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- 저자 : Sadullahoglu, (검색결과 1 건)
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Demir, Lutfiye,Yigit, Seyran,Sadullahoglu, Canan,Akyol, Murat,Cokmert, Suna,Kucukzeybek, Yuksel,Alacacioglu, Ahmet,Cakalagaoglu, Fulya,Tarhan, Mustafa Oktay Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.22
Purpose: We aimed to evaluate the effects of hormone receptor, HER2, and epidermal growth factor receptor (EGFR) expression on epithelial ovarian cancer (EOC) prognosis and investigate whether or not phenotypic subtypes might exist. Materials and Methods: The medical records of 82 patients who were diagnosed with EOC between 2003 and 2012 and treated by platinum-based chemotherapy were retrospectively evaluated. Expression of EGFR, oestrogen (ER), progesterone (PR), and cerbB2 (HER2) receptors were assessed immunohistochemically on paraffin-embedded tissues of these patients. Three phenotypic subtypes were defined according to ER, PR, and HER2 expression and associations of these with EGFR expression, clinicopathologic features, platinum sensitivity, and survival were investigated. Results: When we classified EOC patients into three subtypes, 63.4% had hormone receptor positive (HR(+)) (considering breast cancer subtypes, luminal A), 18.3% had triple negative, and 18.3% had HER2(+) disease. EGFR positivity was observed in 37 patients (45.1%) and was significantly more frequent with advanced disease (p=0.013). However, no significant association with other clinicopathologic features and platinum sensitivity was observed. HER2(+) patients had significantly poorer outcomes than HER2(-) counterparts (triple negative and HR positive patients) (p=0.019). Multivariate analysis demonstrated that the strongest risk factor for death was residual disease after primary surgery. Conclusions: Triple negative EOC may not be an aggressive phenotype as in breast cancer. The HER2 positive EOC has more aggressive behaviour compared to triple negative and HR(+) phenotypes. EGFR expression is more frequent in advanced tumours, but is not related with poorer outcome. Additional ovarian cancer molecular subtyping using gene expression analysis may provide more reliable data.
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