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Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation [miRNA]

ABSTRACT: Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation [miRNA]

PROVIDER: PRJNA478484 | ENA |

REPOSITORIES: ENA

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Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation [miRNA]

Project description: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.

2018-06-29 | GSE113620 | GEO

Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation [RNA-seq]

2018-06-29 | GSE113619 | GEO

Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation

Project description:Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation

| PRJNA453497 | ENA

Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation

Project description:This SuperSeries is composed of the SubSeries listed below.

2018-06-29 | GSE113621 | GEO

Project description:Time series integrative analysis of RNA-Seq and miRNA expression data reveals key biologic pathways during keloid formation

| PRJNA448679 | ENA

Keloid Transcriptome

Project description:Keloid Transcriptome

| PRJNA901908 | ENA

HOXA11-AS regulates NIPAL3 via hsa-miRNA-19a-3p, hsa-miR-141-3p and hsa-miR-140-5p in keloid fibroblast: stepwise bioinformatical screen for an integrated molecular network [miRNA-Seq]

Project description:Purpose: To explore the potential integrated molecular network by long non-coding RNA HOXA11-AS in keloid fibroblast Methods: Using primary cultured keloid-derived fibroblasts (sample 0), small interfering RNAs were designed and transfected into two keloid fibroblast samples (samples 1 and 2) to knockdown HOXA11-AS. One nonspecific transfection control (sample 3) and one blank control (sample 4) were used to remove nonspecific overlap from the studied group. The lncRNAs, messenger RNAs (mRNAs), and microRNAs (miRNAs) of five samples were sequenced to identify differentially expressed (DE) profiles in HOXA11-AS-knockdown keloid fibroblasts in samples 1 and 2, which facilitated removal of overlap with the nonspecific controls (samples 3 and 4). Using stepwise bioinformatic analysis, DE lncRNA and mRNAs characterized by close and natural antisense relationship were constructed into an interactive network by bioinformatic analysis. Based on this network, a lncRNA–mRNA–protein interaction network was extended by integration of the human protein–protein interaction (PPI) network. The Page Rank algorithm was used to score each mRNA in the extended LMN network to reveal significant functioning genes. Next, screened genes were validated by real-time PCR and western blot ting. Validated genes were used to construct a competing endogenous network based on DE miRNA profiles. Results: SNED1, NIPAL3, and VTN were detected significantly changed in HOXA11-AS-knockdown keloid fibroblasts. Only NIPAL3 was predicted to be involved in an intergated network for HOXA11-AS via three competing endogenous miRNAs (hsa-miRNA-19a-3p, hsa-miR-141-3p, and hsa-miR-140- 5p). Conclusion: An interactive molecular network of HOXA11-AS–three miRNAs–NIPAL3 was predicted in keloid fibroblasts

2021-12-22 | GSE191266 | GEO

Quantitative proteomic analysis of keloid scars and normal skin tissues

Project description:Keloid scars is a pathologic fibro-proliferative disorders of the skin, which exhibit abnormal phenotypes including fibroblasts proliferation and collagen deposits. There have been several treatments of keloids including conventional surgical therapies and adjuvant therapies, but a high recurrence rate of keloids was also observed after treatment. Quantitative proteomics approach has been proved an efficient approach to investigate pathological mechanism and novel biomarkers. In this study, we present a label-free quantitative proteomics analysis to explore differential protein expression profiles in normal skin and keloid scar tissues based on nano-liquid chromatography and tandem mass spectrometry (Nano-LC–MS/MS). The study results displayed a more comprehensive keloid protein expression landscape and provided novel pathological insight of keloid.

2023-03-11 | PXD029631 | Pride

Gene expression profile of keloid tissue

Project description:Comparison of keloid to normal tissue Keywords: examination of keloid tissue

2005-07-16 | GSE2945 | GEO

site-specific gene expression profiling in keloid disease

Project description:Keloid disease (KD) is a fibroproliferative cutaneous tumour characterised by heterogeneity, excess collagen deposition and aggressive local invasion. Normal and keloid scar tissues were analysed with a site-specific in situ approach through combined laser capture microdissection, as well as whole tissue biopsy and monolayer cell culture techniques.

2017-12-07 | E-MTAB-4945 | biostudies-arrayexpress

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