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Secondary data mining of GEO database for long non-coding RNA and Competing endogenous RNA network in keloid-prone individuals

Yu Deng, Yangbin Xu, Shuqia Xu, Yujing Zhang, Bing Han, Zheng Liu, Xiangxia Liu, Zhaowei Zhu

2020Aging18 citationsDOIOpen Access PDF

Abstract

FC|>1 and p<0.05 were set as screening criteria, genes expressed only in keloid-prone individuals were selected as research objects, and DEmRNAs, DElncRNAs, and DEmiRNAs before injury and 6 weeks after injury were screened. A Pearson correlation coefficient (PCC) of > 0.95 was selected as the index to predict the targeting relationships among lncRNAs, miRNAs, and mRNAs; and a network diagram was constructed using Cytoscape. The expression of 2356 lncRNAs was changed in the keloid-prone group-1306 were upregulated and 1050 were downregulated. Six lncRNAs, namely, 2 upregulated (DLEU2 and AP000317.2) and 4 downregulated (ADIRF-AS1, AC006333.2, AL137127.1 and LINC01725) lncRNAs, were expressed only in the keloid-prone group and were used to construct a ceRNA network. DLEU2 may regulate fibroblast proliferation, differentiation, and apoptosis through hsa-miR-30a-5p/hsa-miR-30b-5p. In-depth mining of GEO data indicated that lncRNAs and a ceRNA regulatory network participate in the wound healing process in keloid-prone individuals, possibly providing novel intervention targets and treatment options for keloid scars.

Topics & Concepts

RNALong non-coding RNANon-coding RNACoding (social sciences)Competing endogenous RNAComputer scienceComputational biologyBiologyGeneticsGeneStatisticsMathematicsCancer-related molecular mechanisms research
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