Bioinformatics-Led Identification of Potential Biomarkers and Inflammatory Infiltrates in Burn Injury

Abstract Burn injury is a life-threatening disease with a poor prognosis. The immune change and underlying mechanisms remain largely unknown. Thus, this study aims to find potential biomarkers and analyze the immune infiltrates after burn injury. Gene expression data of burn patients were obtained from the Gene Expression Omnibus database. Key immune-related genes (IRGs) were screened by differential and least absolute shrinkage and selection operator (LASSO) regression analysis. Based on key IRGs, patients were divided into two clusters by consensus cluster analysis. Immune infiltration was analyzed by the single sample gene set enrichment analysis (GSEA) method and the immune score was calculated by the principal component analysis method. A nomogram model was constructed based on the calculated immune score and clinical features. Finally, the expression of screened key genes was validated by an external cohort and quantitative polymerase chain reaction experiment. Fifty-nine IRGs were differently expressed in burn patients. After LASSO regression analysis, 12 key genes remained, namely AZU1, OLR1, RNASE2, FGF13, NR1D2, NR2E1, TLR5, CAMP, DEFA4, PGLYRP1, CTSG, and CCR3. Then, patients were divided into two clusters. Immune infiltration analysis revealed that more immune cells were infiltrated and more pathways were activated in cluster A, in which patients showed high immune scores. Finally, a nomogram model was constructed and showed high accuracy and reliability. The expression pattern of 12 key genes in an external cohort and clinical samples was in accordance with the theoretical analysis results. In conclusion, this research elucidated the key role of immune response in burns and could be used as a guide for burn treatment.