4.0 Article

Relationship between epidermal growth factor receptor gene mutation and copy number in Chinese patients with non-small cell lung cancer

Journal

CHINESE JOURNAL OF CANCER
Volume 31, Issue 10, Pages 491-499

Publisher

SUN YAT SEN UNIV MED SCI WHO
DOI: 10.5732/cjc.011.10409

Keywords

Epidermal growth factor receptor; gene mutation; gene copy number; non-small cell lung cancer; correlation

Categories

Funding

  1. Ministry of Science and Technology of China [2006AA02A401]

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Epidermal growth factor receptor (EGFR) gene mutation and copy number are useful predictive markers that guide the selection of non-small cell lung cancer (NSCLC) patients for EGFR-targeting therapy. This study aimed to investigate the correlation between EGFR gene mutation and copy number and clinicopathologic characteristics of Chinese patients with NSCLC. NSCLC specimens collected from 205 patients between November 2009 and January 2011 were selected to detect EGFR gene mutations with real-time polymerase chain reaction (RT-PCR) and to detect EGFR gene copy number with fluorescence in situ hybridization (FISH). EGFR mutations primarily occurred in females, non-smokers, and patients with adenocarinomas (all P < 0.001). Tissues from 128 (62%) patients were FISH-positive for EGFR, including 37 (18%) with gene amplification and 91 (44%) with high polysomy. EGFR gene mutation was correlated with FISH-positive status (R = 0.340, P < 0.001). Multivariate analysis showed that not smoking (OR = 5.910, 95% CI = 2.363-14.779, P < 0.001) and having adenocarcinoma (OR = 0.122, 95% CI = 0.026-0.581, P = 0.008) were favorable factors for EGFR gene mutation. These results show a high frequency of EGFR FISH positivity in NSCLC tissues from Chinese patients and a significant relevance between EGFR gene mutations and FISH-positive status. Among the FISH-positive samples, EGFR gene mutation occurred more frequently in samples with gene amplification compared to those with high polysomy, suggesting that EGFR mutation and gene amplification should be used as clinical decision parameters to predict response to EGFR-targeting therapy.

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