In silico analysis of identification dysregulated genes in doxorubicin treatment human cervical cancer cell (HeLa)

Cervical cancer, the second most diagnosed gynecological cancer globally after breastcancer, is seeing increasing incidence and mortality rates despite effective screening and vaccinationprograms [۱]. Doxorubicin (DOX), an anthracycline drug used in clinical chemotherapy for cervicalcarcinoma [۲], acts by intercalating into DNA, inhibiting topoisomerase II, disrupting mitochondria,generating free radicals [۳], and inducing apoptosis through various mechanisms [۴]. DOX triggersearly activation of p۵۳, followed by caspase-۳ activation and DNA fragmentation in tumor cells [۵].The objective of this investigation is to analyze the gene expression profile of HeLa cells treated bydoxorubicin, aimed at delineating novel functional mechanisms of the drug.Methods: The raw data set GSE۱۲۵۲۴۹ was downloaded from the Gene Expression Omnibus.Differentially expressed genes (DEGs) between doxorubicin-treated HeLa cells and untreated cells wereidentified using R packages such as GEOquery, limma, BiocGenerics, affy, and oligo. The DEGs werethen used to construct a protein-protein interaction (PPI) network via the STRING database.Subsequently, Cytoscape software was employed to recognize hub genes. The DEGs also underwentgene ontology (GO) analysis and KEGG pathway analysis.Results: The study detected ۹۹۸ DEGs (|log۲FC (fold change) |>۱), comprising ۳۳۵ upregulated and۶۶۳ downregulated DEGs between doxorubicin-treated and untreated cervical cancer cells (HeLa).Dysregulated genes were enriched in pathways such as NF-kappa B signaling, TNF signaling, and p۵۳signaling in KEGG, and in biological processes including Positive Regulation of p۳۸MAPK cascadeand regulation of mitotic cytokinesis. CytoHubba plugin in Cytoscape identified ۱۰ hub genes: CENPA,PLK۱, CDCA۸, KIF۲C, CDK۱, AURK, KIF۲۳, KIF۲۰A, TTK, and ASPM. These hub genes werenotably enriched in cell cycle, p۵۳ signaling, FoxO signaling, and cellular senescence pathways.Conclusion: Transcriptome datasets from doxorubicin-treated cancer cells offer insights into cancerspecificbiological functions, pathways, and novel mechanisms for predicting clinical outcomes incervical cancer.

کلیدواژه ها:

Cervical cancer ، doxorubicin ، Transcriptome ، In silico