Author of

• 31161

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  P1.09 - Pathology (ID 173)

  • Event: WCLC 2019
  • Type: Poster Viewing in the Exhibit Hall
  • Track: Pathology
  • Presentations: 1
  • Moderators:
  • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall

  • 31185

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    P1.09-21 - Tumor Responses Based on Tumor Growth Rate During PD-1 Inhibitor Therapy in Advanced Non-Small-Cell Lung Cancer Patients (ID 1906)

    09:45 - 18:00  |  Author(s): Ron H.J. Mathijssen
    • Abstract

    Background
    

    Immune checkpoint inhibitors have emerged as a standard of care treatment for non-small cell lung cancer (NSCLC). However, there remains debate about the tumor growth kinetics during treatment, for instance the incidence of rapid disease progression, described as hyperprogressive disease (HPD). To get insight into variations in tumor growth kinetics and their potential predictive values for outcome we evaluated tumor growth rate (TGR) in patients receiving PD-1 checkpoint inhibitors.

    Method
    

    An analysis and radiological review of all Nivolumab treated NSCLC patients (n=196) between 06-2015 and 09-2017 in an early access program and as standard of care was performed. Differences in TGR before and after the start of treatment were calculated by entering the sum of the longest diameters from CT-scans before and after the initiation of therapy into a formula that assumes a volumetric exponential tumor growth. TGR variations, possible predictors for TGR changes and its relationship to overall survival (OS) were studied. For comparison tumor response was assessed using Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST1.1).

    Result
    

    Among the 58 evaluable patients, 37 patients (64%) showed deceleration of TGR and 16 patients (27%) showed acceleration of TGR after initiation of therapy, with a significant difference in median OS of 18.0 versus 6.0 months (HR=0.35; 95%CI:0.18-0.71) between these groups. Four patients (7%) were defined as having HPD. In 5 patients (9%), the tumor growth remained stable. These TGR categories were not significantly different according to age, gender, histology, smoking or previous radiotherapy. Of the patients defined as having progressive disease by RECIST1.1 at first follow up 40% showed response to CPI by a decrease in tumor growth rate. (Figure 1)

    Conclusion
    

    Tumor growth kinetics can be used as a clinically relevant predictor for OS in anti-PD1 treated NSCLC patients, and may provide additional information to RECIST measurements.

    

• 30943

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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

  • 30996

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    P2.04-47 - Tumor Mutational Load, CD8+ T Cells, Expression of PD-L1 and HLA Class I to Guide Immunotherapy Decisions (ID 1259)

    10:15 - 18:15  |  Author(s): Ron H.J. Mathijssen
    • Abstract

    Background
    

    A minority of NSCLC patients benefit from anti-PD1 immune checkpoint inhibitor therapy. A rational combination of biomarkers is needed. The value of using a series of mechanism-of-action based parameters was studied for response prediction of immunotherapy: tumor mutational load (TML), CD8⁺ T cell infiltration, HLA class I expression and the currently used PD-L1 tumor proportion score.

    Method
    

    Patients were prospectively included between April 2016 and August 2017, and retrospectively analyzed. Metastatic NSCLC patients (n=30) with sufficient archival tissue, obtained prior to the first nivolumab administration, were selected. Response was assessed by RECIST v1.1. Progression-free survival (PFS) and overall survival (OS) were analyzed by Kaplan-Meier methodology. TML was determined using a next-genome sequencing panel (409 cancer-related genes). Immunohistochemistry was performed to score PD-L1, total CD8⁺ T cell infiltration and HLA class I.

    Result
    

    In 30 patients with adenocarcinoma (67%) or squamous cell carcinoma (33%), high TML was significantly associated with better PFS (p=0.004) and OS (p=0.025). Interaction analyses revealed that patients with both high TML and high total CD8⁺ T cell infiltrate (p=0.023) or no loss of HLA class I (p=0.026), patients with high total CD8⁺ T cell infiltrate and no loss of HLA class I (p=0.041) or patients with both high PD-L1 and high TML (p=0.003) or no loss of HLA class I (p=0.032) were significantly associated with better PFS. Unsupervised cluster analysis based on the four markers revealed three sub-clusters, of which cluster 1A was overrepresented by patients with progressive disease (15 out of 16), with significant effect on PFS (p=0.007).

    Conclusion
    

    This proof-of-concept study suggests that a combination of PD-L1 expression, TML, CD8⁺ T cell infiltration and HLA class I expression function as a better predictive biomarker for the response to anti-PD-1 immunotherapy and PFS. Consequently, refinement of this proposed set of biomarkers and validation in a larger set of patients is warranted.