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Y. Asmann



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    MA 05 - Immuno-Oncology: Novel Biomarker Candidates (ID 658)

    • Event: WCLC 2017
    • Type: Mini Oral
    • Track: Immunology and Immunotherapy
    • Presentations: 1
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      MA 05.01 - Integrating INDEL Mutations into Neoantigen Prediction in Lung Cancer: Developing Personalized Cancer Vaccines  (ID 10150)

      15:45 - 17:30  |  Author(s): Y. Asmann

      • Abstract
      • Presentation
      • Slides

      Background:
      Mutant neoantigens generated from genetic alterations that are exclusively present in tumors represent highly promising cancer vaccine targets. However, publically available neoantigen prediction algorithms only identify and utilize single nucleotide mutations (SNVs) but not short insertion and deletions (INDELs). Short INDELs can lead to the generation of novel junctional or frameshift neoantigens which may be more immunogenic than neoantigens that result from single nucleotide missense mutations.

      Method:
      We developed a bioinformatics pipeline for neoantigen prediction using paired normal tissue and tumor exome sequencing, RNA sequencing and HLA binding prediction. 536 lung adenocarcinoma (LUAD) and 466 lung squamous cell carcinoma (LUSC) cases were analyzed using our bioinformatics pipeline. The non-synonymous somatic SNVs and short INDELs mutations were identified to generate a list of mutation neoantigen-derived and, when possible, their corresponding wild-type epitopes. Binding affinities of the paired wild-type and mutant peptides to HLA class I were then predicted and compared.

      Result:
      On average, 8.65 (range1-158) mutant neoantigen peptides per sample were identified in 395 out of 536 (73.6%) LUAD samples. Among them, 63.7% were SNVs and 36.3% were INDELs. On average, 8.54 (range 1-504) mutant neoantigen peptides per sample were identified in 360 out of 466 LUSC samples. Among those, 67% were SNVs and 33% were INDELs. Most neoantigen peptides are private in both LUAD and LUSC. The mutant neoantigen peptides identified from INDELs were predicted to have 3.9 (p = 2.42E-74) and 1.14 (p = 5.44E-67) fold higher HLA class I binding affinity than wild type peptide compared to those from SNVs in LUAD and LUSC respectively.

      Conclusion:
      Tumor INDELs may be a rich source of neoantigens with a higher predicted high HLA binding affinity in lung cancers that warrant consideration in development of a personalized cancer vaccine.

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