進行非小細胞肺癌における免疫療法の反応予測因子としての炎症性分子クラスター

Background/Objectives: Immunotherapy has improved outcomes for selected patients with advanced non-small-cell lung cancer (NSCLC), yet the predictive value of individual biomarkers such as PD-L1 remains limited. Systemic inflammatory indices derived from routine blood tests may complement molecular and immunohistochemical features, offering a broader view of host-tumor immunobiology. Methods: We conducted a retrospective study of 298 patients with stage IIIB-IV NSCLC treated with immune checkpoint inhibitors (ICIs) at a tertiary oncology center between 2022 and 2024. Baseline neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII) were collected alongside PD-L1 expression and molecular alterations (EGFR, KRAS, ALK, TP53). Patients were stratified into inflammatory-molecular clusters integrating these parameters. Associations with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were evaluated using Kaplan-Meier and multivariate Cox analyses. Results: Four distinct inflammatory-molecular clusters demonstrated significantly different outcomes (p < 0.001). Patients with low NLR and high PD-L1 expression (Cluster A) showed the highest ORR (41%), longest median PFS (13.0 months), and OS (22.5 months). The EGFR/ALK-driven, inflammation-dominant cluster (Cluster C) exhibited poor response (ORR 7%) and shortest survival (PFS 4.3 months). High NLR (HR 2.12), PD-L1 < 1% (HR 1.91), and EGFR mutation (HR 2.36) independently predicted shorter PFS. A combined model incorporating NLR, PD-L1, and molecular status outperformed individual biomarkers (AUC 0.82). Conclusions: Integrating systemic inflammatory indices with PD-L1 expression and molecular alterations identifies clinically meaningful NSCLC subgroups with distinct immunotherapy outcomes. This multidimensional approach improves prediction of ICI response and may enhance real-world patient stratification, particularly in settings with limited access to extended molecular profiling.