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D. Lin



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    P2.01 - Poster Session with Presenters Present (ID 461)

    • Event: WCLC 2016
    • Type: Poster Presenters Present
    • Track: Biology/Pathology
    • Presentations: 1
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      P2.01-053 - PD-L1 Expression in Patients with Small Cell Lung Cancer (ID 4835)

      14:30 - 14:30  |  Author(s): D. Lin

      • Abstract

      Background:
      Small Cell Lung Cancer (SCLC) is a highly aggressive tumor. Alough most of SCLC cases are sensitive to chemotherapy, the prognosis of SCLC is still dismal. Programmed death-ligand 1 (PD-L1), which is expressed on many cancer cells, has been reported as a predictive biomarker for immune checkpoint inhibitors treatment in advanced non-small-cell lung cancer. However, expression of PD-L1 in SCLC has not been fully studied.

      Methods:
      Totally 72 surgical specimens of SCLC ( 42 primary, 30 metastasis) were involved in this study. Only 5 cases had received neoadjuvant chemotherapy before surgery while 67 cases did not. Rabbit anti-PD-L1 monoclonal antibody (Spring Bio, SP142,1:100) was used on tissue microarray to detect the expression of PD-L1 on these cases.

      Results:
      PD-L1 was strongly expressed on the membrane of tumor cells of 8 cases (11.1%) and in the immune stroma of 35 cases (48.6%). Another 29 cases (40.3%) were totally negative for PD-L1 staining. Expression of PD-L1 was significantly associated with tumor sites (primary, P=0.017) and had a trend of low lymphonode metastasis(P=0.057). There was no significant correlation between PD-L1 expression and other clinical-pathological parameters (age, gender, T staging, nodal status, TNM staging, vascular invasion and treatment).

      Conclusion:
      PD-L1 was expressed in more than half of SCLC cases and correlated with tumor sites. These data may provide useful information for future research or clinical trial on immune checkpoint therapy for SCLC.

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

    • Event: WCLC 2016
    • Type: Poster Presenters Present
    • Track: Advanced NSCLC
    • Presentations: 1
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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 - 14:30  |  Author(s): D. Lin

      • 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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