Cargando…
Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients
BACKGROUND: Stroke is the second leading cause of death and the third leading cause of disability worldwide, with ischemic stroke (IS) being the most prevalent. A substantial number of irreversible brain cell death occur in the short term, leading to impairment or death in IS. Limiting the loss of b...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10332266/ https://www.ncbi.nlm.nih.gov/pubmed/37435058 http://dx.doi.org/10.3389/fimmu.2023.1164742 |
_version_ | 1785070406277791744 |
---|---|
author | Chen, Wenli Chen, Yuanfang Wu, Liting Gao, Yue Zhu, Hangju Li, Ye Ji, Xinyu Wang, Ziyi Wang, Wen Han, Lei Zhu, Baoli Wang, Hongxing Xu, Ming |
author_facet | Chen, Wenli Chen, Yuanfang Wu, Liting Gao, Yue Zhu, Hangju Li, Ye Ji, Xinyu Wang, Ziyi Wang, Wen Han, Lei Zhu, Baoli Wang, Hongxing Xu, Ming |
author_sort | Chen, Wenli |
collection | PubMed |
description | BACKGROUND: Stroke is the second leading cause of death and the third leading cause of disability worldwide, with ischemic stroke (IS) being the most prevalent. A substantial number of irreversible brain cell death occur in the short term, leading to impairment or death in IS. Limiting the loss of brain cells is the primary therapy target and a significant clinical issue for IS therapy. Our study aims to establish the gender specificity pattern from immune cell infiltration and four kinds of cell-death perspectives to improve IS diagnosis and therapy. METHODS: Combining and standardizing two IS datasets (GSE16561 and GSE22255) from the GEO database, we used the CIBERSORT algorithm to investigate and compare the immune cell infiltration in different groups and genders. Then, ferroptosis-related differently expressed genes (FRDEGs), pyroptosis-related DEGs (PRDEGs), anoikis-related DEGs (ARDEGs), and cuproptosis-related DEGs (CRDEGs) between the IS patient group and the healthy control group were identified in men and women, respectively. Machine learning (ML) was finally used to generate the disease prediction model for cell death-related DEGs (CDRDEGs) and to screen biomarkers related to cell death involved in IS. RESULTS: Significant changes were observed in 4 types of immune cells in male IS patients and 10 types in female IS patients compared with healthy controls. In total, 10 FRDEGs, 11 PRDEGs, 3 ARDEGs, and 1 CRDEG were present in male IS patients, while 6 FRDEGs, 16 PRDEGs, 4 ARDEGs, and 1 CRDEG existed in female IS patients. ML techniques indicated that the best diagnostic model for both male and female patients was the support vector machine (SVM) for CDRDEG genes. SVM’s feature importance analysis demonstrated that SLC2A3, MMP9, C5AR1, ACSL1, and NLRP3 were the top five feature-important CDRDEGs in male IS patients. Meanwhile, the PDK4, SCL40A1, FAR1, CD163, and CD96 displayed their overwhelming influence on female IS patients. CONCLUSION: These findings contribute to a better knowledge of immune cell infiltration and their corresponding molecular mechanisms of cell death and offer distinct clinically relevant biological targets for IS patients of different genders. |
format | Online Article Text |
id | pubmed-10332266 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-103322662023-07-11 Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients Chen, Wenli Chen, Yuanfang Wu, Liting Gao, Yue Zhu, Hangju Li, Ye Ji, Xinyu Wang, Ziyi Wang, Wen Han, Lei Zhu, Baoli Wang, Hongxing Xu, Ming Front Immunol Immunology BACKGROUND: Stroke is the second leading cause of death and the third leading cause of disability worldwide, with ischemic stroke (IS) being the most prevalent. A substantial number of irreversible brain cell death occur in the short term, leading to impairment or death in IS. Limiting the loss of brain cells is the primary therapy target and a significant clinical issue for IS therapy. Our study aims to establish the gender specificity pattern from immune cell infiltration and four kinds of cell-death perspectives to improve IS diagnosis and therapy. METHODS: Combining and standardizing two IS datasets (GSE16561 and GSE22255) from the GEO database, we used the CIBERSORT algorithm to investigate and compare the immune cell infiltration in different groups and genders. Then, ferroptosis-related differently expressed genes (FRDEGs), pyroptosis-related DEGs (PRDEGs), anoikis-related DEGs (ARDEGs), and cuproptosis-related DEGs (CRDEGs) between the IS patient group and the healthy control group were identified in men and women, respectively. Machine learning (ML) was finally used to generate the disease prediction model for cell death-related DEGs (CDRDEGs) and to screen biomarkers related to cell death involved in IS. RESULTS: Significant changes were observed in 4 types of immune cells in male IS patients and 10 types in female IS patients compared with healthy controls. In total, 10 FRDEGs, 11 PRDEGs, 3 ARDEGs, and 1 CRDEG were present in male IS patients, while 6 FRDEGs, 16 PRDEGs, 4 ARDEGs, and 1 CRDEG existed in female IS patients. ML techniques indicated that the best diagnostic model for both male and female patients was the support vector machine (SVM) for CDRDEG genes. SVM’s feature importance analysis demonstrated that SLC2A3, MMP9, C5AR1, ACSL1, and NLRP3 were the top five feature-important CDRDEGs in male IS patients. Meanwhile, the PDK4, SCL40A1, FAR1, CD163, and CD96 displayed their overwhelming influence on female IS patients. CONCLUSION: These findings contribute to a better knowledge of immune cell infiltration and their corresponding molecular mechanisms of cell death and offer distinct clinically relevant biological targets for IS patients of different genders. Frontiers Media S.A. 2023-06-26 /pmc/articles/PMC10332266/ /pubmed/37435058 http://dx.doi.org/10.3389/fimmu.2023.1164742 Text en Copyright © 2023 Chen, Chen, Wu, Gao, Zhu, Li, Ji, Wang, Wang, Han, Zhu, Wang and Xu 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 | Immunology Chen, Wenli Chen, Yuanfang Wu, Liting Gao, Yue Zhu, Hangju Li, Ye Ji, Xinyu Wang, Ziyi Wang, Wen Han, Lei Zhu, Baoli Wang, Hongxing Xu, Ming Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients |
title | Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients |
title_full | Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients |
title_fullStr | Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients |
title_full_unstemmed | Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients |
title_short | Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients |
title_sort | identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10332266/ https://www.ncbi.nlm.nih.gov/pubmed/37435058 http://dx.doi.org/10.3389/fimmu.2023.1164742 |
work_keys_str_mv | AT chenwenli identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT chenyuanfang identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT wuliting identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT gaoyue identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT zhuhangju identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT liye identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT jixinyu identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT wangziyi identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT wangwen identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT hanlei identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT zhubaoli identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT wanghongxing identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients AT xuming identificationofcelldeathrelatedbiomarkersandimmuneinfiltrationinischemicstrokebetweenmaleandfemalepatients |