Identification of differentially expressed genes in cervical cancer by bioinformatics analysis.

Cervical cancer is the most common gynecological malignancy. In recent years, the incidence of cervical cancer has had a younger trend. Cervical cancer morbidity and mortality rates have been significantly reduced due to recent decades of cervical cytology screening leading to the early detection and treatment of cervical cancer and precancerous lesions. There are a number of methods used to treat cervical cancer and improve the survival rate. However, the prevalence and recurrence rates of cervical cancer are increasing every year. There is an urgent requirement for a better understanding of the molecular mechanism cervical cancer development. The present study used scientific information retrieval from the Gene Expression Omnibus database to download the GSE26511 dataset, which contained 39 samples, including 19 cervical cancer lymph node-positive samples and 20 cervical cancer lymph node-negative samples. Using Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and weighted gene co-expression network analysis, 1,263 differentially expressed genes were found that affected the biological processes, including 'cell cycle process', 'signaling pathways', 'immune response', 'cell activation', 'regulation of immune system process' and 'inflammatory response'. These areas should be the focus of study for cervical cancer in the future.