Mutations in the epidermal growth factor receptor (EGFR) are commonly occurring in glioblastoma. Enhanced activation of EGFR can occur through a variety of different mechanisms, both ligand-dependent and ligand-independent. Numerous evidence has suggested that EGFR is overexpressed in most of primary glioblastomas and some of the secondary glioblastomas and is characteristic of more aggressive glioblastoma phenotypes. Additionally, recent studies have revealed that wild-type EGFR, and to a greater extent hyper-activating EGFR mutants induced a substantial upregulation of Fyn expression. Furthermore, it was determined that Fyn expression is upregulated across a panel of patient-derived glioblastoma stem cells (GSCs) relative to normal progenitor controls. Moreover, researchers are continuously involved in elucidation of novel mechanism linking EGFR EGFR-expressing glioblastoma. The present review highlights current aspects of EGFR receptor in glioblastoma and concludes that the concept of EGFR signaling and related receptors and associated factors is evolving, however, it needs detailed evaluation for future clinical applications in cancer patients.
Previous studies on the association between reproductive factors and brain tumor risk in women have provided inconclusive findings. Thus, an updated meta-analysis was performed to obtain more precise risk estimates for brain tumor regarding several common reproductive factors. A comprehensive literature search for relevant publications in the PubMed and Embase databases was carried out from their inception up to June 20, 2014. Pooled relative risks (RRs) with corresponding 95% confidence intervals (CIs) were calculated. There were 27 independent studies with a total of 12,129 cases and 1,433,915 controls included into the present meta-analysis. We found that an elevated risk of brain tumors (RR=1.17, 95% CI 1.06-1.29, P=0.002), particularly glioma (RR=1.33, 95% CI 1.15-1.54, P<0.001), was related to older age at menarche. Interestingly, stratified analysis by type of brain tumors showed that the longer duration of breast feeding was associated with the risk of meningioma negatively but glioma positively (for meningioma: RR=0.76, 95% CI 0.64-0.91, P=0.002; for glioma: RR=1.70, 95% CI 1.14-2.55, P=0.010). No significant association was observed when estimating the roles of other reproductive factors including parity, age at first birth, menopausal status, and age at menopause in brain tumorigenesis. Our study suggests that older age at menarche is a risk factor of brain tumors and glioma in particular. Additionally, more studies are warranted to further elucidate roles and mechanisms of common reproductive factors in the risk of brain tumors.
Previous studies have shown the association of the Cyclin D1 (CCND1) G870A polymorphism with glioma risk, but the findings are inconsistent and inconclusive. To shed some light on the findings across individual studies and acquire a quantitative assessment of this association, we conducted a meta-analysis of all published case-control studies thus far. Four independent studies with a total of 690 cases and 1,014 controls were identified after a systematic search of the PubMed, Embase, Web of Science, and Wanfang databases. The strength of the association between the CCND1 G870A polymorphism and glioma risk was estimated by the pooled odds ratios (ORs) with 95 % confidence intervals (95 %CIs). Subgroup analysis by ethnicity was also performed. Overall, a statistically significant association was found between the CCND1 G870A polymorphism and glioma risk in three genetic models (ORA vs. G = 1.178, 95 %CI 1.025-1.354, P OR = 0.021; ORAA vs. GG = 1.328, 95 %CI 1.007-1.750, P OR = 0.045; ORAA + AG vs. GG = 1.253, 95 %CI 1.006-1.516, P OR = 0.044). In subgroup analysis, the pooled ORs suggested that the CCND1 G870A polymorphism was associated with an increased risk of glioma in Caucasians under the heterozygote and dominant genetic models (ORAG vs. GG = 1.329, 95 %CI 1.001-1.766, P OR = 0.049; ORAA + AG vs. GG = 1.332, 95 %CI 1.019-1.740, P OR = 0.036). The meta-analysis suggests that the CCND1 G870A polymorphism is a risk factor for the development of glioma.
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