Objective This study is to investigate the expression profile of related genes and its correlation with the prognosis of cervical cancer cells by using weighted gene co-expression network analysis. Methods The expression data of cervical cancer (CC) with accession number GSE63514 were obtained from gene expression omnibus database of National Center for Biotechnology Information (NCBI). The gene expression data of cervical squamous cell carcinoma and adenocarcinoma (Cesc) were downloaded from the Cancer Genome Atlas (TCGA) database for verification. A total of 104 tumor samples and 24 normal samples were screened from GSE63514 dataset. Co-expression network of the differentially expressed mRNA was constructed by weighted gene co expression network analysis (WGCNA) using these 128 samples. Genes with similar expression patterns were aggregated into the same module and the most relevant module was selected. Then, genes with significant expression differences in tumor tissues were identified and Go enrichment analysis and KEGG enrichment analysis were performed with genes that were obtained. Additionally, protein-protein interaction (PPI) network of these differentially expressed genes was constructed and 10 hub genes were screened out. Survival analysis was carried out to identify genes that are significantly related to the prognosis and grading of cervical cancer. Finally, the online database of Oncomine is used to verify the results. Results MEblack module had the most significant correlation with tissue carcinogenesis. Then 10 core genes, namely CDC45, MCM2, CDC6, CHEK1, CDT1, CDC7, MCM10, GMNN, BUB1B and MAD2L1 were screened out. Survival analysis of these 10 core genes by gepia2 showed that CDC4 and MCM2 genes were significantly associated with survival, which was validated by Oncomine database. Conclusion The expression of CDC45 and MCM2 has certain reference significance for judging the disease development and predicting the prognosis of cervical cancer.