Cell division cycle associated 8: A novel diagnostic and prognostic biomarker for hepatocellular carcinoma

Abstract The cell division cycle associated 8 (CDCA8) is a crucial component of the chromosome passenger complex (CPC). It has been implicated in the regulation of cell dynamic localization during mitosis. However, its role in hepatocellular carcinoma (HCC) is not clearly known. In this study, data of 374 patients with HCC were retrieved from the Cancer Genome Atlas (TCGA) database. Pan analysis of Gene Expression Profiling Interactive Analysis (GEPIA) database was performed to profile the mRNA expression of CDCA8 in HCC. Then, the Kaplan‐Meier plotter database was analysed to determine the prognostic value of CDCA8 in HCC. In addition, samples of tumour and adjacent normal tissues were collected from 88 HCC patients to perform immunohistochemistry (IHC), reverse transcription‐quantitative polymerase chain reaction (qRT‐PCR) and Western blotting. The results obtained from bioinformatic analyses were validated through CCK‐8 assay, EdU assay, colony formation assay, cell cycle assays and Western blotting experiments. Analysis of the Kaplan‐Meier plotter database showed that high expression of CDCA8 may lead to poor overall survival (OS, p = 4.06e‐05) in patients with HCC. For the 88 patients with HCC, we found that stages and grades appeared to be strongly linked with CDCA8 expression. Furthermore, the high expression of CDCA8 was found to be correlated with poor OS (p = 0.0054) and progression‐free survival (PFS, p = 0.0009). In vitro experiments revealed that inhibition of CDCA8 slowed cell proliferation and blocked the cell cycle at the G0/G1 phase. In vivo experiments demonstrated that inhibition of CDCA8 inhibited tumour growth. Finally, blockade of CDCA8 reduced the expression levels of cyclin A2, cyclin D1, CDK4, CDK6, Ki67 and PCNA. And, there is an interaction between CDCA8 and E2F1. In conclusion, this research demonstrates that CDCA8 may serve as a biomarker for early diagnosis and prognosis prediction of HCC patients. In addition, CDCA8 could be an effective therapeutic target in HCC.


| INTRODUC TI ON
With a rapidly increasing global incidence and postoperative recurrence rate, liver cancer is the fifth most common type of cancer, accounting for the second-highest number of cancer-related deaths. 1,2 Hepatocellular carcinoma (HCC) is the most predominant histological type of liver cancer, accounting for about 80% of all liver cancers. 1 In 2021, HCC-associated morbidities and mortalities were 42230 and 30230, respectively, in the United States. 3 However, only 30% of patients were diagnosed at an early stage and received appropriate treatments, including resection, chemotherapy or liver transplantation. 3 However, clinical diagnosis is often delayed, with advanced HCC accounting for most of the diagnosed cases. 4 Advances in HCC prevention and treatment have not improved the clinical outcomes for HCC, with a 5-year overall survival rate of only 15%. 5 Therefore, there is a need to identify sensitive biomarkers to inform the development of novel therapeutic strategies.
The occurrence and progression of HCC are associated with various factors, especially the accumulation of genetic variations.
The cell division cycle-related protein family, including cell division cycle associated [1][2][3][4][5][6][7][8], is an essential regulator of cell proliferation. 6 During the cell cycle, chromosomal passenger complex (CPC) plays important roles in right chromosome segregation and cytokinesis. The CPC is made up of enzymatic core Aurora-B kinase, scaffold protein inner centromere protein, CDCA8 and two other non-enzymatic surviving subunits. 7 Therefore, CDCA8 may be an important component in mitosis regulation. 8,9 Elevated CDCA8 levels are associated with poor prognostic outcomes for breast, gastric, kidney and bladder cancers. [10][11][12] Moreover, overexpressed CDCA8 is critical for the growth of embryonic stem cells and breast cancer. 13 CDCA8 induces tamoxifen resistance in breast cancer cells and promotes their proliferation. 14 Moreover, CDCA8 affects the proliferation of breast cancer cell lines by directly mediating E2. 14 Currently, the role of CDCA8 in HCC has not been elucidated. We aimed at determining the significance of CDCA8 as a prognostic and therapeutic target for HCC.
The Cancer Genome Atlas (TCGA) is the largest cancer database, with more than 20,000 primary cancer samples and paired paracancer samples for 32 cancer types. Therefore, the genetic data for HCC can be obtained from this database and evaluated through bioinformatics methods. To assess the relationship between CDCA8 and HCC progression, raw data were processed by multi-dimensional analysis using the R software. Finally, findings from bioinformatics analyses were validated by in vivo and in vitro experiments.

