissues (T). Colors ranging from red (high expression) to blue (low expression) represent changes in expression levels. (C) Gene Ontology (GO) enrichment analysis results, showing the top 30 biological process (BP) terms significantly associated with the differentially expressed genes, primarily involving cell differentiation, T cell differentiation, regulation of cell adhesion, etc. (D) KEGG enrichment analysis results, displaying the top 20 significant pathways, including the “MAPK signaling pathway,” “T cell receptor signaling pathway,” and pathways related to viral infections and cancer, etc. The pathways were generated using KEGG Mapper (https://www.kegg.jp/kegg/tool/map_pathway.html) and are reproduced with permission from Kanehisa Laboratories ©2025.

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