Identification of a transcriptional signature for the wound healing continuum.
Bottom Line: Central to these outcomes is the role of the fibroblast.Genes whose expression increases following serum exposure in the order OMF < NF < CWF are candidates for a negative/impaired healing phenotype (the dysfunctional healing group), whereas genes with the converse pattern are potentially associated with a positive/preferential healing phenotype (the enhanced healing group).Sixty-six genes in the enhanced healing group and 38 genes in the dysfunctional healing group were identified.
Affiliation: Wound Biology Group, Cardiff Institute of Tissue Engineering and Repair, Tissue Engineering and Reparative Dentistry, School of Dentistry.Show MeSH
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Mentions: The aim of the continuum analysis was to identify serum responsive genes whose expression were found to be either greatest in OMF and decreased in NF1 and NF2 to CWF, or conversely were lowest in OMF and then showed increased levels in NF1 and NF2 to CWF. Each of the ∼22,000 probe sets was analyzed individually. For each probe set, all 112 possible subsets were selected that comprised the matched 0-hour and 6-hour data for one OMF, one NF, and one CWF sample. Each subset was then assessed for its “compliance/fit” with a series of hypothetical gene profiles reflective of either enhanced wound healing (Figure 2, top) or dysfunctional wound healing (Figure 2, bottom). A subset was scored as having a “continuum pattern” if it matched the following criteria. First, there was a minimum of a twofold change in expression level in response to serum in the NF pair and either or both of the CWF and OMF. Second, a correlation coefficient of 0.7 or greater to one of the hypothetical profiles was required. The direction of the continuum gradient was defined as either increasing (OMF < NF < CWF) or decreasing (OMF > NF > CWF). For each probe set, the number of the 112 subsets where the data were scored as matching the continuum was recorded. Statistical probability was then determined by a permutation-based test where 10,000 random subsets were created for each probe set, each made by selecting three random 0-hour/6-hour pairs but ignoring the tissue type. For each probe set, the number of times it was scored as a continuum gene in the 112 subsets was then compared with the number of times it was scored as a continuum gene in the 10,000 random subsets. A p-value was then generated using a chi-square test. Probe sets with a false discovery rate (FDR) corrected p-value of <0.05 were selected. These probes were then annotated and analyzed by overrepresentation analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID) version 6.7 (http://www.david.abcc.ncifcrf.gov). Gene Ontology (GO) biological process (GOTERM_BP_ALL) categories that were identified (p < 0.05) as overrepresented were then ranked by Expression Analysis of Systematic Explorer (EASE) score. Probe sets were then classified as having an ascending or descending pattern based on being in a particular group when at least one quarter of the samplings matched for one or more of the continuums (continuum patterns as laid out in Figure 2), resulting in the final enhanced healing and dysfunctional healing gene sets.
Affiliation: Wound Biology Group, Cardiff Institute of Tissue Engineering and Repair, Tissue Engineering and Reparative Dentistry, School of Dentistry.