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Current Bioinformatics

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ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

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Research Article

Screening and Identification of Key Genes for Cervical Cancer, Ovarian Cancer and Endometrial Cancer by Combinational Bioinformatic Analysis

Author(s): Feng Pang, Dong Shi and Lin Yuan*

Volume 18, Issue 8, 2023

Published on: 27 June, 2023

Page: [647 - 657] Pages: 11

DOI: 10.2174/1574893618666230428095114

Price: $65

Abstract

Introduction: Cervical cancer, ovarian cancer and endometrial cancer are the top three cancers in women. With the rapid development of gene chip and high-throughput sequencing technology, it has been widely used to study genomic functional omics data and identify markers for disease diagnosis and treatment. At the same time, more and more public databases containing genetic data have appeared. The result of the bioinformatic analysis can provide a diagnosis of new perspectives on cell origin and differences.

Methods: In this paper, three datasets about cervical cancer, ovarian cancer and endometrial cancer from GEO were used to dig out common DEGs (differentially expressed genes) among cervical cancer/ovarian cancer/endometrial cancer. DEGs contain 400 up-regulation genes and 157 down-regulation genes.

Results: The results of GO (gene ontology) functional enrichment analysis show that the BP (biological process) changes of DEGs are mainly in cell division, mitotic nuclear division, sister chromatid cohesion, and DNA replication. The CC (cell component) function enrichments of DEGs were mainly in the nucleoplasm, nucleus, condensed chromosome kinetochore, chromosome, centromeric region. The MF (molecular function) function enrichments of DEGs were mainly in protein binding. The results of the KEGG pathway analysis showed that the upregulation DEGs were mainly enriched in retinoblastoma gene in the cell cycle, cellular senescence, oocyte meiosis, and pathways in cancer, while the downregulation DEGs enriched in thiamine metabolism, protein processing in endoplasmic reticulum. Similarly, the function of the most significant module was enriched in cell division, condensed chromosome kinetochore, and microtubule motor activity.

Conclusion: In the result, 4 of the top 10 hub genes (CCNA2, CCNB1, CDC6 and CDK1) will provide help for future biomedical experimental research.

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