BACKGROUND: Mutations in the epidermal growth factor receptor (EGFR) have been confirmed as predictors of efficacy for EGFR-tyrosine kinase inhibitors (TKIs). We investigated whether polymorphisms of the EGFR and cytochrome P450, family 1, member A1 (CYP1A1) genes were associated with clinical outcome in NSCLC patients treated with EGFR-TKI. METHODS: Genotypes for the intron 1 (CA)n repeat and R497K polymorphisms in the EGFR gene and the *2A (3801 T→C) and *2C (2455 A→G) polymorphisms in CYP1A1 gene were evaluated in 115 NSCLC patients by PCR-RFLP and DNA sequencing. Genetic polymorphisms were correlated with clinical outcomes of EGFR-TKIs. From a subgroup of patients whose tumour tissues were available, associations between somatic EGFR mutations, EGFR expression, and genomic polymorphisms were also analysed. RESULTS: EGFR intron 1 (CA)n and CYP1A1*2A polymorphisms were independent predictive factors (p=0.046, p=0.011, respectively) and the latter was also a prognostic factor (p=0.001) for patients treated with EGFR-TKIs. We also observed a strong synergistic effect from two genotypes. Specifically, patients with both the T/T allele of the CYP1A1 gene and shorter intron 1 CA repeats (≤ 16 CA) of the EGFR gene showed an improved response (p=0.002) compared with patients with the T/C or C/C allele and longer intron 1 CA repeats (both alleles >16 CA). In contrast, for R497K and CYP1A1*2C, no relationship was observed with clinical outcome for patients treated with EGFR-TKIs (p=0.573; p=0.629, respectively). Both SNPs in the CYP1A1 gene showed a correlation with EGFR somatic mutations. CONCLUSIONS: The findings of this study suggest that the CYP1A1*2A polymorphism is a predictor for clinical outcome in NSCLC patients treated with EGFR-TKI therapy, and combining analysis of both CYP1A1*2A and EGFR intron 1 (CA)n polymorphisms may be useful for predicting treatment outcome in NSCLC patients treated with EGFR-TKIs.
BACKGROUND: Mutations in the epidermal growth factor receptor (EGFR) have been confirmed as predictors of efficacy for EGFR-tyrosine kinase inhibitors (TKIs). We investigated whether polymorphisms of the EGFR and cytochrome P450, family 1, member A1 (CYP1A1) genes were associated with clinical outcome in NSCLCpatients treated with EGFR-TKI. METHODS: Genotypes for the intron 1 (CA)n repeat and R497K polymorphisms in the EGFR gene and the *2A (3801 T→C) and *2C (2455 A→G) polymorphisms in CYP1A1 gene were evaluated in 115 NSCLCpatients by PCR-RFLP and DNA sequencing. Genetic polymorphisms were correlated with clinical outcomes of EGFR-TKIs. From a subgroup of patients whose tumour tissues were available, associations between somatic EGFR mutations, EGFR expression, and genomic polymorphisms were also analysed. RESULTS:EGFR intron 1 (CA)n and CYP1A1*2A polymorphisms were independent predictive factors (p=0.046, p=0.011, respectively) and the latter was also a prognostic factor (p=0.001) for patients treated with EGFR-TKIs. We also observed a strong synergistic effect from two genotypes. Specifically, patients with both the T/T allele of the CYP1A1 gene and shorter intron 1 CA repeats (≤ 16 CA) of the EGFR gene showed an improved response (p=0.002) compared with patients with the T/C or C/C allele and longer intron 1 CA repeats (both alleles >16 CA). In contrast, for R497K and CYP1A1*2C, no relationship was observed with clinical outcome for patients treated with EGFR-TKIs (p=0.573; p=0.629, respectively). Both SNPs in the CYP1A1 gene showed a correlation with EGFR somatic mutations. CONCLUSIONS: The findings of this study suggest that the CYP1A1*2A polymorphism is a predictor for clinical outcome in NSCLCpatients treated with EGFR-TKI therapy, and combining analysis of both CYP1A1*2A and EGFR intron 1 (CA)n polymorphisms may be useful for predicting treatment outcome in NSCLCpatients treated with EGFR-TKIs.
Authors: Roberta R Alfieri; Maricla Galetti; Stefano Tramonti; Roberta Andreoli; Paola Mozzoni; Andrea Cavazzoni; Mara Bonelli; Claudia Fumarola; Silvia La Monica; Elena Galvani; Giuseppe De Palma; Antonio Mutti; Marco Mor; Marcello Tiseo; Ettore Mari; Andrea Ardizzoni; Pier Giorgio Petronini Journal: Mol Cancer Date: 2011-11-23 Impact factor: 27.401
Authors: Minkyu Jung; Byoung Chul Cho; Chul Ho Lee; Hyung Soon Park; Young Ae Kang; Se Kyu Kim; Joon Chang; Dae Jun Kim; Sun Young Rha; Joo Hang Kim; Ji Hyun Lee Journal: Yonsei Med J Date: 2012-11-01 Impact factor: 2.759