Single Cell RNA-seq analysis reveals the connection between the miR-124-3p/NEAT1 axis and Erlotinib Drug Resistance in Non Small Cell Lung Cancer

Abstract

Erlotinib resistance remains a critical barrier in treating EGFR-mutant non-small cell lung cancer (NSCLC). While distinct resistance mechanisms have been identified, the temporal evolution of transcriptional states and the role of non-coding RNAs in this process remain poorly understood. To address this, we performed a secondary single-cell RNA sequencing (scRNA-seq) analysis of PC9 cells treated with Erlotinib (GEO Accession: GSE149383). We employed pseudotime trajectory inference (Monocle3) and rigorous in silico modeling to map resistance evolution and predict miRNA-lncRNA interactions. Our trajectory analysis revealed a biphasic evolution of resistance: an early phase characterized by ribosomal stress responses (RPS5, RPL21) followed by a late proliferative phase driven by cell cycle regulators (CENPF, HMGB2). Notably, the long non-coding RNA NEAT1 showed dynamic upregulation during this transition. Computational modeling identified miR-124-3p as a high-confidence regulator of NEAT1, with structural analysis confirming a thermodynamically stable interaction ({Delta}G = - 14.8 kcal/mol). These findings suggest that Erlotinib resistance is not a static state but a dynamic process involving sequential transcriptional reprogramming. We propose the miR-124-3p/NEAT1 axis as a potential therapeutic target to disrupt the stress-adaptation phase of drug resistance.