Integrative bioinformatics and experimental validation of hub genetic markers in acne vulgaris: Toward personalized diagnostic and therapeutic strategies

Abstract Background Acne vulgaris is a widespread chronic inflammatory dermatological condition. The precise molecular and genetic mechanisms of its pathogenesis remain incompletely understood. This research synthesizes existing databases, targeting a comprehensive exploration of core genetic markers. Methods Gene expression datasets (GSE6475, GSE108110, and GSE53795) were retrieved from the GEO. Differentially expressed genes (DEGs) were identified using the limma package. Enrichment analyses were conducted using GSVA for pathway assessment and clusterProfiler for GO and KEGG analyses. PPI networks and immune cell infiltration were analyzed using the STRING database and ssGSEA, respectively. We investigated the correlation between hub gene biomarkers and immune cell infiltration using Spearman's rank analysis. ROC curve analysis validated the hub genes' diagnostic accuracy. miRNet, TarBase v8.0, and ChEA3 identified miRNA/transcription factor–gene interactions, while DrugBank delineated drug–gene interactions. Experiments utilized HaCaT cells stimulated with Propionibacterium acnes, treated with retinoic acid and methotrexate, and evaluated using RT‐qPCR, ELISA, western blot, lentiviral transduction, CCK‐8, wound‐healing, and transwell assays. Results There were 104 genes with consistent differences across the three datasets of paired acne and normal skin. Functional analyses emphasized the significant enrichment of these DEGs in immune‐related pathways. PPI network analysis pinpointed hub genes PTPRC, CXCL8, ITGB2, and MMP9 as central players in acne pathogenesis. Elevated levels of specific immune cell infiltration in acne lesions corroborated the inflammatory nature of the disease. ROC curve analysis identified the acne diagnostic potential of four hub genes. Key miRNAs, particularly hsa‐mir‐124‐3p, and central transcription factors like TFEC were noted as significant regulators. In vitro validation using HaCaT cells confirmed the upregulation of hub genes following Propionibacterium acnes exposure, while CXCL8 knockdown reduced pro‐inflammatory cytokines, cell proliferation, and migration. DrugBank insights led to the exploration of retinoic acid and methotrexate, both of which mitigated gene expression upsurge and inflammatory mediator secretion. Conclusion This comprehensive study elucidated pivotal genes associated with acne pathogenesis, notably PTPRC, CXCL8, ITGB2, and MMP9. The findings underscore potential biomarkers, therapeutic targets, and the therapeutic potential of agents like retinoic acid and methotrexate. The congruence between bioinformatics and experimental validations suggests promising avenues for personalized acne treatments.