EPDR1 expression is significantly elevated in HCC tissues
First we compared the expression of EPDR1 in HCC and normal liver tissues using multiple datasets obtained from TCGA, ICGC, GEPIA and GEO databases. Analysis of several HCC cohorts in the TCGA and ICGC databases revealed that EPDR1 mRNA expression was significantly higher in HCC tissues than in the adjacent normal tissues (Fig. 1A and 1B. Further, the expression data in the GEPIA database indicated up-regulation of EPDR1 in the HCC tissues compared to the normal tissues from TCGA (Fig. 1C) or GTEx database (Fig. 1D). Additionally, three independent microarray studies obtained from the GEO database validated the significant higher expression of EPDR1 in tumor tissues than in the normal tissue (Fig. 1E).
Finally, we verified the protein levels of EPDR1 in HCC tissues using HPA and CPTAC databases. The IHC data in HPA database revealed that the expression of EPDR1 was significantly higher in HCC tissue than the normal tissues (Fig. 1F). Further, EPDR1 level was found to be significantly increased in the HCC group compared to that in normal group (p = 9.938-e04) based on CPTAC data, as shown in Fig. 1G.
Prognostic Significance Of Epdr1 Expression In Hcc
Next, we sought to investigate the prognostic significance of EPDR1 expression in HCC. The association between EPDR1 level and the survival outcomes of HCC patients was assessed using Kaplan-Meier survival curves (Fig. 2). The results showed clustering of patients into two groups according to the median value of EPDR1 expression level in each cohort. The group with high EPDR1 expression had significantly shorter overall survival (OS), progression-free survival (PFS), recurrence free survival (RFS) and disease specific survival (DSS) compared to the group with low expression of EPDR1 based on TCGA data using GEPIA database (Fig. 2A). Figure 2B indicates significant correlation (p < 0.001) between high EPDR1 mRNA expression and worse OS for HCC patients based on the data obtained from ICGC database. As shown in Fig. 2C, univariate analysis using Cox regression revealed that EPDR1 expression and T stage are significantly associated with overall survival (p < 0.05). Multivariate analysis and ROC curve revealed that up-regulated expression of EPDR1 is an independent prognostic factor of poor prognosis based on TCGA data (p < 0.005). The prognostic significance of EPDR1 verified using the data obtained from ICGC database is shown in Fig. 2D.
Correlation between EPDR1 expression and clinical characteristics of HCC patients
The correlation between EPDR1 expression and various clinicopathological parameters in HCC patients based on TCGA and ICGC data are shown in Fig. 3a and Fig. 3B, respectively. We observed significantly higher levels of EPDR1 in male patients (p = 0.015), and in patients with advanced stage of the disease (p = 0.018) and bad prognosis (p = 0.012). Furthermore, the expression of EPDR1 was shown to be significantly increased gradually from stage I to stage IV (p = 0.001), and was found to be significantly higher in patients with follow-up death (p = 0.003). Thus, these results indicate that EPDR1 is overexpressed and positively associated with advanced tumor stage in HCC.
Expression Of Epdr1 In Human Normal Tissues
EPDR1 expression in normal human tissueswas determined using the data obtained from the GTEx database. Red represents high expression, black represents median expression, and green represents low expression (Fig. 4A). EPDR1 was found to be highly expressed in most tissues except in the liver, as shown in Fig. 4A and B,. Further, no significant gender based difference was observed in the expression of EPDR1 in most tissues or organs, except in case of blood and skeletal muscle (p < 0.05 and p < 0.01, respectively) (Fig. 4B).
