Screening and bioinformatics analysis of differentially expressed genes in hyperplastic scar.
- Author:
Yanghong HU
1
,
2
;
Yangliu HU
;
Dewu LIU
;
Jianxing YU
;
Deming LIU
Author Information
- Publication Type:Journal Article
- MeSH: Cicatrix; genetics; Cluster Analysis; Computational Biology; Down-Regulation; Gene Expression Profiling; Humans; Oligonucleotide Array Sequence Analysis; Signal Transduction; Transcriptome; Up-Regulation
- From: Journal of Southern Medical University 2014;34(7):939-944
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo screen differentially expressed genes in hyperplastic scar to explore the pathogenesis of hyperplastic scar and identify new therapeutic targets.
METHODSThree pairs of surgical specimens of hyperplastic scar and adjacent normal skin tissues were collected to investigate the differentially expressed genes in hyperplastic scar using Agilent gene oligonucletide microarray and clustering analysis. DAVID Bioinformatics Resources 6.7 was used for GO analysis and pathway analysis.
RESULTS AND CONCLUSIONDistinctly different gene expression profiles were found between hyperplastic scar tissues and normal skin tissues. Compared with normal skin tissue, hyperplastic scar tissues showed 3142 up-regulated and 2984 down-regulated genes by two folds and 28 up-regulated and 44 down-regulated genes by 5 folds after repeating the experiment once; after repeating the experiment twice, 3004 genes were found up-regulated and 3038 down-regulated by 2 folds and 25 up-regulated and 38 down-regulated by 5 folds in hyperplastic scars. In all the 3 specimens, 1920 genes were up-regulated and 1912 down-regulated by 2 folds and 18 up-regulated and 29 down-regulated by 5 folds. The dysregulated genes in hyperplastic scar were involved in cell cycles, cell proliferation, immune response and cell adhesion (CDKN1C, CDKN2A, CTNNA3, COL6A3, and HOXB4) and in signaling pathway of focal adhesion, TGF-beta signaling pathway, p53 signaling pathway, cell cycle, and tumor-associated pathways (TGFβ1, CDKN1C, CDKN2A, CDC14A , ITGB6, and EGF).