Author of

• 16549

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  P1.02 - Poster Session with Presenters Present (ID 454)

  • Event: WCLC 2016
  • Type: Poster Presenters Present
  • Track: Biology/Pathology
  • Presentations: 1
  • Moderators:
  • Coordinates: 12/05/2016, 14:30 - 15:45, Hall B (Poster Area)

  • 16580

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    P1.02-031 - Mutations in TP53, PIK3CA, PTEN and Other Genes in EGFR Mutated Lung Cancers: Correlation with Clinical Outcomes (ID 5254)

    14:30 - 14:30  |  Author(s): P. Vanderlaan
    • Abstract
    • Slides

    Background:
    The degree and duration of response to epidermal growth factor receptor (EGFR) inhibitors in EGFR mutated lung cancer are heterogeneous. We hypothesized that the concurrent genomic landscape of these tumors, which is currently largely unknown in view of the prevailing single gene assay diagnostic paradigm in clinical practice, could play a role in clinical outcomes and/or mechanisms of resistance.
    
    Methods:
    We retrospectively probed our institutional lung cancer patient database for tumors harboring EGFR kinase domain mutations that were also evaluated by more comprehensive molecular profiling, and assessed tumor response to EGFR tyrosine kinase inhibitors (TKIs).
    
    Results:
    Out of 171 EGFR mutated tumor-patient cases, 20 were sequenced using at least a limited comprehensive genomic profiling platform. 50% of these harbored concurrent TP53 mutation, 10% PIK3CA mutation, and 5% PTEN mutation, among others. The response rate to EGFR TKIs, the median progression-free survival (PFS) to TKIs, the percentage of EGFR-T790M TKI resistance and survival were higher in EGFR mutant/TP53 wild-type cases when compared to EGFR mutant/TP53 mutant tumors; with a significantly longer median PFS in EGFR-exon 19 deletion mutant/TP53 wild-type cancers treated with 1st generation EGFR TKIs.
    
    Conclusion:
    Concurrent mutations, specifically TP53, are common in EGFR mutated lung cancer and may alter clinical outcomes. Additional cohorts will be needed to determine if comprehensive molecular profiling adds clinically relevant information to single gene assay identification in oncogene-driven lung cancers.
    
    

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