Bar plot of the genes inside the two databases are shown in Fig. 3. Based on the above benefits, all nine ERK2 custom synthesis pathways enriched within the HCC gene set from GEO are also enriched in the TCGA information. HCC genes have been drastically enriched in the ATR, FANCONI, AURORA_B, PLK1, ARF3, MTOR4, P53_REGULATION, LKB1, ATM, and E2F pathways. All of those pathways are upregulated in HCC. A total of three,569 differential genes had been obtained soon after differential analysis such as 1,614 up-regulated genes and 955 down-regulated genes from TCGA. We obtained 1,078 differential genes, which includes 370 up-regulated genes and 708 down-regulated genes from GEO. Differential expression genes of TCGA and GEO are shown in a volcano map (Fig. 4).Analysis of compound-disease target networkA total of 3,101 HCC differential genes have been obtained after synthesizing the differential genes of your two databases and removing the duplicates. Sixty-four HCC target genes have been obtained by means of the intersection of SNS targets and HCC differential genes. We built a visualized compound-disease target network by combining these with 113 bioactive compounds that had been previously obtained (Fig. five). A total of 177 nodes and 610 edges are shown within the network. Most SNS molecules can act on multiple HCC targets, probably the most predominant of that is quercetin (MOL000098) with 40 edges, followed by kaempferol (MOL000422) with 17 edges. Table 1 shows the 30 most prevalent ingredients in SNS prescriptions that act around the biggest variety of HCC targets. PTGS2 (106 edges), ESR1 (84 edges), AR (74 edges), NOS2 (74 edges), CCNA2 (53 edges) and CHEK1 (50 edges) are the genes regulated by a minimum of 1 compound. The target gene linkage is 50 degrees, indicating that these targets may possibly be a essential target for SNS therapy of HCC.Analysis of protein-protein interactions (PPI) networkThe protein interactions of HCC differential genes extracted from the human genome were shown in the PPI network (Fig. six). Every single node within the network diagram represents a target gene, the connection between the nodes indicates that there is an interaction relationship, and the color of your nodes altering from blue to red represents the degree of your nodesZhang et al. (2021), PeerJ, DOI 10.7717/peerj.6/Figure 1 The outcomes of GSEA enrichment Macrolide Species evaluation of stage III HCC genes from TCGA database. (A) The normalized enrichment score (NES) and significance evaluation of C2 curated gene sets (c2.cp.pid.v7.1) of GSEA; (B ) The top eight significantly enriched pathways (p worth 0.05 and FDR 25 ), namely: ARF pathway, ATM pathway, P53 REGULATION pathway, ATR pathway, AURORA A pathway, E2F pathway, FANCONI pathway and FOXM1 pathway. Full-size DOI: 10.7717/peerj.10745/fig-Zhang et al. (2021), PeerJ, DOI ten.7717/peerj.7/Figure two The results of GSEA enrichment analysis of stage III HCC genes from GEO database. (A) The normalized enrichment score (NES) and significance evaluation of C2 curated gene sets (c2.cp.pid.v7.1) of GSEA; (B ) The best 8 significantly enriched pathways (p value 0.05 and FDR 25 ), namely: ATR pathway, AURORA B pathway, DELTA NP63 pathway, FANCONI pathway, FOXM1 pathway, HIF1A pathway, P73 pathway and PLK1 pathway. Full-size DOI: 10.7717/peerj.10745/fig-Zhang et al. (2021), PeerJ, DOI 10.7717/peerj.8/Figure 3 The enriched pathway of GSEA evaluation depending on HCC targets from TCGA and GEO database. (A) GSEA enrichment analysis of stage III HCC genes from TCGA database. (B) GSEA enrichment evaluation of stage III HCC genes from GEO database. Full-si.