Cell cycle progression is regulated by the interaction of cyclin, cyclin dependent kinases . Therefore, the detection of their expression are important in progression and control of the cell cycle in many tumours . Several studies demonstrated high cyclin B1 expression in different carcinomas, which was associated with aggressiveness of tumour, and might serve as a prognostic marker . It can be present in the cytoplasm and in the nucleus, the latter associated with poorer prognosis (as demonstrated in breast and oesophageal carcinomas) [16, 17]. Furthermore, the cyclin A2 (CCNA2)-CDK2 complex is essential for the progression of G2 phase into mitosis . CCNA2 is localised in the nucleus during S phase, controlling DNA synthesis .
In this study, we sought to determine the role of CCNA2 expression in CCA progression, especially as a prognostic factor for CCA. In addition, we also tried to screen signaling pathways related to CCNA2 in CCA to understand the underlying mechanism involved in the regulation of CCA development by CCNA2. First, we analyzed the data in the GEO database and compared the differentially expressed genes in CCA and adjacent noncancerous tissues. Then, the PPI network analysis was used to further screen real hub genes with a significant p value. It's worth noting that CCNA2 were especially outstanding. It was not only highly correlated with CCA grade, but also may be potential biomarkers for prognosis. It is noteworthy that we established Kaplan–Meier risk estimates to predict survival of CCA patients based on tumor-infiltrating immune cells, the survival rate of patients in the low-CCNA2 expression group was higher than that of patients in the high-CCNA2 expression group.
The tumor microenvironment often affects the invasive processes. The extracellular matrix molecules and secreted growth factors are involved in the transition of tumor cells into an invasive phenotype. The invasion and metastasis of tumor cells may have nothing to do with the proliferation of tumor cells but have occurred already at the early developmental stage of the tumor . Previous studies about tumors and immune infiltration mostly focused on immune cell types. For example, Li B et al. infers the abundance of the six immune cell types (B cells, CD4 T cells, CD8 T cells, neutrophil, macrophage, and dendritic cells) using approach of constrained least squares fitting and found many significant associations between immune cell abundance and outcome of 23 cancer types patients . For instance, except for association with prolonged survival of patients, CD8 T cells may also play an important role in preventing tumor recurrence (in melanoma and colorectal cancer and cervical cancer. Notably, the focus of our research is to estimate the degree of 6 immune cells infiltration, and finally determined their most promising co-expression patterns associated with CCNA2.These differences may illustrate that CCNA2 may affect the immune microenvironment of CCA to a certain extent.
Based on that, in this study, GSEA was implemented to calculate the immune cell infiltration levels for each sample. Since previous studies had shown immune-infiltration to have better prognosis in different carcinomas, we analyzed the CCNA2 expression in differential groups. CCA-related tumor samples from various databases and literatures were collected. Functional analysis showed these samples to be closely associated with the expression of CCNA2, such as via cytokine-cytokine receptor interaction,natural killer cell mediated cytotoxicity, cell cycle༌and calcium signaling pathway.
Our research also has some limitations. First, the clinical information is not perfect, and some important information, such as tumor size, was not provided. Second, there is a lack of specific details, such as surgical treatment and surgical details, which are crucial to the prognosis of patients. Finally, it is impossible to evaluate the protein level and direct mechanism of CCNA2 in CCA from GEO and TCGA database.
In conclusion, our study first analyzed the GEO and TCGA database and found that the expression of CCNA2 in CCA tissues is higher than that in adjacent noncancerous tissues. The upregulation of CCNA2 is closely correlated with some clinicopathological features of CCA, which are related to the occurrence and the development of CCA. Importantly, the fraction of 6 immune-related cells is significantly correlated with the expression of CCNA2, which highlighted the immunotherapy might actually change the therapeutic landscape of CCA. In summary, we found that the expression level of CCNA2 may be a marker for the diagnosis and the prognosis of CCA. In future analyses, other clinical trials will be needed to verify the corresponding results to reveal the prognostic value of CCNA2 in CCA