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G.A. Meijer



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    P1.06 - Poster Session 1 - Prognostic and Predictive Biomarkers (ID 161)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Biology
    • Presentations: 1
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      P1.06-021 - Validation of DNA Hypermethylation Analysis in Sputum for the Diagnosis of Lung Cancer (ID 1774)

      09:30 - 16:30  |  Author(s): G.A. Meijer

      • Abstract

      Background
      Lung cancer has the highest mortality of all cancers worldwide with a 5 year survival rate of <15%. The prognosis improves dramatically when the disease is detected at an early stage, and when curative treatment is possible. Current (low dose CT) screening and diagnostic procedures are suboptimal with low specificity. Thus, novel detection methods for lung cancer as stand alone or in combination with other methods are needed. DNA hypermethylation of biomarkers in sputum have shown to distinguish lung cancer cases from cancer-free controls. The aim of the present study was to validate the usage of DNA hypermethylation of biomarkers in sputum samples of lung cancer patients and controls for lung cancer diagnosis, in comparison with sputum cytology.

      Methods
      We prospectively collected sputum of lung cancer patients and controls during 3-9 days in the Amsterdam and Nieuwegein area, The Netherlands. From this sputum bank, a learning set (n=80 lung cancer patients, n=91 controls) and validation set (n=173 lung cancer patients, n=164 controls) were randomly composed. DNA promoter hypermethylation of the following biomarkers was assessed by means of quantitative methylation specific PCR: RASSF1A, APC, cytoglobin, 3OST2, PRDM14, FAM19A4 and PHACTR3. Cut-off values for positive hypermethylation were calculated using Youden’s index. Sputum cytology analysis was performed for all sputum samples. McNemar’s test was used to compare the difference between sensitivity of hypermethylation and sputum cytology for lung cancer diagnosis. A two-sided p-value <0.05 was considered significant.

      Results
      RASSF1A was best able to distinguish cases from controls, with sensitivity of 37-41% and specificity of 91-97% in both learning and validation sets. In multivariate analysis, a panel of RASSF1A, 3OST2 and PRDM14 showed highest sensitivity of 82% [95% confidence interval (CI): 76 – 88%] with a specificity of 68% [95% CI: 61 – 74%] in the learning set, with consistent results in the validation set. Molecular analysis was superior (P<0.001) over sputum cytology (sensitivity of 15%). The sensitivity of the biomarker panel did not improve when it was combined with sputum cytology. There was no association observed between DNA hypermethylation and clinical parameters such as age, smoking status, tumor stage, and histology.

      Conclusion
      This study validates hypermethylation analysis in sputum for the diagnosis of lung cancer. RASSF1A hypermethylation showed high specificity and thereby can have an important role in lung cancer diagnosis in symptomatic patients. A panel of biomarkers RASSF1A, 3OST2 and PRDM14 showed high sensitivity, but relatively low specificity.

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    P2.20 - Poster Session 2 - Early Detection and Screening (ID 173)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Imaging, Staging & Screening
    • Presentations: 1
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      P2.20-004 - DNA copy number aberrations in endobronchial lesions: a validated predictor for cancer (ID 1166)

      09:30 - 16:30  |  Author(s): G.A. Meijer

      • Abstract

      Background
      Individuals who present with squamous metaplastic and dysplastic lesions are considered at high risk of lung cancer. However, these lesions behave erratically and only a minority progresses towards lung cancer. Therefore, biomarkers need to be discovered that can aid in assessing an individual’s risk for subsequent cancer. We recently identified a DNA copy number aberration (CNA)-classifier, including changes at 3p26.3-p11.1, 3q26.2-29, and 6p25.3-24.3, as a risk predictor for cancer in individuals presenting with endobronchial squamous metaplasia (van Boerdonk et al, AJRCCM, 2011). The current study was set out to validate this classifier in an independent series of endobronchial squamous metaplastic and dysplastic lesions.

