Transcriptome network analysis of inflammation and fibrosis in keloids
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA996549 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25339354.fastq.gz | Fastqsanger.gz | |||
| SRR25339355.fastq.gz | Fastqsanger.gz | |||
| SRR25339356.fastq.gz | Fastqsanger.gz | |||
| SRR25339357.fastq.gz | Fastqsanger.gz | |||
| SRR25339358.fastq.gz | Fastqsanger.gz |
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Project description:Background:Keloid (KL) is a common benign skin tumor. KL is typically characterized by significant fibrosis and an intensive inflammatory response. Therefore, a comprehensive understanding of the interactions between cellular inflammation and fibrotic cells is essential to elucidate the mechanisms driving the progression of KL and to develop therapeutics. Objective: Investigate the transcriptome landscape of inflammation and fibrosis in keloid scars. Methods: In this paper, we performed transcriptome sequencing and microRNA (miRNA) sequencing on unselected live cells from six human keloid tissues and normal skin tissues to elucidate a comprehensive transcriptome landscape. In addition, we used single-cell RNA sequencing (scRNA-seq) analysis to analyze intercellular communication networks and enrich fibroblast populations in two additional keloid and normal skin samples to study fibroblast diversity. Results: By RNA sequencing and a miRNA-mRNA-PPI network analysis, we identified miR-615-5p and miR-122b-3p as possible miRNAs associated with keloids, as they differed most significantly in keloids. Similarly, COL3A1, COL1A2, THBS2, TNC, IGTA, THBS4, TGFB3 as genes with significant differences in keloid may be associated with keloid development. Using single-cell RNA sequencing data from 24086 cells collected from normal or keloid, we report reconstructed intercellular signaling network analysis and aggregation to modules associated with specific cell subpopulations at the cellular level for keloid alterations. Conclusions: Our multitranscriptomic dataset delineates inflammatory and fibro heterogeneity of human keloids, underlining the importance of intercellular crosstalk between inflammatory cells and fibro cells and revealing potential therapeutic targets.
2024-09-30 | GSE237754 | GEO
Project description:Background:Keloid (KL) is a common benign skin tumor. KL is typically characterized by significant fibrosis and an intensive inflammatory response. Therefore, a comprehensive understanding of the interactions between cellular inflammation and fibrotic cells is essential to elucidate the mechanisms driving the progression of KL and to develop therapeutics. Objective: Investigate the transcriptome landscape of inflammation and fibrosis in keloid scars. Methods: In this paper, we performed transcriptome sequencing and microRNA (miRNA) sequencing on unselected live cells from six human keloid tissues and normal skin tissues to elucidate a comprehensive transcriptome landscape. In addition, we used single-cell RNA sequencing (scRNA-seq) analysis to analyze intercellular communication networks and enrich fibroblast populations in two additional keloid and normal skin samples to study fibroblast diversity. Results: By RNA sequencing and a miRNA-mRNA-PPI network analysis, we identified miR-615-5p and miR-122b-3p as possible miRNAs associated with keloids, as they differed most significantly in keloids. Similarly, COL3A1, COL1A2, THBS2, TNC, IGTA, THBS4, TGFB3 as genes with significant differences in keloid may be associated with keloid development. Using single-cell RNA sequencing data from 24086 cells collected from normal or keloid, we report reconstructed intercellular signaling network analysis and aggregation to modules associated with specific cell subpopulations at the cellular level for keloid alterations. Conclusions: Our multitranscriptomic dataset delineates inflammatory and fibro heterogeneity of human keloids, underlining the importance of intercellular crosstalk between inflammatory cells and fibro cells and revealing potential therapeutic targets.
2024-09-30 | GSE237753 | GEO
Project description:Background:Keloid (KL) is a common benign skin tumor. KL is typically characterized by significant fibrosis and an intensive inflammatory response. Therefore, a comprehensive understanding of the interactions between cellular inflammation and fibrotic cells is essential to elucidate the mechanisms driving the progression of KL and to develop therapeutics. Objective: Investigate the transcriptome landscape of inflammation and fibrosis in keloid scars. Methods: In this paper, we performed transcriptome sequencing and microRNA (miRNA) sequencing on unselected live cells from six human keloid tissues and normal skin tissues to elucidate a comprehensive transcriptome landscape. In addition, we used single-cell RNA sequencing (scRNA-seq) analysis to analyze intercellular communication networks and enrich fibroblast populations in two additional keloid and normal skin samples to study fibroblast diversity. Results: By RNA sequencing and a miRNA-mRNA-PPI network analysis, we identified miR-615-5p and miR-122b-3p as possible miRNAs associated with keloids, as they differed most significantly in keloids. Similarly, COL3A1, COL1A2, THBS2, TNC, IGTA, THBS4, TGFB3 as genes with significant differences in keloid may be associated with keloid development. Using single-cell RNA sequencing data from 24086 cells collected from normal or keloid, we report reconstructed intercellular signaling network analysis and aggregation to modules associated with specific cell subpopulations at the cellular level for keloid alterations. Conclusions: Our multitranscriptomic dataset delineates inflammatory and fibro heterogeneity of human keloids, underlining the importance of intercellular crosstalk between inflammatory cells and fibro cells and revealing potential therapeutic targets.
