NSCLC的免疫分析与可靶向生物标志物：迈向基于CKI的联合方案的合理设计

Background: Actionable mutations guide first-line targeted therapies in non-small cell lung cancer (NSCLC), yet resistance frequently develops. Immune checkpoint inhibitors (CKIs) improve outcomes, and recent evidence suggests potential synergy with targeted agents for rare NSCLC biomarkers. This study explored correlations between actionable targets and immune contexture to inform combination strategies. Methods: Twenty-five NSCLC FFPE resected specimens were analyzed by immunohistochemistry for PD-L1 (clone 22C3), ALK, ROS1, HER2, EGFR, pan-TRK, BRAF, c-Met, and MEK1. Two in-house multiplex panels (PD-1/PD-L1/CD3/CD8 and CD3/CD8/FoxP3) assessed PD-1, PD-L1, and T-cell subsets. Chromogenic simplex IHC stains were scored by a thoracic oncology pathologist per clinical standards or literature; immune populations were quantified in tumor and non-tumor regions using Halo image analysis. Results: Targetable protein expression largely reflected published prevalence. PD-L1 correlated positively with c-Met, MEK1, and EGFR, but not HER2. HER2 expressions were associated with increased helper and cytotoxic T cells, supporting limited benefit of PD-1/PD-L1 blockade in HER2-positive NSCLC while suggesting alternative immunomodulators. MEK1+ tumor cells showed strong correlation with infiltrating immune cells and PD-1 expression, reinforcing MEK1 inhibition as a promising approach to counter immune evasion. No correlation was observed between PD-L1 and PD-1+ cytotoxic T cells, highlighting the need to assess both PD-1 and PD-L1 for optimal CKI efficacy. Conclusions: Immune profiling within the tumor microenvironment may complement actionable target testing and guide rational design of CKI-based combination therapies in NSCLC. This text has been revised with the assistance of Microsoft Copilot to comply with the specified character limit.