A Comprehensive Pan-cancer Analysis of the Biological Immunomodulatory Function and Clinical Value of CD27

Abstract

Background: CD27 is an immunological checkpoint gene, plays a critical function inInhibition or activation of cancer immunity. The CD27/CD27L axis is its pathway of action. Therefore, our goal was to examine the predictive role of CD27 in the clinical prognosis of 33 cancer types and its functions in cancer progression, as well as explore the link between pan-cancer CD27 gene expression and immune infiltration. Methods: By comprehensive use of datasets and methods from TCGA, cBioPortal, GTEx, HPA, KM-plotter, Spearman, CellMinerTM, R packages and RT-qPCR, we delved deeper into the potential impact of the CD27 on cancer development. These include expression differences, immune infiltration, matrix infiltration, gene mutations, DNA methylation, signaling pathways, TMB, MSI, and prognosis. Also, we explored CD27 interactions with different drugs. Results: The results showed that, mutated CD27 was highly expressed in most cancers. The CD27 showed strong diagnostic value in 4 cancers and marked a positive prognosis for CESC, intracervical adenocarcinoma, HNSC, and endometrial cancer, and a poor prognosis for UVM. In addition, CD27 affects multiple immune and inflammatory signaling pathways and is positively correlated with immune cell infiltration, T cell differentiation, macrophage M1 polarization, stromal infiltration, and drug sensitivity. DNA methylation is involved in CD27 expression in cancer. Conclusion: CD27, which is mutated in cancers and appears widely highly expressed and altered tumor immune invasion and stromal invasion by affecting multiple immune-related and inflammation signaling pathways, plays a significant role in CESC, HNSC, UCEC and UVM, and may be used as a therapeutic target for related cancers.

Keywords: CD27; immune; pan-cancer; prognosis..

Figure 1

The flow chart of the study design and analysis.

Figure 2

mRNA and protein expression of CD27. (A) CD27 expression data from TCGA. (B) CD27 expression data from TCGA and GTEx. (C) mRNA expression of CD27 in liver cell lines. (D) mRNA expression of CD27 in colon cell lines. (E) mRNA expression of CD27 in kidney cell lines. (F) mRNA expression of CD27 in gastric cell lines. (G) Immunohistochemical of normal cervix uterus. (H) Immunohistochemical of CESC. (I) Immunohistochemical of normal nasopharynx epithelial tissue. (J) Immunohistochemical of HNSC. (K) Immunohistochemical of normal endometrium. (L) Immunohistochemical of UCEC. *P<0.05, ** P<0.01, and *** P<0.001.

Figure 3

Kaplan-Meier survival curves comparison of high and low expression of CD27 gene for different cancer types. (A) OS of BRCA, CESC, HNSC, SARC, SKCM, UCEC, UVM. (B) DSS of BLCA, CESC, HNSC, LUAD, OV, SKCM, UCEC, UVM. (C) DFI of BLCA, CESC, CHOL, HNSC, UCEC. (D) PFI of ACC, BLCA, BRCA, CESC, CHOL, GBM, HNSC, SKCM, UCEC, UVM.

Figure 4

Correlation of CD27 mRNA expression with survival in TCGA. (A) OS. (B) DSS. (C) DFI. (D) PFI.

Figure 5

Correlation of CD27 Expression and Clinical pathology. CD27 expression related with the stage in LUAD (A), KIRC (B), SKCM (C), and STAD (D).CD27 expression associated with age in ESCA (E), LAML (F), LGG (G), BRCA (H), KIRP (I), SKCM (J), STAD (K), THYM (L) and UCEC (M).

Figure 6

Indicators of gene mutation and DNA Methyltransferase. (A) The radar chart of the association between TMB and CD27 gene expression. (B) The radar chart of the relationship between MSI and CD27 gene expression (C) DNA methyltransferase. (D) Immune genes. *P < 0.05, **P < 0.01, and ***P < 0.001.

Figure 7

Correlation of CD27 expression with stromal score and immune score. (A) Immune score. (B) Stromal score.

Figure 8

Immune correlation. TIICs analysis and correlation analysis of CD27 expression with immune checkpoints in tumors. (A) CD27 expression and immune-associated cell infiltration in the TIMER database. (B) CD27 expression and immune-associated cell infiltration using the CIBERSORT algorithm. (C) The heatmap of the association between CD27 and immunosuppressive genes in TCGA.

Figure 9

Drug sensitivity analysis of CD27. CD27 expression was associated with the sensitivity of nelarabine, dexamethasone, chelerythrine, fludarabine, fluphenazine, PX-316, asparaginase, hydroxyurea, cytarabine, chlorambucil, idarubicin, thiotepa, batracylin, pipobroman, triethylenemelamine, decitabine, uracil mustard, LMP-400, cyclophosphamide, fenretinide, melphalan, raltitrexed, ifosfamide, cladribine, XK-469.

Figure 10

GSEA for samples with high CD27 expression and low expression. (A, C, E and G) GO functional annotation of CD27 in CESC, HNSC, UCEC and UVM. (B, D, F and H) KEGG pathway analysis of CD27 in CESC, HNSC, UCEC and UVM.

Figure 11

Univariate Cox regression analysis of CD27 and other clinicopathological variables in SKCM (A), UVM (B). Multivariate Cox analysis of CD27 and other clinicopathological variables in SKCM (C), UVM (D). Nomogram for 1-year, 3-year and 5-year OS of SKCM (E), UVM (F). Time-dependent ROC curves and AUC values for 1-year, 3-year and 5-year OS prediction of SKCM (G) and UVM (H) patients. Calibration plots for 1-year, 3-year and 5-year OS prediction of SKCM (I) and UVM (J). CD27 expression, risk score and survival time distribution of SKCM (K) and UVM (L) patients.