      Methods
      DNA copy number profiles (i.e., chromosomal gains and losses) were determined in a set of endobronchial lesions (8 squamous metaplasia (SqM), and 28 dysplasias (Dys) of various grades), identified and biopsied during autofluorescence bronchoscopy, of 36 high-risk subjects using a nested case-control design. Of the 36 patients, 12 cases had a carcinoma in situ or invasive carcinoma at the same site at follow-up (median 11 months, range 4-24), while 24 controls remained cancer-free (median 78 months, range 21-142). DNA copy number profiles were related to lesion outcome. The prediction accuracy of the predefined CNA-based classifier to predict endobronchial carcinoma (in situ) in this series was determined.

      Results
      All SqM and Dys lesions of controls showed no or a relatively low number of CNAs (i.e., quiescent profile with on average 0.2% altered probe features, range 0.0 – 2.4%), while the majority of lesions of cases showed multiple CNAs (i.e. highly aberrant profile with on average 38.8% altered probe features, range 0.0 – 76.7%). The previously defined CNA-classifier demonstrated 92% accuracy for cancer (in situ) prediction in the current series. All nine subjects with CNA-classifier-positive endobronchial lesions at baseline had cancer as final outcome (i.e., a positive predictive value of 100%). The negative predictive value of the classifier was 89%, i.e., all 24 controls and 3 cases were classified as being low-risk.

      Conclusion
      CNAs are a highly accurate biomarker for assessing the progression risk of endobronchial squamous metaplastic and dysplastic lesions. This classifier could assist in selecting subjects with endobronchial lesions who might benefit from more aggressive therapeutic interventions.

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    P3.18 - Poster Session 3 - Pathology (ID 177)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Pathology
    • Presentations: 1
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      P3.18-021 - <strong>Array CGH is useful in the evaluation of patients with synchronic or metachronic tumors</strong> (ID 3380)

      09:30 - 16:30  |  Author(s): G.A. Meijer

      • Abstract

      Background
      Synchronic or metachronic tumors may develop in patients with a lung tumor. Determining whether these tumors originate from the same clone or are separate lesions may be challenging. Clinical, morphological and immunohistochemical criteria are often not distinctive. The aim of our study was to investigate comparative genomic hybridization (array CGH) analysis for the evaluation of clonality in patients with metachronic or synchronic tumors, having at least one intrathoracic tumor localization.

      Methods
      A database was constructed of consecutive patients (n=77) referred by clinicians or pathologists for assessment of clonality by array CGH from 2007 till 2012. All cases with at least one intrathoracic tumor were selected. The array CGH patterns were analyzed by a visual comparison of CGH patterns performed by two investigators and by two mathematical models on the raw data. One model uses a log likelihood ratio as described previously[1], the other a Pearson correlation between the segmented values. Clonality cut-off and p-values were set according to copy number profiles from individual patients, which are therefore by definition non-clonal. The results of the visual evaluation and the mathematical approach were correlated. A control group was formed by the specimens of one lung tumor from every patient in the database, which were all compared, using the mathematical models. 1. Ostrovnaya I, Seshan VE, Olshen AB, et al. Clonality: an R package for testing clonal relatedness of two tumors from the same patient based on their genomic profiles. Bioinformatics. 2011;27:1698-1699.

      Results
      Specimens of 77 patients were referred for analysis. Samples of 14 cases were not suited to array CGH due to insufficient material or bad quality of DNA. The remaining 63 cases comprised of 142 samples. In 8 patients DNA from more than 2 tumors was compared. In the mathematical model the outcome of 3 cases was missing, 23 cases were determined clonal, 22 non-clonal, 5 with clonal as well as non-clonal tumors and 10 were undetermined. In the negative control group > 96% of cases were scored as non-clonal. The visual analysis determined 40 cases clonal, 14 non-clonal, 1 with clonal as well as non-clonal tumors and 8 were undetermined. 46 cases were available for comparing the outcomes of the mathematical and visual evaluation, as for 3 cases data were missing and in 14 cases the outcome was undetermined. The concordance rate for clonal and non-clonal tumors between visual analysis and the mathematical approach was 35 out of 46 (76%). In 4 cases in which the visual judgment was clonal, the mathematical model determined clonal as well as non-clonal samples. In 7 cases discordance was noted: the visual outcome was clonal and the mathematical non-clonal.

