Identification of dynamic network biomarker for erlotinib pre-resistance using single-cell differential covariance entropy.

Acquired erlotinib resistance is the primary cause of treatment failure in patients with non-small cell lung cancer (NSCLC). Most current research focuses on end-stage resistance, whereas early events leading to resistance have been largely overlooked. In this study, we developed a novel dynamic network biomarker (DNB) method called single-cell differential covariance entropy (scDCE) to identify the pre-resistance state and associated DNB genes. We identified the DNB core gene using protein-protein interactions (PPIs) and Mendelian randomization (MR) analyses. Cell Counting Kit-8 assay demonstrated that downregulation increases the sensitivity of PC9 cells to erlotinib. Survival analyses suggested that high expression was associated with poor prognosis in NSCLC. Mechanistically, we found that and DNB-neighboring genes were significantly enriched in the focal adhesion pathway, where upregulates the expression of (focal adhesion kinase), leading to phosphorylation of downstream effectors, which activated the PI3K-Akt and MAPK signaling pathways to promote cell proliferation and mediate erlotinib resistance. Additionally, the transcription factor / binds to the promoter, synergistically regulating its expression. The experiment also shows that the erlotinib-trametinib combination therapy effectively inhibits resistance. These findings provide new clues for future research on erlotinib resistance mechanisms and early intervention.