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Mitochondrial autophagy plays a crucial role in the development, progression, and treatment of triple-negative breast cancer (TNBC). A total of 43 genes related to mitochondria were obtained from the scientific literature in Pubmed. To assess the expression of these genes, they were categorized into high and low-scoring groups using the ssGSEA algorithm. Additionally, the infiltration of immune cells in the combined dataset was evaluated using the CIBERSORTx algorithm. To analyze the expression of the selected genes, one-way Cox regression analysis, along with clinical staging variables, was employed. A multifactorial Cox regression model was constructed, and a forest plot was generated to assess the predictive power of the model on the actual outcomes. The accuracy of the model was confirmed by validating the expression of the PINK1 gene and its model through immunohistochemistry. TNBC cancer was categorized into two molecular subtypes (cluster1 and cluster2) based on the MRGs. Finally, a prognostic model was developed using the PINK1 gene, which demonstrated a considerable degree of accuracy. The validity of the PINK1 gene and its model was confirmed through immunohistochemistry, indirectly indicating that PINK1 might serve as a potential therapeutic target and prognostic biomarker for TNBC.
Tian et al. (Thu,) studied this question.