In Silico Analysis of Potential miRNAs-EGFR Binding Complex for EGFR-TKI Resistance Lung Cancer Cells

Introduction: Overexpression of Epidermal Growth Factor Receptor (EGFR) plays a critical role in the progression and high mortality of Non-Small Cell Lung Cancer (NSCLC). Although EGFR tyrosine kinase inhibitors (EGFR-TKIs) demonstrate promising efficacy as first-line therapy, acquired resistance remains a major clinical challenge. Increasing evidence suggests that microRNAs (miRNAs) regulate EGFR signaling pathways and may influence therapeutic response and the development of resistance. Methods: This study aimed to identify EGFR-targeting microRNAs (miRNAs) and evaluate their binding stability using in silico approaches. Experimentally validated EGFR-targeting miRNAs were retrieved from miRTarBase and subsequently screened using miRDB and TargetScan based on their expression in lung adenocarcinoma cell lines. The secondary structures of miRNA–EGFR duplexes and three-dimensional structures of the miRNA–EGFR complexes were gener-ated using RNAfold and RNAComposer, respectively. Binding affinity was evaluated using HNADOCK molecular docking. Further validation included survival and co-expression analyses using OncomiR and starBase, RNA-Binding Protein (RBP) interaction analysis using POSTAR3, and pathway enrichment analysis using DIANA-miRPath. results: The docking analysis predicted the good binding affinity of 3 miRNAs i.e., hsa-miR-7-5p, hsa-miR-133b and hsa-miR-302b-3p with EGFR. Followed by the resulted docking scores i.e., -340.80 kcal/moL, -473.46 kcal/moL, and -491.18 kcal/moL respectively of the best docked complexes were visualized using Discovery Studio Visualizer. Results: Three miRNAs—miR-7-5p, miR-133b, and miR-302b-3p were identified as potential regulators of EGFR. Molecular docking analysis demonstrated strong binding affinities, with docking scores of −339.30, −476.76, and −491.18 kcal/mol, respectively. Survival analysis re-vealed no significant association between the expression of these miRNAs and patient prognosis. In contrast, co-expression analysis demonstrated a significant correlation between miR-133b and EGFR expression. Several upregulated RNA- Binding Proteins (RBPs) that interact with EGFR were identified, suggesting enhanced post-transcriptional regulation that may contribute to the development of EGFR-TKI resistance. Pathway enrichment analysis further identified hsa-miR-7-5p as being significantly associated with EGFR-mediated PI3K–Akt signaling and the NSCLC pathway. Discussion: These findings highlight candidate miRNAs as potential regulators of EGFR signal-ing and possible biomarkers influencing targeted therapy response. Conclusion: Further experimental and clinical validation is required to confirm their therapeutic relevance in EGFR-TKI-resistant lung cancer.