Research ResourcesCancer

A method of high-throughput functional evaluation of EGFR gene variants of unknown significance in cancer

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Science Translational Medicine  15 Nov 2017:
Vol. 9, Issue 416, eaan6566
DOI: 10.1126/scitranslmed.aan6566

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No longer unknown

Mutations in the epidermal growth factor are present in a variety of tumor types and are often responsible for driving cancer progression and drug resistance. A variety of mutations in this gene have been reported in genomics studies, but their effects on the tumor phenotype were often uncertain. To identify and classify these potentially pathogenic mutations, Kohsaka et al. developed a high-throughput method for assessing the effects of epidermal growth factor mutations alone and in combinations, which should help predict tumor behavior and treatment response for each mutation pattern found in patients.


Numerous variants of unknown significance (VUS) have been identified through large-scale cancer genome projects, although their functional relevance remains uninvestigated. We developed a mixed-all-nominated-mutants-in-one (MANO) method to evaluate the transforming potential and drug sensitivity of oncogene VUS in a high-throughput manner and applied this method to 101 nonsynonymous epidermal growth factor receptor (EGFR) mutants. We discovered a number of mutations conferring resistance to EGFR tyrosine kinase inhibitors (TKIs), including gefitinib- and erlotinib-insensitive missense mutations within exon 19 and other gefitinib-resistant mutations, such as L833V, A839T, V851I, A871T, and G873E. L858R-positive tumors (12.8%) harbored compound mutations primarily in the cis allele, which decreased the gefitinib sensitivity of these tumors. The MANO method further revealed that some EGFR mutants that are highly resistant to all types of TKIs are sensitive to cetuximab. Thus, these data support the importance of examining the clinical relevance of uncommon mutations within EGFR and of evaluating the functions of such mutations in combination. This method may become a foundation for the in vitro and in vivo assessment of variants of cancer-related genes and help customize cancer therapy for individual patients.

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