AUTHOR=Zhang Zexin , He Yan , Lin Rongjie , Lan Junhong , Fan Yueying , Wang Peng , Jia Chiyu 

TITLE=Identification of Important Modules and Biomarkers That Are Related to Immune Infiltration Cells in Severe Burns Based on Weighted Gene Co-Expression Network Analysis

JOURNAL=Frontiers in Genetics

VOLUME=13

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.908510

DOI=10.3389/fgene.2022.908510

ISSN=1664-8021

ABSTRACT=<p><bold>Background:</bold> Immunosuppression is an important trigger for infection and a significant cause of death in patients with severe burns. Nevertheless, the prognostic value of immune-related genes remains unclear. This study aimed to identify the biomarkers related to immunosuppression in severe burns.</p><p><bold>Methods:</bold> The gene expression profile and clinical data of 185 burn and 75 healthy samples were obtained from the GEO database. Immune infiltration analysis and gene set variation analysis were utilized to identify the disorder of circulating immune cells. A weighted gene co-expression network analysis (WGCNA) was carried out to select immune-related gene modules. Enrichment analysis and protein–protein interaction (PPI) network were performed to select hub genes. Next, LASSO and logistic regression were utilized to construct the hazard regression model with a survival state. Finally, we investigated the correlation between high- and low-risk patients in total burn surface area (TBSA), age, and inhalation injury.</p><p><bold>Results:</bold> Gene set variation analysis (GSVA) and immune infiltration analysis showed that neutrophils increased and T cells decreased in severe burns. In WGCNA, four modular differently expressed in burns and controls were related to immune cells. Based on PPI and enrichment analysis, 210 immune-related genes were identified, mainly involved in T-cell inhibition and neutrophil activation. In LASSO and logistic regression, we screened out key genes, including <italic>LCK, SKAP1</italic> and <italic>GZMB,</italic> and <italic>LY9</italic>. In the ROC analysis, the area under the curve (AUC) of key genes was 0.945, indicating that the key genes had excellent diagnostic value. Finally, we discovered that the key genes were related to T cells, and the regression model performed well when accompanied by TBSA and age.</p><p><bold>Conclusion:</bold> We identified LCK, SKAP1, GZMB, and LY9 as good prognostic biomarkers that may play a role in post-burn immunosuppression against T-cell dysfunction and as potential immunotherapeutic targets for transformed T-cell dysfunction.</p>