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Identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis
BACKGROUND: Atherosclerosis is an underlying cause of cardiovascular disease which is a leading cause of death worldwide. Foam cells play a crucial role in atherosclerotic lesion development, and macrophages and vascular smooth muscle cells (VSMCs) appear to contribute to the formation of the majori...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10061454/ https://www.ncbi.nlm.nih.gov/pubmed/37007574 http://dx.doi.org/10.21037/atm-22-3761 |
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author | Xu, Jing Yang, Yuejin |
author_facet | Xu, Jing Yang, Yuejin |
author_sort | Xu, Jing |
collection | PubMed |
description | BACKGROUND: Atherosclerosis is an underlying cause of cardiovascular disease which is a leading cause of death worldwide. Foam cells play a crucial role in atherosclerotic lesion development, and macrophages and vascular smooth muscle cells (VSMCs) appear to contribute to the formation of the majority of atheromatous foam cells via oxidized low-density lipoprotein (ox-LDL) uptake. METHODS: An integrated, microarray-based analysis using GSE54666 and GSE68021, which contain samples of human macrophages and VSMCs incubated with ox-LDL, was conducted. The differentially expressed genes (DEGs) in each dataset were investigated via the linear models for microarray data (limma) v. 3.40.6 software package in R v. 4.1.2 (The R Foundation for Statistical Computing). Gene ontology (GO) and pathway enrichment were performed via the ClueGO v. 2.5.8 and CluePedia v. 1.5.8 databases and the Database of Annotation, Visualization and Integrated (DAVID; https://david.ncifcrf.gov). The convergent DEGs in the two cell types were obtained, and the protein interactions and network of transcriptional factors were analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) v. 11.5 and the Transcriptional Regulatory Relationships Unraveled by Sentence-based Text-mining (TRRUST) v. 2 databases. The selected DEGs were further validated using external data from GSE9874, and a machine learning algorithm of the least absolute shrinkage and selection operator (LASSO) regression and receiver operating characteristic (ROC) analysis were applied to explore the candidate biomarkers. RESULTS: We discovered the significant DEGs and pathways that were shared or unique among the 2 cell types, coupling with enriched lipid metabolism in macrophages, and upregulated defense response in VSMCs. Moreover, we identified BTG2, ABCA1, and SLC7A11 as potential biomarkers and molecular targets for atherogenesis. CONCLUSIONS: Our study provides a comprehensive summary of the landscape of the transcriptional regulations in macrophages and VSMCs under ox-LDL treatment from a bioinformatics perspective, which may contribute to a better understanding of the pathophysiological mechanisms of foam cell formation. |
format | Online Article Text |
id | pubmed-10061454 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-100614542023-03-31 Identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis Xu, Jing Yang, Yuejin Ann Transl Med Original Article BACKGROUND: Atherosclerosis is an underlying cause of cardiovascular disease which is a leading cause of death worldwide. Foam cells play a crucial role in atherosclerotic lesion development, and macrophages and vascular smooth muscle cells (VSMCs) appear to contribute to the formation of the majority of atheromatous foam cells via oxidized low-density lipoprotein (ox-LDL) uptake. METHODS: An integrated, microarray-based analysis using GSE54666 and GSE68021, which contain samples of human macrophages and VSMCs incubated with ox-LDL, was conducted. The differentially expressed genes (DEGs) in each dataset were investigated via the linear models for microarray data (limma) v. 3.40.6 software package in R v. 4.1.2 (The R Foundation for Statistical Computing). Gene ontology (GO) and pathway enrichment were performed via the ClueGO v. 2.5.8 and CluePedia v. 1.5.8 databases and the Database of Annotation, Visualization and Integrated (DAVID; https://david.ncifcrf.gov). The convergent DEGs in the two cell types were obtained, and the protein interactions and network of transcriptional factors were analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) v. 11.5 and the Transcriptional Regulatory Relationships Unraveled by Sentence-based Text-mining (TRRUST) v. 2 databases. The selected DEGs were further validated using external data from GSE9874, and a machine learning algorithm of the least absolute shrinkage and selection operator (LASSO) regression and receiver operating characteristic (ROC) analysis were applied to explore the candidate biomarkers. RESULTS: We discovered the significant DEGs and pathways that were shared or unique among the 2 cell types, coupling with enriched lipid metabolism in macrophages, and upregulated defense response in VSMCs. Moreover, we identified BTG2, ABCA1, and SLC7A11 as potential biomarkers and molecular targets for atherogenesis. CONCLUSIONS: Our study provides a comprehensive summary of the landscape of the transcriptional regulations in macrophages and VSMCs under ox-LDL treatment from a bioinformatics perspective, which may contribute to a better understanding of the pathophysiological mechanisms of foam cell formation. AME Publishing Company 2023-02-24 2023-03-15 /pmc/articles/PMC10061454/ /pubmed/37007574 http://dx.doi.org/10.21037/atm-22-3761 Text en 2023 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Xu, Jing Yang, Yuejin Identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis |
title | Identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis |
title_full | Identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis |
title_fullStr | Identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis |
title_full_unstemmed | Identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis |
title_short | Identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis |
title_sort | identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10061454/ https://www.ncbi.nlm.nih.gov/pubmed/37007574 http://dx.doi.org/10.21037/atm-22-3761 |
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