Pan-Cancer Analysis Reveals CENPI as a Potential Biomarker and Therapeutic Target in Adrenocortical Carcinoma

Abstract

Background: Centromere protein I (CENPI) has been shown to affect the tumorigenesis of breast and colorectal cancers. However, its biological role and prognostic value in other kinds of cancer, especially adrenocortical carcinoma (ACC), remained to be further investigated.

Methods: Various bioinformatics tools were adopted for exploring the significance of differential expression of CENPI in several malignant tumors from databases such as Depmap portal, GTEx, and TCGA. ACC was selected for further analyzed, and information such as clinicopathological features, the prognostic outcome of diverse subgroups, differentially expressed genes (DEGs), co-expression genes, as well as levels of tumor-infiltrating immune cells (TIIC), was extracted from multiple databases. To verify the possibility of CENPI as a therapeutic target in ACC, drug sensitivity assay and si-RNA mediate knockdown of CENPI were carried out.

Results: The pan-cancer analyses showed that the CENPI mRNA expression levels differed significantly among most cancer types. Additionally, a high precision in cancer prediction and close relation with cancer survival indicated that CENPI could be a potential candidate biomarker to diagnose and predict cancer prognosis. In ACC, CENPI was closely related to multiple clinical characteristics, such as pathological stage and primary therapy outcome. High CENPI levels predicted poor overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS) of ACC patients, particularly for different clinical subgroups. Moreover, the expression of CENPI showed positive relationship to Th2 cells but negatively related to most of the TIICs. Furthermore, drug sensitivity assay showed that vorinostat inhibit CENPI expression and ACC cell growth. Additionally, si-RNA mediated knockdown of CENPI inhibited ACC cell growth and invasion and showed synergistic anti-proliferation effect with AURKB inhibitor barasertib.

Conclusion: Pan-cancer analysis demonstrated that CENPI is a potential diagnostic and prognostic biomarker in various cancers as well as an anti-ACC therapeutic target.

Keywords: CENPI; adrenocortical carcinoma; diagnosis; pan-cancer analysis; prognostic biomarker.

Figure 1

Gene expression level of CENPI in tumors and normal tissues. (A) CENPI expression in normal tissues; (B) CENPI expression in tumor cell lines; (C) CENPI expression in TCGA tumors and normal tissues. (ns, p≥0.05, *p<0.05, ***p<0.001).

Figure 2

Protein–protein interaction network, GO analysis, and KEGG analysis of top 50 target interacting proteins of CENPI. (A) Protein–protein interaction network; (B) Correlation between CENPI and its top 5 predicted interacting protein across TCGA tumors; (C) Visual network of GO and KEGG analyses; (D) GO analysis; (E) KEGG analysis.

Figure 3

Receiver operating characteristic (ROC) curve of CENPI expression in pan-cancer. (A) ACC; (B) BRCA; (C) COAD; (D) HNSC; (E) KIRP; (F) LAML; (G) LGG; (H) LIHC; (I) LUAD; (J) LUSC; (K) OV; (L) PAAD; (M) SKCM; (N) STAD; (O) UCEC; (P) UCS.

Figure 4

Correlation between CENPI expression and the prognosis outcomes (OS, DSS, and PFI) of different cancers. (A–C) ACC; (D–F) MESO; (G–I) PAAD; (J–L) SARC; (M–O) UCEC.

Figure 5

Correlation between CENPI expression and different clinical characteristics of ACC. (A) Pathologic stage; (B) Primary therapy outcome; (C) N stage; (D) M stage; (E) Residual tumor; (F) New event; (G) Weiss-Atypical mitotic figures; (H) Weiss-Necrosis; (I) Weiss-Invasion of tumor capsule. Data were shown as mean ±SD. (ns, p≥0.05, *p < 0.05, **p < 0.01, ***p < 0.001).

Figure 6

Association between CENPI expression and OS, DSS, and PFI in different clinical subgroups of ACC. (A–C) M stage (M0); (D–F) N stage (N0); (G–I) Mitotane therapy (Yes).

Figure 7

Association between CENPI expression and OS, DSS, and PFI in different clinical subgroups of ACC. (A–C) Residual tumor (R0); (D–F) Tumor status: with tumor; (G–I) New event (Yes).

Figure 8

Top 50 genes positively correlated with CENPI expression in ACC. (A) Gene co-expression heatmap of top 50 genes positively correlated with CENPI in ACC: (B–K) Heatmap showing correlation analysis of top 10 genes and CENPI. (***p < 0.001).

Figure 9

Top 50 genes negatively correlated with CENPI expression in ACC. (A) Gene co-expression heatmap of top 50 genes negatively correlated with CENPI in ACC. (B–K) Heatmap showing correlation analysis of top 10 genes and CENPI. (*p < 0.05,**p < 0.01, ***p < 0.001).

Figure 10

Protein–protein interaction (PPI) network building and GO and KEGG analyses of DEGs between CENPI high expression and low expression groups in ACC. (A) Volcano map of DEGs (red: upregulation; blue: downregulation); (B and C) GO and KEGG analyses of DEGs; (D–F) Hub genes of PPI network and MCODE2 components identified in the gene lists.

Figure 11

Association between CENPI expression and the immune cell infiltration in ACC. (A) Spearman correlation analysis of the CENPI expression and 24 tumor infiltration immune cells. Correlation analysis between CENPI expression and (B) Th2 cells, (C) cytotoxic cells, (D) mast cells, (E) CD8 T cells, (F) B cells, (G) plasmacytoid dendritic cells, (H) T cells, (I) macrophages, (J) Th17 cells, (K) Th1 cells, (L) and TFH cells.

Figure 12

Vorinostat inhibits CENPI expression and cell growth of ACC cell lines. (A–F) Correlation between CENPI expression and FDA-approved drugs in various cancer cell lines; (G) Molecular docking analysis of CENPI and vorinostat; (H) Vorinostat inhibits CENPI expression of ACC cell lines; (I and J) Vorinostat inhibits cell growth of ACC cell lines. Data were shown as mean ±SD. (***p<0.001).

Figure 13

Knockdown of CENPI inhibited the proliferation and migration of ACC cells. (A) SW-13 and NCI-H295R cells were transfected with si-CENPI, and the level of CENPI was evaluated by qRT-PCR. (B and C) The proliferation of ACC cells was examined by (B) CCK-8 assay and (C) colony-formation assay. (D) The migration of ACC cells was examined by Transwell assay. (E and F) Cell viability in SW-13 and NCI-H295R cells treated with siRNA and/or barasertib at indicated concentrations. (G and H) The Chou-Talalay plot showing the combination effect of indicated treatments in SW-13 and NCI-H295R cells. CI values <1, =1, >1 indicate synergistic, additive, or antagonistic effects, respectively. Data were shown as mean ±SD. Images in D were taken at 10x objective, scale bar represent 50μm. (***p < 0.001).