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A.V. Bokhoven



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    MA 13 - New Insights of Diagnosis and Update of Treatment (ID 674)

    • Event: WCLC 2017
    • Type: Mini Oral
    • Track: Early Stage NSCLC
    • Presentations: 1
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      MA 13.02 - Comprehensive Genetic Analysis Related to  PD-L1 Expression in Early-stage Lung Squamous Cell Carcinoma (ID 9077)

      15:45 - 17:30  |  Author(s): A.V. Bokhoven

      • Abstract
      • Presentation
      • Slides

      Background:
      Recently, anti PD-1/PD-L1 immunotherapies have yielded promising outcomes in advanced squamous NSCLC. Several studies have suggested that tumor PD-L1 protein expression status might correlate with outcome and response to treatment. The aim of this study is to identify mRNA gene signatures and microRNAs associated with tumor PD-L1 expression in early-stage lung squamous cell carcinoma (SCC).

      Method:
      Early stage (I-II) SCC resected patient tumors were collected from 6 cancer centers as part of the SPECS II program. Gene expression profiling was performed on the specimens. PD-L1 protein expression was evaluated by immunohistochemistry on SCC FFPE tissue using the Dako 22C3 PD-L1 antibody. The tumor proportion score (TPS) for PD-L1 protein expression was compared with comprehensive clinicopathological, mRNA and miRNA data.

      Result:
      The prevalence of PD-L1 expression in this cohort of 255 Stage I-II SCC patients was 46.7% with a TPS cutoff of ≥ 1%, and 9.8% with a cutoff of ≥ 50%. Among 202 cases with available clinical and expression data, no significant association was observed between PD-L1 expression and clinical outcome. We identified a 12-gene signature from mRNA microarray using the Minimax Concave Penalty (MCP) regression method with an AUC of 0.92 at ≥ 5% TPS cutoff. A subset of 138 miRNAs was shown to be significantly differentially expressed between PD-L1 positive and PD-L1 negative groups at false discovery rate (FDR) of 0.05 with TPS cutoffs of ≥ 1%, ≥ 5% and ≥ 10%. No miRNAs were found to be significantly differentially expressed between the groups using a TPS cutoff of ≥ 50%. Gene Set Enrichment Analysis (GSEA) identified two pathways with gene sets that were significantly enriched (FDR < 0.05) in the PD-L1 negative group. No significant association was found between tumor mutation burden and PD-L1 expression level.

      Conclusion:
      PD-L1 expression prevalence is lower in early-stage lung SCC than in advanced NSCLC. No significant association was found between PD-L1 expression and prognosis in this cohort. Both mRNA gene signatures and miRNAs were identified to be predictive of PD-L1 expression. Through GSEA, two distinct gene sets were identified with expression correlated to PD-L1, one comprising genes related to ovary and another related to collagens and extracellular matrix (ECM). No significant association was found between tumor mutation burden and PD-L1 expression level. Following validation, these predictive signatures could be used to select patients with positive PD-L1 expression who may benefit from immunotherapy.

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