Abstract

Background Brain metastasis (BM) remains a severe and fatal complication in patients with lung cancer (LC), presenting a major therapeutic challenge. Although epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) have emerged as a cornerstone of targeted therapy, their clinical efficacy is often limited by the inevitable development of drug resistance. Methods We initially constructed a general atlas of the tumor microenvironment (TME) in LCBM lesions by integrating single-cell RNA sequencing (scRNA-seq) data. The sensitivity of each cell cluster to EGFR-TKIs was assessed by the “Beyondcell” method. By performing high-dimensional Weighted Gene Co-expression Network Analysis (hdWGCNA), we identified hub genes within an EGFR-TKI resistance-associated cell cluster. Finally, the functional role of the most promising candidate, ACTN1, was further investigated in a constructed osimertinib-resistant LC cell line. Results We identified a malignant and therapy-resistant ACTN1 + epithelial cell subcluster. Both signaling and functional enrichment analyses demonstrated marked activation of PI3K-Akt and IL-17 signaling pathways in ACTN1-high patient subgroups. Finally, we applied machine learning methods to the ACTN1-related genes to select prognostic factors. In vitro experiments confirmed the pro-resistance and pro-metastatic functions of ACTN1 in osimertinib-resistant LC cells. Conclusion ACTN1 was discovered to induce malignant progression and formation of EGFR-TKI resistance. Targeting ACTN1-related pathways may provide novel insights to treat LCBM and overcome intracranial EGFR-TKI resistance.