Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Jul 25:13:929293.
doi: 10.3389/fgene.2022.929293. eCollection 2022.

Identification of novel biomarkers in septic cardiomyopathy via integrated bioinformatics analysis and experimental validation

Feng Lu  1 , Feng Hu  2 , Baiquan Qiu  1 , Hongpeng Zou  1 , Jianjun Xu  1
Affiliations

Identification of novel biomarkers in septic cardiomyopathy via integrated bioinformatics analysis and experimental validation

Feng Lu et al. Front Genet. .

Abstract

Purpose: Septic cardiomyopathy (SCM) is an important world public health problem with high morbidity and mortality. It is necessary to identify SCM biomarkers at the genetic level to identify new therapeutic targets and strategies. Method: DEGs in SCM were identified by comprehensive bioinformatics analysis of microarray datasets (GSE53007 and GSE79962) downloaded from the GEO database. Subsequently, bioinformatics analysis was used to conduct an in-depth exploration of DEGs, including GO and KEGG pathway enrichment analysis, PPI network construction, and key gene identification. The top ten Hub genes were identified, and then the SCM model was constructed by treating HL-1 cells and AC16 cells with LPS, and these top ten Hub genes were examined using qPCR. Result: STAT3, SOCS3, CCL2, IL1R2, JUNB, S100A9, OSMR, ZFP36, and HAMP were significantly elevated in the established SCM cells model. Conclusion: After bioinformatics analysis and experimental verification, it was demonstrated that STAT3, SOCS3, CCL2, IL1R2, JUNB, S100A9, OSMR, ZFP36, and HAMP might play important roles in SCM.

Keywords: biomarkers; differentially expressed genes; integrated bioinformatics analysis; sepsis; septic cardiomyopathy.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Analysis of DEGs. (A) Volcano map of DEGs based on GSE53007 (|logFC|>1, p. adj<0.05). (B) Heatmap of DEGs for GSE53007. (C) Volcano map of DEGs based on GSE79962 (|logFC|>1, p. adj<0.05). (D) Heatmap of DEGs for GSE79962.
FIGURE 2
FIGURE 2
Venn diagram of overlapping upregulated DEGs of GSE53007 and GSE79962. (A) Two datasets overlapping upregulated DEGs. (B) Two datasets overlapping downregulated DEGs.
FIGURE 3
FIGURE 3
GO enrichment analysis and the KEGG pathway enrichment analysis of DEGs.
FIGURE 4
FIGURE 4
PPI network of DEGs constructed using Cytoscape. (A) PPI network containing 23 nodes and 24 edges constructed based on the STRING online database and visualized using Cytoscape. (B) The most significant genes obtained from the PPI network.
FIGURE 5
FIGURE 5
Results of Quantitative real-time PCR experiments for the top ten genes (*<0.05, **<0.01, ***<0.001). (A) Expression of Hub gene in HL-1 cells. (B) Expression of Hub gene in AC16 cells.
See this image and copyright information in PMC

References

    1. Alkhateeb T., Kumbhare A., Bah I., Youssef D., Yao Z. Q., McCall C. E., et al. (2019). S100A9 maintains myeloid-derived suppressor cells in chronic sepsis by inducing miR-21 and miR-181b. Mol. Immunol. 112, 72–81. 10.1016/j.molimm.2019.04.019 - DOI - PMC - PubMed
    1. Beesley S. J., Weber G., Sarge T., Nikravan S., Grissom C. K., Lanspa M. J., et al. (2018). Septic cardiomyopathy. Crit. Care Med. 46 (4), 625–634. 10.1097/CCM.0000000000002851 - DOI - PubMed
    1. Canales R. D., Luo Y., Willey J. C., Austermiller B., Barbacioru C. C., Boysen C., et al. (2006). Evaluation of DNA microarray results with quantitative gene expression platforms. Nat. Biotechnol. 24 (9), 1115–1122. 10.1038/nbt1236 - DOI - PubMed
    1. Chen L., Long X., Xu Q., Tan J., Wang G., Cao Y., et al. (2020a). Elevated serum levels of S100A8/A9 and HMGB1 at hospital admission are correlated with inferior clinical outcomes in COVID-19 patients.Research Support, Non-U.S. Gov't]. J. Artic. Mol. Immunol. 17 (9), 992–994. 10.1038/s41423-020-0492-x - DOI - PMC - PubMed
    1. Chen M., Kong C., Zheng Z., Li Y. (2020b). Identification of biomarkers associated with septic cardiomyopathy based on bioinformatics analyses. J. Comput. Biol. 27 (1), 69–80. 10.1089/cmb.2019.0181 - DOI - PubMed