Integrated Analysis of Single-cell and Bulk-RNA Sequencing Data to Identify Redox-related Genes as Prognostic Biomarkers and Therapeutic Targets of Lung Adenocarcinoma With Osimertinib Resistance

Background: Acquired resistance limits the therapeutic efficacy of osimertinib in lung adenocarcinoma (LUAD). Redox homeostasis is crucial for LUAD progression. However, how redox imbalance interacts with the tumor microenvironment (TME) to drive osimertinib resistance (OR) remains unclear. Methods: The single-cell RNA sequencing (scRNA-seq) data GSE243562 were combined with the Cancer Genome Atlas (TCGA)-LUAD transcriptomes to map the TME cell population heterogeneity in osimertinib-resistant LUAD. Through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regularization, a prognostic signature founded on redox-related genes (RRGs) was built. Therapeutic compounds targeting these signature genes were prioritized by molecular docking. Their expression patterns were subsequently validated in vitro. Results: Cancer-associated fibroblasts (CAFs) were central hubs in the TME of osimertinib-resistant LUAD, exhibiting enhanced intercellular communication. Computational profiling identified 10 differentially expressed RRGs, predominantly enriched in CAFs. Using a six-gene signature comprising AGER, CYP2J2, FMO2, HSPA1B, SOD3, and VASN, we categorized LUAD patients into separate risk categories. High-risk patients showed significantly reduced survival, an immunosuppressive status, and a higher tumor mutation burden (p < 0.05). The overexpression of these six genes was confirmed in OR cells. Critically, inhibiting SOD3 restored osimertinib sensitivity in vitro (p < 0.05). Clinically, SOD3 expression was lower in patients sensitive to third-generation epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) than in those with resistant disease. Conclusions: Targeting CAFs represents a promising strategy to overcome osimertinib resistance. Our six-gene redox signature offers a clinical framework for patient risk stratification and novel therapeutic strategy design. Future work will explore these targets to develop new treatments for LUAD.