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pmid:36531223

Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury.

Shuo Sun · Jianming Xue · Yunfei Guo · Jianling Li

Frontiers in genetics · 2022 doi:10.3389/fgene.2022.1072544

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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title
Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury.
doi
10.3389/fgene.2022.1072544
pmid
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Shuo Sun
[1]
Jianming Xue
[2]
Yunfei Guo
[3]
Jianling Li
journal
Frontiers in genetics
year
2022
abstract
Background: Primary liver cancer is the sixth most commonly diagnosed cancer and the third leading cause of cancer death worldwide in 2020, and it ranks fifth in global incidence. Liver resection or liver transplantation are the two most prominent surgical procedures for treating primary liver cancer. Both inevitably result in HIRI, causing severe complications for patients and affecting their prognosis and quality of survival. Ferroptosis, a newly discovered mode of cell death, is closely related to HIRI. We used bioinformatics analysis to explore the relationship between the two further. Methods: The GEO database dataset GSE112713 and the FerrDB database data were selected to use bioinformatic analysis methods (difference analysis, FRGs identification, GO analysis, KEGG analysis, PPI network construction and analysis, Hub gene screening with GO analysis and KEGG analysis, intergenic interaction prediction, drug-gene interaction prediction, miRNA prediction) for both for correlation analysis. The GEO database dataset GSE15480 was selected for preliminary validation of the screened Hub genes. Results: We analysed the dataset GSE112713 for differential gene expression before and after hepatic ischemia-reperfusion and identified by FRGs, yielding 11 genes. These 11 genes were subjected to GO, and KEGG analyses, and PPI networks were constructed and analysed. We also screened these 11 genes again to obtain 5 Hub genes and performed GO analysis, KEGG analysis, intergenic interaction prediction, drug-gene interaction prediction, and miRNA prediction on these 5 Hub genes. Finally, we obtained preliminary validation of all these 5 Hub genes by dataset GSE15480. Conclusion: There is a close relationship between HIRI and ferroptosis, and inhibition of ferroptosis can potentially be a new approach to mitigate HIRI treatment in the future.
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We performed the differential analysis of gene expression data before and after liver reperfusion for 11 selected samples in the GSE112713 dataset by the GEO2R (Barrett T et al., 2012) online tool in the GEO database.
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We performed the differential analysis of gene expression data before and after liver reperfusion for 11 selected samples in the GSE112713 dataset by the GEO2R (Barrett T et al., 2012) online tool in the GEO database.
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Liver resection or liver transplantation are the two most prominent surgical procedures for treating primary liver cancer. Both inevitably result in HIRI, causing severe complications for patients and affecting their prognosis and quality of survival. Ferroptosis, a newly discovered mode of cell death, is closely related to HIRI. We used bioinformatics analysis to explore the relationship between the two further. Methods: The GEO database dataset GSE112713 and the FerrDB database data were selected to use bioinformatic analysis methods (difference analysis, FRGs identification, GO analysis, KEGG analysis, PPI network construction and analysis, Hub gene screening with GO analysis and KEGG analysis, intergenic interaction prediction, drug-gene interaction prediction, miRNA prediction) for both for correlation analysis. The GEO database dataset GSE15480 was selected for preliminary validation of the screened Hub genes. 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