Transcriptome network analysis of inflammation and fibrosis in keloids [scRNA-seq]
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA996555 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25339558_1.fastq.gz | Fastqsanger.gz | |||
| SRR25339558_2.fastq.gz | Fastqsanger.gz | |||
| SRR25339559_1.fastq.gz | Fastqsanger.gz | |||
| SRR25339559_2.fastq.gz | Fastqsanger.gz | |||
| SRR25339560_1.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:Transcriptome network analysis of inflammation and fibrosis in keloids
| PRJNA996549 | ENA
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: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:Transcriptome network analysis of inflammation and fibrosis in keloids [mRNA-seq]
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Project description:Transcriptome network analysis of inflammation and fibrosis in keloids [miRNA-seq]
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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
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2024-09-30 | GSE237755 | GEO
Project description:Multiomics analysis demonstrated the distinct expression profile of active and inactive keloids. Clinically, these findings may provide the future appropriate directions for treatment of keloids depending on their activity and characteristics.
2023-06-01 | GSE220300 | GEO