Abstract: Objective To analyze the differentially expressed genes (DEGs) and miRNAs of cervical cancer based on bioinformatics, and further verify the differentially expressed genes and proteins, in order to find potential biomarkers and therapeutic targets. Methods Cervical cancer related data were obtained from TCGA database, and DEGs and differential miRNAs were screened by edgeR algorithm. The mRNA-miRNA co-expression network was constructed using Cytoscape3. 8. 2 software. GO enrichment analysis and KEGG enrichment analysis were performed for DEGs and target genes of differential miRNA predicted by miRWalk website using DAVID software. DEGs was further verified by qPCR and Western blotting. Results A total of 149 up-regulated and 171 down-regulated DEGs, 46 up-regulated differential miRNAs and 64 down-regulated differential miRNAs were screened out. The enrichments of DEGs and miRNA target genes were consistent in cell composition, and they were all enriched in cytoplasm, nucleus and cytoplasm. However, co-expression network found no significant regulatory relationship between DEGs and differential miRNAs. Therefore, we subsequently focused on the verification of DEGs, and verified TCEAL6, CLEC3B, LMOD1 and CNN1 with relatively significant differential expression. QPCR showed that the expression levels of CNN1 in cervical cancer were significantly reduced, which was in line with expectations. Western blotting analysis of CNN1 also showed that it was lowly expressed in cervical cancer. Conclusion In this study, DEGs and differentially expressed miRNAs of cervical cancer were screened and analyzed based on the TCGA database, and TCEAL6, CLEC3B, LMOD1 and CNN1were further verified. The results showed that they were significantly under-expressed in cervical cancer, which is expected to become biomarkers of cervical cancer

Key words: cervical cancer, DEGs, differentially expressed miRNAs, TCEAL6, CLEC3B; LMOD1, CNN1