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  P3.06 - Poster Session 3 - Prognostic and Predictive Biomarkers (ID 178)

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

  • 12488

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    P3.06-048 - Progress with candidate predictive gene expression signatures for MEK inhibitors in non-small cell lung cancer (NSCLC) (ID 3243)

    09:30 - 09:30  |  Author(s): R. McEwen
    • Abstract

    Background
    Several MEK inhibitors are in late-stage clinical trials in mutant BRAF melanoma, where novel patient selection biomarkers are not major impediments to clinical development. In non-mutant BRAF disease, there is a presumption that the optimum patient population may also be selected according to gain of function mutations in key genes, resulting in pathway activation. In the present work we have taken a different approach, based on two publications (Dry et al. Cancer Res 2010;70:2264–2273; Loboda et al. BMC Med Genomics 2010;3:26), attempting to define NSCLC patient populations for MEK inhibitors based on gene expression signature measurements of pathway output.

    Methods
    In silico analyses were performed to test the sensitivity of candidate transcriptome signatures for detecting KRAS mutations in NSCLC. NanoString assays were subsequently developed for the signatures and used in: i) cell line based cross-platform comparisons with Affymetrix technology ii) formalin-fixed paraffin-embedded (FFPE) NSCLC samples to determine measurable genes, variation in gene expression and the limit of quantification for the signatures iii) matched tumour samples from the same patients iv) a blinded cohort of 50 NSCLC samples with known KRAS mutation status.

    Results
    In silico data confirmed the published correlations of transcriptome signatures with KRAS status in NSCLC samples. NanoString data appear to be robust, demonstrating a strong correlation with the Affymetrix platform and reproducible signature scores across separate samples from the same tumour. Reproducibility is maintained across dilutions of the same isolated RNA sample and supports previous observations regarding the sensitivity of these signatures for detecting KRAS mutations in clinical samples. In addition, we showed that high expression of these signatures is not restricted to samples with KRAS mutation, confirming previous observations that RAS or MEK activation is not exclusively linked to KRAS mutation.

    Conclusion
    We have developed a clinically relevant, robust assay platform, determined biological variation within tumours and confirmed the link to KRAS mutation status in a cohort of blinded NSCLC samples. The NanoString assays provide a means to test the prognostic and predictive capabilities of the gene signatures in the samples routinely provided in clinical practice. We intend to test the concordance of the gene signature indices between primary and metastatic tumours from the same patients, the prognostic relevance of the signatures in first- and second-line NSCLC patients treated with standards of care and wherever possible in future clinical trials of MEK inhibitors.