Clinicogenomic Predictors of First-line Immune Checkpoint Inhibitor Outcomes in Non-Small Cell Lung Cancer: A...

The efficacy of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) varies, requiring predictive biomarkers.

We analyzed the nationwide Center for Cancer Genomics and Advanced Therapeutics (CCAT) database and identified 1629 patients with stage IV NSCLC who received first-line ICI-based therapy between 2019 and 2025. The primary endpoint was time to treatment failure (TTF); the secondary endpoint was overall survival (OS). Age-stratified Cox models were adjusted for covariates. Genomic covariates included KRAS, KEAP1, and STK11, with genes from exploratory screening. We tested KRAS-KEAP1 and KRAS-STK11 interactions. Sensitivity analyses included an FFPE-only subset with tumor mutational burden (TMB) and models adjusting for the ECOG status.

BRAF mutation was independently associated with longer TTF (HR 0.77, 95% CI 0.59-1.00; P = .049), whereas KRAS, KEAP1, and STK11 alone were not. A significant KRAS-KEAP1 interaction was associated with shorter TTF (HR 1.89, 95% CI 1.06-3.36; P = .032). In a 4-level comparison versus wild-type, KRAS-only and KEAP1-only were not significant, whereas KRAS-KEAP1 co-mutation was associated with higher risk of failure (HR 2.48, 95% CI 1.50-4.10; P < .001). Results were consistent across sensitivity analyses. KEAP1 and STK11 were associated with worse OS, while BRAF showed no OS advantage.

In first-line ICI-treated stage IV NSCLC, KRAS-KEAP1 co-mutation, not KRAS or KEAP1 alone, identifies patients at high risk of early failure, whereas BRAF was associated with longer TTF. These findings highlight the importance of co-mutation profiling and warrant prospective validation with integrative models incorporating PD-L1 and TMB.