Discussion
Knockdown of NNMT in lung cancer cells enhances drug sensitivity by modulating autophagy, providing a promising therapeutic target to overcome chemoresistance in NSCLC. The study underscores the importance of NNMT in lung cancer pathology and underscores its potential as a predictive marker for clinical outcomes. Additionally, the developed predictive model further supports the clinical relevance of NNMT-associated gene expression in improving the prognosis of lung cancer patients.
Methods
Proteomic analysis was utilized to identify changes in protein expression following NNMT knockdown in H1975 and H1975 osimertinib resistance (H1975OR) lung cancer cell lines. Gene expression patterns and their correlation with NNMT expression in lung cancer patients were analyzed using The Cancer Genome Atlas (TCGA) dataset. Additionally, a predictive model for lung cancer survival was developed via lasso regression analysis based on NNMT-associated gene expression. Drug sensitivity was assessed using the IC50 values and apoptosis ratio, and autophagy was evaluated through Western blot and flow cytometric analysis.
Results
Significant variations in the expression of 1,182 proteins were observed following NNMT knockdown, with a significant association with autophagy-related genes. Analysis of gene expression patterns unveiled a significant correlation between NNMT expression and specific changes in gene expression in lung cancer. The predictive model successfully forecasted lung cancer patient survival outcomes, highlighting the potential of NNMT-associated genes in predicting patient survival. Knockdown of NNMT reversed osimertinib resistance in H1975 cells, as evidenced by altered IC50 values and apoptosis ratio, and changes were observed in autophagy markers.