Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury
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 cance...
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Language: | English |
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Frontiers Media S.A.
2022-12-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.1072544/full |
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author | Shuo Sun Jianming Xue Yunfei Guo Jianling Li |
author_facet | Shuo Sun Jianming Xue Yunfei Guo Jianling Li |
author_sort | Shuo Sun |
collection | DOAJ |
description | 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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issn | 1664-8021 |
language | English |
last_indexed | 2024-04-13T12:51:57Z |
publishDate | 2022-12-01 |
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spelling | doaj.art-43135512607c4f8caa478ba758632b232022-12-22T02:46:11ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-12-011310.3389/fgene.2022.10725441072544Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injuryShuo SunJianming XueYunfei GuoJianling LiBackground: 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.https://www.frontiersin.org/articles/10.3389/fgene.2022.1072544/fullhepatic ischemia-reperfusion injuryferroptosisbioinformatics analysisprediction of drug-gene interactionsMiRNA prediction |
spellingShingle | Shuo Sun Jianming Xue Yunfei Guo Jianling Li Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury Frontiers in Genetics hepatic ischemia-reperfusion injury ferroptosis bioinformatics analysis prediction of drug-gene interactions MiRNA prediction |
title | Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury |
title_full | Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury |
title_fullStr | Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury |
title_full_unstemmed | Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury |
title_short | Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury |
title_sort | bioinformatics analysis of genes related to ferroptosis in hepatic ischemia reperfusion injury |
topic | hepatic ischemia-reperfusion injury ferroptosis bioinformatics analysis prediction of drug-gene interactions MiRNA prediction |
url | https://www.frontiersin.org/articles/10.3389/fgene.2022.1072544/full |
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