Cargando…
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...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755192/ https://www.ncbi.nlm.nih.gov/pubmed/36531223 http://dx.doi.org/10.3389/fgene.2022.1072544 |
_version_ | 1784851374464303104 |
---|---|
author | Sun, Shuo Xue, Jianming Guo, Yunfei Li, Jianling |
author_facet | Sun, Shuo Xue, Jianming Guo, Yunfei Li, Jianling |
author_sort | Sun, Shuo |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-9755192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97551922022-12-17 Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury Sun, Shuo Xue, Jianming Guo, Yunfei Li, Jianling Front Genet Genetics 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. Frontiers Media S.A. 2022-12-02 /pmc/articles/PMC9755192/ /pubmed/36531223 http://dx.doi.org/10.3389/fgene.2022.1072544 Text en Copyright © 2022 Sun, Xue, Guo and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Sun, Shuo Xue, Jianming Guo, Yunfei Li, Jianling Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury |
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 | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755192/ https://www.ncbi.nlm.nih.gov/pubmed/36531223 http://dx.doi.org/10.3389/fgene.2022.1072544 |
work_keys_str_mv | AT sunshuo bioinformaticsanalysisofgenesrelatedtoferroptosisinhepaticischemiareperfusioninjury AT xuejianming bioinformaticsanalysisofgenesrelatedtoferroptosisinhepaticischemiareperfusioninjury AT guoyunfei bioinformaticsanalysisofgenesrelatedtoferroptosisinhepaticischemiareperfusioninjury AT lijianling bioinformaticsanalysisofgenesrelatedtoferroptosisinhepaticischemiareperfusioninjury |