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Z. Jiang



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    MA 11 - Emerging Diagnostic/Biomarkers in NSCLC (ID 668)

    • Event: WCLC 2017
    • Type: Mini Oral
    • Track: Advanced NSCLC
    • Presentations: 1
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      MA 11.05 - Targeted DNA- and RNA-Based Next-Generation Sequencing for Identifying MET Exon 14 Alterations in Pulmonary Sarcomatoid Carcinoma (ID 9266)

      11:00 - 12:30  |  Author(s): Z. Jiang

      • Abstract
      • Presentation
      • Slides

      Background:
      Highly diverse somatic splice site alteration at MET exon 14 (METex14) result in exon skipping, which is supposed to be a therapeutic target in NSCLC. Here we report detection of METex14 alterations using targeted DNA- and RNA-based Next-Generation Sequencing (NGS) in pulmonary sarcomatoid carcinoma (PSC) with a high frequency of METex14 skipping.

      Method:
      Tumor specimens were collected from 77 Chinese PSC patients. DNA and RNA were subject to targeted NGS, allowing the detection of somatic splice site alterations and intragenic METex14 skipping respectively. Then, somatic mutations (mutation allele frequency ≥2%) that lead to METex14 skipping were recognized, and Fisher’s exact test was used to examine the association between METex14 skipping and clinical characteristics or other mutations. Two-sided P-values <0.05 were considered statistically significant. Moreover, RT-PCR and Sanger sequencing was also performed on the METex14-positive specimens.

      Result:
      We have detected genetic aberrations in 77 FFPE samples. For RNA-based NGS, METex14 skipping was identified in 16 (20.78%) of 77 patient cases. And 15 (93.75%) METex14-positive patients were detected somatic mutations by DNA-based NGS, including 12 (80%) cases with splice donor site mutations, 1 (6.67%) cases with splice acceptor site alterations, 1 (6.67%) case with a novel deletion (chr7: 116411868 - 116411883) at MET intron 13 region and 1 (6.67%) case with a novel deletion (chr7: 116412027 - 116412042) at MET exon14 region. In this study, 6 somatic mutations which induce METex14 skipping were firstly discovered. So far, RT-PCR and Sanger sequencing were performed on 3 specimens, including 1 sample with conflicting RNA- and DNA-based NGS results and 2 samples with unreported somatic deletions. According to the results of RT-PCR and Sanger, the unmatched sample was false negative on the basis of DNA-based NGS result. Interestingly, METex14 skipping was mutually exclusive with other recognized genomic alterations (such as mutations in KRAS, BRAF, EGFR, NRAS and PIK3CA), while no significant difference was found between METex14 skipping and single driver gene.

      Conclusion:
      Mutational events of MET leading to exon 14 skipping are frequent occurred in Chinese PSC patients. DNA-based NGS could discover new somatic mutations which results in METex14 skipping. However, RNA-based NGS could provide more accurate results than DNA-based NGS. METex14 skipping was mutually exclusive with other drivers, thus strongly highlighting its potential oncogenic role.

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    P2.02 - Biology/Pathology (ID 616)

    • Event: WCLC 2017
    • Type: Poster Session with Presenters Present
    • Track: Biology/Pathology
    • Presentations: 1
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      P2.02-006 - NovoSV: Identify and Parse the Pattern of Chromosomal Structural Variation (ID 8283)

      09:30 - 16:00  |  Author(s): Z. Jiang

      • Abstract
      • Slides

      Background:
      With the development of High-throughput DNA sequencing technologies, several tools have been developed aim at searching structural variations. However, most of available structural variation predication tools can only identity the abnormal connections, a systematically parsing the pattern of structure variation to obtain the length and connection type of SVs is still tough work.

      Method:
      In this study, we present a tool, NovoSV, which can identify the abnormal connections precisely, and based on associated abnormal connections NovoSV will report the length and connection type of the structural variation.

      Result:
      NovoSV took a BWA mapped results as input and identified abnormal connections and pattern of chromosomal structure variations would be reported. For validation, NovoSV was applied to target sequencing data derived from 10 samples, NovoSV identified 8 abnormal connections, and 7 of these results could be validated by polymerase chain reaction (PCR). When applied to whole-genome sequencing data derived from 5 samples, NovoSV reported 46 SVs with their length and connection type. Of the 4 random selected identified results, 3 were validated by Sanger sequencing.

      Conclusion:
      NovoSV is an efficient tool for chromosomal variation detection, which can accurately identify abnormal connections and parse the pattern of chromosomal variations. NovoSV has been validated on GNU/Linux systems, and an open source PERL program is available.

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