CYP1A1*2A polymorphism as a predictor of clinical outcome in advanced lung cancer patients treated with EGFR-TKI and its combined effects with EGFR intron 1 (CA)n polymorphism

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.