| Data acquisition and identification of differentially expression mRNAs
Transcriptome data for HCC, including 50 normal tissues and 374 HCC tissues, were downloaded from the TCGA database. Clinical information, including age, gender, stage, pathological information and OS, was obtained from TCGA-LIHC. Transcriptome data were subjected to differential analysis using the edgeR package. Significant criteria were |log 2 (fold change [FC])| > 1 and p < 0.05.

| Screening for independent prognostic genes and core node
Protein-protein interaction (PPI) network analysis is essential for identification of molecules that mediate vital cellular processes in HCC progression. We established the PPI networks of the top 9 pivotal genes with high connectivities. The PPI data were obtained by querying independent prognostic gene queries from public databases. The Cytoscape plugin was used for network visualization, analysis and publication.

| GEPIA Database Analysis
Transcriptional profiles of CDCA8 in multiple cancers were obtained from the GEPIA database (http://gepia.cance r-pku.cn/index. html). TCGA tumour versus TCGA normal +The Genotype-Tissue Expression (GTEx) normal data set was used to establish the expression box plots. The log2FC cut-off was set to 1, while the p-value cut-off was set to 0.01. Genes with higher |log2FC| values and pvalues below a preset threshold were considered to be differentially expressed genes (DEGs).

| The Human Protein Atlas (HPA)
The HPA provides information on tissue and cellular distributions of 26,000 human proteins. Using this database, expression levels of each protein in 64 cell lines, 48 normal human tissues and 20 tumour tissues were evaluated using immunoassay techniques. To establish the expression and location of CDCA8 in normal liver and HCC tissues, CDCA8-related information was searched in HPA.
F I G U R E 1 Screening results for differentially expressed genes. (A) Volcano maps of gene expression in HCC and normal tissues. Data points in red and green represent upregulated and downregulated genes, respectively. (B) Screening for independent prognostic genes using multifactorial cox analysis. (C) In HCC, seven upregulated proteins were associated with risk factor. (D) CDCA8 was the core gene in the PPI network

| Western Blotting
The RIPA lysis buffer (Beyotime Biotechnology, Shanghai, China) was used to lyse the HCC cell lines and liver tissues. Then, proteins were collected and quantified using the bicinchoninic acid (BCA) kit

| Colony formation assay
Huh7 and Hep-3B cells were seeded in 6-well plates (1 × 10 3 cells/ well) and incubated for 14 days. Cells were fixed for 15 min in 4% paraformaldehyde and stained with 1% crystal violet for 1 min after which colonies were counted.

| Statistical analysis
Data analysis was performed using the SPSS 25.0 software and GraphPad Prism 5.0. Chi-square or Fisher's exact tests were used to assess the relationships between protein expression levels and clinic-pathological information. Kaplan-Meier curves and log-rank tests were used to assess progression-free survival (PFS) and overall survival (OS) outcomes. Student's t tests were used to establish differences between the two groups, and p < 0.05 was the threshold for statistical significance.

| Screening for DEGs and selection of core genes
To screen for DEGs, TCGA-LIHC transcriptome data for 50 cases of normal tissue and 374 cases of HCC tissues were downloaded.
DEGs, including upregulated (red) and downregulated (green) genes are shown by volcano plots ( Figure 1A). Multivariate Cox analysis was used to screen independent prognostic genes ( Figure 1B). The upregulated DEGs and risk factor-related genes were overlapped after which LPCAT1, HMMR, EZH2, CDCA8, KPNA2, PIGU and MAFG were screened ( Figure 1C). Finally, protein interaction (PPI) network analysis of independent prognostic genes revealed that CDCA8 was the most significant core gene in the PPI network ( Figure 1D). Therefore, we performed comprehensive bioinformatic analyses and experimental validation for CDCA8.

| CDCA8 is Upregulated in HCC and Correlates with HCC Prognosis
Using the GEPIA database, we established that CDCA8 was upregulated in various malignancies, especially HCC (Figure 2A). Based on TCGA and GTEx databases, CDCA8 was found to be significantly upregulated in HCC tissues ( Figure 2B). To visualize the expression levels of CDCA8 in normal liver tissues and HCC, we downloaded three typical IHC samples of CDCA8 from normal liver tissues and liver cancer tissues in HPA (Supplement Material Figure S1).
In the TCGA database, expression levels of CDCA8 in patients were allocated into high-and low expression groups according to the median value of CDCA8 expression levels in each HCC patient ( Figure 2C). Then, we plotted the Kaplan-Meier curves using the TCGA data and found that elevated CDCA8 levels were associated with poor OS outcomes ( Figure 2D). Finally, ROC curves were

| Validation of the Association between Aberrantly Expressed CDCA8 and Prognosis of Clinical HCC Cohorts
To validate the results of Kaplan-Meier curves that had been plotted using the TCGA database, 88 HCC samples were subjected to tumour size (p = 0.005) ( Table 1). Therefore, we postulated that CDCA8 is likely to function as an oncogene in HCC progression.

