Author of

• 25913

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  MA22 - New Therapeutics, Pathology, and Brain Metastases for Small Cell and Neuroendocrine Tumour (ID 925)

  • Event: WCLC 2018
  • Type: Mini Oral Abstract Session
  • Track: Small Cell Lung Cancer/NET
  • Presentations: 1
  • Moderators:
  • Coordinates: 9/25/2018, 15:15 - 16:45, Room 206 BD

  • 26150

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    MA22.03 - SCLC Circulating Tumour Cell Derived Explants: The Clinical Characteristics of Patients Whose Samples Generate CDX (ID 12969)

    15:25 - 15:30  |  Author(s): Mathew Carter
    • Abstract
    • Presentation
    • Slides

    Background
    

    Small cell lung cancer (SCLC) prognosis is dismal, with minimal improvement in recent years. Work with SCLC cell lines and targeted therapies have been disappointing when translated into clinical practice. Circulating tumour cells (CTCs) represent a readily accessible liquid biopsy, which can be used to generate CTC derived explants (CDXs) for the study of SCLC biology and the investigation of biomarkers and therapeutics. These clinically relevant models appear to mirror patient response to therapeutics. Our aim was to assess if the patients whose samples generated a CDX represent the SCLC population, and determine if the clinical features of these patients offer insight into CTC biology.

    a9ded1e5ce5d75814730bb4caaf49419 Method
    

    This was a single centre, retrospective analysis of 147 SCLC patients who had participated in The CHEMORES Study in which SCLC patients were asked to donate blood samples for the discovery and validation of novel biomarkers. Paired patient blood samples were taken for CTC enumeration using CellSearch Technology and for attempted CDX model generation. We obtained demographic and clinical information on these patients, and analysed the data for differences between patients whose blood samples generated a CDX and those whose did not.

    4c3880bb027f159e801041b1021e88e8 Result
    

    231 paired blood samples were taken from 147 patients, with 45 CDXs successfully generated from 34 patients. CTC number was significantly higher in samples which generated a CDX than those which didn’t, p=0.001. Successful progression samples had a significantly lower CTC number than successful baseline samples, p=0.026. There was no significant difference in age, gender, pack year history, performance status, stage, chemosensitivity or the presence of liver or brain metastases between patients whose samples did and did not generate a CDX. Metastatic burden was significantly higher in patients whose samples generated a CDX, p=<0.001. Progression free (PFS) and overall survival were significantly shorter in patients whose samples generated a CDX, p=<0.001

    8eea62084ca7e541d918e823422bd82e Conclusion
    

    CTC number correlates with CDX success, although a specific CTC phenotype may be more important. CTCs at progression may have a more aggressive phenotype than those at baseline. CDXs appeared to represent the SCLC population which is important when translating knowledge gained by studying CDXs into clinical practice. CTCs may play a role in the widespread metastatic dissemination of SCLC and thus survival of patients. Shortened PFS in the absence of difference in chemosensitivity may be due to outliers with particularly long PFS in the unsuccessful group. Further genomic and phenotypic analysis of subpopulations of CTCs may provide further insight.

    6f8b794f3246b0c1e1780bb4d4d5dc53

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• 25946

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  P2.09 - Pathology (Not CME Accredited Session) (ID 958)

  • Event: WCLC 2018
  • Type: Poster Viewing in the Exhibit Hall
  • Track:
  • Presentations: 1
  • Moderators:
  • Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall

  • 27071

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    P2.09-15 - A Next Generation Sequencing (NGS) RNA-Scan Multiplex Panel (QIAseq) to Identify Gene-Rearranged Non-Small Cell Lung Cancer (ID 12777)

    16:45 - 18:00  |  Author(s): Mathew Carter
    • Abstract
    • Slides

    Background
    

    Oncogenic fusion gene rearrangements are detected in up to 10% of advanced NSCLC with important therapeutic (eg. ALK, ROS1) or translational impact (eg. RET, NTRK1). The ‘QIAseq’ fusion panel is a 31-gene NGS multiplex assay that synchronously detects multiple oncogene fusion transcripts from formalin-fixed paraffin-embedded (FFPE) tissue derived RNA (Figure 1).

    a9ded1e5ce5d75814730bb4caaf49419 Method
    

    QIAseq analysis was undertaken in 33 samples (31 NSCLC samples, 2 commercial controls). 12/31 NSCLC samples were positive controls with a known fusion genotype identified by Quantide X NGS or FISH +/- RT-PCR. The remaining 19/31 fusion negative NSCLC controls included 6 samples with EGFR/KRAS/NRAS mutations. Analysis required a minimum 2x 5ųM thick FFPE scrolls with >30% neoplastic cell content. Manual RNA extraction was undertaken in all samples except n=6 (ExScale automation extraction). NGS fusion breakpoints, crossing and spanning reads were calculated in QIAseq fusion-detected samples. An additional validation cohort of 40 NSCLC samples, including 20 with unknown fusion status will optimise QIAseq thresholds for fusion detection.

    4c3880bb027f159e801041b1021e88e8 Result
    

    48 QIAseq sequencing experiments was undertaken in 33 samples with ≥2 sequencing runs in 12 samples. QIAseq analysis detected a corresponding NGS fusion breakpoint in 14/14 (100%) positive controls including EML4-ALK (n=8), CLTC-ALK (n=1), CD74-ROS1 (n=3), CCDC6-RET (n=1) and 5-fusion control (n=1). QIAseq analysis was negative in 17/19 (89.4%) negative controls samples including all KRAS (n=4), NRAS (n=1) and EGFR (n=1) mutation samples. QIAseq detected novel fusion gene CD74 Exon 6-CAMK2A Exon 2 in n=1 sample subsequently confirmed on Sanger sequencing. Two separate runs detected TPM3 Exon 8-S100A7A Exon 2 fusion in n=1 sample not identified with Sanger sequencing. Both fusions have uncertain clinical significance. Validation cohort results will be presented.

    8eea62084ca7e541d918e823422bd82e Conclusion
    

    QIAseq detects NSCLC oncogenic fusions with high sensitivity and specificity. Future applications include optimising use of small biopsy specimens for synchronous gene rearrangement screening and identification of novel gene fusion targets.

    6f8b794f3246b0c1e1780bb4d4d5dc53

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