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Tereza Takagaki



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    P1 - Poster Viewing (ID 5)

    • Event: NACLC 2019
    • Type: Poster Session
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 10/11/2019, 16:45 - 18:00, Exhibit Hall
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      P1.14 - Immune Profiling Data and Mutational Status Improves Prediction of Risk of Death in Non-small Cell Lung Carcinoma (ID 123)

      16:45 - 18:00  |  Author(s): Tereza Takagaki

      • Abstract

      Background:
      Recently, multiplexed immunofluorescence (mIF) has shown promise to investigate immune evasion mechanisms and discovering potential biomarkers to assess mechanisms of action and to predict response to a given treatment in NSCLC. In this study, we sought to validate the importance of mIF for immune profiling and to study the relationship between tumor immune checkpoint and epithelial-to-mesenchymal (EMT) genomic profiling in non-metastatic non-small cell lung carcinoma (NSCLC).


      Method:
      Tissue microarrays containing 164 primary tumors from patients with stage I–IIIA NSCLC were examined by mIF and image analysis. The specimens included 94 adenocarcinomas, 51 squamous cell carcinomas, and 19 large cell carcinomas.We evaluated the expression status of programmed death ligand 1 (PD-L1) expression in malignant cells (MCs), CD68+ macrophages, and cells expressing the immune markers CD3, CD8, CD57, CD45RO, FOXP3, PD-1, and CD20. Cell immune phenotype data were then integrated with clinicopathologic characteristic and next-generation sequencing gene mutation profiling.


      Results:
      PD-L1 expression by MCs and other cells was associated with specific clinicopathologic characteristics. In addition, higher densities of antigen-experienced T-cells were associated with metastases. The most frequent tumor microenvironment profiles in the NSCLC samples were those associated with immunologic ignorance and immune tolerance. Multivariate Cox regression model, controlled for stage, histologic type and adjuvant treatment, reliably predicted low risk of death for patients with high density of CD3+CD45RO+ memory T cells and absence of CTLA4 and ZEB1 genes mutation.


      Conclusion:
      The integration of EMT and immune checkpoints genes mutational status with quantitative mIF immune profiling provides additional information on NSCLC behavior, including clinicopathologic characteristics and immunomodulatory control of local disease progression, and may be a promising tool to predict combining target therapy.