Cargando…
Integrated bioinformatics analysis of core regulatory elements involved in keloid formation
BACKGROUND: Keloid is a benign fibro-proliferative dermal tumor formed by an abnormal scarring response to injury and characterized by excessive collagen accumulation and invasive growth. The mechanism of keloid formation has not been fully elucidated, especially during abnormal scarring. Here, we i...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487518/ https://www.ncbi.nlm.nih.gov/pubmed/34600545 http://dx.doi.org/10.1186/s12920-021-01087-7 |
_version_ | 1784577972173275136 |
---|---|
author | Li, Chuying Jin, Meitong Luo, Yinli Jin, Zhehu Pi, Longquan |
author_facet | Li, Chuying Jin, Meitong Luo, Yinli Jin, Zhehu Pi, Longquan |
author_sort | Li, Chuying |
collection | PubMed |
description | BACKGROUND: Keloid is a benign fibro-proliferative dermal tumor formed by an abnormal scarring response to injury and characterized by excessive collagen accumulation and invasive growth. The mechanism of keloid formation has not been fully elucidated, especially during abnormal scarring. Here, we investigated the regulatory genes, micro-RNAs (miRNAs) and transcription factors (TFs) that influence keloid development by comparing keloid and normal scar as well as keloid and normal skin. METHODS: Gene expression profiles (GSE7890, GSE92566, GSE44270 and GSE3189) of 5 normal scar samples, 10 normal skin samples and 18 keloid samples from the Gene Expression Omnibus (GEO) database were interrogated. Differentially expressed genes (DEGs) were identified between keloid and normal skin samples as well as keloid and normal scar samples with R Project for Statistical Computing. Gene Ontology (GO) functional enrichment analysis was also performed with R software. DEG-associated protein–protein interaction (PPI) network was constructed by STRING, followed by module selection from the PPI network based on the MCODE analysis. Regulatory relationships between TF/miRNA and target genes were predicted with miRnet and cytoscape. Core regulatory genes were verified by RT-qPCR. RESULTS: We identified 628 DEGs, of which 626 were up-regulated and 2 were down-regulated. Seven core genes [neuropeptide Y(NPY), 5-hydroxytryptamine receptor 1A(HTR1A), somatostatin (SST), adenylate cyclase 8 (ADCY8), neuromedin U receptor 1 (NMUR1), G protein subunit gamma 3 (GNG3), and G protein subunit gamma 13 (GNG13)] all belong to MCODE1 and were enriched in the “G protein coupled receptor signaling pathway” of the GO biological process category. Furthermore, nine core miRNAs (hsa-mir-124, hsa-let-7, hsa-mir-155, hsa-mir-26a, hsa-mir-941, hsa-mir-10b, hsa-mir-20, hsa-mir-31 and hsa-mir-372), and two core TFs (SP1 and TERT) were identified to play important roles in keloid formation. In the TF/miRNA-target gene network, both hsa-mir-372 and hsa-mir-20 had a regulatory effect on GNG13, ADCY8 was predicted to be target by hsa-mir-10b, and HTR1A and NPY were potentially by SP1. Furthermore, the expression of core regulatory genes (GNG13, ADCY8, HTR1A and NPY) was validated in clinical samples. CONCLUSIONS: GNG13, ADCY8, NPY and HTR1A may act as core genes in keloid formation and these core genes establish relationship with SP1 and miRNA (hsa-mir-372, hsa-mir-20, hsa-mir-10b), which may influence multiple signaling pathways in the pathogenesis of keloid. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-021-01087-7. |
format | Online Article Text |
