Identification of Core Prognosis-Related Candidate Genes in Cervical Cancer via Integrated Bioinformatical Analysis.

Jianxia Wei,Yang Wang,Ying Wang,Kejian Shi

doi:10.1155/2020/8959210

Abstract

Purposes Cervical cancer (CC) is one of the highest frequently occurred malignant gynecological tumors with high rates of morbidity and mortality. Here, we aimed to identify significant genes associated with poor outcome. Materials and methods. Differentially expressed genes (DEGs) between CC tissues and normal cervical tissues were picked out by GEO2R tool and Venn diagram software. Database for Annotation, Visualization and Integrated Discovery (DAVID) was performed to analyze gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. The protein-protein interactions (PPIs) of these DEGs were visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). Afterwards, Kaplan-Meier analysis was applied to analyze the overall survival among these genes. The Gene Expression Profiling Interactive Analysis (GEPIA) was applied for further validation of the expression level of these genes. Results The mRNA expression profile datasets of GSE63514, GSE27678, and GSE6791 were downloaded from the Gene Expression Omnibus database (GEO). In total, 76 CC tissues and 35 normal tissues were collected in the three profile datasets. There were totally 73 consistently expressed genes in the three datasets, including 65 up-regulated genes and 8 down-regulated genes. Of PPI network analyzed by Molecular Complex Detection (MCODE) plug-in, all 65 up-regulated genes and 4 down-regulated genes were selected. The results of the Kaplan-Meier survival analysis showed that 3 of the 65 up-regulated genes had a significantly worse prognosis, while 3 of the 4 down-regulated genes had a significantly better outcome. For validation in GEPIA, 4 of 6 genes (PLOD2, ANLN, AURKA, and AR) were confirmed to be significantly deregulated in CC tissues compared to normal tissues. Conclusion We have identified three up-regulated (PLOD2, ANLN, and AURKA) and a down-regulated DEGs (AR) with poor prognosis in CC on the basis of integrated bioinformatical methods, which could be regarded as potential therapeutic targets for CC patients.

Highlights

Cervical cancer (CC) is the fourth most common female cancer affecting a majority of women worldwide; it is the leading cause of cancer-associated death in women and around 87% CC-related death occur in the developing world, including China [1]
To identify genes that are closely related to CC prognosis, first of all, we sought to explore Differentially expressed genes (DEGs) that are possibly involved in the progression from normal cervical epithelium tissue to CC
All 73 commonly deregulated DEGs were analyzed by DAVID web tool and the results of the gene ontology (GO) analysis indicated that (1) for biological processes (BP), the up-regulated DEGs were enriched in regulation of DNA replication, cell division, mitotic nuclear division, G1/S transition of mitotic cell cycle, sister chromatid cohesion, and DNA replication initiation, and the down-regulated DEGs in positive regulation of cell proliferation, positive regulation of cell differentiation, and negative regulation of epithelial cell proliferation; (2) for cell component (CC), the up-regulated DEGs were mostly significantly enriched in the nucleoplasm, nucleus, midbody, condensed chromosome kinetochore, kinetochore, and spindle microtubule

Summary

Introduction

Cervical cancer (CC) is the fourth most common female cancer affecting a majority of women worldwide; it is the leading cause of cancer-associated death in women and around 87% CC-related death occur in the developing world, including China [1]. The high incidence of CC is due to human papilloma virus infection, tobacco smoking, genetic alterations, and other factors. The known genetic alterations related with CC involve the epidermal growth factor receptor (EGFR) [2], human telomerase RNA component (hTERC) [3], phosphatase and tensin homolog (PTEN) [4], c-MYC [5], and other aberrations. The current therapy for CC mainly includes surgical treatment, cytotoxic chemotherapy, and radiotherapy. Despite advances in these traditional and newly emerging therapeutic modalities for CC, the 5-year disease-free survival (DFS) rates for advanced staged CC patients are only 45% [6]. It is crucial to investigate and identify the molecular aberrations in CC so as to develop more effective therapeutic strategies

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