A Pan-Cancer Analysis of the Oncogenic Role of Cell Division Cycle-Associated Protein 4 (CDCA4) in Human Tumors

Abstract

Purpose: To unravel the oncogenic role of CDCA4 in different cancers from the perspective of tumor immunity.

Methods: Raw data on CDCA4 expression in tumor samples and paracancerous samples were obtained from TCGA and GTEX databases. In addition, we investigated pathological stages and the survival analysis of CDCA4 in pan-cancer across Gene Expression Profiling Interactive Analysis (GEPIA) database. Cox Proportional Hazards Model shows that high CDCA4 levels are associated with several vital indicators in oncology. On the one hand, we explored the correlation between CADA4 expression and tumor immune infiltration by the TIMER tool; On the other hand, we utilized the methods of CIBERSORT and ESTIMATE computational to evaluate the proportion of tumor infiltrating immune cells (TIIC) and the amounts of stromal and immune components based on TCGA database. The use of antineoplastic drugs and the expression of CDCA4 also showed a high correlation via linear regression. Protein-Protein Interaction analysis was performed in the GeneMANIA database, and enrichment analysis was performed and predicted signaling pathways were identified by using Gene Ontology and Kyoto Encyclopedia of Genes. The correlation between CDCA4 expression with Copy number variations (CNV) and methylation is detailed, respectively. Molecular biology experiments including Western blotting, flow cytometry, EDU staining, Transwell and Wound Healing assay to validate the cancer promoting role of CDCA4 in hepatocellular carcinoma (HCC).

Results: Most tumors highly expressed CDCA4. Elevated CDCA4 expression was associated with poor OS and DFS. There was a significant correlation between CDCA4 expression and TITCs. Moreover, markers of TIICs exhibited distinct patterns of CDCA4 associated immune infiltration. In addition, we pay attention to the association between the expression of CDCA4 and the use of the anti-tumor drugs. CDCA4 is related to biological progress (BP), cellular component (CC) and molecular function (MF). Dopaminergic Synapse, AMPK, Sphingolipid, Chagas Disease, mRNA Surveillance were significantly enriched pathways in positive and negative correlation genes with CDCA4. CNV is thought to be a positive correlation with CDCA4 expression. Conversely, methylation is negative correlation with CDCA4 expression. Molecular biology experiments confirm a cancer promoting role for CDCA4 in HCC.

Conclusion: CDCA4 may serve as a biomarker for cancer immunologic infiltration and poor prognosis, providing a new way of thinking for cancer treatment.

Keywords: CDCA4; HCC; molecular biology experiments; pan-cancer analysis; tumor.

Figure 1

(A) Using data from the GTEx database, mRNA expression levels of CDCA4 in multiple organs of healthy persons; (B) From the data of CCLE database, CDCA4 expression levels are not only higher universally in diverse cancer cell lines, but also in tighter ranges when compared to the range of expression in normal tissues; (C) Taking TCGA data alone, CDCA4 expression differences between tumor and normal tissues for 20 cancers; (D) Combining the data from TCGA and GTEx, CDCA4 expression differences between tumor and normal tissues for 27 cancers. (*** represents p < 0.001).

Figure 2

The correlation between CDCA4 expression and the pathological stages of cancers, including ACC (A), ESCA (B), KICH (C), KIRP (D), LUAD (E), LIHC (F), THCA (G), TGCT (H) using HEPIA2’s “Pathological Stage Plot” module.

Figure 3

(A) The relationship between CDCA4 expression levels and OS in various cancer types through single variate Cox regression analysis using data from the TCGA database; (B) The survival analyses for median expression value in various cancer types using data from the TCGA database; (C) A high CDCA4 expression level was associated with a poorer OS when compared to a low expression level in the 16 cancer types (HR = 1.5) using data from the TCGA database.