Epdr1 Co-expressed Genes In Hcc
To gain insight into the biological importance of EPDR1 in HCC, the function module of LinkedOmics was used to examine the EPDR1 co-expression in liver HCC (LIHC) cohort. Figure 5A shows genes highly co-expressed with EPDR1 based on Pearson correlation; genes positively and negatively correlated with EPDR1 are marked in dark red and dark green dots, respectively (FDR < 0.01). Top 50 genes showing significant positive and negative correlation with EPDR1 are shown in heatmaps (Fig. 5B and C). The prognostic role of the top 50 genes positively and negatively correlated with EPDR1 in LIHC cohort are shown in Fig. 5D. Further, 24 of the top 50 positively correlated genes were shown to be high-risk genes; whereas 8 of the top 50 negatively correlated genes were low-risk genes (Fig. 5D). Gene Ontology (GO) enrichment analysis showed that EPDR1 co-expressed genes were significantly associated with the activation of integrin-mediated signaling pathway, antigen processing, and presentation and leukocyte apoptotic process, while the processes, such as fatty acid metabolism, protein activation cascade were inhibited (Fig. 5E). KEGG pathway analysis showed enrichment of pathways such as, hippo signaling, pathways related to various infections, small cell lung cancer, nucleotide excision repair, and DNA replication (Fig. 5F). These results suggest a widespread impact of EPDR1 expression on the global transcriptome of HCC tissues.
To further analyze the biological functions of EPDR1 in HCC, GSEA was performed on datasets with high and low expression of EPDR1. These results revealed significant differences (FDR q-value < 0.01) in the enrichment of MSigDB Collection (c2.cp.biocarta and h.all. v6.1. symbols). The most markedly enriched signaling pathways screened according to their NES are shown in Fig. 5G. As shown, pathways related to lysosome, NOD like receptor signaling, WNT signaling, ubiquitin mediated proteolysis, MAPK signaling, cancer and apoptosis were significantly represented by EPDR1 high expression phenotype, whereas, pathways associated with glycine, serine and threonine metabolism were represented by EPDR1 low expression phenotype.
Epdr1 Expression And Tumor-infiltrating Immune Cells (tiics)
The survival of patients in several cancers is determined by the number and activity of tumor-infiltrating lymphocytes . Therefore, we explored the relationship between EPDR1 expression and immune cell infiltration in HCC using the TIMER database. Figure 6A shows that EPDR1 expression significantly correlates with purity, and infiltration of B cells, CD8 + T cells, CD4 + T cells, macrophages, neutrophils and dendritic cells in HCC tissues. Moreover, copy number variation of EPDR1 was shown to affect the infiltration of B cells, CD4 + T cells, neutrophils, and dendritic cells in HCC (Fig. 6B). Further, the association between EPDR1 expression and level of infiltration of 22 immune cells in TCGA HCC datasets using CIBERSORT indicated clear infiltration of the immune cell subpopulations. The correlation heatmap (Fig. 6C) revealed the proportions of different TIIC subpopulations that were weakly to moderately correlated with the expression of EPDR1.
To better broaden the understanding of EPDR1 crosstalk with immune related genes, we analyzed the association between EPDR1 expression and various immune signatures from TCGA and ICGC datasets. The signatures include immune marker genes of common tumor-infiltrating lymphocytes (TILs), T cell exhaustion, immune inhibitory or stimulatory genes (including immune checkpoint gene sets), cytokine-related genes, major histocompatibility complex genes, and mast cells (Fig. 6D). The results showed that expression of KIR2DL4 (natural killer cell), ITGAM (neutrophil), GATA3 (TH2), STAT6 (TH2), STAT5A (TH2), BCL6 (Tfh), STAT3 (Th17) and HAVCR2 (T cell exhaustion) were significantly correlated with EPDR1 expression levels based on TCGA database (p < 0.05), while KIR2DL2 (natural killer cell), KIRDS4 (natural killer cell), ITGAM (neutrophil), STAT4 (Th1), STAT5A (Th2), STAT6 (Th2), LAG3 (T cell exhaustion), HAVCR2 (T cell exhaustion) and HDC (mast cells) were significantly correlated with EPDR1 expression levels based on ICGC database (p < 0.05).