Development of an immuno-wall device for the rapid and sensitive detection of EGFR mutations in tumor tissues resected from lung cancer patients

Naoyuki Yogo, Tetsunari Hase, Toshihiro Kasama, Keine Nishiyama, Naoya Ozawa, Takahiro Hatta, Hirofumi Shibata, Mitsuo Sato, Kazuki Komeda, Nozomi Kawabe, Kohei Matsuoka, Toyofumi Fengshi Chen-Yoshikawa, Noritada Kaji, Manabu Tokeshi, Yoshinobu Baba, Yoshinori Hasegawa

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    Detecting molecular targets in specimens from patients with lung cancer is essential for targeted therapy. Recently, we developed a highly sensitive, rapid-detection device (an immuno-wall device) that utilizes photoreactive polyvinyl alcohol immobilized with antibodies against a target protein via a streptavidin–biotin interaction. To evaluate its performance, we assayed epidermal growth factor receptor (EGFR) mutations, such as E746_A750 deletion in exon 19 or L858R substitution in exon 21, both of which are common in non-small cell lung cancer and important predictors of the treatment efficacy of EGFR tyrosine kinase inhibitors. The results showed that in 20-min assays, the devices detected as few as 1% (E746_A750 deletion) and 0.1% (L858R substitution) of mutant cells. Subsequent evaluation of detection of the mutations in surgically resected lung cancer specimens from patients with or without EGFR mutations and previously diagnosed using commercially available, clinically approved genotyping assays revealed diagnostic sensitivities of the immuno-wall device for E746_A750 deletion and L858R substitution of 85.7% and 87.5%, respectively, with specificities of 100% for both mutations. These results suggest that the immuno-wall device represents a good candidate next-generation diagnostic tool, especially for screening of EGFR mutations.

    Original languageEnglish
    Article numbere0241422
    JournalPloS one
    Volume15
    Issue number11 November
    DOIs
    Publication statusPublished - Nov 2020

    All Science Journal Classification (ASJC) codes

    • General

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