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A Study on the Expression of Messenger RNAs and Long Noncoding RNA in Keloid Fibroblasts Based on Gene Expression Omnibus Microarray Data Mining.
Journal of Craniofacial Surgery 2022 August 18
OBJECTIVE: The purpose of this study was to find the coding RNA [messenger RNA (mRNA)] and long noncoding RNA (lncRNA) expressed in keloid through the analysis of Gene Expression Omnibus microarray chip of keloid fibroblasts.
MATERIALS AND METHODS: Gene Expression Omnibus database GSE7890 database was downloaded with selection of keloids and normal scar group data. The data were analyzed by R language combined with online database. The log2FC>1, P value <0.01 was chosen as screening criteria, and the differentially expressed mRNAs were screened for GO and KEGG function analysis.
RESULTS: One hundred fifty-five mRNA expression in the keloid group was significantly different from that in the normal group, including 31 groups with upregulated mRNA expression and 124 groups with down-regulated mRNA expression. Meanwhile, 8 lncRNAs were changed in the keloid group, including 3 upregulated (Rp11-420a23.1, Rp11-522b15.3, and Rp11-706j10.1) and 5 down-regulated (LINC00511, LINC00327, Hoxb-as3, Rp11-385n17.1, and Rp3-428l16.2). Quantitative polymerase chain reaction analysis of DElncRNAs in keloid fibroblasts showed that the expression of all DElncRNAs except for RP11-385N17.1 was increased in the keloid group compared with the control group. Moreover, the differences in LINC00511 and RP11-706J10.1 were statistically significant.
CONCLUSION: The noncoding RNA information of Gene Expression Omnibus chip data can be deeply mined through bioinformatics, and the potential epigenomic mechanism affecting keloid formation can be found from the existing database.
MATERIALS AND METHODS: Gene Expression Omnibus database GSE7890 database was downloaded with selection of keloids and normal scar group data. The data were analyzed by R language combined with online database. The log2FC>1, P value <0.01 was chosen as screening criteria, and the differentially expressed mRNAs were screened for GO and KEGG function analysis.
RESULTS: One hundred fifty-five mRNA expression in the keloid group was significantly different from that in the normal group, including 31 groups with upregulated mRNA expression and 124 groups with down-regulated mRNA expression. Meanwhile, 8 lncRNAs were changed in the keloid group, including 3 upregulated (Rp11-420a23.1, Rp11-522b15.3, and Rp11-706j10.1) and 5 down-regulated (LINC00511, LINC00327, Hoxb-as3, Rp11-385n17.1, and Rp3-428l16.2). Quantitative polymerase chain reaction analysis of DElncRNAs in keloid fibroblasts showed that the expression of all DElncRNAs except for RP11-385N17.1 was increased in the keloid group compared with the control group. Moreover, the differences in LINC00511 and RP11-706J10.1 were statistically significant.
CONCLUSION: The noncoding RNA information of Gene Expression Omnibus chip data can be deeply mined through bioinformatics, and the potential epigenomic mechanism affecting keloid formation can be found from the existing database.
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