Differential expression of HAVCR2 in normal tissues and tumor samples
To compare the variations in HAVCR2 gene expression in normal and tumor samples, the TCGA database was used. HPA database was used to view the expression levels of HAVCR2 mRNA in normal human tissues. The results are shown in Fig. 1A, HAVCR2 mRNA expression was higher in normal lymph node, kidney and spleen tissues (nTPM > 24), and HAVCR2 mRNA expression was detected in other normal human tissues but at lower levels (nTPM < 24). Figure 1B shows that HAVCR2 was expressed between 24 tumors and normal tissues, except for cancers for which no normal tissue data were available, with significant differences in HAVCR2 expression in 14 cancer types,10 cancer types included BRCA, CHOL, ESCA, GBM, HNSC,KIRC,KIRP,STAD,THCA and UCEC showed distinct upregulation of HAVCR2 expression in tumor samples,while HAVCR2 was significantly downregulated in 4 cancer types,including LUAD, LUSC, PAADand PCPG.Since ACC, DLBC, LAML, LGG, OV, TGCT and UCS lacked normal tissue controls in TCGA expression profiles, GEPIA2 database (TCGA + GTEx) was used to analyze the differential expression of HAVCR2 in these cancers, and the results were shown in Fig. 1C.
Prognostic and diagnostic value of HAVCR2 in multiple aspects of cancer
Survival correlations were analyzed by TCGA database for 33 cancer types including OS, DSS, DFI and PFI. In Fig. 2A,OS Cox regression models revealed that high expression of HAVCR2 was associated with good prognosis in CESC, KIRC, KIRP and SKCM, and with poor prognosis in LGG, TGCG, THYM and UVM. Kaplan-Meier curves revealed that high HAVCR2 expression was associated with good prognosis in SKCM (Fig. 2C),whereas high HAVCR2 expression in LGG and UVM was associated with poor prognosis (Fig. 2B,D). In Fig. 3A,DSS Cox analysis showed that high HAVCR2 expression was correlated with good prognosis in CESC, KIRC, SKCM and THCA,In contrast, upregulation of HAVCR2 expression in tumor samples was associated with poor prognosis for KICH, LGG, THYM and UVM. KM analysis showed that patients with high levels of HAVCR2 expression in CESC, KIRC and SKCM (Fig. 3B,C,D) survived longer, whereas high HAVCR2 expression in LGG and UVM was associated with poor prognosis(Fig. 3E,F). PFI data analysis showed that upregulation of HAVCR2 expression in tumor samples was associated with good prognosis in CESC, KIRC and SKCM, and upregulation of HAVCR2 expression was associated with poor prognosis in GBM, LGG, PRAD, and THYM (Fig. 4A). KM survival analysis showed that upregulation of HAVCR2 expression in tumor samples was associated with good prognosis in CESC, KIRC, SKCM (Fig. 4B,C F), whereas in LGG and PRAD, high HAVCR2 expression was associated with poorer PFI (Fig. 4D,E).In terms of DFI, the forest plot in Figure (5A) showed that high HAVCR2 expression was associated with good prognosis in BLCA and COAD, and with poor prognosis in PAAD. KM data showed that in patients with CESC and UCEC (Fig. 5B,C), high expression of HAVCR2 was associated with a good prognosis. Furthermore,the diagnostic value of HAVCR2 in various malignancies was examined using the receiver operating characteristic (ROC) curve.As shown in Fig. 6, the HAVCR2 had a moderate diagnostic accuracy of CESC(A), GBM༈B༉,LUAD༈C༉, OSCC༈D༉, CHOL༈E༉,LUSC༈F༉, STAD༈G༉,ESCA༈H༉,HNSC༈I༉,KIRC༈J༉,KIRP༈K༉ and ESAD༈L༉ (AUCs were above 0.7). To summarize, the Survival and ROC curve analyses indicated that HAVCR2 has significant prognostic and diagnostic value in multiple types of cancers.
Correlation between HAVCR2 expression and tumor progression
TCGA and UALCAN databases were used to analyze the relationship between HAVCR2 and the progression of pan-cancerous tumors. The analysis of the TCGA data shows that the expression of HAVCR2 is significantly correlated with the TNM phase in both BLCA and STAD(Fig. 7A,B).The UALCAN database was used to explore the differences in HAVCR2 expression in BLCA, ESCA, STAD and UCEC that occur between Stage I, II, III and IV tumors(Fig. 7C,D,E,F).
