Network-Based Integrated Analysis of Transcriptomic Studies in Dissecting Gene Signatures for LPS-Induced Acute Lung Injury
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature..
Acute lung injury (ALI) is a type of serious clinical syndrome leading to morbidity and mortality. However, the precise pathogenesis of ALI remains elusive. Here, we implemented an integrative meta-analysis of six GEO microarray studies with 76 samples in the ALI mouse model. A total of 958 differentially expressed genes (DEGs) were identified in LPS relative to normal samples. Then, a network-based meta-analysis was used to mine core DEGs and to unfold the interactions among these genes. We found that Ebi3 was the top upregulated genes in the LPS-induced ALI. GO, KEGG, and GSEA analyses were performed for functional annotation. qRT-PCR revealed augmented expression of six candidate genes (Stat1, Syk, Jak3, Rac2, Ripk1, and Traf6) in the established ALI mouse model with LPS exposure. Taken together, our study investigated comprehensively hub DEGs and their networks for LPS-stimulated ALI, which might afford an additional approach to determine biomarkers and therapeutic targets and explore the molecular pathophysiology toward ALI.
| Errataetall: | |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:44 |
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| Enthalten in: |
Inflammation - 44(2021), 6 vom: 30. Dez., Seite 2486-2498 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Cao, Fang [VerfasserIn] |
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| Links: |
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| Themen: |
Acute lung injury |
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| Anmerkungen: |
Date Completed 17.03.2022 Date Revised 26.02.2024 published: Print-Electronic ErratumIn: Inflammation. 2021 Nov 13;:. - PMID 34773189 Citation Status MEDLINE |
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| doi: |
10.1007/s10753-021-01518-8 |
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| funding: |
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| PPN (Katalog-ID): |
NLM330055755 |
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| 520 | |a © 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. | ||
| 520 | |a Acute lung injury (ALI) is a type of serious clinical syndrome leading to morbidity and mortality. However, the precise pathogenesis of ALI remains elusive. Here, we implemented an integrative meta-analysis of six GEO microarray studies with 76 samples in the ALI mouse model. A total of 958 differentially expressed genes (DEGs) were identified in LPS relative to normal samples. Then, a network-based meta-analysis was used to mine core DEGs and to unfold the interactions among these genes. We found that Ebi3 was the top upregulated genes in the LPS-induced ALI. GO, KEGG, and GSEA analyses were performed for functional annotation. qRT-PCR revealed augmented expression of six candidate genes (Stat1, Syk, Jak3, Rac2, Ripk1, and Traf6) in the established ALI mouse model with LPS exposure. Taken together, our study investigated comprehensively hub DEGs and their networks for LPS-stimulated ALI, which might afford an additional approach to determine biomarkers and therapeutic targets and explore the molecular pathophysiology toward ALI | ||
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