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Impact of EGFR genetic variants on glioma risk and patient outcome

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Cancer Epidemiol Biomarkers Prev.pdf250.11 KBAdobe PDF Download

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Abstract(s)

BACKGROUND: The epidermal growth factor receptor (EGFR) regulates important cellular processes and is frequently implicated in human tumors. Three EGFR polymorphisms have been described as having a transcriptional regulatory function: two single-nucleotide polymorphisms in the essential promoter region, -216G/T and -191C/A, and a polymorphic (CA)(n) microsatellite sequence in intron 1. We aimed to elucidate the roles of these EGFR polymorphisms in glioma susceptibility and prognosis. METHODS: We conducted a case-control study with 196 patients with glioma and 168 cancer-free controls. Unconditional multivariate logistic regression models were used to calculate ORs and 95% confidence intervals. A Cox regression model was used to evaluate associations with patient survival. False-positive report probabilities were also assessed. RESULTS: None of the EGFR -216G/T variants was significantly associated with glioma risk. The -191C/A genotype was associated with higher risk for glioma when the (CA)(n) alleles were classified as short for ≤16 or ≤17 repeats. Independently of the (CA)(n) repeat cutoff point used, shorter (CA)(n) repeat variants were significantly associated with increased risk for glioma, particularly glioblastoma and oligodendroglioma. In all tested models with different (CA)(n) cutoff points, only -191C/A genotype was consistently associated with improved survival of patients with glioblastoma. CONCLUSIONS: Our findings implicate EGFR -191C/A and the (CA)(n) repeat polymorphisms as risk factors for gliomas, and suggest -191C/A as a prognostic marker in glioblastoma. IMPACT: Our data support a role of these EGFR polymorphisms in determining glioma susceptibility, with potential relevance for molecularly based stratification of patients with glioblastoma for individualized therapies

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Keywords

Neoplasias Cerebrais Glioma Receptor do Factor de Crescimento Epidérmico

Citation

Cancer Epidemiol Biomarkers Prev. 2011;20(12):2610-7

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