| Underlying Biological Pathways in which CDCA8 is enriched
The CDCA family is involved in cell cycle progression and cell pro- Data are presented as the mean ± SD of at least three independent experiments. * p < 0.05, ** p < 0.01 and *** p < 0.001. p < 0.05 was considered statistically significant activated by CDCA8 upregulation might be involved in its effects on HCC progression. Figure 5 shows that CDCA8 is associated with E2F targets and IL2 STAT5 signalling. Therefore, CDCA8 may be involved in immunerelated processes in HCC. Correlation analyses of CDCA8 levels and infiltrating immune cells were performed to investigate the significance of CDCA8 in immunity. Differential expressions of CDCA8

| Correlation between CDCA8 and immune infiltrating cells
were correlated with naive B cell, plasma B cell, resting memory T cell CD4+, activated memory T cell CD4+, helper T cell follicular, regulatory T cell (Tregs), resting NK cell, Monocyte, Macrophage M0, activated mast cell and neutrophil levels ( Figure 6A, B).

| Suppressed CDCA8 affected HCC cell proliferation and cell cycle progression
In 20 pairs of HCC tissues, CDCA8 mRNA expression levels were found to be upregulated ( Figure 7A). Moreover, protein levels of CDCA8 were upregulated in 6 HCC pairs ( Figure 7B). To verify the significance of CDCA8 in HCC cell proliferation and cell cycle progression, CDCA8 levels in HCC cell lines were evaluated ( Figure 7C). First, Huh7 and Hep-3B cell lines were infected with shCDCA8 and shNT lentivirus ( Figure 7D). Through CCK-8 and colony formation assays, growth and proliferation rates of the shCDCA8 group were significantly lower than those of the shNT group ( Figure 7E, F). The apoptosis assays confirmed that there were no differences in apoptotic levels between the shCDCA8 and shNT groups (Supplement Material Figure 2). Then, MHCC-LM3 wells were infected with CDCA8 and NC lentivirus ( Figure 7G).
Through the CCK-8 and colony formation assays, growth and proliferation rates of the CDCA8 group were significantly improved, relative to the NC group ( Figure 7H, I). EDU assays were performed to evaluate the effects of CDCA8 knockdown and overexpression on the proliferative capacity of cells ( Figure 7J). Moreover, flow cytometry was used to determine whether cell proliferation was influenced by cell cycle distribution. Cells in the shCDCA8 group were arrested at the G0/G1 phase ( Figure 7K). Interestingly, the arrest in the G0/G1 phase is P53-dependent (Supplement Material Figure S3). To confirm the effects of CDCA8 in HCC in vivo, a xenograft model was established using shCDCA8 and shNT stable strains constructed from the Huh7 cell line, respectively ( Figure 7L). After 36 days, the nude mice were sacrificed, xenograft tumours were excised and analysed. Tumours from the shCDCA8 group exhibited a significant decrease in weight and volume relative to the shNT group ( Figure 7N). Moreover, xenograft models were established using CDCA8 and NC stable strains constructed from the MHCC-LM3 cell line ( Figure 7M) and tumours from the CDCA8 group showed a significant increase in weight and volume relative to the NC group ( Figure 7O). Finally, expression levels of cell cycle-related markers of shCDCA8 and shNT were investigated ( Figure 7P). Compared to the shNT group, expression levels of Cyclin A2, Cyclin D1, CDK4, CDK6, Ki67 and PCNA were down-regulated in the shCDCA8 group ( Figure 7P). We found that CDCA8 levels had an effect on E2F1 levels ( Figure 8A, B). In the Huh7 cell line, CDCA8 interacted with E2F1 ( Figure 8C). We overexpressed E2F1 in the shCDCA8#2 and shNT cell groups, respectively ( Figure 8D). Then, we evaluated whether overexpressed E2F1 in shCDCA8#2 and shNT groups affected cell proliferation rates. Overexpressed E2F1 rescued the proliferative ability of shCDCA8#2 group cells ( Figure 8E, F). In vivo recovery of E2F1 expression levels also rescued the tumour proliferation inhibition caused by CDCA8 knockdown (Figure 8G, H).

