A J Schoenfeld1, H Rizvi2, C Bandlamudi3, J L Sauter4, W D Travis4, N Rekhtman4, A J Plodkowski5, R Perez-Johnston5, P Sawan5, A Beras4, J V Egger2, M Ladanyi4, K C Arbour1, C M Rudin6, G J Riely1, B S Taylor3, M T A Donoghue3, M D Hellmann7. 1. Thoracic Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, New York, USA. 2. Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, New York, USA. 3. Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, New York, USA. 4. Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, USA. 5. Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, USA. 6. Thoracic Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, New York, USA; Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, New York, USA. 7. Thoracic Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, New York, USA. Electronic address: hellmanm@mskcc.org.
Abstract
BACKGROUND: Programmed death-ligand 1 (PD-L1) expression is the only FDA-approved biomarker for immune checkpoint inhibitors (ICIs) in patients with lung adenocarcinoma, but sensitivity is modest. Understanding the impact of molecular phenotype, clinical characteristics, and tumor features on PD-L1 expression is largely unknown and may improve prediction of response to ICI. PATIENTS AND METHODS: We evaluated patients with lung adenocarcinoma for whom PD-L1 testing and targeted next-generation sequencing (using MSK-IMPACT) was performed on the same tissue sample. Clinical and molecular features were compared across PD-L1 subgroups to examine how molecular phenotype associated with tumor PD-L1 expression. In patients treated with anti-PD-(L)1 blockade, we assessed how these interactions impacted efficacy. RESULTS: A total of 1586 patients with lung adenocarcinoma had paired PD-L1 testing and targeted next-generation sequencing. PD-L1 negativity was more common in primary compared to metastatic samples (P < 0.001). The distribution of PD-L1 expression (lymph nodes enriched for PD-L1 high; bones predominantly PD-L1 negative) and predictiveness of PD-L1 expression on ICI response varied by organ. Mutations in KRAS, TP53, and MET significantly associated with PD-L1 high expression (each P < 0.001, Q < 0.001) and EGFR and STK11 mutations associated with PD-L1 negativity (P < 0.001, Q = 0.01; P = 0.001, Q < 0.001, respectively). WNT pathway alterations also associated with PD-L1 negativity (P = 0.005). EGFR and STK11 mutants abrogated the predictive value of PD-L1 expression on ICI response. CONCLUSION: PD-L1 expression and association with ICI response vary across tissue sample sites. Specific molecular features are associated with differential expression of PD-L1 and may impact the predictive capacity of PD-L1 for response to ICIs.
BACKGROUND: Programmed death-ligand 1 (PD-L1) expression is the only FDA-approved biomarker for immune checkpoint inhibitors (ICIs) in patients with lung adenocarcinoma, but sensitivity is modest. Understanding the impact of molecular phenotype, clinical characteristics, and tumor features on PD-L1 expression is largely unknown and may improve prediction of response to ICI. PATIENTS AND METHODS: We evaluated patients with lung adenocarcinoma for whom PD-L1 testing and targeted next-generation sequencing (using MSK-IMPACT) was performed on the same tissue sample. Clinical and molecular features were compared across PD-L1 subgroups to examine how molecular phenotype associated with tumor PD-L1 expression. In patients treated with anti-PD-(L)1 blockade, we assessed how these interactions impacted efficacy. RESULTS: A total of 1586 patients with lung adenocarcinoma had paired PD-L1 testing and targeted next-generation sequencing. PD-L1 negativity was more common in primary compared to metastatic samples (P < 0.001). The distribution of PD-L1 expression (lymph nodes enriched for PD-L1 high; bones predominantly PD-L1 negative) and predictiveness of PD-L1 expression on ICI response varied by organ. Mutations in KRAS, TP53, and MET significantly associated with PD-L1 high expression (each P < 0.001, Q < 0.001) and EGFR and STK11 mutations associated with PD-L1 negativity (P < 0.001, Q = 0.01; P = 0.001, Q < 0.001, respectively). WNT pathway alterations also associated with PD-L1 negativity (P = 0.005). EGFR and STK11 mutants abrogated the predictive value of PD-L1 expression on ICI response. CONCLUSION: PD-L1 expression and association with ICI response vary across tissue sample sites. Specific molecular features are associated with differential expression of PD-L1 and may impact the predictive capacity of PD-L1 for response to ICIs.
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