Int J Med Sci 2019; 16(6):800-812. doi:10.7150/ijms.34172 This issue

Research Paper

Identification of Key Genes and Pathways in Cervical Cancer by Bioinformatics Analysis

Xuan Wu1,2, Li Peng3, Yaqin Zhang1,2, Shilian Chen1,2, Qian Lei1,2, Guancheng Li1,2✉, Chaoyang Zhang1,4✉

1. Key Laboratory of Carcinogenesis of the Chinese Ministry of Health and the Key Laboratory of Carcinogenesis and Cancer Invasion of Chinese Ministry of Education, Xiangya Hospital, Central South University, Changsha 410078, P.R. China;
2. Cancer Research Institute, Central South University, Changsha, P.R. China;
3. Guangdong Province Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Research Center of Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China;
4. Division of Functional Genome Analysis, German Cancer Research Centre (DKFZ), Heidelberg, Germany.

This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license ( See for full terms and conditions.
Wu X, Peng L, Zhang Y, Chen S, Lei Q, Li G, Zhang C. Identification of Key Genes and Pathways in Cervical Cancer by Bioinformatics Analysis. Int J Med Sci 2019; 16(6):800-812. doi:10.7150/ijms.34172. Available from

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Cervical cancer is a common malignant tumour of the female reproductive system that seriously threatens the health of women. The aims of this study were to identify key genes and pathways and to illuminate new molecular mechanisms underlying cervical cancer. Altogether, 1829 DEGs were identified, including 794 significantly down-regulated DEGs and 1035 significantly up-regulated DEGs. GO analysis suggested that the up-regulated DEGs were mainly enriched in mitotic cell cycle processes, including DNA replication, organelle fission, chromosome segregation and cell cycle phase transition, and that the down-regulated DEGs were primarily enriched in development and differentiation processes, such as tissue development, epidermis development, skin development, keratinocyte differentiation, epidermal cell differentiation and epithelial cell differentiation. KEGG pathway analysis showed that the DEGs were significantly enriched in cell cycle, DNA replication, the p53 signalling pathway, pathways in cancer and oocyte meiosis. The top 9 hub genes with a high degree of connectivity (over 72 in the PPI network) were down-regulated TSPO, CCND1, and FOS and up-regulated CDK1, TOP2A, CCNB1, PCNA, BIRC5 and MAD2L1. Module analysis indicated that the top 3 modules were significantly enriched in mitotic cell cycle, DNA replication and regulation of cell cycle (P < 0.01). The heat map based on TCGA database preliminarily demonstrated the expression change of the key genes in cervical cancer. GSEA results were basically coincident with the front enrichment analysis results. By comprehensive analysis, we confirmed that cell cycle was a key biological process and a critical driver in cervical cancer. In conclusion, this study identified DEGs and screened the key genes and pathways closely related to cervical cancer by bioinformatics analysis, simultaneously deepening our understanding of the molecular mechanisms underlying the occurrence and progression of cervical cancer. These results might hold promise for finding potential therapeutic targets of cervical cancer.

Keywords: Cervical cancer, Microarray, Bioinformatics analysis, Differentially expressed gene