RESUMEN
PURPOSE: This study aims to reveal the mechanism of fibroblast-related mitochondrial genes on keloid formation and explore promising signature genes for keloid diagnosis. METHOD: The distribution of fibroblasts between the keloid sample and control sample based on three keloid datasets, followed by the differentially expressed genes (DEGs) investigation and associated enrichment analysis. Then, hub genes were explored based on DEGs, mitochondrial genes from an online database, as well as fibroblast-related genes that were revealed by WCGNA. Subsequently, signature genes were screened through machine learning, and their diagnostic value was validated by nomogram. Moreover, the targeted drugs and related transcriptional regulation of these genes were analyzed. Finally, the verification analysis was performed on signature genes using qPCR analysis. RESULT: A total of totally 329 DEGs were revealed based on three datasets, followed by enrichment analysis. WGCNA revealed a total of 258 fibroblast-related genes, which were primarily assembled in functions like muscle tissue development. By using machine learning, we screened four signature genes (ACSF2, ALDH1B1, OCIAD2, and SIRT4) based on eight hub genes (fibroblast-related mitochondrial genes). Nomogram and validation analyses confirmed the well-diagnostic performance of these four genes in keloid. Immune infiltration and drug correlation analyses showed that SIRT4 was significantly associated with immune cell type 2 T helper cells and molecular drug cyclosporin. All these findings provided new perspectives for the clinical diagnosis and therapy of keloid. CONCLUSION: The fibroblast-related mitochondrial genes including SIRT4, OCIAD2, ALDH1B1, and ACSF2 were novel signature genes for keloid diagnosis, offering novel targets and strategies for diagnosis and therapy of keloid.