Virtual Library

Start Your Search

Zhobo Gao



Author of

  • +

    FP07 - Pathology (ID 109)

    • Event: WCLC 2020
    • Type: Posters (Featured)
    • Track: Pathology, Molecular Pathology and Diagnostic Biomarkers
    • Presentations: 1
    • Moderators:
    • Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
    • +

      FP07.05 - An Optimized Neoantigen Load Model Based on Immune Editing to Predict Response and Prognosis of Immune Checkpoint Therapy (ID 1776)

      00:00 - 00:00  |  Author(s): Zhobo Gao

      • Abstract
      • Presentation
      • Slides

      Introduction

      Only a minority of patients achieve clinical benefit from immune checkpoint therapy, how to distinguish responders and non-responders is still far from clearly understood. Recent studies have identified neoantigen reactive T cells in multiple tumors, such as non-small-cell lung cancer (NSCLC), melanoma and intrahepatic cholangiocarcinoma (ICC), and highlight their role of determining the responsiveness to immunotherapy. However, almost all the researches are focused on total neoantigen load at present, which predict immune response or prognosis only in small subset of tumors. Therefore, it is necessary to optimize the neoantigen load calculation to better predict clinical outcome of immune checkpoint therapy.

      Methods

      Tumor neoantigen load (oTNL) was optimized by counting neoantigen load selected from tumor clones which had ability of inducing immune elimination. We used a published method to quantify the DNA immune editing status for tumor clones, the number of neoantigen in the observed was lower than expected (immune editing score < 1) in a clone, suggesting immune-mediated elimination, and then neoantigen load was calculated. Tumor clonal architecture was calculated by PyClone. Three cohorts of immunotherapy-treated patients were collected from published and our own cohort. Clinical outcome including response and survival were compared between groups divided by oTNL score.

      Results

      We applied oTNL to three tumor immunotherapy cohorts, including 65 cases of NSCLC treated with anti-PD-1/PD-L1, 30 cases of melanoma treated with anti-PD-1 and 15 cases of ICC treated with anti-PD-1 plus lenvatinib. In the NSCLC cohort, the oTNL score of patients with durable clinical benefit (DCB, CR/PR/SD>6 month) was higher than those with non-durable clinical benefit (NDB, SD<6 month/PD) (median 62.62 vs 15.77, p = 0.025). The cut point of oTNL score was set at combined maximal sensitivity with best specificity. The DCB rate in oTNL-high patients was 55.00% versus 17.39% in oTNL-low patients (p = 0.0032). Progression-free survival (PFS) in patients with oTNL-high was longer than those with oTNL-low (median 146 vs 62 days, p = 0.00091). In the melanoma cohort, it was found that patients in oTNL-high group had higher objective response rate (ORR, CR/PR) than those in oTNL-low group (58.33% vs 5.56%, p = 0.026); the overall survival was longer (median 121 vs 39 weeks, p = 0.0062). Analysis of ICC cohort showed that longer PFS was also observed in oTNL-high group (median 7 vs 3.5 months, p = 0.023). For comparison, we also analyzed the correlation between total neoantigen load and clinical outcomes of three cohorts, but found no significant correlations.

      Conclusion

      It has been previously reported that tumor clones with neoantigen have immunogenicity and thus eliminated by T-cell-mediated immune editing. Moreover, genetic evidence of immune editing in lung cancer shows neoantigen may induce multiple routes to immune escape and affect tumor evolution. Therefore, not every neoantigen could induce immune elimination. Identifying neoantigen clones with the ability of inducing immune elimination would help to better predict the efficacy of immunotherapy. Our new optimized mathematical model could predict the response and prognosis of patients with lung cancer, melanoma and intrahepatic cholangiocarcinoma, and have better predicting value than prior's genetic method.

      Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.

      Only Active Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login or select "Add to Cart" and proceed to checkout.