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M. Thomas



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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): M. Thomas

      • 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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    OA 06 - Global Tobacco Control and Epidemiology I (ID 662)

    • Event: WCLC 2017
    • Type: Oral
    • Track: Epidemiology/Primary Prevention/Tobacco Control and Cessation
    • Presentations: 1
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      OA 06.07 - Survival Trends Among Non-Small Cell Lung Cancer (NSCLC) Patients Over A Decade: Impact of Initial Therapy at Academic Centers (ID 10149)

      15:45 - 17:30  |  Author(s): M. Thomas

      • Abstract
      • Presentation
      • Slides

      Background:
      Treatment of NSCLC is rapidly advancing and academic centers are considered equipped with better expertise. NSCLC outcome trends in novel therapeutic era and impact of initial treatment at academic centers have not been reported.

      Method:
      The National Cancer Database (NCDB) with NSCLC incident cases between 2004-2013 was used. Overall survival (OS) was plotted by year of diagnosis and type of treatment facility, accounting for several available factors in NCDB.

      Result:
      A total of 1,150,722 NSCLC patients were included and separated by initial treatment facility type (academic: 31.5%, non-academic: 68.5%). Several characteristics were significantly different between the two cohorts (Table 1). Median OS for all patients was 13.1 months and improved significantly for those diagnosed in 2010-2013 (14.8 months) as compared to 2004-2009 (12.4 months) (p<0.001). Treatment at academic centers was associated with reduced risk of death [Multivariate HR=0.91 (95% CI 0.906-0.919), P<0.001]. Four-year OS for academic and non-academic cohorts was 25% and 19%, respectively (p<0.001), the difference more pronounced in stage 1-3. (Figure 1) Figure 1 Figure 2





      Conclusion:
      In this largest analysis thus far, NSCLC survival has improved over time and type of treatment facility significantly influences survival. Factors influencing treatment facility choice should be addressed for easier access to academic centers.

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