Objective: Keloid disease (KD) is a benign fibroproliferative skin tumor that results from abnormal wound healing and has no single definitive treatment. This study aims to identify KD biomarkers, which are cellular mediators that can serve as indicators of normal, pathological, and therapeutic processes.
Methods: Bioinformatics analytic approaches, including comprehensive literature searches and DAVID Bioinformatics Resources 2008, were performed on the established KD linkage and previously reported microarray data to identify potential candidate genes for the study. Keloid margins and unaffected skin were obtained from KD patients (n = 4). RNA was extracted from the biopsies and second-passage culture equivalents. Reverse-transcriptase quantitative polymerase chain reactions were used to determine the gene expression levels. Student t tests were used to analyze the statistical significance in differential gene expressions.
Results: Nineteen candidate genes were initially selected by bioinformatics analysis. Of the 19 genes, 10 were significantly (P < .05) upregulated in keloid margin biopsy specimens. The top-5 fold changes range from 10-fold to 175-fold, including aggrecan; asporin; inhibin, beta A; tumor necrosis factor-alpha inducible protein 6; and chromosome 5 open reading frame 13. There was no significant differential gene expression between the fibroblasts established using keloid margin or internal control sites.
Conclusions: The transcriptomic data generated from cultures did not consistently correlate to the biopsy equivalents. This study has demonstrated 10 genes that are significantly upregulated in biopsy samples of keloid margin, 5 of which have a fold change higher than 10-fold. Importantly these genes may serve as a potential biomarker for KD.