Int J Med Sci 2020; 17(15):2362-2372. doi:10.7150/ijms.47356

Research Paper

Potential mechanism of RRM2 for promoting Cervical Cancer based on weighted gene co-expression network analysis

Jingtao Wang, Yuexiong Yi, Yurou Chen, Yao Xiong, Wei Zhang

Department of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China.

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Wang J, Yi Y, Chen Y, Xiong Y, Zhang W. Potential mechanism of RRM2 for promoting Cervical Cancer based on weighted gene co-expression network analysis. Int J Med Sci 2020; 17(15):2362-2372. doi:10.7150/ijms.47356. Available from

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Cervical cancer is the most common gynecologic malignant tumor, with a high incidence in 50-55-year-olds. This study aims to investigate the potential molecular mechanism of RRM2 for promoting the development of cervical cancer based on The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). RRM2 was found to be significant upregulated in cervical tissue (P<0.05) by extracting the expression of RRM2 from TCGA, GSE63514, GSE7410, GSE7803 and GSE9750. Survival analysis indicated that the overall survival was significantly worse in the patients with high-expression of RRM2 (P<0.05). The top 1000 positively/negatively correlated genes with RRM2 by Pearson Correlation test were extracted. The gene co-expression network by Weighted Gene Co-Expression Network Analysis (WGCNA) with these genes and the clinical characteristics (lymphocyte infiltration, monocyte infiltration, necrosis, neutrophil infiltration, the number of normal/stromal/tumor cells and the number of tumor nuclei) was constructed. By screening the hub nodes from the co-expression network, results suggested that RRM2 may co-express with relevant genes to regulate the number of stromal/tumor cells and the process of lymphocyte infiltration to promote the progression of cervical cancer. RRM2 is likely to become a novel potential diagnostic and prognostic biomarker of cervical cancer and provide evidence to support the study of mechanisms for cervical cancer.

Keywords: Bioinformatics, Cervical cancer, Ribonucleotide reductase M2, Stromal cells, Tumor cells, Lymphocyte infiltration