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Y. Lu

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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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      P1.06-038 - Single Cell Genomic Analyses of Circulating Tumor Cells from Lung Cancer Patients (ID 2509)

      09:30 - 16:30  |  Author(s): Y. Lu

      • Abstract

      Circulating tumor cells (CTCs),which can be detected from peripheral blood, offer the potential for the assessment of clinical outcome. Whole genome sequencing of CTCs may provide comprehensive information related to tumor invasion and metastases, but has been hampered by their low abundance

      From 7.5 ml peripheral blood, we captured with the CellSearch platform a small numberof CTCs, which, after further isolation with 95% specificity, were subject to whole genome amplification with Multiple Annealing and Looping-Based Amplification Cycles (MALBAC). The individual CTCs’ copy number variations (CNVs) were determined by whole-genome sequencing, and their single nucleotide variations (SNVs) and insertions/deletions (INDELs) were detected by exome sequencing.

      We sequenced 24 CTCs from four patients with advanced lung adenocarcinoma and compared them with the matched primary/metastatic tumors. Patient 1 with EGFR mutation experienced a phenotypic transition from lung adenocarcinoma to small cell lung cancer in liver, and resistance to EGFR-TKIs. Individual CTCs from each patient exhibited reproducible copy number variation (CNV) patterns, which resembled those of the metastatic tumors. CTCs from different patients showed similar CNV patterns on certain chromosomes. Some rare single nucleotide variations (SNVs) and insertions/deletions (INDELs) in primary tumor, including those that may relate to drug resistance and phenotypic transition, were enriched in CTCs.

      CTCs exhibit highly reproducible CNV patternswhich offer a potential biomarker for cancer diagnosis and classification. The SNVs/INDELS in individual CTCs can be detected and provide molecular targets for personalized treatment.