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Adela Rodríguez



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    P2.04 - Immuno-oncology (ID 167)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Immuno-oncology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.04-22 - Programmed Death 1-mRNA Expression Predicts Benefit to Anti-PD1 Monotherapy in a Prospective Cohort of Advanced NSCLC (ID 1092)

      10:15 - 18:15  |  Author(s): Adela Rodríguez

      • Abstract

      Background

      Immunotherapy (IO) targeting PD1 or PD-L1 represents a new treatment option for patients (pts) with advanced non-small cell lung cancer (NSCLC). Besides PD-L1 IHC, other predictive biomarkers are being explored as potential predictors of outcomes. Our group has recently described an association between PD1-mRNA expression and response to IO in a retrospective multi-tumor dataset (Annals Oncol 2018). We aimed to corroborate these results in a prospective cohort of advanced NSCLC.

      Method

      We prospectively evaluated the expression of 7 immune-related genes (CD4, CD8, PD1, PDL1, IFNG, GZMM andFOXP3) and 5 housekeeping genes in formalin-fixed paraffin-embedded tumor samples obtained before anti-PD1 therapy using the nCounter platform (Nanostring Technologies). The study cohort included consecutive pts with advanced NSCLC, ECOG/PS 0-1, no targetable oncogenes, treated in the first or second-line setting with anti-PD1 monotherapy from June 2017 to January 2019. Associations between the expression of PD1 mRNA (as a continuous variable and using a previously defined pre-specified cutpoint) and response (complete and partial response) were assessed using logistic regression analysis. Kaplan-Meier method was used for survival analysis. PD-L1 IHC tumor cell expression was assessed using the 22C3 clone. Pearson correlation between PD-L1 IHC and PD1 mRNA was explored.

      Result

      A total of 43 pts were included (men 79%; adenocarcinoma 53%; nivolumab 55%; pembrolizumab 45%; first-line 30%; second-line 70%). Response occurred in 23% of pts and was significantly associated with PD1 (p=0.029) and FOXP3 (p=0.035) expression. Using the pre-established PD1 cutoff (Annals Oncol 2018), 37% and 63% samples were PD1-high and PD1-low, respectively. PD1-high was significantly associated with increased overall response rate (ORR) (43% vs 11%, OR=6.22 [CI=1.31-29.44], p=0.021) and progression-free survival (HR 0.36 [CI= 0.14-0.90], p=0.028) but not with overall survival (p=0.117). PD-L1 IHC expression was available in 35 cases, of which 46% had high (>=50%) expression levels. A moderate concordance (0.49) was observed between PD-L1 IHC and PD1-mRNA. In this subset analysis, high PD-L1 IHC was significantly associated with response (50% vs 11%, OR=8.50 [CI= 1.45-49.53], p=0.043). Importantly, when combining predefined high/low-sets for both biomarkers (PD-L1 IHC/PD1-mRNA), response was significantly increased in PD-L1-high/PD1-high compared to PD-L1-low/PD1-low (ORR 58% vs 0%, p=0.019).

      Conclusion

      PD1-mRNA expression is associated with response to anti-PD1 monotherapy and can increase the predictive ability of PD-L1 IHC. Further validation of these findings in pivotal clinical trials evaluating IO in advanced NSCLC pts seems warranted.