ArticleMedical science monitor : international medical journal of experimental and clinical research2022
Identification of Novel Genes and Associated Drugs in Cervical Cancer by Bioinformatics Methods.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- From Lab to Clinic: Success Stories of Repurposed Drugs in Treating Major Diseases.Advances in pharmacological and pharmaceutical sciences · 2025Review
- Identification of a disulfidptosis-related genes signature for diagnostic and immune infiltration characteristics in cervical cancer.PloS one · 2025Article
- Screening and identification of susceptibility genes for cervical cancer via bioinformatics analysis and the construction of an mitophagy-related genes diagnostic model.Journal of cancer research and clinical oncology · 2024Article
- Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis.BMC medical genomics · 2023Article
- Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer.Journal, genetic engineering & biotechnology · 2023Article
- Comprehensive Expression Profiling and Molecular Basis of CDC28 Protein Kinase Regulatory Subunit 2 in Cervical Cancer.International journal of genomics · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Cervical cancer is one of the common gynecological tumors that seriously harm women's health, so it is particularly important to accurately explore the underlying mechanism of its occurrence and clinical prognosis. MATERIAL AND METHODS In the GEO database, GEO2R was used to analyze the differentially expressed genes from the 4 databases: GSE6791, GSE9750, GSE63514, and GSE67522. Then, the DAVID website was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. These protein-protein interaction (PPI) networks of DEGS were visualized and analyzed using the STRING website and the hub genes were further screened using the Cytohubba plugin. Lastly, the functions of the hub genes were further analyzed by Gene Expression Profiling Interactive Analysis (GEPIA) online tools, Human Protein Atlas (HPA) databases, and the QuartataWeb database. RESULTS In the 4 Profile datasets, 101 cancer tissues and 67 normal tissues were collected. Among the 78 differentially expressed genes in the 4 datasets, 51 genes were upregulated and 27 genes were downregulated. The PPIs of these differentially expressed genes were visualized using Cytoscape and the Interaction Gene Search Tool (STRING). Then, further analysis of hub genes using the GEPIA tool and Kaplan-Meier curves that showed upregulation of CDK1 and PRC1 is associated with better survival, while AURKA is associated with worse survival. Among these hub genes, only AURKA was closely related to the prognosis of cervical cancer, and 21 potential drugs were found. CONCLUSIONS These results suggest that AURKA and its drug candidates can improve the individualized diagnosis and treatment of cervical cancer in the future.
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