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S.J. Yoon



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    MO12 - Prognostic and Predictive Biomarkers III (ID 96)

    • Event: WCLC 2013
    • Type: Mini Oral Abstract Session
    • Track: Medical Oncology
    • Presentations: 1
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      MO12.11 - The predictive role of common BIM deletion polymorphism and BIM expression on the EGFR-TKI therapy in never-smoking lung adenocarcinoma (ID 2161)

      11:30 - 11:35  |  Author(s): S.J. Yoon

      • Abstract
      • Presentation
      • Slides

      Background
      The BCL-2 homology domain 3 (BH3)-only protein, B-cell lymphoma 2 interacting mediator of cell death (BIM) is a potent pro-apoptotic protein. Recent data suggest that pretreatment BIM level may predict responsiveness to EGFR-TKI in EGFR-mutant non-small cell lung cancer (NSCLC). In addition, a common BIM deletion polymorphism contributes to the heterogeneity of response to EGFR-TKI in EGFR-mutant NSCLC. We investigated whether BIM expression and BIM deletion polymorphism (BIM-DEL) are predictive for response rate (RR) and progression-free survival (PFS) to EGFR-TKI therapy in never-smoking lung adenocarcinoma (NSLA).

      Methods
      We analyzed EGFR mutation status by Sanger sequencing, BIM-DEL genotyping by polymerase-chain reaction and BIM expression by immunohistochemistry using archival tissues or blood from 203 patients who participated in the FIRST-SIGNAL trial (1[st] line gefitinib vs. Gemcitabine/cisplatin in advanced NSLA).

      Results
      EGFR mutation test, BIM-DEL genotyping and BIM-IHC analysis were available in 82, 126 and 60 patients, respectively. Forty-five (55%) patients had EGFR mutations, 22 (18%) showed BIM-DEL and 22 (37%) showed negative BIM expression. BIM expression was significantly associated with EGFR mutation status; more patients with EGFR-mutant NSCLC showed negative BIM expression (48% vs. 21%, P=0.030). BIM-DEL was not associated with EGFR mutation status or BIM expression. Among 181 patients who received EGFR-TKI as 1[st] or 2[nd]-line therapy, EGFR mutation, BIM-DEL and BIM expression data were available in 74, 11, 56 patients, respectively. EGFR mutation was predictive for higher RR (66% vs. 15%, P<.001) and longer PFS (4.5 vs. 1.9 months, P=.061) to EGFR-TKI therapy. Negative BIM expression also showed a trend toward higher RR (68% vs. 42%, P=.061) and longer PFS (6.9 vs. 2.3 months, P=.233) with EGFR-TKI. However, BIM-DEL was not predictive for RR (41% vs. 47%, P=.645) or PFS (3.5 vs. 3.7 months, P=.892) to EGFR-TKI.

      Conclusion
      Both BIM-DEL and BIM expression were not predictive for responsiveness to EGFR-TKI in NSLA. The trend between negative BIM expression and favorable response to EGFR-TKI may be resulted from higher frequency of EGFR mutation in these patients.

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    P2.03 - Poster Session 2 - Technology and Novel Development (ID 151)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Biology
    • Presentations: 1
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      P2.03-004 - Clinical application of targeted deep sequencing as a molecular screening for epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) therapy in never-smoking lung adenocarcinoma (ID 2170)

      09:30 - 09:30  |  Author(s): S.J. Yoon

      • Abstract

      Background
      The molecular screening is a key step to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) therapy. We investigated the clinical relevance of targeted next generation sequencing (NGS) as a molecular screening for EGFR-TKI therapy in never-smoking lung adenocarcinoma (NSLA).

      Methods
      We obtained DNA from 48 NSLA received gefitinib or erlotinib for their recurrent disease after surgery. The Sanger sequencing and peptide nucleic acid clamp polymerase chain reaction (PCR) were used to analyze EGFR, KRAS, BRAF and PIK3CA mutations. We analyzed ALK, RET and ROS1 rearrangements by fluorescent in situ hybridization or reverse transcriptase-PCR and quantitative real-time PCR. Finally, Ion Torrent NGS was performed in 31 cases harboring only EGFR exon 19 deletions (19DEL) or L858R mutation or none of above mutations.

      Results
      After excluding mutations other than EGFR 19DEL or L858R, samples were divided into 4 groups; 1) responders to EGFR-TKIs with only 19DEL or L858R (n=15); 2) primary resistance to EGFR-TKI with only 19DEL or L858R (n=4); 3) primary resistance to EGFR-TKI without any mutations (n=8); 4) responders to EGFR-TKI without any mutations (n=4). All conventionally detected mutations were confirmed with NGS. Additionally uncovered predictive mutations include; one PIK3CA E542K and one BRAF in group 2; two KRAS (G12V and G12D), one PIK3CA E542K and one concomitant PIK3CA and EGFR L858R in group 3; one EGFR 19DEL in group 4. Newly detected mutations were validated by Sanger sequencing.

      Conclusion
      Targeted NGS provided more accurate and clinically useful molecular classification of NSLA. It may improve personalized therapy for individual patients.