Therapeutic target genes and regulatory networks of gallic acid in cervical cancer
IntroductionThis study aims to identify the therapeutic targets and regulatory mechanisms of the antitumor drug gallic acid (GA) in cervical cancer (CC).MethodsHeLa cells were treated with GA and subjected to RNA-sequencing using the DNBSEQ platform. By combining the results of the Gene Expression O...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2024.1508869/full |
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| author | Zhixi You Ye Lei Yongkang Yang Zhihui Zhou Xu Chao Keyi Ju Songyi Wang Yuanyuan Li Yuanyuan Li |
| author_facet | Zhixi You Ye Lei Yongkang Yang Zhihui Zhou Xu Chao Keyi Ju Songyi Wang Yuanyuan Li Yuanyuan Li |
| author_sort | Zhixi You |
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| description | IntroductionThis study aims to identify the therapeutic targets and regulatory mechanisms of the antitumor drug gallic acid (GA) in cervical cancer (CC).MethodsHeLa cells were treated with GA and subjected to RNA-sequencing using the DNBSEQ platform. By combining the results of the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) analysis and RNA-seq, the differentially expressed genes (DEGs), including those upregulated and downregulated genes in CC compared with the normal cervix in the GEO and TCGA database, while expressed reversed after treatment with GA, were identified. Subsequently, the function enrichment analysis and protein–protein interaction of the DEGs were conducted. The candidate genes were identified using the Cytoscape software Gentiscape2.2 and MCODE plug-ins. Furthermore, the upstream microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) of the candidate genes were predicted using the online tools of MirDIP, TarBase, and ENCORI. Finally, the regulatory network was constructed using Cytoscape software.ResultsCC cells are significantly inhibited by GA. Combining the GEO and TCGA databases and RNA-seq analyses, 127 DEGs were obtained and subjected to functional enrichment analysis. This analysis revealed that 221 biological processes, 82 cellular components, 63 molecular functions, and 36 KEGG pathways were employed to identify three therapeutic candidate genes, including CDC20, DLGAP5, and KIF20A. The upstream 13 miRNAs, 4 lncRNA, and 42 circRNAs were detected and used to construct a lncRNA/circRNA-miRNA-mRNA-pathway regulatory network.ConclusionThis study identified candidate genes and the regulatory networks underlying the therapeutic effects of GA on CC using GA data mining methods, thus establishing a theoretical basis for targeted therapy of CC. |
| format | Article |
| id | doaj-art-bd6461871c054a448252179bf510d55c |
| institution | Kabale University |
| issn | 1664-8021 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj-art-bd6461871c054a448252179bf510d55c2025-01-20T17:25:15ZengFrontiers Media S.A.Frontiers in Genetics1664-80212025-01-011510.3389/fgene.2024.15088691508869Therapeutic target genes and regulatory networks of gallic acid in cervical cancerZhixi You0Ye Lei1Yongkang Yang2Zhihui Zhou3Xu Chao4Keyi Ju5Songyi Wang6Yuanyuan Li7Yuanyuan Li8The Second Clinical Medical College, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, ChinaThe Second Affiliated Hospital, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, ChinaThe Second Affiliated Hospital, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, ChinaThe Second Affiliated Hospital, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, ChinaThe Second Affiliated Hospital, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, ChinaThe Second Clinical Medical College, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, ChinaThe Second Clinical Medical College, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, ChinaThe Second Clinical Medical College, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, ChinaThe Second Affiliated Hospital, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, ChinaIntroductionThis study aims to identify the therapeutic targets and regulatory mechanisms of the antitumor drug gallic acid (GA) in cervical cancer (CC).MethodsHeLa cells were treated with GA and subjected to RNA-sequencing using the DNBSEQ platform. By combining the results of the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) analysis and RNA-seq, the differentially expressed genes (DEGs), including those upregulated and downregulated genes in CC compared with the normal cervix in the GEO and TCGA database, while expressed reversed after treatment with GA, were identified. Subsequently, the function enrichment analysis and protein–protein interaction of the DEGs were conducted. The candidate genes were identified using the Cytoscape software Gentiscape2.2 and MCODE plug-ins. Furthermore, the upstream microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) of the candidate genes were predicted using the online tools of MirDIP, TarBase, and ENCORI. Finally, the regulatory network was constructed using Cytoscape software.ResultsCC cells are significantly inhibited by GA. Combining the GEO and TCGA databases and RNA-seq analyses, 127 DEGs were obtained and subjected to functional enrichment analysis. This analysis revealed that 221 biological processes, 82 cellular components, 63 molecular functions, and 36 KEGG pathways were employed to identify three therapeutic candidate genes, including CDC20, DLGAP5, and KIF20A. The upstream 13 miRNAs, 4 lncRNA, and 42 circRNAs were detected and used to construct a lncRNA/circRNA-miRNA-mRNA-pathway regulatory network.ConclusionThis study identified candidate genes and the regulatory networks underlying the therapeutic effects of GA on CC using GA data mining methods, thus establishing a theoretical basis for targeted therapy of CC.https://www.frontiersin.org/articles/10.3389/fgene.2024.1508869/fullgallic acidRNA-sequencingdifferentially expressed genescandidate genesregulatory networkcervical cancer |
| spellingShingle | Zhixi You Ye Lei Yongkang Yang Zhihui Zhou Xu Chao Keyi Ju Songyi Wang Yuanyuan Li Yuanyuan Li Therapeutic target genes and regulatory networks of gallic acid in cervical cancer Frontiers in Genetics gallic acid RNA-sequencing differentially expressed genes candidate genes regulatory network cervical cancer |
| title | Therapeutic target genes and regulatory networks of gallic acid in cervical cancer |
| title_full | Therapeutic target genes and regulatory networks of gallic acid in cervical cancer |
| title_fullStr | Therapeutic target genes and regulatory networks of gallic acid in cervical cancer |
| title_full_unstemmed | Therapeutic target genes and regulatory networks of gallic acid in cervical cancer |
| title_short | Therapeutic target genes and regulatory networks of gallic acid in cervical cancer |
| title_sort | therapeutic target genes and regulatory networks of gallic acid in cervical cancer |
| topic | gallic acid RNA-sequencing differentially expressed genes candidate genes regulatory network cervical cancer |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2024.1508869/full |
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