Transcriptome network analysis of inflammation and fibrosis in keloids.

J Dermatol Sci

Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address:

Published: February 2024

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 24,086 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.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jdermsci.2023.12.007DOI Listing

Publication Analysis

Top Keywords

network analysis
12
rna sequencing
12
inflammation fibrosis
8
keloid
8
transcriptome landscape
8
normal skin
8
single-cell rna
8
cells
5
sequencing
5
transcriptome
4

Similar Publications

A Chinese isolate of the fungus Penicillium chrysogenum was analyzed using liquid chromatography coupled with Q-Exactive Orbitrap mass spectrometry combined with Global Natural Products Social Networking (GNPS) on culture condition leading to the rapid identification of 20 secondary metabolites. Among them are eight polyketones, two phthalides, six diketopiperazine alkaloids, and others. A meleagrine network was examined and proposed as a promising candidate for new natural products.

View Article and Find Full Text PDF

Developing a decision support tool to predict delayed discharge from hospitals using machine learning.

BMC Health Serv Res

January 2025

Department of Industrial Engineering, Dalhousie University, PO Box 15000, Halifax, B3H 4R2, NS, Canada.

Background: The growing demand for healthcare services challenges patient flow management in health systems. Alternative Level of Care (ALC) patients who no longer need acute care yet face discharge barriers contribute to prolonged stays and hospital overcrowding. Predicting these patients at admission allows for better resource planning, reducing bottlenecks, and improving flow.

View Article and Find Full Text PDF

Background: Ferroptosis and immune responses are critical pathological events in spinal cord injury (SCI), whereas relative molecular and cellular mechanisms remain unclear.

Methods: Micro-array datasets (GSE45006, GSE69334), RNA sequencing (RNA-seq) dataset (GSE151371), spatial transcriptome datasets (GSE214349, GSE184369), and single cell RNA sequencing (scRNA-seq) datasets (GSE162610, GSE226286) were available from the Gene Expression Omnibus (GEO) database. Through weighted gene co-expression network analysis and differential expression analysis in GSE45006, we identified differentially expressed time- and immune-related genes (DETIRGs) associated with chronic SCI and differentially expressed ferroptosis- and immune-related genes (DEFIRGs), which were validated in GSE151371.

View Article and Find Full Text PDF

Background: Mounting evidence suggests that Parkinson's disease (PD) and inflammatory bowel disease (IBD) are closely associated and becoming global health burdens. However, the causal relationships and common pathogeneses between them are uncertain. Furthermore, they are uncurable.

View Article and Find Full Text PDF

Bayesian network for predicting mandibular third molar extraction difficulty.

BMC Oral Health

January 2025

Sub-Institute of Public Safety Standardization, China National Institute of Standardization, No.4 Zhichun Road, Haidian District, Beijing, 100191, PR China.

Background: This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output quantitative difficulty-evaluation results based on the patient's personal situation; and (3) identify key surgical points and propose surgical protocols to decrease complications.

Methods: Relevant articles were searched to identify risk factors. Clinical knowledge and experience were used to analyse the risk factors to establish the Bayesian network.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!