      Conclusion
      Array CGH is a useful approach for evaluating clonality of synchronic or metachronic tumors.

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    P3.21 - Poster Session 3 - Diagnosis and Staging (ID 171)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Prevention & Epidemiology
    • Presentations: 1
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      P3.21-007 - <em>EGFR</em> mutation analysis in sputum of lung cancer patients: a multicenter multitechnique study (ID 1782)

      09:30 - 16:30  |  Author(s): G.A. Meijer

      • Abstract

      Background
      Mutations in the epidermal growth factor receptor (EGFR) gene have been identified in lung adenocarcinomas and are associated with a high response to EGFR tyrosine kinase inhibitors. EGFR mutations can be detected in tumour tissue, cytology specimens and blood from lung cancer patients. Thus far, EGFR mutation analysis has not been systematically demonstrated for sputum samples. The aim of the present study was to determine whether EGFR mutation analysis is feasible on sputum samples, employing different assays in a multicenter study.

      Methods
      Sputum samples were collected from 10 lung cancer patients with confirmed EGFR mutation in their tumour tissue, 10 lung cancer patients without evidence of an EGFR mutation, and 10 patients with chronic obstructive pulmonary disease (COPD). DNA was isolated from the sputum and used for mutation analysis by Cycleave PCR, COLD-PCR, PangaeaBiotech SL technology (PST), and High Resolution Melting, respectively. Targeted resequencing (TruSeq Amplicon Cancer Panel) and droplet digital PCR were additionally performed on the 10 samples with EGFR mutation.

      Results
      Dependent on the assay, EGFR mutations could be detected in 30-50% of the sputum samples of patients with EGFR mutations (Table). The different techniques revealed consistent results, with slightly higher sensitivity for PST. Neither the lung cancer patients without EGFR mutation nor the COPD controls tested positive for EGFR mutations in their sputum samples, indicating high clinical specificity of all assays.

      Subject Gender Age (years) Tumour stage EGFR mutation status of tumour tissue[1] EGFR mutation analysis on sputum specimens[2]
      Cycleave PCR COLD-PCR PST[3] HRM-sequencing Cytology[4]
      A F 72 IV Del E746-A750 0 0 0 0 0
      B M 66 I Del E746-A750 0 2 0 0 0
      C[6] F 78 IV Del E746-A750 1 1 1 1 2
      D F 46 III Del E746-A750 0 0 1 0 0
      E[6] M 54 IV Del E746-A750 1 1 1 1 0
      F F 49 III Del E746-A750 & c.2369C>T [p.T790M] 0 0 0 0 0
      G F 54 IV Del E746-A750 & c.2369C>T [p.T790M] 0 0 1[5] 0 1
      H F 73 IV c.2753T>G [p.L858R] 0 0 0 0 0
      I F 61 IV c.2753T>G [p.L858R] 0 0 0 0 0
      J[6] M 60 IV Del E746-A750 1 1 1 1 2
      [1 ]del E746-A750= deletion exon 19 [2] mutation identified: 0=no, 1=yes, 2=dubious [3] exclusively del19 and L858R were assessed [4] tumour cells: 0=no, 1=yes, 2=in related sample of same patient [5 ]only del19 detected [6 ]TSACP and ddPCR both tested EGFR mutation (del19) positive.

      Conclusion
      EGFR mutations can be detected in sputum samples from patients with EGFR-mutated non-small cell lung cancer, which may replace biopsy procedure for some patients.