| DISCUSS ION
Clinically, in advanced stages, HCC is associated with a rapid proliferation rate and multiple metastatic patterns. Delayed diagnoses lead to poor prognostic outcomes. 15 Early HCC diagnosis is essential for clinical management of HCC. The current screening methods for HCC, including ultrasonography and AFP, are not sensitive and specific enough to detect early lesions. 16 Therefore, identification of biomarkers for early-stage HCC will significantly improve its diagnosis.
In this study, CDCA8 levels were found to be upregulated in  (n = 5) * p < 0.05, ** p < 0.01 and *** p < 0.001. p < 0.05 were considered statistically significant E2F2 and E2F3a) and transcriptional repressors (E2F3b, E2F4, E2F5, E2F6, E2F7 and E2F8). 21 Upregulated CDCA8 promotes HCC cell proliferation. Therefore, we evaluated the roles of E2F1, E2F2 and E2F3a in HCC. E2F1 regulated the G1/S phase of the cell cycle by mediating chromosomal DNA replication and gene promoters. 22 E2F1 is involved in regulation of the proliferation of retinoblastoma in a cell cycle-dependent manner. In p53-deficient colon cancer cell lines, Mdm2 inhibition activated E2F1 and enhanced p73-mediated expressions of Siva-1 and PUMA to trigger apoptosis. 23 Previously, E2F1 was found to be significantly upregulated in colon cancer, 24 however, its levels were not correlated with colon cancer stage and OS, implying that E2F1 may be an important factor in tumorigenesis induction. E2F2 plays a dual role in tumour progression. It can maintain cells in a quiescent state by inhibiting cell cycle regulators and downregulating myc, thereby suppressing tumorigenesis and proliferation. 25 E2F2 can also act as an 'activator' to increase the expression of its target genes. 26 MiR-490-5P prevents HCC metastasis by mediating the downregulation of E2F2 and ECT2, 27 while LBX2-AS1 has been shown to enhance E2F2 gene expression to promote ovarian cancer progression. 28 E2F3 is critical in regulating the transcriptional activation of various oncogenes, which control the rate of tumour and progenitor cell proliferation. 29 Circ_PGPEP1 promotes gastric cancer proliferation, invasion and migration by regulating E2F3 levels. 30 MiR-145-5P inhibits osteosarcoma cell proliferation by targeting inhibit of E2F3b, which affected Cyclin D1, CDK2, CDK4 and CDK6 expression. 31 Our results were consistent with those of previous studies.
Under various conditions, the tumour immune microenvironment (TIME) regulates cancer progression. As an inflammation-associated tumour, the immune-suppressive microenvironment of HCC contributes to immune tolerance and avoidance. 32,33 The cell cycle is associated with increased anti-tumour immunity in multiple cancers. [34][35][36][37][38] Specifically, CDK4/6 inhibition can induce a diminished tumour immunity in various cancers. 37 Interestingly, there is a correlation between the E2F protein family and tumour immunity. For example, E2F1 upregulates the expression of Treg cell surface receptors, CD39 and CD73, and further promotes Treg infiltrations. 39 E2F2-deficient T lymphocytes exhibit elevated T cell receptor-induced proliferation, which may contribute to autoimmunity in E2F2-deficient mice. 40 In osteoarthritis, E2F3 is positively correlated with multiple immune cells, including resting mast cells, T regulatory cells, CD4 resting memory T cells and activated NK cells. 41 Therefore, we postulate that CDCA8 mediates cell cycle regulation by affecting E2F functions and HCC immunity.
Due to its significant association with the E2F and CDK pathways, it should be determined whether CDCA8 is a potential immune checkpoint. Although the role of CDCA8 involvement in HCC has previously been reported, our results confirm the conclusion of Shuai et al. 42

| CON CLUS IONS
Compared to adjacent normal tissues, expression levels of CDCA8 were elevated in HCC tissues. Elevated CDCA8 levels were associated with poor OS, PFS and clinical features, including TNM stages, grades and tumour size. Therefore, we postulate that CDCA8 promotes tumour growth through the cell cycle.
Besides, CDCA8 has a significant role in HCC-related immunity.
Consequently, CDCA8 may be a potential biomarker for early HCC diagnosis and prognostic prediction.

ACK N OWLED G EM ENT
None.

D I SCLOS U R E
The authors declare that they have no competing interests.

E TH I C A L A PPROVA L
This study was approved by the Research Ethics Committee of the Second People's Hospital of Changzhou, China. All participants provided written informed consents.

DATA AV I L A B I L I T Y S TAT E M E N T
All relevant data from this research are available from the corresponding author upon a reasonable request.