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pmid:33927789

Transcriptome-Wide Gene Expression in a Murine Model of Ventilator-Induced Lung Injury.

Zhao Li · Guoshao Zhu · Chen Zhou · Hui Wang · Le Yu · Yunxin Xu · Li Xu · Qingxiu Wang

Disease markers · 2021 doi:10.1155/2021/5535890

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:33927789
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science-record
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2026-11-01T15:41:34Z
updated_at
2026-11-01T22:03:39Z
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paper object · 10 fields
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title
Transcriptome-Wide Gene Expression in a Murine Model of Ventilator-Induced Lung Injury.
doi
10.1155/2021/5535890
pmid
33927789
authors array · 8 items
[0]
Zhao Li
[1]
Guoshao Zhu
[2]
Chen Zhou
[3]
Hui Wang
[4]
Le Yu
[5]
Yunxin Xu
[6]
Li Xu
[7]
Qingxiu Wang
journal
Disease markers
year
2021
abstract
BACKGROUND: Mechanical ventilation could lead to ventilator-induced lung injury (VILI), but its underlying pathogenesis remains largely unknown. In this study, we aimed to determine the genes which were highly correlated with VILI as well as their expressions and interactions by analyzing the differentially expressed genes (DEGs) between the VILI samples and controls. METHODS: GSE11434 was downloaded from the gene expression omnibus (GEO) database, and DEGs were identified with GEO2R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using DAVID. Next, we used the STRING tool to construct protein-protein interaction (PPI) network of the DEGs. Then, the hub genes and related modules were identified with the Cytoscape plugins: cytoHubba and MCODE. qRT-PCR was further used to validate the results in the GSE11434 dataset. We also applied gene set enrichment analysis (GSEA) to discern the gene sets that had a significant difference between the VILI group and the control. Hub genes were also subjected to analyses by CyTargetLinker and NetworkAnalyst to predict associated miRNAs and transcription factors (TFs). Besides, we used CIBERSORT to detect the contributions of different types of immune cells in lung tissues of mice in the VILI group. By using DrugBank, small molecular compounds that could potentially interact with hub genes were identified. RESULTS: A total of 141 DEGs between the VILI group and the control were identified in GSE11434. Then, seven hub genes were identified and were validated by using qRT-PCR. Those seven hub genes were largely enriched in TLR and JAK-STAT signaling pathways. GSEA showed that VILI-associated genes were also enriched in NOD, antigen presentation, and chemokine pathways. We predicted the miRNAs and TFs associated with hub genes and constructed miRNA-TF-gene regulatory network. An analysis with CIBERSORT showed that the proportion of M0 macrophages and activated mast cells was higher in the VILI group than in the control. Small molecules, like nadroparin and siltuximab, could act as potential drugs for VILI. CONCLUSION: In sum, a number of hub genes associated with VILI were identified and could provide novel insights into the pathogenesis of VILI and potential targets for its treatment.
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Ventilator-induced lung injury in C57BL\6 mice
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GO analysis of the most significant clustering module in PPI networks.
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3.2. PPI Network and Module Analysis of DEGs
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GO analysis of the most significant clustering module in PPI networks.
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0.002782
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3.2. PPI Network and Module Analysis of DEGs
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KEGG analysis of the most significant clustering module in PPI networks.
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3.3. The Identification and Validation of Hub Genes
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GO enrichment analysis of hub genes.
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KEGG enrichment analysis of hub genes.
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3.3. The Identification and Validation of Hub Genes
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Table 4
caption
KEGG enrichment analysis of hub genes.
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0.001727
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0.002419
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[0]
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0.003158
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[0]
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[2]
0.004063
[15] array · 3 items
[0]
KEGG_PATHWAY
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[2]
0.00434
[16] array · 3 items
[0]
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[2]
0.006194
[17] array · 3 items
[0]
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[2]
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[2]
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Potential drugs that target hub genes derived from DrugBank.
structure object · 5 fields
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PMC8049808
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20
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3.7. Drug Prediction for Hub Genes
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Table 5
caption
Potential drugs that target hub genes derived from DrugBank.
