Literature DB >> 17671150

Selecting patients for treatment with epidermal growth factor tyrosine kinase inhibitors.

Philip D Bonomi1, Lela Buckingham, John Coon.   

Abstract

Identification of objective tumor regressions with epidermal growth factor receptor tyrosine kinases (EGFR TKI) in non-small cell lung cancer (NSCLC) patients has resulted in intense, worldwide clinical and basic research directed toward finding the optimal use of EGFR TKIs in NSCLC. EGFR TKI clinical trials have shown that higher response rates and longer survival are associated with specific patient characteristics and that using conventional chemotherapy simultaneously with EGFR TKIs in unselected patients does not increase survival. Molecular studies have revealed that EGFR-activating mutations and high EGFR gene copy number are frequently found in patients who have the best outcomes with EGFR TKIs. More recent studies suggest that KRAS mutations may identify the subset of patients who have the worst outcome with the EGFR TKI treatment. Currently, investigators are trying to determine the optimal approach to selecting patients for treatment with EGFR TKIs. Studies that have evaluated the potential predictive value of clinical features and/or molecular profiles in EGFR TKI-treated NSCLC patients are discussed in this review.

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Year:  2007        PMID: 17671150     DOI: 10.1158/1078-0432.CCR-07-0332

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  19 in total

1.  Integrating molecular diagnostics into anticancer drug discovery.

Authors:  István Peták; Richárd Schwab; László Orfi; László Kopper; György Kéri
Journal:  Nat Rev Drug Discov       Date:  2010-06-07       Impact factor: 84.694

2.  Distribution of some activating KRAS and BRAF mutations in Slovene patients with colorectal cancer.

Authors:  Alenka Ličar; Petra Cerkovnik; Srdjan Novaković
Journal:  Med Oncol       Date:  2010-07-20       Impact factor: 3.064

3.  STAT-Related Profiles Are Associated with Patient Response to Targeted Treatments in Locally Advanced SCCHN.

Authors:  Vassiliki Kotoula; Sofia Lambaki; Despina Televantou; Anna Kalogera-Fountzila; Angelos Nikolaou; Konstantinos Markou; Despina Misailidou; Konstantinos N Syrigos; George Fountzilas
Journal:  Transl Oncol       Date:  2011-02-01       Impact factor: 4.243

Review 4.  KRAS mutation testing for predicting response to anti-EGFR therapy for colorectal carcinoma: proposal for an European quality assurance program.

Authors:  J H J M van Krieken; A Jung; T Kirchner; F Carneiro; R Seruca; F T Bosman; P Quirke; J F Fléjou; T Plato Hansen; G de Hertogh; P Jares; C Langner; G Hoefler; M Ligtenberg; D Tiniakos; S Tejpar; G Bevilacqua; A Ensari
Journal:  Virchows Arch       Date:  2008-09-18       Impact factor: 4.064

5.  Design of clinical trials for biomarker research in oncology.

Authors:  Sumithra J Mandrekar; Daniel J Sargent
Journal:  Clin Investig (Lond)       Date:  2011-12

6.  Utility of Genomic Assessment of Blood-Derived Circulating Tumor DNA (ctDNA) in Patients with Advanced Lung Adenocarcinoma.

Authors:  Maria C Schwaederlé; Sandip P Patel; Hatim Husain; Megumi Ikeda; Richard B Lanman; Kimberly C Banks; AmirAli Talasaz; Lyudmila Bazhenova; Razelle Kurzrock
Journal:  Clin Cancer Res       Date:  2017-05-24       Impact factor: 12.531

7.  Predictive biomarker validation in practice: lessons from real trials.

Authors:  Sumithra J Mandrekar; Daniel J Sargent
Journal:  Clin Trials       Date:  2010-04-14       Impact factor: 2.486

8.  Molecular mechanisms of acquired resistance to tyrosine kinase targeted therapy.

Authors:  J Rafael Sierra; Virna Cepero; Silvia Giordano
Journal:  Mol Cancer       Date:  2010-04-12       Impact factor: 27.401

9.  Clinical trial designs for predictive biomarker validation: one size does not fit all.

Authors:  Sumithra J Mandrekar; Daniel J Sargent
Journal:  J Biopharm Stat       Date:  2009       Impact factor: 1.051

10.  KIT as a therapeutic target in melanoma.

Authors:  Maria C Garrido; Boris C Bastian
Journal:  J Invest Dermatol       Date:  2010-01       Impact factor: 8.551

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