Figure 4

(A) Correlation between CDCA4 expression and DFS analyzed by Cox regression using data from the TCGA database; (B) The survival analysis for CDCA4 expression and prognosis in various cancer types; (C) A high expression level of CDCA4 was concerned to have a correlation with a worse DFS in the 12 cancer types (HR = 1.3) using data from the TCGA database.

Figure 5

(A) K-M plots showed that different CDCA4 levels were associated with pathological stages of OS, PFS, DFS, RFS, DMFS, PSS, DSS and FP events; (B) The results of survival analysis of multiple cancers were integrated into the meta-analysis, and the combined results showed that high expression of CDCA4 in cancer patients was significantly associated with poor prognosis.

Figure 6

A strong connection between CDCA4 expression and the degree of immune cell infiltration in multiple malignancies using the infiltration scores of six immune cell types (B cell, CD4+ T cell, CD8+ T cell, neutrophil, macrophage, and dendritic cell) accessible in the TIMER database and obtained from TCGA.

Figure 7

The top three tumors with the most significant correlation between the degree of immune infiltration and CDCA4 expression were TGCT, LUSC and BRCA (StromalScore); LUSC, UCEC and SKCM (ImmuneScore); LUSC, UCEC and SKCM (ESTIMATEScore), respectively.

Figure 8

(A) CDCA4 expression was inversely linked with most immunological checkpoint molecules in HNSC, LUSC, SARC, SKCM, THYM, UCEC and UCS, though not to a substantial degree in some of them; (B) In BRCA, COAD, ESCA, LGG, LUAD, LUSC, PAAD, PRAD, SARC, SKCM, STAD, THYM and UCEC, CDCA4 expression was positively connected with TMB, whereas in ESCA, KIRC, THYM and UCEC, it was adversely correlated with TMB; (C) In DLBC and TGCT, CDCA4 expression was inversely connected with MSI, but it was positively correlated in COAD, KICH, MESO, SARC, STAD and UCEC; (D) CDCA4 expression considerably and strongly correlates with MMR gene expression in most cancer types (excluding CHOL, COAD, KICH, and READ); MLH1, MSH2, and MSH6 are all positively connected with CDCA4 in most cancer types. (* represents 0.01 < p < 0.05, ** represents 0.001 < p < 0.01, *** represents p < 0.001).

Figure 9

An illustration of the relationship between CDCA4 expression and expected medication response.

Figure 10

(A) a PPI network for CDCA4; (B) The biological processes (BP) enriched in this dataset were primarily those related to DNA Conformation Change/Regulation of Transcription Initiation from RNA Polymerase II Promoter/Cellular Response to dsRNA/Peptidyl-Serine Dephosphorylation/Cellular Response to Exogenous dsRNA, while the cellular components (CC) enriched were primarily those related to Phosphatase Complex/Protein Serine/Threonine Phosphatase Complex/Protein Phosphatase Type 2a Complex. Furthermore, the enriched molecular functions (MF) were linked to Transcription Coactivator Activity/Phosphatase Regulator Activity/Protein Phosphatase Regulator Activity/Protein Serine/Threonine Phosphatase Activity/DNA-Dependent ATPase Activity. The major enriched pathways were those connected with Dopaminergic Synapse, AMPK, Sphingolipid, Chagas Disease, and mRNA Surveillance, according to the KEGG analysis.

Figure 11

(A) A Spearman association between CDCA4 CNV and mRNA was performed in pan-cancer. In BLCA, HNSC, LUSC, OV, and SARC, there is a substantial positive connection between CDCA4 CNV and mRNA expression. On the contrary, this connection was not significant in ACC, DLBC, KIRP, LAML, LIHC, PCPG, THCA and UVM; (B) The top six with the highest correlation scores between CDCA4 CNV and mRNA; (C) With the exception of THYM, CDCA4 methylation was shown to be strongly linked with CDCA4 mRNA expression in most cancer types. Especially in BRCA, ESCA and TGCT, the relevance is particularly obvious; (D) The top six with the highest correlation scores between CDCA4 methylation and mRNA.