ABSTRACT Here, we utilized advanced bioinformatics approaches alongside experimental validation to identify key prognostic biomarkers and potential immune checkpoint inhibitors (ICIs) in non‐small cell lung cancer (NSCLC). Our findings highlight distinct differences in the immune and molecular environments between primary and brain metastatic NSCLC. Brain metastases exhibited higher proportions of cancer stem cells (CSCs), reduced infiltration of B and T cells, and a greater immune escape potential, contributing to diminished responsiveness to ICIs. Specifically, Tregs, with the highest immune checkpoint activity, emerged as critical mediators of immune suppression, offering potential therapeutic targets. Pseudotime analysis revealed that Tcm and Tregs are at the terminal stages of T cell differentiation, with immune checkpoint gene expression reflecting dynamic shifts in immune response regulation. Machine learning models revealed that TNFRSF8, CD160, and TNFSF9 are survival‐associated biomarkers. Immunofluorescence confirmed significant upregulation of TNFRSF8, CD160, and TNFSF9 in lung cancer tissues, particularly in brain metastasis, underscoring their involvement in tumor progression and immune evasion. The identification of TNFRSF8, CD160, and TNFSF9 as key prognostic biomarkers emphasizes their potential as ICIs in brain metastatic NSCLC. These findings provide insights into the immune landscape of both primary and metastatic NSCLC and highlight novel therapeutic avenues, including combinatorial strategies targeting immune evasion mechanisms and tumor‐specific pathways in brain metastasis. Our study suggests that tailored approaches, integrating immune checkpoint inhibition with other targeted strategies, could improve the efficacy of immunotherapy in brain metastatic NSCLC.
Liu et al. (Thu,) studied this question.