https://doi.org/10.31288/oftalmolzh201326167

Profiles of the molecular markers (P53,BCL-2, CD95, IPo38) as predictors of recurrence development in patients with malignant epithelial tumors of the eyelid skin

I. A. Safronenkova, E. I. Dragomiretskaya

SI «Filatov Institute of Eye Diseases and Tissue Therapy of National Academy of Medical Sciences of Ukraine»

Key words: malignant epithelial tumors of the eyelid skin, a monoclonal antibody (Bcl-2, p53, IPO38, CD95), the forecast of relapse

Introduction. To select the tactics impact on the tumor to identify predictors of treatment outcome. Substantial assistance in this study may have a malignant epithelial tumors (MET) of the eyelid skin at immunohistochemical level.

Purpose. Determine the information content of the expression of molecular markers of p53, Bcl-2, and CD95, IPO38 in tumor tissues to predict relapse in patients with MET eyelid skin.

Materials and methods. With the help of molecular markers (p53, Bcl-2, CD95, IPO38) conducted immunohistochemical studies of paraffin sections ofbiopsiesfrom 185 patients with eyelid skin MET (81 men and 104 women) aged 34 to 89years (me¬dian = 64,3, SD = 11.1) before treatment (radiotherapy + cryosurgery). To estimate the probability of recurrence developed a scoring scale on the basis ofwhich carry out the construction of the characteristic curve (ROC), found the optimal point of separation, calculated the area under the ROC curve and held its statistical evaluation.

Results. Found threshold values relative expression of molecular markers, which increases the probability of recurrent MET eyelid skin. Based on the thresholds found four markers developed a probabilistic model for prediction of recurrence MET eyelid skin, where the sensitivity was 97.1 %, specificity — 85.0 %. Conclusions. 1. When the index Bcl-2/CD95> 1.0 chances of relapse increase MET age of 21, 5 times. 2. If the total scoring risk assessment (relative values of p53, Bcl-2, CD95 and IPO38) recurrence MET eyelid skin is a threshold value for the sum OR> 76,2. The sensitivity of the model prediction was 97.1 % and specificity — 85.0 %.

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