2024-09-30 | GSE237752 | GEO
Project description:Transcriptome network analysis of inflammation and fibrosis in keloids [miRNA-seq]
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Project description:Transcriptome network analysis of inflammation and fibrosis in keloids [scRNA-seq]
| PRJNA996555 | ENA
Project description:Transcriptome network analysis of inflammation and fibrosis in keloids [mRNA-seq]
| PRJNA996551 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below.
2024-09-30 | GSE237755 | GEO
Project description:We previously observed reduced graft survival for kidney transplants having interstitial fibrosis with subclinical inflammation, but not fibrosis alone, on 1-year protocol biopsy. The current study aimed to determine whether fibrosis with inflammation at 1 year is associated with renal functional decline in a low-risk transplant cohort and to characterize the nature of the inflammation. Subjects were living-donor, tacrolimus/mycophenolate-treated transplant recipients without overt risk factors for reduced graft survival (n=151). Transplants with normal histology (n=86) or fibrosis alone (n=45) on 1-year protocol biopsy had stable renal function between 1 and 5 years, while those having fibrosis with inflammation (n=20) had declining glomerular filtration rate and reduced graft survival. Immunohistochemistry confirmed increased interstitial T-cells and macrophages/dendritic cells in the fibrosis with inflammation group. Gene expression was performed on a subset of biopsies in each group and demonstrated increased expression of transcripts related to innate and cognate immunity in transplants having fibrosis with inflammation. Pathway- and pathological process-specific analyses of microarray profiles revealed that, in fibrosis with inflammation, over-expressed transcripts were enriched for potentially damaging immunological activities including Toll-like receptor signaling, antigen presentation/dendritic cell maturation, interferon gamma-inducible response, cytotoxic T lymphocyte-associated and acute rejection-associated genes. Thus, fibrosis with inflammation in 1-year protocol biopsies is associated with reduced graft survival and function and with a rejection-like gene expression signature even in recipients with no clinical risk for inferior outcome. Early interventions aimed at altering rejection-like inflammation may favor improved long-term KTx survival. We analyzed gene expression from a group of 65 renal transplant recipients. Patient groups were carefully selected to include patients on the same immunosuppression (Prograf-MMF-Pred), transplant type (LD), absence of over post-transplant complications (AR, BK, DGF). For each patient a 1 year protocol biopsy was examined by conventional histology and gene expression. By histology the patients were categorized as histologically normal (n=25, i/cg/ci=0), IF/TA (n=24, i/cg=0, ci>0) and IFTA+i (n=16, cg=0, i/ci>0). This dataset is part of the TransQST collection.
2010-11-01 | E-GEOD-22459 | biostudies-arrayexpress
Project description:To uncover the underlying pathophysiology of keloids, we used two technologies, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST). we focused on the molecular signature of keloids. In this study, we provide the comprehensive transcriptomic atlas of keloids and its matched spatial information, essential to understanding intercellular crosstalk in the skin microenvironments.
2022-01-21 | GSE181297 | GEO
Project description:Fibrosis is a leading cause of deaths in industrialized countries and has no effective therapy. We demonstrated that blockade of OX40L prevented inflammation-driven fibrosis affecting the skin and the lungs and promotes regression of established dermal fibrosis in different murine models. To characterize the pathways involved in the protection of skin fibrosis and affected by OX40L blocking, we used microarrays and identified distinct genes differentially expressed between ox40l+/+ and ox40l-/- in the bleomycin-induced dermal fibrosis mouse model. Total RNA were extracted from lesional skin samples of 3 ox40l+/+ and 4 ox40l-/- male mice aged 9 weeks treated with bleomycin for 3 weeks, and were hybridized on Affymetrix microarrays.
2016-08-09 | E-GEOD-73705 | biostudies-arrayexpress