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Purpose Treatment of advanced non–small-cell lung cancer with immune checkpoint inhibitors (ICIs) is characterized by durable responses and improved survival in a subset of patients. Clinically available tools to optimize use of ICIs and understand the molecular determinants of response are needed. Targeted next-generation sequencing (NGS) is increasingly routine, but its role in identifying predictors of response to ICIs is not known. Methods Detailed clinical annotation and response data were collected for patients with advanced non–small-cell lung cancer treated with anti–programmed death-1 or anti–programmed death-ligand 1 [anti-programmed cell death (PD)-1] therapy and profiled by targeted NGS (MSK-IMPACT; n = 240). Efficacy was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1, and durable clinical benefit (DCB) was defined as partial response/stable disease that lasted > 6 months. Tumor mutation burden (TMB), fraction of copy number–altered genome, and gene alterations were compared among patients with DCB and no durable benefit (NDB). Whole-exome sequencing (WES) was performed for 49 patients to compare quantification of TMB by targeted NGS versus WES. Results Estimates of TMB by targeted NGS correlated well with WES (ρ = 0.86; P < .001). TMB was greater in patients with DCB than with NDB ( P = .006). DCB was more common, and progression-free survival was longer in patients at increasing thresholds above versus below the 50th percentile of TMB (38.6% v 25.1%; P < .001; hazard ratio, 1.38; P = .024). The fraction of copy number–altered genome was highest in those with NDB. Variants in EGFR and STK11 associated with a lack of benefit. TMB and PD-L1 expression were independent variables, and a composite of TMB plus PD-L1 further enriched for benefit to ICIs. Conclusion Targeted NGS accurately estimates TMB and elevated TMB further improved likelihood of benefit to ICIs. TMB did not correlate with PD-L1 expression; both variables had similar predictive capacity. The incorporation of both TMB and PD-L1 expression into multivariable predictive models should result in greater predictive power.

9003Background: Treatment with PD-(L)1 inhibitors is now standard therapy for patients with lung cancer. The immunosuppressive effect of steroids may reduce efficacy of PD-(L)1 blockade. On-treatme...

9022Background: The transcendent feature of response to anti-PD-(L)1 therapy is durable, long-term responses, which can last up to years. Much effort in biomarkers has focused exclusively on initia...

9016 Background: Identification of molecular predictors of response to PD-1/PD-L1 inhibitors is critical in order to maximize their therapeutic potential. We previously reported that KRAS-mutant lung adenocarcinomas (LUAC) with co-occurring genetic events in STK11/LKB1(KL) or TP53 (KP) define subgroups with marked differences in immune contexture, including a paucity of CD8+ TILs in KL LUAC. Here, we assess clinical responses to PD-1/PD-L1 therapy in KL and KP subsets, with data assembled under the auspices of the SU2C/ACS Lung Cancer Dream Team. Methods: Patients (pts) with metastatic KRAS-mutant LUAC who received at least one cycle of PD-1/PD-L1 therapy, were alive for ≥14 days thereafter, and had available molecular profiling were identified retrospectively. Efficacy assessment was based on RECIST v1.1. PD-L1 expression was tested using 22C3 pharmDx or E1L3N IHC assays and quantified as percent of staining tumor cell membranes. Isogenic derivatives of the LKR10 KrasLA1/+ murine LUAC cell line with CRISPR/Cas9-mediated Lkb1knockout were used in preclinical experiments. Results: 165 pts with KRAS-mutant LUAC who received PD-1/PD-L1 therapy were included [KL: 27%, KP: 36%, K-only: 37%]. Best overall response differed significantly in the KL (PR: 9.1%, SD: 15.9%, PD: 75%) and KP (PR: 33.3%, SD: 20%, PD: 46.7%) sub-groups (P = 0.005, Fisher’s exact test). PFS was significantly longer in KP compared to KL LUAC (median 12.9 wks vs 8.4 wks, HR = 0.64, 95% CI 0.39-0.95, P = 0.032, log-rank test). ORR in K-only tumors was 21.3% and median PFS 11.4 wks. PD-L1 positivity (≥1%) was more frequent in KP tumors compared to KL (75% vs 22%, P = 0.03, Fisher’s exact test). In syngeneic murine models of KRAS-mutant LUAC, loss of LKB1 promoted resistance to PD-1 inhibitor monotherapy, suggesting a causative role. Conclusions: Mutational inactivation of STK11/LKB1 represents a novel genomic predictor of de novo resistance to immune checkpoint blockade in KRAS-mutant LUAC, whereas TP53 co-mutations are associated with high likelihood of response. Precision immunotherapy will require tailoring to the co-mutation status of individual tumors.