The expression and prognostic significance of CCNB1 in colorectal cancer based on TCGA database

Abstract

Background Numerous studies have shown that cell cycle-associated protein B1 (Cyclin B1, CCNB1) is overexpressed in many cancers and is involved in cancer cell growth, differentiation, apoptosis, and metastasis. However, the biological functions and molecular mechanisms of CCNB1 in colorectal cancer (CRC) still remain unclear. Methods Herein, the HPA database and the UCSC genomic database were used to analyze the mRNA and protein expression levels of CCNB1 in different tissues of humans or vertebrates. The TIMER database was used to evaluate the expression of CCNB1 in various cancer tissue samples and adjacent normal tissue. R statistical software (version 4.2.1) was employed to analyze the relationship between CCNB1 expression and clinicopathological characteristics in the TCGA database. Kaplan-Meier survival curve and Cox regression were performed to evaluate the prognostic value. Receiver operating characteristic (ROC) curve analysis was applied to assess the diagnostic value of CCNB1. Functional enrichment analysis of CCNB1 and its co-expressed genes was performed to explore the potential molecular mechanisms of CCNB1 in CRC. The correlation of critical cell-cycle regulators and the protein-protein interaction (PPI) network of CCNB1 and CRC was established through the STRING (Search Tool for the Retrieval of Interacting Genes) website and GEPIA database. Results Significant upregulation of CCNB1 was observed in a variety of tumor tissues, with limited tissue specificity and tumor specificity. TCGA database and immunohistochemistry data demonstrated that CCNB1 expression was significantly upregulated in CRC tumor tissues. In addition, CCNB1 expression was correlated with the clinical stage and TNM stage. The progression-free survival (PFS) was considerably improved in the CCNB1 high-expression group. Univariate and multifactorial Cox analysis indicated that CCNB1 could not be used as an independent prognostic factor for patients with CRC. Moreover, we found that genes such as BCAS3, ZBTB4, PTTG1, H2AZ1, LRP1B, KCNJ9, and SCARNA7 could be potential targets for regulating CCNB1. The gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analyses revealed that CCNB1 was implicated in multiple cancer-related signaling pathways and biological processes. Meanwhile, CCNB1 expression was significantly correlated with the immune infiltrating levels of diverse immune markers. CCNB1 expression was positively correlated with tumor mutation burden and negatively correlated with several immune checkpoint genes. In addition, the efficacy of chemotherapeutic medicines such as 5-Fluorouracil, bexarotene, bleomycin, camptothecin, and cisplatin significantly differed between the high and low CCNB1 expression groups. Conclusion CCNB1 could be a promising biomarker for predicting the diagnosis and prognosis of CRC patients and a potential novel molecular target for tumor immunotherapy.