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| Status |
Public on Jun 29, 2018 |
| Title |
Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation [miRNA] |
| Platform organism |
synthetic construct |
| Sample organism |
Homo sapiens |
| Experiment type |
Non-coding RNA profiling by array
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| Summary |
Keloids represent a common form of exaggerated wound scarring that cause considerable morbidity. Moreover, there are limited data on molecular mechanisms underlying keloids and effective therapies are lacking. To gain new insight in the transcriptomic alterations of wound healing in keloid-prone individuals, we followed an integrative approach of RNA-Seq and miRNA expression data analysis in serial skin biopsies of the same site (baseline and six weeks after wounding) in keloid-prone (n=8) and healthy matched control individuals (n=6). Bioinformatic analysis identified 37 miRNAs and 1449 genes that are differentially expressed specifically in keloid-prone individuals during wound healing. Pathway enrichment analysis was undertaken in the RNA-Seq data and identified NOTCH signaling, MAPK signaling, and Toll-like receptor pathways to be altered in keloid-prone individuals after wounding. In addition, dysregulation of DNA repair, p53 signalling and metabolic pathways (RNA, protein, fructose, mannose and glycerophospholipid metabolism) was highlighted during keloid formation. Gene association network analysis demonstrated divergent average expression profiles of cytokine signaling genes, as well as lipid metabolism genes between keloid-prone and healthy individuals during wound healing. In summary, our study provides a comprehensive and integrative analysis of the keloid transcriptome and miRNAome and highlights biological pathways that feature during keloid formation.
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| Overall design |
miRNA gene expression profiling skin biopsies at baseline and 6 weeks after wounding in keloid-prone and healthy individuals.
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| Contributor(s) |
Onoufriadis A, Hsu C, Ainali C, Ung CY, Rashidghamat E, Yang H, Huang H, Niazi U, Yang J, Nuamah R, Saxena A, de Rinaldis E, McGrath JA |
| Citation(s) |
29870686 |
| |
| Submission date |
Apr 24, 2018 |
| Last update date |
Dec 05, 2018 |
| Contact name |
John Alexander McGrath |
| E-mail(s) |
john.mcgrath@kcl.ac.uk
|
| Organization name |
King's College London
|
| Department |
St John's Institute of Dermatology
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| Lab |
St John's Institute of Dermatology
|
| Street address |
Great Maze Pond
|
| City |
London |
| ZIP/Postal code |
SE1 9RT |
| Country |
United Kingdom |
| |
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| Platforms (1) |
| GPL19117 |
[miRNA-4] Affymetrix Multispecies miRNA-4 Array |
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| Samples (27)
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| This SubSeries is part of SuperSeries: |
| GSE113621 |
Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation |
|
| Relations |
| BioProject |
PRJNA478484 |
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