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X. Meng



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    P1.02 - Poster Session with Presenters Present (ID 454)

    • Event: WCLC 2016
    • Type: Poster Presenters Present
    • Track: Biology/Pathology
    • Presentations: 1
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      P1.02-023 - Application of an Amplicon-Based NGS Strategy in the Molecular Diagnosis of NSCLC: Comparable Performance with FISH and ARMS-PCR (ID 4967)

      14:30 - 15:45  |  Author(s): X. Meng

      • Abstract
      • Slides

      Background:
      Next generation sequencing (NGS) enables us to detect comprehensive genetic aberrations within a tumor sample, which provides potential alternative to well adopted clinical diagnostic approaches such as amplification refractory mutation system PCR (ARMS-PCR) and FISH. However, there is no enough data to illustrate the overall concordance between NGS with traditional clinical diagnostic approaches. This study is aimed to fill in this blank.

      Methods:
      We have used 20 cell lines from ATCC and 19 FFPE samples to construct molecular standards and there are 50, 34 and 48 samples for SNV and Indel, CNV and fusion, respectively. All the mutations were verified by Sanger sequencing or QuantStudio 3D digital PCR. To assess the performance of NGS, an amplicon-based NGS strategy was used to detect gene mutations in molecular standards. In order to illustrate the overall concordance between NGS with ARMS-PCR and FISH, we further verified NGS in 2500 retrospective FFPE samples from non-small lung cancer (NSCLC) and breast cancer patients.

      Results:
      So far, we have detected genetic aberrations in 108 FFPE samples. For SNV and Indel, we focused on the mutation profile of EGFR, KRAS, BARF and PIK3CA, which were the most common mutations in NSCLC. In molecular standards, 34 of 50 (68%) were positive for Sanger and 33 of 50 were positive for NGS, thus the sensitivity, specificity and accuracy was 97%, 100% and 98%, respectively. In FFPE samples from 31 lung cancer patients, NGS results were consistent with ARMS-PCR. For CNV, in molecular standards, the copy number of HER2, MET, EGFR and FGFR1 detected by NGS was high consistent with digital PCR and R[2 ]was 0.9673. In FFPE samples from 45 breast cancer patients, 80% of cases (36/45) were HER2 amplification positive and 20% (9/45) were negative for FISH, 34 HER2 positive and 9 HER2 negative for FISH were also classified by NGS. Thus, the overall concordance between NGS and FISH were 95.56%. For ALK and ROS1 gene fusion, the overall concordance were both 100% in 48 molecular standards (NGS versus Sanger sequencing) and 32 FFPE samples (NGS versus FISH).

      Conclusion:
      Our result reveal that the amplicon-based NGS strategy for detecting genetic aberrations is of high accuracy and comparable with standard clinical diagnostic approaches, and therefore provides a promising diagnosis approach for clinical in the future.

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    P2.03b - Poster Session with Presenters Present (ID 465)

    • Event: WCLC 2016
    • Type: Poster Presenters Present
    • Track: Advanced NSCLC
    • Presentations: 2
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      P2.03b-073 - High Concordance of Somatic SNVs between Tumor-Only and Tumor-Normal Testing: Implications for Clinical Practice (ID 4837)

      14:30 - 15:45  |  Author(s): X. Meng

      • Abstract
      • Slides

      Background:
      Typically, somatic mutations are detected by comparing sequencing data from tumor and matched normal samples. However, the normal control is not always available in many practical situations. Moreover, it is cost-intensive to sequence and analyze tumor-normal pairs in clinical application, especially when hundreds of genes are targeted. Therefore, it is imperative to explore the possibility of identifying somatic mutations without matched normal control.

