title: Transcriptomic response of murine liver to severe injury and hemorrhagic shock: a dual-platform microarray analysis.
abstract: Trauma-hemorrhagic shock (HS/T) is a complex process that elicits numerous molecular pathways. We hypothesized that a dual-platform microarray analysis of the liver, an organ that integrates immunology and metabolism, would reveal key pathways engaged following HS/T. C57BL/6 mice were divided into five groups (n = 4/group), anesthetized, and surgically treated to simulate a time course and trauma severity model: 1) nonmanipulated animals, 2) minor trauma, 3) 1.5 h of hemorrhagic shock and severe trauma (HS/T), 4) 1.5 h HS/T followed by 1 h resuscitation (HS/T+1.0R), 5) 1.5 h HS/T followed by 4.5 h resuscitation (HS/T+4.5R). Liver RNA was hybridized to CodeLink and Affymetrix mouse whole genome microarray chips. Common genes with a cross-platform correlation >0.6 (2,353 genes in total) were clustered using k-means clustering, and clusters were analyzed using Ingenuity Pathways Analysis. Genes involved in the stress response and immunoregulation were upregulated early and remained upregulated throughout the course of the experiment. Genes involved in cell death and inflammatory pathways were upregulated in a linear fashion with elapsed time and in severe injury compared with minor trauma. Three of the six clusters contained genes involved in metabolic function; these were downregulated with elapsed time. Transcripts involved in amino acid metabolism as well as signaling pathways associated with glucocorticoid receptors, IL-6, IL-10, and the acute phase response were elevated in a severity-dependent manner. This is the first study to examine the postinjury response using dual-platform microarray analysis, revealing responses that may enable novel therapies or diagnostics.
authors.affiliation: Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
authors.forename: Rebecca D
authors.initials: RD
authors.lastname: Edmonds
authors.forename: Yoram
authors.initials: Y
authors.lastname: Vodovotz
authors.forename: Claudio
authors.initials: C
authors.lastname: Lagoa
authors.forename: Joyeeta
authors.initials: J
authors.lastname: Dutta-Moscato
authors.forename: Yawching
authors.initials: Y
authors.lastname: Yang
authors.forename: Mitchell P
authors.initials: MP
authors.lastname: Fink
authors.forename: Ryan M
authors.initials: RM
authors.lastname: Levy
authors.forename: Jose M
authors.initials: JM
authors.lastname: Prince
authors.forename: David J
authors.initials: DJ
authors.lastname: Kaczorowski
authors.forename: George C
authors.initials: GC
authors.lastname: Tseng
authors.forename: Timothy R
authors.initials: TR
authors.lastname: Billiar
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D015415:Biomarkers / Q000378:metabolism; D016000:Cluster Analysis; D004195:Disease Models, Animal; D053263:Gene Regulatory Networks / Q000235:genetics; D008099:Liver / Q000293:injuries* / Q000378:metabolism* / Q000473:pathology; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D005810:Multigene Family / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D011786:Quality Control; D012771:Shock, Hemorrhagic / Q000235:genetics* / Q000473:pathology*; D015398:Signal Transduction / Q000235:genetics; D013997:Time Factors; D059467:Transcriptome / Q000235:genetics*; D016159:Tumor Suppressor Protein p53 / Q000235:genetics
chemical_list: D015415:Biomarkers; D016159:Tumor Suppressor Protein p53