Cyclin genes as potential novel prognostic biomarkers and therapeutic targets in breast cancer

Cell cycle progression and cell proliferation are tightly controlled processes physiologically; however, in cancerous cells, uncontrolled cell proliferation may be attributed to abnormal expression of the cyclin genes. Therefore, analysis of the expression of the cyclin genes may result in the discovery of biomarkers that can be used to predict a prognosis and help to evaluate the therapeutic efficacy more accurately in several types of cancer, including breast cancer. In this study, 15 subtypes of the cyclin genes in breast cancer from public databases were selected using bioinformatics analysis, the correlation between their transcriptional expression levels and survival rates were analyzed, and the results were further confirmed using reverse transcription-quantitative PCR in vitro in various breast cancer cell lines. The expression of the majority of the cyclin genes in SK-BR-3, a HER2 overexpressing breast cancer cell line, was lower than that in MCF-10A cells. CCNC mRNA expression was higher and CCNH mRNA expression was lower in tumor and tumor-adjacent tissues compared with that in normal tissues; however, CCNC expression was lower and CCNH expression was higher in breast cancer cell lines compared with that in MCF-10A cells. The expression of the 13 other cyclin genes in breast cancer cell lines was generally consistent with the data from the bioinformatics analyses of breast cancer tissue samples, tumor-adjacent tissues, and normal tissues. Low expression of CCNA2, CCNB1/2, CCNC, CCND1, CCNE1/2 and CCNF, and high expression of CCNA1, CCNB3, CCND2/3, CCNG1/2 and CCNH genes was correlated with a higher survival rate for breast cancer patients (P<0.05). In conclusion, CCNA2, CCNB1/2, CCND1/2 and CCNE1/2 may serve as relatively mature and accurate biomarkers, and CCNG1/2 may be used to evaluate the prognosis and therapeutic efficacy of hormone receptor-positive breast cancer. Furthermore, CCNA1, CCNB3, CCNC, CCND3, CCNF and CCNH may serve as promising targets for the management of breast cancer.