Abstract

9018 Background: PD-L1 expression is the only FDA-approved predictive biomarker for patients with NSCLC treated with immune checkpoint inhibitors. The impact of tumor molecular profiling on tumor PD-L1 expression is not known. We hypothesized that somatic mutations and copy number alterations may be associated with distinct patterns of PD-L1 expression in patients with NSCLC. Methods: We examined patients with NSCLC in whom PD-L1 testing and targeted next-generation sequencing (MSK-IMPACT) were performed on the same tissue sample. PD-L1 expression was determined by IHC using the E1L3N antibody clone and categorized as PD-L1 high (≥ 50%), intermediate (1-49%), or negative ( < 1%) expression. The association of PD-L1 with individual genes, pathways, tumor mutation burden, whole genome duplication (WGD), and aneuploidy (fraction of genome altered (FGA)) were evaluated. P-values < 0.05 and q-values < 0.15 were considered significant for individual genes. Results: 1023 patients with NSCLC had PD-L1 testing and MSK-IMPACT performed on the same tissue sample, 18% (n = 180) had high, 21% (n = 218) had intermediate, and 61% (n = 625) had negative PD-L1 expression. High PD-L1 expression was significantly enriched in metastatic vs primary lesions (p < 0.001). There was a minor correlation between PD-L1 and TMB (spearman rho = 0.195) and PD-L1 and FGA (spearman rho = 0.11). Similar rates of WGD were found among patients with high, intermediate, and negative PD-L1 expression (p = 0.38). Mutations in KRAS and TERT were significantly enriched in PD-L1 high compared to other groups (p = 0.001, q = 0.14; p < 0.001, q = 0.003). By contrast, mutations in EGFR and STK11 were associated with PD-L1 negativity (p < 0.001, q = 0.001; p = 0.001, q = 0.14). Pathway analysis showed DNA repair (p < 0.001), TP53 (p < 0.001), and SWI/SNF (p = 0.04) pathways significantly associated with PD-L1 high compared to PD-L1 negative expression. Conclusions: The genetic features of NSCLC are associated with distinct patterns of PD-L1 expression. This data may provide insight to how the molecular phenotype can interact with the immunologic phenotype of tumors.

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