Figures & data
Figure 1. Construction of ES event prediction model.
a. The upset plot of AS events associated with prognosis.
b. Heatmap of ES events in the model. We ranked patients based on risk scores and assigned gradient colours to PSI values based on the range of PSI values for each ES event. Red represents high PSI values, and green represents low PSI values.
c. Distribution of survival status and risk score of HCC patients. In the survival status part, each point represents a patient. Red represents death and green represents alive. The risk score of patients was increased from left to right.
d. Kaplan-Meier curves of overall survival of patients. The patients in the low-risk group had a better prognosis than those in the high-risk group. The result was statistically significant (p < 0.05).
Table 1. The prognostic model related to exon skip events.
Figure 2. The prediction ability and independent verification of the model.
a. ROC curve analysis of the model over time. The AUC was calculated for ROC curves, and sensitivity and specificity were calculated to assess score performance. This model showed good prediction ability.
b. Univariate Cox analysis. Analyzed the correlation between relevant factors and prognosis.
c. Multivariate Cox analysis. Comprehensive analysis of the correlation between relevant factors and prognosis.
d. Stratified patients by 65 years old, and compared the prognosis of patients with high and low ages according to risk assessment score. The results were statistically significant (p < 0.05).
e. Stratified patients by stage, and compared the prognosis of patients with early and late stages according to risk assessment score. The results were statistically significant (p < 0.05).
Figure 3. Correlation of model with clinical features.
a. The boxplot showed the correlation between risk scores and tumour grades.
b. The boxplot showed the correlation between risk scores and tumour stages.
c. Comparison of ROC curves of different clinical features and ES event model. ES event model has the best prediction ability.
d. The expression of IRF3 in HCC and liver tissues.
e. The boxplot showed the correlation between IRF3 expression and tumour grades.
f. Kaplan-Meier curves of patients between high and low IRF3 expression groups. The patients with low IRF3 expression had a better prognosis. The result was statistically significant (p < 0.05).
Figure 4. The structure and isoforms of IRF3.
a. Association analysis between IRF3 expression and IRF3 ES event proportion (1-PSI).
b. Structure composition of IRF3
a. The arrangement of IRF3 exons displayed in TCGA SpliceSeq database. The thin exon represents the untranslated region (UTR), and the thick exon represents the coding region. The splice sequence exon number is obtained based on the TCGA SpliceSeq database.
b. The IRF3 encoding exons displayed in the Ensembl database. The number above represents the starting and ending nucleotide positions of the exon, while the number below represents the name of the exon in the Ensembl database.
c. The protein structure of IRF3 displayed in the UniProt database. The orange region is the DNA binding region, the blue region is the HERC5 binding region, and the red line is the ISG15 binding site. The number above represents the starting and ending nucleotide positions of the region.
c. Amino acid sequences of IRF3 and its two isoforms in the UniProt protein database.
Table 2. The IRF3 ES events associated with prognosis.
Figure 5. Screening and grouping of patients based on the proportion of IRF3 ES events.
a. Screening differentially expressed genes between the high ES group and the low ES group. |LogFC|>1 and FDR < 0.05 were used as the criteria. Red indicates upregulation of gene relative expression, while blue indicates downregulation. The top 20 genes are shown in the figure.
b. Kaplan-Meier curves of patients in high ES and low ES groups. The patients with a low proportion of IRF3 ES events had a better prognosis. The result was statistically significant (p < 0.05).
c. Functional enrichment analysis of upregulated genes in the high ES group.
d. Venn diagrams of differentially expressed genes and IRF3 target genes. The blue circle represents the differentially expressed gene in the high ES group, and the red circle represents the IRF3 target genes. The genes in the middle intersection area are shown on the right. IRF3 target genes set was from the GSE31477 data set selected in the Htftarget database.
Figure 6. Expression and prognosis of differentially expressed target genes in HCC.
a. The expression of target genes between high and low ES groups. The left represents liver tumour tissue, and the right represents normal liver tissue. Data was obtained through the GEPIA database.
b. The prognosis of target genes in the cancer RNA seq database of Kaplan Meier plotter. The genes shown in the figure were statistically significant.
Figure 7. Correlation of IRF3 and its ES events with tumour immune characterization.
a. The correlation between IRF3 expression and immune cell infiltration in the Timer2.0 database, including CD8+T cells, M1 macrophage, M2 macrophage, and Treg cells.
b. The boxplot shows the correlation between immune checkpoint gene expression and IRF3 expression level.
c. Association analysis between the proportion of IRF3 ES events and immune checkpoint gene expression.
Figure 8. Detection of IRF3 exon skipping by cDNA microarray.
a. IRF3-EX refers to the transcriptional isoforms with missing exon ENSE0002224211.
b. The relative expression level of the IRF3-EX isoform in 66 liver cancer patients.
c. The proportion of IRF3-EX in 66 liver cancer patients. It was calculated by 
.
d. Univariate Cox analysis. Analyzed the correlation between the proportion of IRF3-EX and prognosis.
Supplemental material
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The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.