Clinical and molecular correlates of PD-L1 expression in patients with lung adenocarcinomas.

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.

COVID-19 in patients with lung cancer.

BACKGROUND: Patients with lung cancers may have disproportionately severe coronavirus disease 2019 (COVID-19) outcomes. Understanding the patient-specific and cancer-specific features that impact the severity of COVID-19 may inform optimal cancer care during this pandemic. PATIENTS AND METHODS: We examined consecutive patients with lung cancer and confirmed diagnosis of COVID-19 (n = 102) at a single center from 12 March 2020 to 6 May 2020. Thresholds of severity were defined a priori as hospitalization, intensive care unit/intubation/do not intubate ([ICU/intubation/DNI] a composite metric of severe disease), or death. Recovery was defined as >14 days from COVID-19 test and >3 days since symptom resolution. Human leukocyte antigen (HLA) alleles were inferred from MSK-IMPACT (n = 46) and compared with controls with lung cancer and no known non-COVID-19 (n = 5166). RESULTS: COVID-19 was severe in patients with lung cancer (62% hospitalized, 25% died). Although severe, COVID-19 accounted for a minority of overall lung cancer deaths during the pandemic (11% overall). Determinants of COVID-19 severity were largely patient-specific features, including smoking status and chronic obstructive pulmonary disease [odds ratio for severe COVID-19 2.9, 95% confidence interval 1.07-9.44 comparing the median (23.5 pack-years) to never-smoker and 3.87, 95% confidence interval 1.35-9.68, respectively]. Cancer-specific features, including prior thoracic surgery/radiation and recent systemic therapies did not impact severity. Human leukocyte antigen supertypes were generally similar in mild or severe cases of COVID-19 compared with non-COVID-19 controls. Most patients recovered from COVID-19, including 25% patients initially requiring intubation. Among hospitalized patients, hydroxychloroquine did not improve COVID-19 outcomes. CONCLUSION: COVID-19 is associated with high burden of severity in patients with lung cancer. Patient-specific features, rather than cancer-specific features or treatments, are the greatest determinants of severity.