Bioinformatics analysis and validation of differentially expressed genes and small molecule drug prediction in proliferative scar

doi:10.12307/2024.332

Abstract

Abstract: BACKGROUND: Hypertrophic scar is a skin fibrosis disease characterized by excessive proliferation of fibroblasts, epidermal thickening, and stratum corneum dysfunction. At present, the pathogenesis of Hypertrophic scar is still unclear.
OBJECTIVE: To screen the core (Hub) genes and important signaling pathways in hypertrophic scar-related datasets based on bioinformatics, and then verify them by cell experiments to predict small molecule drugs that may have therapeutic effects on hypertrophic scar.
METHODS: Datasets related to hypertrophic scar were searched from Gene Expression Omnibus (GEO) database, and differentially expressed genes were identified by R software analysis. Gene ontology and KEGG enrichment analyses were performed for differentially expressed genes. Protein-protein interaction network of differentially expressed genes was constructed using String online platform. Then, the key genes and core modules in the protein-protein interaction network were screened by Cytohubba and MCODE plugin-in Cytoscape software respectively, and the Hub genes were obtained by the intersection of the above key genes and the genes that formed the core module. Real-time fluorescent quantitative PCR was used to verify the difference in Hub gene mRNA expression between human hypertrophic scar and normal skin epidermal stem cells. The histological data from the Human Protein Atlas were used to verify the differences in the expression and distribution of Hub gene-encoded proteins in the two kinds of human tissues. Finally, the potential drugs for hypertrophic scar were predicted by the connectivity map database.
RESULTS AND CONCLUSION: Among the identified differentially expressed genes, 102 genes were up-regulated and 702 genes were down-regulated. Gene ontology and KEGG analysis showed that the enriched signaling pathways and biological processes were mainly involved in tight junction, arachidonic acid metabolism, extracellular matrix receptor interaction, epidermal development and keratinization. Eight Hub genes were found to be closely related to the mevalonate pathway that regulates cholesterol metabolism, including HMGCS1, DHCR7, MSMO1, FDPS, MVK, HMGCR, MVD and ACAT2. Compared with the normal skin group, the mRNA expression of HMGCS1, DHCR7, MSMO1, FDPS, HMGCR, MVD and ACAT2 in the hypertrophic scar group decreased significantly (P < 0.05), while MVK mRNA expression had no significant change (P > 0.05). Except for MVK, the expression levels of other Hub gene-encoded proteins in normal skin tissue were higher than those in hypertrophic scar tissue (P < 0.05). The top 10 candidate drugs included protein kinase A inhibitor (H-89), serine protease inhibitor (Dabigatran-Etexilate), FLT3 inhibitor (sunitinib), among which resveratrol and β-sitosterol are plant extracts. To conclude, Hub genes closely related to mevalonate metabolism may affect the structure and function of the epidermis by regulating lipid metabolism, which may an important pathogenesis of hypertrophic scar. The small-molecule compounds identified in this study can be used as candidate drugs for the treatment of hypertrophic scar.

Key words: hypertrophic scar, bioinformatics, fibroblast, epidermal stem cell, keratinization, lipid metabolism, mevalonate metabolic pathway, drug prediction

CLC Number:

Zuo Jun, Ma Shaolin. Bioinformatics analysis and validation of differentially expressed genes and small molecule drug prediction in proliferative scar[J]. Chinese Journal of Tissue Engineering Research, 2024, 28(14): 2166-2172.

Figures/Tables 7

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