Cervical cancer (CC) is the fourth commonest cancer in women worldwide. Increasing evidence proves that microRNA (miRNA)-messenger RNA (mRNA) network is involved in CC. In this study, miRNA and mRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Differently expressed miRNAs (DE-miRNAs) and mRNAs (DE-mRNAs) were obtained by "Empirical Analysis of Digital Gene Expression Data in R (EdgeR)" package. Then, functional analyses were conducted. With Cytoscape software, a protein-protein interaction (PPI) network was established to identify hub genes that were used for building an miRNA-hub gene network. Next, a prognostic signature based on hub genes was constructed by Cox regression analysis, and its prognostic value was assessed by a nomogram. Finally, the relationship between immune cell infiltration and the three genes in the prognostic model was investigated by using the CIBERSORT algorithm. We screened out 5096 DE-mRNAs and 114 DE-miRNAs between healthy cervical and CC tissues. Then, 102 target DE-mRNAs of upregulated DE-miRNAs and 150 target DE-mRNAs of downregulated DE-miRNAs were obtained. PPI network demonstrated 20 hub nodes with higher connectivity. DE-mRNAs were mostly enriched in pathways in cancer, cell cycle, and proteoglycans in cancer. The miRNA-hub gene network showed that most hub genes could be potentially modulated by miR-200c-3p, miR-23b-3p, and miR-106b-5p. Quantitative real-time PCR proved that 10 miRNAs were downregulated and 6 mRNAs were upregulated markedly in CC tissues. Furthermore, a prognostic signature was established based on enhancer of zeste homolog 2 (EZH2), Fms-related tyrosine kinase 1 (FLT1), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH). The area under the curve value of the 5-year receiver operating characteristic curve was 0.609. The three genes were also found to be related to the infiltration of six types of immune cells, including dendritic cells, macrophages M0 and M1, mast cells, and monocytes. In conclusion, the development of CC is regulated by the miRNA-mRNA network we proposed in this study.
Keywords: TCGA; bioinformatic analysis; cervical cancer; miRNAs; prognostic value.