Dataset Information

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

ABSTRACT: This study aimed to identify long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) differentially expressed (DE) during keloid formation, predict DElncRNA-DEmiRNA-DEmRNA interactions, and construct a competing endogenous RNA (ceRNA) network through secondary data mining of keloid-related sequencing and microarray data in the open-source Gene Expression Omnibus (GEO) database. The GSE113621 dataset was downloaded from the GEO database, |log₂FC|>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.

SUBMITTER: Deng Y

PROVIDER: S-EPMC7803517 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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

Deng Yu Y Xu Yangbin Y Xu Shuqia S Zhang Yujing Y Han Bing B Liu Zheng Z Liu Xiangxia X Zhu Zhaowei Z

Aging 20201116 24

This study aimed to identify long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) differentially expressed (DE) during keloid formation, predict DElncRNA-DEmiRNA-DEmRNA interactions, and construct a competing endogenous RNA (ceRNA) network through secondary data mining of keloid-related sequencing and microarray data in the open-source Gene Expression Omnibus (GEO) database. The GSE113621 dataset was downloaded from the GEO database, |log<sub>2</sub>FC|>1 and p<0.05 wer ...[more]

PMID: 33203788

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Dataset Information

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

Publications

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

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