Jennifer L. Sauter

Abstract KRAS is the most common oncogenic driver in lung adenocarcinoma (LUAC). We previously reported that STK11/LKB1 (KL) or TP53 (KP) comutations define distinct subgroups of KRAS-mutant LUAC. Here, we examine the efficacy of PD-1 inhibitors in these subgroups. Objective response rates to PD-1 blockade differed significantly among KL (7.4%), KP (35.7%), and K-only (28.6%) subgroups (P < 0.001) in the Stand Up To Cancer (SU2C) cohort (174 patients) with KRAS-mutant LUAC and in patients treated with nivolumab in the CheckMate-057 phase III trial (0% vs. 57.1% vs. 18.2%; P = 0.047). In the SU2C cohort, KL LUAC exhibited shorter progression-free (P < 0.001) and overall (P = 0.0015) survival compared with KRASMUT;STK11/LKB1WT LUAC. Among 924 LUACs, STK11/LKB1 alterations were the only marker significantly associated with PD-L1 negativity in TMBIntermediate/High LUAC. The impact of STK11/LKB1 alterations on clinical outcomes with PD-1/PD-L1 inhibitors extended to PD-L1–positive non–small cell lung cancer. In Kras-mutant murine LUAC models, Stk11/Lkb1 loss promoted PD-1/PD-L1 inhibitor resistance, suggesting a causal role. Our results identify STK11/LKB1 alterations as a major driver of primary resistance to PD-1 blockade in KRAS-mutant LUAC. Significance: This work identifies STK11/LKB1 alterations as the most prevalent genomic driver of primary resistance to PD-1 axis inhibitors in KRAS-mutant lung adenocarcinoma. Genomic profiling may enhance the predictive utility of PD-L1 expression and tumor mutation burden and facilitate establishment of personalized combination immunotherapy approaches for genomically defined LUAC subsets. Cancer Discov; 8(7); 822–35. ©2018 AACR. See related commentary by Etxeberria et al., p. 794. This article is highlighted in the In This Issue feature, p. 781

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.

Combination immune checkpoint blockade has demonstrated promising benefit in lung cancer, but predictors of response to combination therapy are unknown. Using whole-exome sequencing to examine non-small-cell lung cancer (NSCLC) treated with PD-1 plus CTLA-4 blockade, we found that high tumor mutation burden (TMB) predicted improved objective response, durable benefit, and progression-free survival. TMB was independent of PD-L1 expression and the strongest feature associated with efficacy in multivariable analysis. The low response rate in TMB low NSCLCs demonstrates that combination immunotherapy does not overcome the negative predictive impact of low TMB. This study demonstrates the association between TMB and benefit to combination immunotherapy in NSCLC. TMB should be incorporated in future trials examining PD-(L)1 with CTLA-4 blockade in NSCLC.

Background: Neoadjuvant anti-PD-1 may improve outcomes for patients with resectable NSCLC and provides a critical window for examining pathologic features associated with response. Resections showing major pathologic response to neoadjuvant therapy, defined as ≤10% residual viable tumor (RVT), may predict improved long-term patient outcome. However, %RVT calculations were developed in the context of chemotherapy (%cRVT). An immune-related %RVT (%irRVT) has yet to be developed. Patients and methods: The first trial of neoadjuvant anti-PD-1 (nivolumab, NCT02259621) was just reported. We analyzed hematoxylin and eosin-stained slides from the post-treatment resection specimens of the 20 patients with non-small-cell lung carcinoma who underwent definitive surgery. Pretreatment tumor biopsies and preresection radiographic 'tumor' measurements were also assessed. Results: We found that the regression bed (the area of immune-mediated tumor clearance) accounts for the previously noted discrepancy between CT imaging and pathologic assessment of residual tumor. The regression bed is characterized by (i) immune activation-dense tumor infiltrating lymphocytes with macrophages and tertiary lymphoid structures; (ii) massive tumor cell death-cholesterol clefts; and (iii) tissue repair-neovascularization and proliferative fibrosis (each feature enriched in major pathologic responders versus nonresponders, P < 0.05). This distinct constellation of histologic findings was not identified in any pretreatment specimens. Histopathologic features of the regression bed were used to develop 'Immune-Related Pathologic Response Criteria' (irPRC), and these criteria were shown to be reproducible amongst pathologists. Specifically, %irRVT had improved interobserver consistency compared with %cRVT [median per-case %RVT variability 5% (0%-29%) versus 10% (0%-58%), P = 0.007] and a twofold decrease in median standard deviation across pathologists within a sample (4.6 versus 2.2, P = 0.002). Conclusions: irPRC may be used to standardize pathologic assessment of immunotherapeutic efficacy. Long-term follow-up is needed to determine irPRC reliability as a surrogate for recurrence-free and overall survival.