A Time-Series Analysis of Severe Burned Injury of Skin Gene Expression Profiles

Abstract

Background/Aims: Major burn injury is one of the main severe forms of wound which lead to a mass of clinical debilitation, this study was to identify core biomarkers for the recovery of severe burned injury. Methods: Gene expression profiles (GSE19743) from the Gene Expression Omnibus (GEO) was downloaded, followed by background correction, normalization of raw microarray dataset and identification of differential expression genes (DEGs) . Soft clustering of DEGs was used for the screening of gene clusters that with sustained increasing (SIG) and decreasing expression (SDG) profiles along with the recovery process of burned injury. The significantly enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of SIGs and SDGs were obtained through the Database for Annotation, Visualization, and Integrated Discovery (DAVID), based on which the miRNA-gene regulation network for SIGs and SDGs were constructed from the miRWalk database. Results: Ten clusters were obtained through soft clustering. The SIGs and SDGs were found to be closely associated with the biological processes of immune system. The miRNA-gene regulation network analysis suggested different roles between SIGs and SDGs in the recovery of severe burned injury. Furthermore, a bunch of important biomarkers were identified, which would be helpful in the treatment of burned patients. Conclusion: Our current findings suggest an interesting molecular link between transcriptional regulation potentially involved in immunosuppressive state after major burn injury, which warrants further exploration for their utilization in the treatment of major burn injury.

Keywords

• Geo
• Burned
• Soft clustering
• DAVID
• R