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R. Brant



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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
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      P2.06-019 - EGFR mutation detection in ctDNA isolated from NSCLC patient plasma; a cross-platform comparison of leading technologies (ID 1797)

      09:30 - 09:30  |  Author(s): R. Brant

      • Abstract

      Background
      The diagnosis and treatment of non-small cell lung cancer (NSCLC) was revolutionised with the discovery of epidermal growth factor receptor (EGFR) activating mutations and the corresponding treatment of mutation-positive cancers with EGFR tyrosine kinase inhibitors (EGFR-TKI, i.e. gefitinib, erlotinib). While EGFR-TKI’s are highly effective in this setting, patients invariably relapse due to acquired resistance to the targeted therapy. In approximately 50% of the cases, resistance to gefitinib and erlotinib is associated with a T790M mutation that renders the EGFR tumor molecule unresponsive to these inhibitors. A number of 2[nd] and 3[rd] generation inhibitors are currently in development to address the primary T790M resistance mechanisms (afatinib, AZD9291, Clovis 1686). Identifying the relevant patient population for such drugs may rely on diagnostic analysis of re-biopsy material to determine the mechanism of acquired resistance. However, such invasive surgical procedures may present a significant challenge in a proportion of patients with EGFR TKI-resistant disease. Availability of a reliable, minimally invasive method to assess the EGFR mutation status of NSCLC patients could have major clinical benefits for patients and support access to novel targeted therapies. Recently, several highly sensitive technologies have been described for detection of EGFR mutations in the small amount of tumor DNA that is shed into the circulating plasma (ctDNA). ctDNA has potential as a minimally-invasive alternative to surgical biopsies and as such, holds promise for disease diagnosis and early assessment of disease progression.

      Methods
      We undertook a comprehensive cross-technology comparison of three technology platforms for detection of T790M mutation in ctDNA extracted from patient plasma: 1) ARMS-based detection using the Roche cobas® EGFR mutation detection kit; 2) digital droplet PCR using the BioRad ddPCR instrument (by MolecularMD); and 3) bead-based digital PCR using the Inostics BEAMing technology. In total, 140 frozen plasma samples (approximately 80 EGFR mutation +ve and 60 EGFR mutation -ve), obtained from EGFR-TKI resistant patients enrolled on two AstraZeneca clinical studies were used to assess mutation prevalence, false negative, and false positive rates. Each individual patient plasma sample was split and evaluated across multiple platforms. ctDNA was extracted and tested by operators blinded to the EGFR tumor mutation result for 3 common mutations (Exon 19 deletion E746_A750delELREA, L858R and T790M). The EGFR mutations status of patient-matched tumor biopsies was available for all plasma samples to allow for ctDNA-tumor concordance testing.

      Results
      Overall, concordance of EGFR mutation status was high between all 3 methods. In addition, the false positive rate in the known EGFR mutation -ve cases was low for all 3 methods. However, differences were seen in the rate of false negative results (assay sensitivity) between methods, with digital PCR showing increased assay sensitivity compared with the ARMS based method. A comprehensive comparative analysis for all 3 technologies will be presented.

      Conclusion
      Digital droplet and BEAMing PCR platforms both provide sensitive detection of EGFR mutations in ctDNA isolated from circulating plasma. Importantly, both platforms also provide results in relation to wild-type EGFR molecules, allowing for quantification EGFR mutation load

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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
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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. Brant

      • 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.