DNA methylation analysis of HAVCR2 in pan-cancer
DNA methylation has a direct or indirect effect on cancer development and progression[18].The DNMIVD database, which contains data from TCGA and GEO, can be used to analyze the relationship between DNA methylation and prognosis for different cancers. Table 2 summarizes the five methylation sites and related information of HAVCR2.Table 3 illustrates the Spearman's correlation of DNA methylation of the HAVCR2 gene in pan-cancer, where a negative correlation between HAVCR2 expression and methylation levels was observed in a variety of cancers, except ESCA, LIHC, LUSC and THYM. In addition, the correlation between HAVCR2 expression and methylation in KIRP (A), LUAD (C), SARC (E), STAD (G) and THCA (I) was investigated to illustrate the impact of HAVCR2 methylation on cancer prognosis(Figure 8). HAVCR2 was highly expressed in KIRP and its hypermethylation showed a worse prognosis(Fig. 8B);HAVCR2 was low expressed in LUAD and SARC and its hypermethylation was correlated with poor prognosis (Fig. 8D, F) ; whereas HAVCR2 was highly expressed in STAD and THCA and their hypermethylation showed a better prognosis than hypomethylation (Fig. 8H, J) .
Table 2
DNA methylation of HAVCR2
CpG | Group | Relation to Island |
cg15371617 | 1stExon;5'UTR | OpenSea |
cg17484237 | 1stExon;5'UTR | OpenSea |
cg18374914 | 3'UTR | OpenSea |
cg19063654 | Body | OpenSea |
cg19646897 | TSS1500 | OpenSea |
Table 3
Methylation-Expression correlation for HAVCR2 in pan cancer
Cancer type | Spearman_r | Spearman_pvalue |
BLCA | -0.258054 | 7.06E-08 |
BRCA | -0.25125 | 0 |
CESC | -0.316408 | 30E-08 |
CHOL | -0.157839 | 0.300421 |
COAD | -0.0802064 | 0.154904 |
ESCA | 0.0201358 | 0.79378 |
GBM | -0.042674 | 0.737764 |
KIRC | -0.504155 | 1.90E-23 |
KIRP | -0.710049 | 0 |
LIHC | 0.128978 | 0.00860497 |
LUAD | -0.171202 | 0.000174649 |
LUSC | 0.131588 | 0.0105393 |
PAAD | -0.217287 | 0.00321443 |
PCPG | -0.0418256 | 0.571883 |
PRAD | -0.203095 | 0.000002379 |
READ | -0.0530462 | 0.598303 |
SARC | -0.497248 | 7.84E-18 |
SKCM | -0.148177 | 0.00132134 |
STAD | -0.0552432 | 0.311952 |
THCA | -0.323898 | 0 |
THYM | 0.188775 | 0.0381113 |
Next, a methylation site of HAVCR2 (cg15371617) was randomly selected for analysis using the EWAS Date Hub database.In gastric cancer tissues, methylation levels were significantly higher than in healthy samples, and high methylation levels showed a worse survival prognosis(Fig. 9A,B).The correlation analysis between HAVCR2 and four methyltransferases (DNMT3A, DNMT3B, DNMT1, DNMT2) expression in 33 tumors (Fig. 9C). In BRCA, DLBC, KICH, KIRC, LIHC, PAAD, PRAD and UVM, HAVCR2 expression was positively correlated with at least one methyltransferase gene, and in other tumors, HAVCR2 expression was negatively correlated with at least one methyltransferase gene.
Analysis of genetic alterations in the HAVCR2 gene in pan-cancer
Targeted blocking of TIM-3 enhances anti-tumor immunity and reduces the tumor burden. The HAVCR2 mutation can induce misfolding of TIM-3 and decrease its function and expression[3].Therefore, the genetic changes of HAVCR2 in pan-cancer samples were understood through cBioPortal (TCGA, Pan-Cancer Atlas) database.As shown in Figure, the highest frequency of changes in HAVCR2 was about 6% in renal clear cell carcinoma patient, amplification is the most common type of genetic alter (Fig. 10A); Fig. 10B is a three dimensional folding diagram of HAVCR2 protein.;figure 10C is the type, locus and case number of genetic changes obviously presented, and HAVCR2 missense mutations occur in A28V in V-set. In addition, the OS, PFS and DSS of tumor patients with HAVCR2 gene changes were better than those without changes (Fig. 10D,E,F), but there was no difference in DFS between the two groups (Fig. 10G).
Correlation between HAVCR2 expression and TME in pan-cancer
HAVCR2 expression was significantly associated with TIICs, such as CD4 + T cells in 25 cancers, CD8 + T cells in 27 cancers, neutrophils in 29 cancers, macrophages in 30 cancers, DCs in 30 cancers, and B cells in 28 cancers by the TIMER method (Fig. 11A).Except THYM and UVM, the expression of HAVCR2 is positively correlated with various infiltrating immune cells in most cancers. The CIBERSOR tool was used to explore the relationship between HAVCR2 expression and infiltration of 22 immune cell subtypes. Results as shown in Fig. 11B, the expression of HAVCR2 was positively correlated with B cell memory, Macrophage (M1,M2), Myeloid dendritic cell resting, T-cell CD4 + memory activated, T-cell CD8 + and T cell gamma delta in many cancers, but negatively correlated with the other 15 immune cell subtypes. Figure 12 revealed that in CESC, KIRC, LGG, PRAD, SKCM, TGCT, UCECand UVM cancers, HAVCR2 expression was significantly associated with stromal and immune scores in cancer patients.