id | pubmed-8487518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84875182021-10-04 Integrated bioinformatics analysis of core regulatory elements involved in keloid formation Li, Chuying Jin, Meitong Luo, Yinli Jin, Zhehu Pi, Longquan BMC Med Genomics Research Article BACKGROUND: Keloid is a benign fibro-proliferative dermal tumor formed by an abnormal scarring response to injury and characterized by excessive collagen accumulation and invasive growth. The mechanism of keloid formation has not been fully elucidated, especially during abnormal scarring. Here, we investigated the regulatory genes, micro-RNAs (miRNAs) and transcription factors (TFs) that influence keloid development by comparing keloid and normal scar as well as keloid and normal skin. METHODS: Gene expression profiles (GSE7890, GSE92566, GSE44270 and GSE3189) of 5 normal scar samples, 10 normal skin samples and 18 keloid samples from the Gene Expression Omnibus (GEO) database were interrogated. Differentially expressed genes (DEGs) were identified between keloid and normal skin samples as well as keloid and normal scar samples with R Project for Statistical Computing. Gene Ontology (GO) functional enrichment analysis was also performed with R software. DEG-associated protein–protein interaction (PPI) network was constructed by STRING, followed by module selection from the PPI network based on the MCODE analysis. Regulatory relationships between TF/miRNA and target genes were predicted with miRnet and cytoscape. Core regulatory genes were verified by RT-qPCR. RESULTS: We identified 628 DEGs, of which 626 were up-regulated and 2 were down-regulated. Seven core genes [neuropeptide Y(NPY), 5-hydroxytryptamine receptor 1A(HTR1A), somatostatin (SST), adenylate cyclase 8 (ADCY8), neuromedin U receptor 1 (NMUR1), G protein subunit gamma 3 (GNG3), and G protein subunit gamma 13 (GNG13)] all belong to MCODE1 and were enriched in the “G protein coupled receptor signaling pathway” of the GO biological process category. Furthermore, nine core miRNAs (hsa-mir-124, hsa-let-7, hsa-mir-155, hsa-mir-26a, hsa-mir-941, hsa-mir-10b, hsa-mir-20, hsa-mir-31 and hsa-mir-372), and two core TFs (SP1 and TERT) were identified to play important roles in keloid formation. In the TF/miRNA-target gene network, both hsa-mir-372 and hsa-mir-20 had a regulatory effect on GNG13, ADCY8 was predicted to be target by hsa-mir-10b, and HTR1A and NPY were potentially by SP1. Furthermore, the expression of core regulatory genes (GNG13, ADCY8, HTR1A and NPY) was validated in clinical samples. CONCLUSIONS: GNG13, ADCY8, NPY and HTR1A may act as core genes in keloid formation and these core genes establish relationship with SP1 and miRNA (hsa-mir-372, hsa-mir-20, hsa-mir-10b), which may influence multiple signaling pathways in the pathogenesis of keloid. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-021-01087-7. BioMed Central 2021-10-02 /pmc/articles/PMC8487518/ /pubmed/34600545 http://dx.doi.org/10.1186/s12920-021-01087-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Li, Chuying Jin, Meitong Luo, Yinli Jin, Zhehu Pi, Longquan Integrated bioinformatics analysis of core regulatory elements involved in keloid formation |
title | Integrated bioinformatics analysis of core regulatory elements involved in keloid formation |
title_full | Integrated bioinformatics analysis of core regulatory elements involved in keloid formation |
title_fullStr | Integrated bioinformatics analysis of core regulatory elements involved in keloid formation |
title_full_unstemmed | Integrated bioinformatics analysis of core regulatory elements involved in keloid formation |
title_short | Integrated bioinformatics analysis of core regulatory elements involved in keloid formation |
title_sort | integrated bioinformatics analysis of core regulatory elements involved in keloid formation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487518/ https://www.ncbi.nlm.nih.gov/pubmed/34600545 http://dx.doi.org/10.1186/s12920-021-01087-7 |
work_keys_str_mv | AT lichuying integratedbioinformaticsanalysisofcoreregulatoryelementsinvolvedinkeloidformation AT jinmeitong integratedbioinformaticsanalysisofcoreregulatoryelementsinvolvedinkeloidformation AT luoyinli integratedbioinformaticsanalysisofcoreregulatoryelementsinvolvedinkeloidformation AT jinzhehu integratedbioinformaticsanalysisofcoreregulatoryelementsinvolvedinkeloidformation AT pilongquan integratedbioinformaticsanalysisofcoreregulatoryelementsinvolvedinkeloidformation |