Associated Papers
Predicting Resistance to Small Molecule Kinase Inhibitors.
Nagarajan A et al.
Journal of Chemical Information and Modeling, 2025
Structure-Guided Strategies of Targeted Therapies for Patients with EGFR-Mutant Non-Small Cell Lung Cancer.
Du Z et al.
Biomolecules, 2023
36830579 (PubMed )
Supplement: biomolecules-13-00210-s001.zip › biomolecules-2098784-supplementary.xlsx › Table_S8
Preclinical assessment of combination therapy of EGFR tyrosine kinase inhibitors in a highly heterogeneous tumor model.
Ikeuchi H et al.
Oncogene, 2022
35304574 (PubMed )
Supplement: 41388_2022_2263_MOESM5_ESM.xlsx › Supplementary_Table_4
A Nationwide Study on the Impact of Routine Testing for EGFR Mutations in Advanced NSCLC Reveals Distinct Survival Patterns Based on EGFR Mutation Subclasses.
Koopman B et al.
Cancers, 2021
Targeted sequencing identifies genetic alterations that confer primary resistance to EGFR tyrosine kinase inhibitor (Korean Lung Cancer Consortium).
Lim SM et al.
Oncotarget, 2016
Structural Stability and Flexibility Direct the Selection of Activating Mutations in Epidermal Growth Factor Receptor Kinase.
Paladino A et al.
Journal of Chemical Information and Modeling, 2015
26121158 (PubMed )
Supplement: ci5b00270_si_001.pdf
The energy landscape analysis of cancer mutations in protein kinases.
Dixit A et al.
Plos One, 2011
21998754 (PubMed )
Supplement: pone.0026071.s009.doc
A comparison of ARMS and DNA sequencing for mutation analysis in clinical biopsy samples.
Ellison G et al.
Journal of Experimental & Clinical Cancer Research : Cr, 2010
Comparison of the EGFR resistance mutation profiles generated by EGFR-targeted tyrosine kinase inhibitors and the impact of drug combinations.
Avizienyte E et al.
The Biochemical Journal, 2008
18588508 (PubMed )
Supplement: supplement_1.pdf
Select a paper to view details