Author of

• 11543

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  P2.06 - Poster Session 2 - Prognostic and Predictive Biomarkers (ID 165)

  • Event: WCLC 2013
  • Type: Poster Session
  • Track: Biology
  • Presentations: 1
  • Moderators:
  • Coordinates: 10/29/2013, 09:30 - 16:30, Exhibit Hall, Ground Level

  • 11548

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    P2.06-005 - The High Incidence of Overlap between Actionable Biomarkers in NSCLC: Potential Impact on Future Clinical Trial Design (ID 360)

    09:30 - 09:30  |  Author(s): L.C. Amler
    • Abstract

    Background
    Recent advances in molecular profiling of non-small cell lung cancer (NSCLC) have led to the replacement of platinum-based chemotherapy with targeted therapies for certain genetic subsets of NSCLC (ALK rearrangements, some EGFR activating mutations). It is also known that myriad pathways can drive resistance, the unfortunate norm for most patients. A greater understanding of the overlap across multiple biomarker subsets, including activating mutations, signal transduction pathways, and immune system markers, might aid in prognostic assessment, predictive biomarker development and the design of combination or sequential treatment regimens.

    Methods
    The prevalence and prognostic significance of nine biomarkers (TTF1, p63, EGFR mutation, KRAS mutation, MET immunohistochemistry [IHC], PDL1 IHC, PTEN IHC, NaPi2B IHC, ECDH IHC) across two independent sample sets (Set 1, n=561; Set 2, n=300) were tested. With the exception of ECDH, all assays were IVD or companion diagnostics. Set 1 was collected from patients who were eligible for surgery with curative intent from 2003–2005 at MD Anderson Cancer Center in the USA. Samples from Set 2 were part of a collaboration between the University of Colorado Cancer Center, USA and The Norwegian Radium Hospital, and contained surgically-resected NSCLC tissues collected from 2006–2011.

    Results
    The prevalence of each biomarker varied significantly by histology. For adenocarcinoma samples, the prevalence of each biomarker was: EGFR mutation (13%), KRAS mutation (29%), TTF1 IHC (83%), p63 IHC (7%), MET IHC (50%), PDL1 IHC (45%), PTEN loss IHC (11%), NaPi2B IHC (76%), EGFR IHC (FLEX cut-off, 11%). In squamous-cell carcinoma, the prevalence of each biomarker was: TTF1 IHC (2%), p63 IHC (87%), MET IHC (13%), PDL1 IHC (50%), PTEN loss IHC (13%), NaPi2B IHC (3%), EGFR IHC (FLEX cut-off, 40%). In addition, more than 67% of patients were positive for more than one biomarker and >33% were positive for at least three biomarkers. The diagnostic criteria for each biomarker and correlations with patient characteristics will be described in further detail. Figure 1. Biomarker Overlap in Adenocarcinoma in Set 1 (n=337) Figure 1

    Conclusion
    Collectively, these data suggest that the biomarker landscape in NSCLC is complex and will be increasingly dynamic as more experimental agents approach pivotal testing. Grant support: this study was partially funded by UT Lung Specialized Programs of Research Excellence grant (P50CA70907; IIW)