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Cervical cancer is one of the most common gynecological malignancies and is related to human papillomavirus (HPV) infection, especially high-risk type HPV16 and HPV18. Aberrantly expressed genes are involved in the development of cervical cancer, which set a genetic basis for patient prognosis. In this study, we identified a set of aberrantly expressed key genes from The Cancer Genome Atlas (TCGA) database, which could be used to accurately predict the survival rate of patients with cervical squamous cell carcinoma (CESC). A total of 3,570 genes that are differentially expressed between normal and cancerous samples were analyzed by the algorithm of weighted gene co-expression network analysis (WGCNA): 1,606 differentially expressed genes (DEGs) were upregulated, while 1,964 DEGs were downregulated. Analysis of these DEGs divided them into 7 modules including 76 hub genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis revealed a significant increase of genes related to cell cycle, DNA replication, p53 signaling pathway, cGMP-PKG signaling pathway, and Fanconi anemia (FA) pathway in CESC. These biological activities are previously reported to associate with cervical cancer or/and HPV infection. Finally, we highlighted 5 key genes (EMEMP2, GIMAP4, DYNC2I2, FGF13-AS1 , and GIMAP1) as robust prognostic markers to predict patient's survival rate (p = 3.706e-05) through univariate and multivariate regression analyses. Thus, our study provides a novel option to set up several biomarkers for cervical cancer prognosis and anticancer drug targets. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the most common malignant tumors in women worldwide. Early diagnosis, treatment, and prognosis of breast cancer are global challenges. Identification of valid predictive diagnosis and prognosis biomarkers and drug targets are crucial for breast cancer prevention. This study characterizes differentially expressed genes (DEGs) based on the TCGA database by using DESeq2, edgeR, and limma. A total of 2032 DEGs, including 1026 up-regulated genes and 1006 down-regulated genes were screened. Followed with WGCNA, PPI analysis, GEPIA 2, and HPA database verification, thirteen hub genes including CDK1, BUB1, BUB1B, CDC20, CCNB2, CCNB1, KIF2C, NDC80, CDCA8, CENPF, BIRC5, AURKB, PLK1, MAD2L1, and CENPE were obtained, and they may serve as potential therapeutic targets of breast cancer. Especially, overexpression of CCNB1 and PLK1 are strongly associated with the low survival rate of breast cancer patients, demonstrating their potentiality as prognostic markers. Moreover, CCNB1 and PLK1 are highly expressed in all breast cancer stages, suggesting that they could be further studied as potential drug targets. Taken together, our study highlights CCNB1 and PLK1 as potential anti-breast cancer drug targets and prognostic markers. [ABSTRACT FROM AUTHOR]