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Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

4215 - Clinical characterization of rare EGFR mutations in non-small cell lung cancer and in silico prediction of drug sensitivity

Date

20 Oct 2018

Session

Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

Presenters

Shinnosuke Ikemura

Citation

Annals of Oncology (2018) 29 (suppl_8): viii493-viii547. 10.1093/annonc/mdy292

Authors

S. Ikemura1, H. Yasuda2, S. Matsumoto3, M. Kamada4, T. Betsuyaku2, Y. Okuno4, K. Goto3, K. Tsuchihara5, K. Soejima6

Author affiliations

  • 1 Cancer Center, Keio University School of Medicine, 160-8582 - Tokyo/JP
  • 2 Department Of Pulmonary Medicine, Keio University School of Medicine, 1608582 - Tokyo/JP
  • 3 Department Of Thoracic Oncology, National Cancer Center Hospital East, 277-8577 - Kashiwa/JP
  • 4 Graduate School Of Medicine, Kyoto University, 668507 - Kyoto/JP
  • 5 Division Of Translational Genomics, Group Of Translational Research, National Cancer Center Hospital, 104-0045 - Tokyo/JP
  • 6 Clinical And Translational Research Center, Translational Research Division, Keio University Hospital, 1608582 - Tokyo/JP

Resources

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Abstract 4215

Background

Recent genome scale characterization of cancers identified overwhelming numbers of novel, rare and uncharacterized somatic mutations, variance of unknown significance (VUS), in non-small cell lung cancer (NSCLC). In order to make these VUS data clinically useful, further functional and biological characterization of each mutation is mandatory. In addition, development of novel strategies to overcome mutation diversity of lung cancer is needed.

Methods

Using the large-scale prospective cohort data of the LC-SCRUM-Japan, nationwide lung cancer clinical and the genomic characterization network in Japan, we characterized the frequency and distribution of rare EGFR mutations in NSCLC and the clinical course of the patients harboring these mutations. In addition, to perform functional and biological characterization of each mutation, we created a Ba/F3 EGFR minor mutation library. Furthermore, the in silico sensitivity prediction model has been developed to demonstrate binding affinity of protein and drug compound and applied to EGFR tyrosine kinase inhibitor with mutated EGFR.

Results

Of the 2164 NSCLC patients examined by LC-SCRUM-Japan, 113 (5.2%) harbored rare EGFR mutations. We found the diverse distribution of EGFR mutations throughout the gene, the most frequent group included EGFR exon 20 insertion mutations (52 cases). We clarified the sensitivity profile of the VUS to EGFR tyrosine kinase inhibitors. Binding affinities calculated by the in silico sensitivity prediction model showed statistically significant correlation (R2: 0.7425, p < 0.05) with the experimentally observed IC50 values.

Conclusions

These data may help in choosing or predicting the appropriate inhibitor for lung cancer with VUS in EGFR, thereby contributing to the further development of precision medicine. Here, we clarified the diversity of VUS in EGFR and provide novel insights, via supercomputer utilized drug sensitivity prediction, in the cancer field.

Clinical trial identification

Legal entity responsible for the study

Keio University School of Medicine.

Funding

Grants-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Culture, Sports, Science, and Technology of Japan.

Editorial Acknowledgement

Disclosure

All authors have declared no conflicts of interest.

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