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[0] array · 5 items
[0]
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[3]
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[4]
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[1]
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[2]
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[3]
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[4]
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[2] array · 5 items
[0]
MYC
[1]
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[2]
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[3]
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[4]
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[0]
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[1]
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[2]
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[3]
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[4]
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[0]
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[1]
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[3]
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[3]
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[3]
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[4]
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[1]
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[2]
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[3]
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[4]
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asset:data:geo:GSE11434 not downloaded
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[1]
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capability:computational_analysis
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[1]
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[3]
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[5]
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Automated Assays Laravel application and simulated adapters
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: ppi_network.
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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[0]
GSE11434
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[0]
GSE11434
statements array · 1 item
[0]
All data generated or analyzed during this study were included in this accepted article.
basis
The paper names GSE11434 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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source:pmid:33927789
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data:geo:GSE11434
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2026-10-31T19:32:51Z
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PMID 33927789 full text
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PMID 33927789 full text
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[0]
Transcriptome-Wide Gene Expression in a Murine Model of Ventilator-Induced Lung Injury.
[1]
breathed without any mechanical assistance). Mice were abstained from food 4 hours prior to anesthe
[2]
ly. After 4 h of mechanical ventilation, the mice were euthanized, and then, lung tissues were harv
[3]
NA targets. In this study, we downloaded the murine gene datasets and selected miRTarBase, Micro
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33927789", "kind": "science-record", "revision": 7, "content_hash": "sha256:dbe47be8633f32cf45e347017d13b1e2577cdf1572aa55d684ace43024bfb55e", "created_at": "2026-11-01T15:41:34Z", "updated_at": "2026-11-01T22:03:39Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Transcriptome-Wide Gene Expression in a Murine Model of Ventilator-Induced Lung Injury.", "doi": "10.1155/2021/5535890", "pmid": "33927789", "authors": ["Zhao Li", "Guoshao Zhu", "Chen Zhou", "Hui Wang", "Le Yu", "Yunxin Xu", "Li Xu", "Qingxiu Wang"], "journal": "Disease markers", "year": 2021, "abstract": "BACKGROUND: Mechanical ventilation could lead to ventilator-induced lung injury (VILI), but its underlying pathogenesis remains largely unknown. In this study, we aimed to determine the genes which were highly correlated with VILI as well as their expressions and interactions by analyzing the differentially expressed genes (DEGs) between the VILI samples and controls.\nMETHODS: GSE11434 was downloaded from the gene expression omnibus (GEO) database, and DEGs were identified with GEO2R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using DAVID. Next, we used the STRING tool to construct protein-protein interaction (PPI) network of the DEGs. Then, the hub genes and related modules were identified with the Cytoscape plugins: cytoHubba and MCODE. qRT-PCR was further used to validate the results in the GSE11434 dataset. We also applied gene set enrichment analysis (GSEA) to discern the gene sets that had a significant difference between the VILI group and the control. Hub genes were also subjected to analyses by CyTargetLinker and NetworkAnalyst to predict associated miRNAs and transcription factors (TFs). Besides, we used CIBERSORT to detect the contributions of different types of immune cells in lung tissues of mice in the VILI group. By using DrugBank, small molecular compounds that could potentially interact with hub genes were identified.