Impact of EGFR Genetic Variants on Glioma Risk and Patient Outcome

• Type: Article in International Scientific Journal
• Date: 2011

Authors

Bruno Marques Costa (Author) Other; Marta Viana Pereira (Author) Other; Ricardo Fernandes (Author) Other; Sandra Costa (Author) Other; Paulo Linhares (Author) Other; Rui Vaz (Author) Other; Celine Pinheiro (Author) Other; Jorge Lima (Author) FMUP; Paula Soares (Author) FMUP; Ana Silva (Author) Other; Fernando Pardal (Author) Other; Julia Amorim (Author) Other; Rui Nabico (Author) Other; Rui Almeida (Author) Other; Carlos Alegria (Author) Other; Manuel Melo Pires (Author) ICBAS; Celia Pinheiro (Author) Other; Ernesto Carvalho (Author) Other; Pedro Oliveira (Author) ICBAS; Jose M Lopes (Author) FMUP; Rui M Reis (Author) Other

Journal

Title: Cancer Epidemiology Biomarkers and Prevention

Vol. 20

Pages: 2610-2617

ISSN: 1055-9965

Publisher: American Association for Cancer Research

Indexing

ISI Web of Knowledge - 30 Citations

Scopus - 35 Citations

Scientific classification

FOS: Medical and Health sciences > Clinical medicine

Other information

Authenticus ID: P-002-HYY

DOI: 10.1158/1055-9965.epi-11-0340

Abstract (EN): 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. Cancer Epidemiol Biomarkers Prev; 20(12); 2610-7. (C) 2011 AACR.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8