Integrative Bioinformatics Analysis of Pyroptosis-Related Genes and Analysis of Immune Cell Infiltration in Infantile Hemangioma Regression - Liu L; Lin S; Bai J; Zhang B (Clinical, Cosmetic and Investigational Dermatology)
Lan Liu,1,2,* Sheng Lin,1,2,* Jianxi Bai,1,2 Bing Zhang1,2 1Pediatric Surgery Department, Fujian Children’s Hospital (Fujian Branch of Shanghai Children’s Medical Center), Fuzhou City, Fujian Province, People’s Republic of China; 2Pediatric Surgery Department, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou City, Fujian Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jianxi Bai, Pediatric Surgery Department, Fujian Children’s Hospital (Fujian Branch of Shanghai Children’s Medical Center), 966 hengyu Road, Jinan District, Fuzhou City, Fujian Province, People’s Republic of China, Tel +8615806032159, Email bjxqqq@126.comBackground: Infantile hemangiomas (IHs) are characterized by spontaneous regression, and their pathogenesis involves immune cell infiltration and programmed cell death. The molecular pathways and mechanisms involved in pyroptosis in IHs are still unclear. This study aimed to identify genes related to pyroptosis in IH regression by bioinformatics methods and to explore the effects of these pyroptosis-related genes (PRGs) on disease pathology and immune cell infiltration.Methods: The microarray dataset GSE127487 was assessed to identify differentially expressed genes (DEGs) between proliferation-phase IH (PIHs) and involution-phase IH (IIHs). The DEGs that overlapped with PRGs were considered IH-PRGs. The IH-PRGs were validated and subjected to functional enrichment analysis and Genomes pathway analyses. Gene set enrichment analysis (GSEA) was also performed to analyse the biological significance of the DEGs. The NetworkAnalyst database was used to analyse the correlation network of IH-PRGs and miRNAs as well as that of IH-PRGs and transcription factors. The STRING online database and Cytoscape were used to identify the hub-IH-PRGs. Additionally, a single-sample GSEA algorithm was applied to assess immune cell infiltration in IHs, and correlation analysis was performed between the hub-IH-PRGs and infiltrating immune cells.Results: Fourteen IH-PRGs were identified. IL6, EGFR, IRF1 and IL32 were identified as hub-IH-PRGs and displayed excellent diagnostic performance. Immune cell infiltration analysis revealed notable differences in CD8+ T cells, Tgd cells and Th17 cells between PIHs and IIHs. IL-6 was significantly positively correlated with Th17 cell infiltration and significantly negatively correlated with Tgd cell infiltration; EGFR was negatively correlated with Tgd cell infiltration; and IRF1 and IL32 were significantly negatively correlated with Th17 cell infiltration.Conclusion: Four PRGs, namely, IL6, EGFR, IRF1 and IL32, may play a significant role in IH regression. This study provides insights into the molecular mechanisms underlying IH pathogenesis, highlighting the importance of pyroptosis and immune cell infiltration.Keywords: infantile hemangiomas, pyroptosis, bioinformatics, immune cell infiltration, regression