Epidermal growth factor receptor gene polymorphisms are associated with prognostic features of breast cancer.

BACKGROUND: The epidermal growth factor receptor (EGFR) is differently expressed in breast cancer, and its presence may favor cancer progression. We hypothesized that two EGFR functional polymorphisms, a (CA)n repeat in intron 1, and a single nucleotide polymorphism, R497K, may affect EGFR expression and breast cancer clinical profile. METHODS: The study population consisted of 508 Brazilian women with unilateral breast cancer, and no distant metastases. Patients were genotyped for the (CA)n and R497K polymorphisms, and the associations between (CA)n polymorphism and EGFR transcript levels (n = 129), or between either polymorphism and histopathological features (n = 505) were evaluated. The REMARK criteria of tumor marker evaluation were followed. RESULTS: (CA)n lengths ranged from 14 to 24 repeats, comprehending 11 alleles and 37 genotypes. The most frequent allele was (CA)16 (0.43; 95% CI = 0.40-0.46), which was set as the cut-off length to define the Short allele. Variant (CA)n genotypes had no significant effect in tumoral EGFR mRNA levels, but patients with two (CA)n Long alleles showed lower chances of being negative for progesterone receptor (ORadjusted = 0.42; 95% CI = 0.19-0.91). The evaluation of R497K polymorphism indicated a frequency of 0.21 (95% CI = 0.19 - 0.24) for the variant (Lys) allele. Patients with variant R497K genotypes presented lower proportion of worse lymph node status (pN2 or pN3) when compared to the reference genotype Arg/Arg (ORadjusted = 0.32; 95% CI = 0.17-0.59), which resulted in lower tumor staging (ORadjusted = 0.34; 95% CI = 0.19-0.63), and lower estimated recurrence risk (OR = 0.50; 95% CI = 0.30-0.81). The combined presence of both EGFR polymorphisms (Lys allele of R497K and Long/Long (CA)n) resulted in lower TNM status (ORadjusted = 0.22; 95% CI = 0.07-0.75) and lower ERR (OR = 0.25; 95% CI = 0.09-0.71). When tumors were stratified according to biological classification, the favorable effects of variant EGFR polymorphisms were preserved for luminal A tumors, but not for other subtypes. CONCLUSIONS: The data suggest that the presence of the variant forms of EGFR polymorphisms may lead to better prognosis in breast cancer, especially in patients with luminal A tumors.

Functional polymorphisms in xenobiotic metabolizing enzymes and their impact on the therapy of breast cancer.

Breast cancer is the top cancer among women, and its incidence is increasing worldwide. Although the mortality tends to decrease due to early detection and treatment, there is great variability in the rates of clinical response and survival, which makes breast cancer one of the most appealing targets for pharmacogenomic studies. The recognition that functional CYP2D6 polymorphisms affect tamoxifen pharmacokinetics has motivated the attempts of using CYP2D6 genotyping for predicting breast cancer outcomes. In addition to tamoxifen, the chemotherapy of breast cancer includes combinations of cytotoxic drugs, which are substrates for various xenobiotic metabolizing enzymes. Because of these drugs' narrow therapeutic window, it has been postulated that impaired biotransformation could lead to increased toxicity. In the present review, we performed a systematic search of all published data exploring associations between polymorphisms in xenobiotic metabolizing enzymes and clinical outcomes of breast cancer. We retrieved 43 original articles involving either tamoxifen or other chemotherapeutic protocols, and compiled all information regarding response or toxicity. The data indicate that, although CYP2D6 polymorphisms can indeed modify tamoxifen pharmacokinetics, CYP2D6 genotyping alone is not enough for predicting breast cancer outcomes. The studies involving other chemotherapeutic protocols explored a great diversity of pharmacogenetic targets, but the number of studies for each functional polymorphism is still very limited, with usually no confirmation of positive associations. In conclusion, the application of pharmacogenetics to predict breast cancer outcomes and to select one individual's chemotherapeutic protocol is still far from clinical routine. Although some very interesting results have been produced, no clear practical recommendations are recognized yet.