Reference Overview - PMID18176089

Overview

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Reference

Prognostic Factors for Gefitinib-Treated Postoperative Recurrence in Non-Small Cell Lung Cancer.

Paper Id
COSP19241
Authors
Okami J,Taniguchi K,Higashiyama M,Maeda J,Oda K,Orita N,Koizumi K,Kodama K and Kato K
Affiliation
Department of Thoracic Surgery, Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka, Japan. okami-ji@mc.pref.osaka.jp
Journal
Oncology 2007;72(3-4):234-42
ISSN:1423-0232
PUBMED:18176089
Abstract
The association between epidermal growth factor receptor (EGFR) mutations and response to EGFR tyrosine kinase inhibitor (TKI) has been consistently confirmed in a number of studies. However, it is still unclear whether a response to TKI treatment translates into increased survival for patients with non-small cell lung cancer (NSCLC). Methods: EGFR mutations were analyzed in 169 primary lung cancer tissues by RT-PCR and sequencing of multiple clones. The association between EGFR mutation status and the clinical outcome of gefitinib treatment was investigated. For mutation-positive cases, the percentage of mutated clones from the total number of clones was calculated. This ratio was used as the quantitative index of EGFR mutations.Results: We identified mutations in 71 of 169 patients with NSCLC. 46 patients were treated with gefitinib for postoperative recurrence. Progression-free survival and overall survival after initial gefitinib were significantly longer in patients with mutation than with wild type (univariate analysis, p < 0.001 for both). Multivariate analyses identified EGFR mutations and longer disease-free intervals after surgery as significant prognostic factors for survival. By quantitative analysis of mutation-positive cases, the increased ratio of mutated EGFR transcripts significantly associated with longer survival after gefitinib.Conclusions: EGFR mutation status and disease-free interval were associated with prolonged progression-free survival and overall survival after gefitinib treatment for postoperative recurrence of NSCLC. Quantitative analysis of mutated EGFR transcripts provided additional information for the stratification of patients with mutated EGFR.
Paper Status
Curated
Genes Analysed
1
Mutations
77

Mutations

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Genes Samples CDS Mutation AA Mutation

Non-Mutant Genes

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Non-Mutant Genes Gene Id (COSG)

Non-Mutant Samples

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Non-Mutant Samples Sample Id (COSS)

Mutated Samples

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Sample Name Mutation Count

Non-Coding mutation

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Sample ID Sample Name ID NCV Annotation Zygosity Chromosome Genome start Genome stop Genome version Strand WT seq Mut seq