Identification of differential genes and bioinformatics analysis related to ferroptosis in ovarian cancer based on transcriptome sequencing
Objective This study aims to explore key differential genes and potential mechanisms related to ferroptosis in ovarian cancer.Methods Transcriptome sequencing was conducted on the ovarian cancer cell line OVCAR8 after treatment with the ferroptosis inducer ras-selective lethal 3(RSL3),utilizing the Illumina sequencing platform.The DESeq2 algorithm was applied to identify differential genes associated with ferroptosis in ovarian cancer.A comprehensive analysis of molecular functions and signaling pathways enriched in these differential genes was carried out through Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG),Gene Set Enrichment Analysis(GSEA),and Protein-Protein Interaction(PPI)network analysis.Results The transcriptome sequencing data passed quality control,with a total alignment rate of(0.968±0.002)％.A total of 1 834 differential genes related to ferroptosis were identified,comprising 805 up-regulated genes and 1 029 down-regulated genes.GO and KEGG analyses revealed that differential genes were mainly enriched in biological functions related to the cell cycle,as well as signaling pathways involved in ferroptosis,protein processing in endoplasmic reticulum,p53 signaling pathway,alanine,aspartate,and glutamate metabolism,among others.GSEA analysis revealed activation of molecular functions such as monooxygenase activity and iron ion binding,biological processes including hydrogen peroxide biosynthetic precess,arachidonic acid metabolic process,and response to iron ion,as well as signaling pathways related to interferon alpha and beta signaling,downregulation of cisplatin resistance,iron uptake and transport.PPI analysis identified 5 key differential genes associated with ferroptosis,which included cyclin-dependent kinase 1(CDK1),cyclin A2(CCNA2),cyclin B1(CCNB1),polo-like kinase 1(PLK1)and breast cancer gene 1(BRCAI).Conclusion Transcriptome sequencing and bioinformatics analysis can effectively identify differential genes and signaling pathways associated with ferroptosis in ovarian cancer,offering potential drug targets for the development of new therapeutic strategies targeting ferroptosis.
国家科技期刊平台
NSTL
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