Correlation between HAVCR2 expression and TMB, MSI and MMR in pan-cancer
Tumor development is associated with TMB, MSI, and MMR[19–21],which prompted us to analyze their relationship with HAVCR2 expression.The results showed that HAVCR2 expression was positively correlated with TMB in COAD, PRAD, SARC, THYM and UCEC, while negatively correlated in HNSC, LAML, LIHC, LUAD, PAAD, TGCT and THCA (Fig. 13A). MSI is a marker for ICP inhibitors and has been found to be crucial in malignancies[22]. For MSI, it was positively correlated with HAVCR2 expression in COAD and KIRC, while negatively correlated in HNSC, LGG, LUAD, LUSC, MESO, OV, SKCM, STAD and TGCT (Fig. 13B).HAVCR2 expression was significantly correlated with at least one MMR gene expression in most tumor types except DLBC, KICH and PCPG (Fig. 13C).
Correlation between HAVCR2 expression and ICPs in pan-cancer
ICP genes have a significant impact on TIICs and immunotherapy[23]. The correlation between HAVCR2 expression and ICPs was analyzed, and the results are shown in the heat map (Fig. 14). In most tumors, HAVCR2 expression was positively correlated with the expression of multiple ICP genes, such as PDCD1 (PD-1), CTLA4, TNFRSF9, CD86, CD274, TIGIT, LAG3, ICOS, CD40LG, CD48 and CD28. In essence, HAVCR2 expression may be involved in the activation of ICP genes in several signaling pathways and play a role in tumor progression.
GESA analysis of HAVCR2 expression
To explore the functional or signaling pathways through which HAVCR2 affects tumourigenesis, we performed GO functional annotation and KEGG pathway analysis of HAVCR2 in different cancer types. GO analysis showed that HAVCR2 expression can affect gene silencing, keratinisation, mRNA export from the nucleus, DNA binding transcriptional activator activity, complement activation and messenger RNA binding, and other biological processes (Fig. 15). The higher the expression of HAVCR2 in (A) HNSC, (C) KIRP, (D) LGG, (E) STAD, (G) THCA and (H) UCEC, the more active the immune function. In contrast, the lower the expression of HAVCR2 in (B) KIRC and (F) TGCT, the more active the immune function. These immune functional activities include regulation of immune responses, humoral immune responses, adaptive immune responses, B-cell mediated immunity, regulation of lymphocyte activation, production of positive regulatory factors, positive regulation of biostimulatory responses, antigen binding, negative regulation of cytosolic processes, negative regulation of epithelial cell proliferation, and positive regulation of immune effector processes. KEGG pathway analysis showed that HAVCR2 regulates key immune cell-related pathways in (I) KIRC, (J) LGG, (K) TGCT and (L) UCEC cancer types(Fig. 15), including cytokine receptor interactions, antigen processing and presentation, nod-like receptor signaling pathways, IGA-producing intestinal immune networks, chemokine signaling pathways, natural killer cell-mediated cytotoxicity, T cell receptor signaling pathway. The above analysis suggests that HAVCR2 plays a key role in tumour immunity.
Validation of HAVCR2 expression
MCF-7, MDA-MB-231,MCF-10A, CAKI-2,HK-2, AGS, MKN-45, HGC-27,GES-1 cell lines were grown to 90–100% confluence at 37°C in a 5% CO2 humidified incubator.After the RNA was extracted, the reverse transcription and RT-qPCR were performed.For all investigated tumors, the signficantly higher (p < 0.05) expression of HAVCR2 was noted in all cancer cell lines compared to normal cell lines (Fig. 16) which is consistent with bioinformatics analysis.The expression of HAVCR2 in cell lines is shown in Table 4.
Table 4
Expression of HAVCR2 in cancer cells
Normal breast epithelial cells | MCF-10A | Normal |
Breast cancer cells | MCF-7 | Upregulated |
MDA-MB-231 | Upregulated |
Normal renal cortical proximal tubular epithelial cells | HK-2 | Normal |
Kidney renal papillary cell carcinoma | CAKI-2 | Upregulated |
Normal gastric epithelial cells | GES-1 | Normal |
Stomach cancer cells | AGS | Upregulated |
MKN-45 | Upregulated |
HGC-27 | Upregulated |