ArticleFrontiers in genetics2020
Integrated WGCNA and PPI Network to Screen Hub Genes Signatures for Infantile Hemangioma.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 27 citations in OpenAlex.
- Identifying Potential Diagnostic and Therapeutic Targets for Infantile Hemangioma Using WGCNA and Machine Learning Algorithms.Biochemical genetics · 2025Article
- Glycolysis-Related Genes,Cardiology research · 2025Article
- Identification of key LncRNAs and mRNAs associated with intramuscular fat in pig via WGCNA.BMC genomics · 2025Article
- Machine learning identifies immune-perinatal predictors of infantile hemangioma.Frontiers in pediatrics · 2025Article
- Integrative Bioinformatics Analysis of Pyroptosis-Related Genes and Analysis of Immune Cell Infiltration in Infantile Hemangioma Regression.Clinical, cosmetic and investigational dermatology · 2025Article
- Efficacy Evaluation of Treatment of Psoriasis Via Narrow Band-Ultraviolet Radiation.Journal of lasers in medical sciences · 2024Article
- Global research trends of infantile hemangioma: A bibliometric and visualization analysis from 2000 to 2022.Heliyon · 2023Article
- Identification of molecular subtypes of ischaemic stroke based on immune-related genes and weighted co-expression network analysis.IET systems biology · 2023Article
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- Comparative transcriptome profiling and weighted gene co-expression network analysis to identify core genes in maize (Frontiers in plant science · 2022Article
- Single-Cell Analysis Reveals the Role of the Neuropeptide Receptor FPR2 in Monocytes in Kawasaki Disease: A Bioinformatic Study.Disease markers · 2022Article
- Identification of Diagnostic Markers in Infantile Hemangiomas.Journal of oncology · 2022Article
- Comprehensive Genetic Analysis of Tuberculosis and Identification of Candidate Biomarkers.Frontiers in genetics · 2022Article
- Identification of Key Signaling Pathways and Genes in Eosinophilic Asthma and Neutrophilic Asthma by Weighted Gene Co-Expression Network Analysis.Frontiers in molecular biosciences · 2022Article
- Using weighted gene co-expression network analysis (WGCNA) to identify the hub genes related to hypoxic adaptation in yak (Bos grunniens).Genes & genomics · 2021Article
- Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods.Computational and structural biotechnology journal · 2021Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInfantile hemangioma (IH) is characterized by proliferation and regression.
methodsBased on the GSE127487 dataset, the differentially expressed genes (DEGs) between 6, 12, or 24 months and normal samples were screened, respectively. STEM software was used to screen the continued up-regulated or down-regulated in common genes. The modules were assessed by weighted gene co-expression network analysis (WGCNA). The enrichment analysis was performed to identified the biological function of important module genes. The area under curve (AUC) value and protein-protein interaction (PPI) network were used to identify hub genes. The differential expression of hub genes in IH and normal tissues was detected by qPCR.
resultsThere were 5,785, 4,712, and 2,149 DEGs between 6, 12, and 24 months and normal tissues. We found 1,218 DEGs were up-regulated or down-regulated expression simultaneously in common genes. They were identified as 10 co-expression modules. Module 3 and module 4 were positively or negatively correlated with the development of IH, respectively. These two module genes were significantly involved in immunity, cell cycle arrest and mTOR signaling pathway. The two module genes with AUC greater than 0.8 at different stages of IH were put into PPI network, and five genes with the highest degree were identified as hub genes. The differential expression of these genes was also verified by qRTPCR.
conclusionFive hub genes may distinguish for proliferative and regressive IH lesions. The WGCNA and PPI network analyses may help to clarify the molecular mechanism of IH at different stages.
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