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<p>The aim of our research was to explore and validate the diagnostic value of mitochondria-related genes (MRGs) in basal cell carcinoma (BCC).&#xa0;The differentially expressed MRGs in BCC were identified based on the GSE39612, GSE42109 and GSE7553 training sets and the GSE53462 validation set, and the PPI network was drawn. The potential signature genes in BCC were screened by LASSO, RF and SVM-RFE. Besides, the performance of the signature genes was evaluated and a nomogram was constructed. Moreover, immunoinfiltration, drug prediction and transcriptional regulation of these signature genes were also analyzed. Finally, qRT-PCR was employed to measure the expression of signature genes in clinical tissues and BCC cells.&#xa0;1699 DEGs were obtained from the training set. Then, taking the intersection of DEGs, WGCNA module genes and MRGs, 36 DEGs-MRGs were obtained. Six potential signature genes in BCC, including ACADL, BCL2L2, CHCHD7, LDHB, NT5DC2, and PDK4, were obtained through LASSO, RF, and SVM-RFE. Nomogram and validation analysis confirmed that these 6 genes have ideal predictive power in BCC. In addition, 6 signature genes were significantly associated with macrophages and interacted with pyruvic acid, sodium chromate, perfluoroheptanoic acid and other drugs. Finally, qRT-PCR analysis showed that the expression trend of these 6 signature genes in clinical tissues and BCC cells was consistent with the results of bioinformatics analysis.&#xa0;ACADL, BCL2L2, CHCHD7, LDHB, NT5DC2 and PDK4 are potential diagnostic signature genes of BCC.</p>

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Identification of mitochondrial associated genes as diagnostic biomarkers for basal cell carcinoma: Comprehensive bioinformatics analysis and experimental validation

  • 期刊论文

  • 发表日期：

    2026年2月12日

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  • Zuojiao Xu,
  • Chunjun Yang

摘要

The aim of our research was to explore and validate the diagnostic value of mitochondria-related genes (MRGs) in basal cell carcinoma (BCC). The differentially expressed MRGs in BCC were identified based on the GSE39612, GSE42109 and GSE7553 training sets and the GSE53462 validation set, and the PPI network was drawn. The potential signature genes in BCC were screened by LASSO, RF and SVM-RFE. Besides, the performance of the signature genes was evaluated and a nomogram was constructed. Moreover, immunoinfiltration, drug prediction and transcriptional regulation of these signature genes were also analyzed. Finally, qRT-PCR was employed to measure the expression of signature genes in clinical tissues and BCC cells. 1699 DEGs were obtained from the training set. Then, taking the intersection of DEGs, WGCNA module genes and MRGs, 36 DEGs-MRGs were obtained. Six potential signature genes in BCC, including ACADL, BCL2L2, CHCHD7, LDHB, NT5DC2, and PDK4, were obtained through LASSO, RF, and SVM-RFE. Nomogram and validation analysis confirmed that these 6 genes have ideal predictive power in BCC. In addition, 6 signature genes were significantly associated with macrophages and interacted with pyruvic acid, sodium chromate, perfluoroheptanoic acid and other drugs. Finally, qRT-PCR analysis showed that the expression trend of these 6 signature genes in clinical tissues and BCC cells was consistent with the results of bioinformatics analysis. ACADL, BCL2L2, CHCHD7, LDHB, NT5DC2 and PDK4 are potential diagnostic signature genes of BCC.