The DEGs between the high and low stromal and immune score groups
The aim was to screen immune-related differential genes in liver cancer. In total, 10,221 genes from the TCGA-LIHC dataset were matched by the ESTIMATE algorithm, and the number of unmatched genes was 191. There were 1811 DEGs (of which 1744 and 67 were up- and downregulated, respectively) were selected according to the high and low immune score groups (Fig. 1A and Supplementary file 1). Meanwhile, a total of 55,955 DEGs (of which 2279 and 153 were up- and downregulated, respectively) were selected between high and low stromal score groups (Fig. 1B and Supplementary file 2). In addition, 1211 overlapped upregulated DEGs and 27 overlapped downregulated DEGs were selected in the stromal score and immune score groups (Fig. 1C, D). The names of DEGs are shown in Supplementary file 3. In the enrichment analysis of 1238 overlapped DEGs, the GO analysis showed that the 1238 DEGs were mainly enriched in 1457 GO-biological processes (BPs; e.g., regulation of lymphocyte activation, leukocyte migration, and lymphocyte differentiation) and 74 KEGG pathways [e.g., cell-adhesion molecules (CAMs)] (Fig. 1E, F).
Identification of T cell-related genes
T cells played an important role in liver cancer occurrence and development. The aim was to further analyze T cell-related genes in liver cancer. The abundance of immune-cell infiltration in tumor samples was estimated and the immune-cell landscape was shown in Fig. 2. Meanwhile, according to the Pearson correlation coefficient, a total of 120 activated memory CD4 T cell-related genes (Supplementary file 4) and 309 CD8 T cell-related genes were identified (Supplementary file 5). In the enrichment analysis of activated memory CD4 T cells and CD8 T cell-related genes, activated memory CD4 T cell-related genes were enriched in 406 GO-BPs and 35 KEGG pathways [e.g., CAMs, Th1 and Th2 cell differentiation, and Hematopoietic cell lineage], the Top 8 GO terms and Top 10 KEGG pathways were shown in Fig. 3A and B, respectively. In addition, CD8 T cell-related genes were involved in 596 GO-BPs and 42 KEGG pathways [e.g., Th17 cell differentiation, Th1 and Th2 cell differentiation, and CAMs], the Top 8 GO terms and Top 10 KEGG pathways were shown in Fig. 3C and D, respectively. In addition, based on the CTD database, activated memory CD4 T cell-related genes were involved in 31 liver cancer-related pathways [e.g., CAMs, Th1 and Th2 cell differentiation, hematopoietic cell lineage] (Table 2), and CD8 T cell-related genes were involved in 36 liver cancer-related pathways [e.g., Th17 cell differentiation, Th1 and Th2 cell differentiation, and CAMs] (Table 3).
T cells associated with prognosis of liver cancer
Liver cancer was an often fatal malignant with poor prognosis. The purpose was to further analyze the role of T cell-related genes in the prognosis of hepatocellular carcinoma. A total of 363 sets of survival information from patients with liver cancer was obtained. Moreover, nine activated memory CD4 T cell-related genes were associated with liver cancer prognosis [e.g., eomesodermin (EOMES), glutathione S-transferase (CST7), and adhesion G protein-coupled receptor E2 (EMR2)] (Table 4). In addition, there were 30 CD8 T cell-related genes associated with liver cancer prognosis [e.g., CD5 molecules like CD5L, EOMES, and CST7] (Table 5). Upregulated expression of T cell-related genes including EOMES, CST7, and CD5L indicated the favorable prognosis of liver cancer. Downregulated expression of T cell-related genes including NCF2 and HTAR3 indicated the poor prognosis of liver cancer.
PPI network of the T cell-related genes
The PPI network was constructed to plot the characteristics of these molecules. PPI network analysis of activated memory CD4 T cell-related genes revealed 53 nodes, including one survival-related gene (EOMES), and 162 interaction pairs (Fig. 4A). The CD8 T cell-related gene PPI network contained 127 nodes, including 11 survival-related genes [e.g., EOMES, CD69 molecule (CD69), and zeta chain of T cell receptor-associated protein kinase 70 (ZAP70)], and 613 interaction pairs (Fig. 4B).
CeRNA network of the T cell-related genes
The ceRNA network was constructed to describe the regulatory effect of non-coding RNA on T cell-related differential molecules. Based on the HMDD database, ten miRNA-mRNA relationships of activated memory CD4 T cell-related genes were obtained (10 miRNAs and three target genes). Also, 26 miRNA-mRNA relationships of CD8 T cell-related genes were obtained (22 miRNAs and 10 target genes). Four miRNA-lncRNA relationships of activated memory CD4 T cell-related genes were obtained (four miRNAs and one lncRNA). Furthermore, 21 miRNA-lncRNA relationships of CD8 T cell-related genes were obtained (21 miRNAs and 13 lncRNAs). Based on the ten miRNA-mRNA relationships and four miRNA-lncRNA relationships of activated memory CD4 T cell-related genes, a ceRNA network of activated memory CD4 T cell-related genes was constructed (Fig. 5A). Here, EOMES was regulated by has-miR-23b-3p and has-miR-23b-3p was regulated by lncRNA AC104820.2. In addition, the ceRNA network of CD8 T cell-related genes was constructed among 26 miRNA-mRNA relationships and 21 miRNA-lncRNA relationships (Fig. 5B). Here, EOMES was regulated by has-miR-23a-3p and has-miR-23a-3p was regulated by lncRNA AC000476.1.
Chemical small-molecule–target network analysis of T cell-related genes
The chemical small-molecule–target network was constructed to find agents that regulate these differentially expressed genes. There were 44 chemical small-molecule–target interaction pairs associated with activated memory CD4 T cells (Fig. 6A), including five mRNAs and 26 chemical small molecules. In addition, there were 276 CD8 T cell-associated chemical small-molecule–target interaction pairs, containing 19 mRNAs and 110 chemical small molecules (Fig. 6B).
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