      Methods:
      To fulfill the need, we firstly carry out the following preparation based on the mutations detected by MuTect: (i) construct a set of 430 white blood cell samples from tumor patients to serve as VirtualControl, and (ii) build MutectRepeat using variations from 321 tumor samples (blood or tissue). Subsequently, a comprehensive analysis was performed to identify the somatic SNVs from tumor-only testing: (i) call candidate somatic mutations with MuTect using the same parameters as in tumor-normal testing; (ii) pick out the SNPs with the aid of 1000 Genomes Project, ExAC and VirtualControl; (iii) calculate the mean frequency of the SNPs on a specific genomic segment to serves as the expected allele frequency for a germline mutation to occur on the segment; (iv) perform Z test for each candidate variation and calculate the corresponding Z-score; (v) discriminate the somatic variants from background mutations according to the Z-score, My Cancer Genome, VirtualControl and MutectRepeat.

      Results:
      We present SomaticExcavator, a solution for the identification of somatic SNVs using tumor-only NGS-based test that targets 483 cancer-related genes. To evaluate the consistency of SomaticExcavator with classical tumor-normal analysis, 275 tumor-only or tumor-normal tests were conducted separately. It demonstrates that, 74 percent of tumor-only tests achieve 95% or higher concordance with corresponding tumor-normal tests.

      Conclusion:
      In summary, the strategy we present here shows power in providing reliable results of somatic SNVs in the absence of matched normal control, which offers a solution for those whose matched normal controls are not available. Furthermore, with the advantage of reducing the cost of somatic variant calling, it has the potential to enlarge the population of cancer patients who can benefit from personalized medicine.

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      P2.03b-098 - Comparison of Digital PCR, Ion Proton with ARMS-PCR in Tumor Tissue and Plasma of NSCLC Patients (ID 5544)

      14:30 - 15:45  |  Author(s): X. Meng

      • Abstract

      Background:
      Deletions in exon 19 and heterozygous mutations (e.g. L858R) in exon 21 are the mutation hotspots of EGFR mutations, which are validated to be sensitive to EGFR-TKI, while exon 20 T790M mutation of EGFR is resistant to EGFR-TKI. A biopsy is needed to characterize EGFR mutation status. However, the amplification-refractory mutation system PCR (ARMS-PCR) is limited to detect mutation frequency below 1%. The QuantStudio 3D Digital PCR (digital PCR) and NGS were new promising techniques for low frequency mutations detection. In current study, we identified the EGFR L858R, T790M and exon 19 Del using a customized Ion AmpliSeq panel and digital PCR, then compared the detection with ARMS-PCR. Besides, in need of liquid biopsy, we also assessed the consistence between tumor tissue and circulating DNA (ctDNA) in digital PCR platform.

      Methods:
      A total of 27 NSCLC patients with stage III/IV were enrolled, paired tumor tissue and plasma (within 7 days before/after tumor biopsy) were collected. ARMS-PCR were provided by hospital. DNA from tumor tissue was sequenced in Ion Proton system with a customized panel based on Ion Ampliseq Colon and Lung Cancer Research Panel and analyzed using digital PCR. The ctDNA was only detected in digital PCR. Mutation frequency was determined and analyzed to reveal the consistency of platforms or sample types.

      Results:
      Compared with ARMS-PCR identification in tumor tissues of 27 patients, all of the corresponding mutation status were identified in Ion Proton and digital PCR, while the specificity is 95.00% and 85.07% respectively. Compared with Ion Proton, digital PCR achieved 100% sensitivity and 89.06% specificity. Ion Proton identified two more T790M mutations, digital PCR identified other six T790M mutations and one L858R mutation with frequency between 0.1%-1%. For the tumor tissue mutations identified by Proton and digital PCR, the Spearman’s rank correlation coefficient showed a strong positive correlation (R[2]=0.9711). In digital PCR platform, plasma had 62.50% sensitivity, 100% specificity and 88.89% concordance with tumor tissue. However, the frequency called by plasma was lower than that of tumor tissue. Plasma in digital PCR had a sensitivity of 81.25%, specificity of 96.97% and total concordance of 93.95%.

      Conclusion:
      This study demonstrated comparable capacity of mutation detection using Proton and digital PCR compared with ARMS-PCR. Digital PCR could identify lower frequency mutations than Ion Proton. The ctDNA showed strong specificity detection in patients with NSCLC, while it also indicated that the lower frequency in tumor tissue, the less possibility to be detected in plasma.