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Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis.

ABSTRACT: BACKGROUND:Non-small cell lung cancer (NSCLC) with activating EGFR mutations, especially exon 19 deletions and the L858R point mutation, is particularly responsive to gefitinib and erlotinib. However, the sensitivity varies for less common and rare EGFR mutations. There are various explanations for the low sensitivity of EGFR exon 20 insertions and the exon 20 T790 M point mutation to gefitinib/erlotinib. However, few studies discuss, from a structural perspective, why less common mutations, like G719X and L861Q, have moderate sensitivity to gefitinib/erlotinib. RESULTS:To decode the drug sensitivity/selectivity of EGFR mutants, it is important to analyze the interaction between EGFR mutants and EGFR inhibitors. In this paper, the 30 most common EGFR mutants were selected and the technique of protein-ligand interaction fingerprint (IFP) was applied to analyze and compare the binding modes of EGFR mutant-gefitinib/erlotinib complexes. Molecular dynamics simulations were employed to obtain the dynamic trajectory and a matrix of IFPs for each EGFR mutant-inhibitor complex. Multilinear Principal Component Analysis (MPCA) was applied for dimensionality reduction and feature selection. The selected features were further analyzed for use as a drug sensitivity predictor. The results showed that the accuracy of prediction of drug sensitivity was very high for both gefitinib and erlotinib. Targeted Projection Pursuit (TPP) was used to show that the data points can be easily separated based on their sensitivities to gefetinib/erlotinib. CONCLUSIONS:We can conclude that the IFP features of EGFR mutant-TKI complexes and the MPCA-based tensor object feature extraction are useful to predict the drug sensitivity of EGFR mutants. The findings provide new insights for studying and predicting drug resistance/sensitivity of EGFR mutations in NSCLC and can be beneficial to the design of future targeted therapies and innovative drug discovery.

SUBMITTER: Zou B

PROVIDER: S-EPMC5842518 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis.

Zou Bin B Lee Victor H F VHF Yan Hong H

BMC bioinformatics 20180307 1

<h4>Background</h4>Non-small cell lung cancer (NSCLC) with activating EGFR mutations, especially exon 19 deletions and the L858R point mutation, is particularly responsive to gefitinib and erlotinib. However, the sensitivity varies for less common and rare EGFR mutations. There are various explanations for the low sensitivity of EGFR exon 20 insertions and the exon 20 T790 M point mutation to gefitinib/erlotinib. However, few studies discuss, from a structural perspective, why less common mutati ...[more]

PMID: 29514601

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Project description:BackgroundSeveral randomized controlled trials have suggested that adjuvant epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) were associated with prolonged disease-free survival (DFS) in EGFR-mutated NSCLC patients after radical resection, comparing with chemotherapy or placebo. We aimed to compare the effectiveness of different first-generation EGFR-TKIs as adjuvant treatment in real-world setting.MethodsEarly-stage EGFR mutated NSCLC patients who underwent radical resection and treated with first-generation EGFR-TKIs (gefitinib, erlotinib, icotinib) as adjuvant therapy between Feb 2010 and Jan 2019 were retrieved from a prospectively-maintained database in our center. The primary endpoint was DFS in stage II/III (TNM 8th) patients with exploratory endpoint regarding DFS in stage I patients. Sensitivity analyses were based on propensity score matched (PSM) cohorts. Treatment failure patterns among different TKIs were also compared.ResultsOf 588 eligible patients, 198 patients (33.7%) received gefitinib, 106 patients (17.9%) received erlotinib, and 284 patients (48.2%) received icotinib. The median DFS of stage II/III patients in the gefitinib, erlotinib and icotinib group were 36.1 months (95% CI, 23.9-49.4), 42.8 months (95% CI, 29.6-97.8), and 32.5 months (95% CI, 23.9-49.4), respectively, with no significant difference (log-rank test P=0.22). There was also no significant difference in DFS among stage I patients receiving different TKIs (P=0.12). PSM adjustments and multivariate analyses adjusting for other confounders revealed similar results. In addition, there were no significant differences in treatment failure pattens in different EGFR-TKI arms, especially in terms of brain metastases (6.1% in gefitinb, 7.5% in erlotinib, 3.9% in icotinib) and bone metastases (8.6% in gefitinb, 9.4% in erlotinib, 7.0% in icotinib).ConclusionsThis first and largest real-world study showed that gefitinib, erlotinib, and icotinib demonstrated comparable clinical effectiveness as adjuvant therapy for patients with early-stage EGFR mutated NSCLC.

Dataset Information

Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis.

Publications

Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis.

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