title: Construction of an immunorelated protein-protein interaction network for clarifying the mechanism of burn.
abstract: OBJECTIVE
  Severe burn is known to induce a series of pathological responses resulting in increased susceptibility to systemic inflammatory response and multiple organ failure, but the underlying molecular mechanism remains unclear at present. The main aim of this study was to expand our understanding of the events leading to circulating leukocyte response after burn by subjecting the gene expression profiles to a bioinformatic analysis.
  
  
  METHODS
  Comprehensive gene expression analysis was performed to identify differentially expressed genes (DEGs) using the expression profile GSE7404 (Mus musculus, circulating leukocyte, 25% of total body surface area (TBSA), full thickness) downloaded from the Gene Expression Omnibus, followed by the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In addition, a postburn protein-protein interaction (PPI) network was constructed to identify potential biomarkers.
  
  
  RESULTS
  Maximum changes in the gene expression profile were detected 1 day post burn. Separate Gene Ontology (GO) functional enrichment analysis for upregulated and downregulated DEGs revealed significant alterations of genes related to biological process such as "response to stimuli," "metabolic," "cellular and immune system processes," "biological regulation," and "death" in the leukocyte transcriptome after the burn. The KEGG pathway enrichment analysis showed that the upregulated DEGs were significantly enriched in the nodes of immunorelated and signal transduction-related pathways, and the downregulated genes were significantly enriched for the immunorelated pathways. The PPI network and module analysis revealed that, 1 day after the burn, lymphocyte-specific protein tyrosine kinase (Lck) (downregulated), Jun (upregulated), Cd19 (downregulated), Stat1 (downregulated), and Cdk1 (upregulated) were located centrally in both the PPI network and modules.
  
  
  CONCLUSIONS
  Based on an integrated bioinformatic analysis, we concluded that Lck, Jun, Cd19, Stat1, and Cdk1 may be critical 1 day after the burn. These findings expand our understanding of the molecular mechanisms of this important pathological process. Further studies are needed to support our work, focused on identifying candidate biomarkers with sufficient predictive power to act as prognostic and therapeutic biomarkers for burn injury.
authors.affiliation: Department of Burns, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
authors.forename: Yanbin
authors.initials: Y
authors.lastname: Gao
authors.affiliation: Department of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
authors.forename: Wenqing
authors.initials: W
authors.lastname: Nai
authors.affiliation: Department of Burns, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China. Electronic address: yuanyang@fimmu.com.
authors.forename: Lei
authors.initials: L
authors.lastname: Yang
authors.affiliation: Department of Burns, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
authors.forename: Zhiyang
authors.initials: Z
authors.lastname: Lu
authors.affiliation: Department of Burns, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
authors.forename: Pengwei
authors.initials: P
authors.lastname: Shi
authors.affiliation: Department of Burns, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Jin
authors.affiliation: Department of Burns, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
authors.forename: Huangding
authors.initials: H
authors.lastname: Wen
authors.affiliation: Department of Burns, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
authors.forename: Guifang
authors.initials: G
authors.lastname: Wang
mesh_terms: D000818:Animals; D018941:Antigens, CD19 / Q000235:genetics; D002056:Burns / Q000235:genetics* / Q000276:immunology / Q000378:metabolism; D019295:Computational Biology; D018844:Cyclin-Dependent Kinases / Q000235:genetics; D016208:Databases, Factual; D015536:Down-Regulation; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000235:genetics / Q000276:immunology; D016758:Genes, jun / Q000235:genetics; D019860:Lymphocyte Specific Protein Tyrosine Kinase p56(lck) / Q000235:genetics; D051379:Mice; D046228:Microarray Analysis; D060066:Protein Interaction Maps; D050794:STAT1 Transcription Factor / Q000235:genetics; D015398:Signal Transduction; D059467:Transcriptome; D015854:Up-Regulation
chemical_list: D018941:Antigens, CD19; C000604812:CD19 antigen, mouse; D050794:STAT1 Transcription Factor; C494080:Stat1 protein, mouse; D019860:Lymphocyte Specific Protein Tyrosine Kinase p56(lck); D018844:Cyclin-Dependent Kinases
keywords: Burn; Differentially expressed genes; Functional enrichment analysis; Protein–protein interaction