2018
DOI: 10.1016/j.jtho.2018.01.003
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Computational Analysis of Epidermal Growth Factor Receptor Mutations Predicts Differential Drug Sensitivity Profiles toward Kinase Inhibitors

Abstract: The present study provides predicted drug sensitivity profiles for a large panel of uncommon EGFR mutations toward multiple inhibitors, which may help clinicians in deciding mutant-specific treatment strategies.

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Cited by 13 publications
(10 citation statements)
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“…1 [6], major studies reviewed in Table 1 [7, 8] and Table 2 [7–10], and additional studies reviewed in supplemental online Table 1 [11–28]). Preclinical experiments and computational analysis by other groups have suggested augmented sensitivity of EGFR ‐G719A to afatinib compared with first‐ and third‐generation TKIs [29, 30]. Similar preclinical results were reported for EGFR ‐S768I and other exon 18 (E709K and exon 18 deletion) mutations, whereas L861Q mutations are sensitive to both afatinib and osimertinib [29, 31].…”
Section: Molecular Tumor Boardsupporting
confidence: 58%
“…1 [6], major studies reviewed in Table 1 [7, 8] and Table 2 [7–10], and additional studies reviewed in supplemental online Table 1 [11–28]). Preclinical experiments and computational analysis by other groups have suggested augmented sensitivity of EGFR ‐G719A to afatinib compared with first‐ and third‐generation TKIs [29, 30]. Similar preclinical results were reported for EGFR ‐S768I and other exon 18 (E709K and exon 18 deletion) mutations, whereas L861Q mutations are sensitive to both afatinib and osimertinib [29, 31].…”
Section: Molecular Tumor Boardsupporting
confidence: 58%
“…Preclinical and computational analysis of uncommon mutations has demonstrated a high degree of heterogeneity in terms of sensitivity to different EGFR TKIs. 22,23,26 The variable sensitivity of different uncommon mutations to different EGFR TKIs indicates that a personalized treatment strategy should be undertaken in patients depending on the underlying uncommon EGFR mutation. However, effective treatment decisions are compromised by the paucity of prospective clinical data.…”
Section: Introductionmentioning
confidence: 99%
“…Tumor EGFR mutations are the strongest predictor for response to EGFR TKI therapy [4,11,13,28]. In our study, all patients with EGFR mutations (both common and uncommon) showed radiological tumor regression on afatinib therapy, while patients with a wild type EGFR showed tumor progression.…”
Section: Correlation Between Tumor Tracer Uptake and Responsementioning
confidence: 48%