\nRESULTS: A total of 141 DEGs between the VILI group and the control were identified in GSE11434. Then, seven hub genes were identified and were validated by using qRT-PCR. Those seven hub genes were largely enriched in TLR and JAK-STAT signaling pathways. GSEA showed that VILI-associated genes were also enriched in NOD, antigen presentation, and chemokine pathways. We predicted the miRNAs and TFs associated with hub genes and constructed miRNA-TF-gene regulatory network. An analysis with CIBERSORT showed that the proportion of M0 macrophages and activated mast cells was higher in the VILI group than in the control. Small molecules, like nadroparin and siltuximab, could act as potential drugs for VILI.\nCONCLUSION: In sum, a number of hub genes associated with VILI were identified and could provide novel insights into the pathogenesis of VILI and potential targets for its treatment.", "claims": [{"id": "claim-data-access", "statement": "All data generated or analyzed during this study were included in this accepted article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33927789", "locator": "sections[25] \"Data Availability\" paragraph 2", "quote": "All data generated or analyzed during this study were included in this accepted article."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33927789"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE11434"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE11434"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33927789", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2021/5535890", "sha256": "sha256:30dc06eb8a0a36a84da610eeb91570b860dcfd4e7520b8628fd95b6c15048d63", "bytes": 39600, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2021/5535890", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8049808", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE11434", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11434", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE11434", "version": null, "note": "All data generated or analyzed during this study were included in this accepted article.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All data generated or analyzed during this study were included in this accepted article.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM288398", "GSM288399", "GSM288400", "GSM288401", "GSM288402", "GSM288403", "GSM288404", "GSM288405", "GSM288406", "GSM288407"], "sample_count": 10, "group_sizes": null, "group_sizes_basis": null, "platform": "1261", "taxon": "Mus musculus", "title": "Ventilator-induced lung injury in C57BL\\6 mice", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:33927789:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:3310a13db8555c643242cd3893f8843479cb5e9ac86c71d4b27e2de9172d12b7", "bytes": 1853, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#tab1", "version": null, "note": "GO analysis of the most significant clustering module in PPI networks.", "structure": {"pmcid": "PMC8049808", "section_index": 15, "section_title": "3.2. PPI Network and Module Analysis of DEGs", "row_count": 18, "column_count": 3}, "table": {"label": "Table 1", "caption": "GO analysis of the most significant clustering module in PPI networks.", "rows": [["Category", "Term", "p value"], ["GOTERM_BP_DIRECT", "GO:0006351~transcription, DNA-templated", "1.19E − 04"], ["GOTERM_BP_DIRECT", "GO:0045893~positive regulation of transcription, DNA-templated", "7.52E − 04"], ["GOTERM_BP_DIRECT", "GO:0006357~regulation of transcription from RNA polymerase II promoter", "7.63E − 04"], ["GOTERM_BP_DIRECT", "GO:0006954~inflammatory response", "0.013427"], ["GOTERM_BP_DIRECT", "GO:0043066~negative regulation of apoptotic process", "0.014684"], ["GOTERM_BP_DIRECT", "GO:0035914~skeletal muscle cell differentiation", "0.024883"], ["GOTERM_BP_DIRECT", "GO:0051091~positive regulation of sequence-specific DNA binding transcription factor activity", "0.048278"], ["GOTERM_BP_DIRECT", "GO:0006355~regulation of transcription, DNA-templated", "0.048792"], ["GOTERM_CC_DIRECT", "GO:0005634~nucleus", "3.27E − 06"], ["GOTERM_CC_DIRECT", "GO:0005654~nucleoplasm", "0.039133"], ["GOTERM_MF_DIRECT", "GO:0003700~transcription factor activity, sequence-specific DNA binding", "1.82E − 06"], ["GOTERM_MF_DIRECT", "GO:0003677~DNA binding", "8.51E − 05"], ["GOTERM_MF_DIRECT", "GO:0000978~RNA polymerase II core promoter proximal region sequence-specific DNA binding", "0.001059"], ["GOTERM_MF_DIRECT", "GO:0043565~sequence-specific DNA binding", "0.002782"], ["GOTERM_MF_DIRECT", "GO:0001077~transcriptional activator activity, RNA polymerase II core promoter proximal region sequence-specific binding", "0.009683"], ["GOTERM_MF_DIRECT", "GO:0000982~transcription factor activity, RNA polymerase II core promoter proximal region sequence-specific binding", "0.014036"], ["GOTERM_MF_DIRECT", "GO:0046983~protein dimerization activity", "0.015108"]], "row_count": 18, "column_count": 3, "numeric_cells": 34, "header_rows": 1, "locator": "section[15]/table-wrap[1]#tab1"}}, {"id": "asset:table:pmid:33927789:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:507dd28ba9633d156805b58b376539654fc8be6b9e95ba36e7debd6a63fea6c3", "bytes": 1013, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[2]#tab2", "version": null, "note": "KEGG analysis of the most significant clustering module in PPI networks.", "structure": {"pmcid": "PMC8049808", "section_index": 15, "section_title": "3.2. 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