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).

Fig. 1
figure1

Differentially expressed genes (DEGs) between the high and low stromal and immune score groups. Based on the median value of stromal and immune scores of all tumor samples, the tumor samples were divided into high- and low-score groups. The standard Bayesian modified t test in the limma package was applied to analyze differentially expressed RNAs (DERNA) between high and low immune-score groups with a cutoff of |logFC| > 1 and P < 0.05. According to the stromal score, there were 55,955 DEGs (2279 upregulated and 153 downregulated) were selected between high and low stromal-score groups. Meanwhile, 1811 DEGs (including 1744 upregulated and 67 downregulated) were selected according to the high and low immune-score groups. In addition, there were 1211 upregulated overlapped DEGs and 27 downregulated overlapped DEGs were selected in the stromal score and immune score groups. In the enrichment analysis of 1238 overlapped DEGs, the GO analysis showed that the 1238 DEGs were mainly enriched in 1457 GO-BPs and 74 KEGG pathways. A The DEGs between high and low stromal-score groups. B The DEGs between high and low immune-score groups. C The upregulated DEGs in the stromal score and immune score groups. D: The downregulated DEGs in the stromal score and immune score groups. E The GO analysis of all overlapped DEGs. F The KEGG pathways analysis of all overlapped DEGs. Red nodes represent upregulated DEGs and blue nodes represent downregulated DEGs. The size of the ball represents the number of genes enriched in each term. The color of the ball represents the value of the P value. DEGs: differentially expressed genes; GO, Gene Ontology; BP, biological process; KEGG, Kyoto Encyclopedia of Genes and Genomes

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).

Fig. 2
figure2

The landscape of the immune cells. To analyze the abundance of infiltration of the immune cells in the samples, RNA-Seq expression profile data were used to target DEGs, and the abundance matrix of the immune cells was evaluated through the CIBERSORT deconvolution algorithm. Finally, the abundance of infiltration of immune cells (including naïve B cells, memory B cells, CD8 T cells, activated memory CD4T cells, M0 macrophages, M1 macrophages, M2 macrophages, activated dendritic cells, and neutrophils) was determined

Fig. 3
figure3

Enrichment analysis of activated memory CD4 T cells and CD8 T cell-related genes. The clusterProfiler package in R was used to perform GO and KEGG pathway enrichment analysis with a cutoff of P < 0.05 and count ≥ 2. 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 (e.g., regulation of lymphocyte activation, regulation of T cell activation, and regulation of cell-cell adhesion) and 35 KEGG pathways [e.g., CAMs, Th1 and Th2 cell differentiation and Hematopoietic cell lineage]. In addition, CD8 T cell-related genes were involved in 596 GO-BPs (e.g., regulation of lymphocyte activation, regulation of T cell activation, and regulation of cell-cell adhesion) and 42 KEGG pathways [e.g., Th17 cell differentiation, Th1 and Th2 cell differentiation, and CAMs]. A The GO analysis of activated memory CD4 T cell-related genes. B The GO analysis of CD8 T cell-related genes. C The KEGG pathways analysis activated memory CD4 T cell-related genes. D The KEGG pathways analysis CD8 T cell-related genes. The size of the ball represents the number of genes enriched in each term. The color of the ball represents the value of the P value. GO, Gene Ontology; BP, biological process; KEGG, Kyoto Encyclopedia of Genes and Genomes

Table 2 The KEGG pathway analysis of activated memory CD4 T cells and CD8 T cell-related genes in the Comparative Toxicogenomics Database. The KEGG pathway analysis of activated memory CD4 T cell-related genes
Table 3 The KEGG pathway analysis of activated memory CD4 T cells and CD8 T cell-related genes in the Comparative Toxicogenomics Database. The KEGG pathway analysis of CD8 T cell-related genes

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.

Table 4 Activated memory CD4 T cells and CD8 T cells associated with prognosis of liver cancer. Activated memory CD4 T cell-related genes associated with liver cancer prognosis
Table 5 Activated memory CD4 T cells and CD8 T cells associated with prognosis of liver cancer. CD8 T cell-related genes associated with liver cancer prognosis

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).

Fig. 4
figure4

The PPI network of activated memory CD4 and CD8 T cell-related genes. The STRING database was used to analyze protein-protein interactions encoded by activated memory CD4 T cells and CD8 T cells. The PPI score was set as 0.7 (high-confidence value). Afterward, the PPI networks of activated memory CD4 T cells and CD8 T cell-related genes were constructed using Cytoscape software. PPI network analysis of activated memory CD4 T cell-related genes revealed 53 nodes and 162 interaction pairs. The CD8 T cell-related gene PPI network contained 127 nodes and 613 interaction pairs. A The PPI network of activated memory CD4 T cell-related genes. B The PPI network of CD8 T cell-related genes. Red nodes represent survival-related DEGs, triangles represent upregulated DEGs, and blue nodes represent other DEGs. The size of nodes represents the value. Larger nodes indicate a larger value. PPI, protein-protein interaction; STRING, Search Tool for the Retrieval of Interacting Genes

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.

Fig. 5
figure5

CeRNA network of activated memory CD4 T cells and CD8 T cell-related genes. The miRNAs of activated memory CD4 T cells and CD8 T cell-related genes were predicted using miRWalk 3.0, and miRNA-target interaction pairs in the TargetScan, MiRDB, and MirTarBase databases were obtained using a threshold of score > 0.95. In addition, the HMDD V3.2 database was used to further validate and screen the predicted miRNA using the keywords “Carcinoma, Hepatocellular”. The lncRNAs-miRNAs relationship between activated memory CD4 T cells and CD8 T cell-related genes was predicted using the DIANA-LncBase database. Finally, activated memory CD4 T cell- and CD8 T cell-related gene lncRNA-miRNA-mRNA network was constructed utilizing Cytoscape software. EOMES was regulated by has-miR-23b-3p and has-miR-23b-3p were regulated by lncRNA AC104820.2. EOMES was regulated by has-miR-23a-3p and has-miR-23a-3p was regulated by lncRNA AC000476.1. A ceRNA network of activated memory CD4 T cell-related genes. B ceRNA network of CD8 T cell-related genes. Red nodes represent upregulated DEGs, green triangles represent miRNA, and the red rhombi represent upregulated lncRNAs

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-moleculetarget 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-moleculetarget interaction pairs, containing 19 mRNAs and 110 chemical small molecules (Fig. 6B).

Fig. 6
figure6

Chemical small-molecule–target network analysis of activated memory CD4 T cells and CD8 T cell-related genes. To search for liver cancer-related genes and chemicals, the Comparative Toxicogenomics Database was searched using “Carcinoma, Hepatocellular” as keywords. Genes that were both associated with liver cancer, and belonged to the T cell-related genes ceRNA network, were used to screen chemical-target pairs. The T cell-related genes chemical small-moleculetarget network was obtained utilizing the Cytoscape software. There were 44 chemical small-moleculetarget interaction pairs associated with activated memory CD4 T cells, including five mRNAs and 26 chemical small molecules. In addition, there were 276 CD8 T cell-associated chemical small-moleculetarget interaction pairs, containing 19 mRNAs and 110 chemical small molecules. A The chemical small-moleculetarget network of genes in activated memory CD4 T cells. B The chemical small-moleculetarget network of genes in CD8 T cells. Red nodes represent survival-related upregulated DEGs, and green nodes represent chemical small molecules. The size of nodes represents the value, such that larger nodes indicate a larger value

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