Evaluation of the Expression Intensity of Glucose Transporter-1 Marker and its Diagnostic Value in Differentiating Between Borderline and Malignant Ovarian Epithelial Tumors

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background

Ovarian cancer ranks second among gynecological cancers worldwide. This study aimed to compare the glucose transporter-1 (GLUT-1) expression in benign, borderline, and malignant ovarian epithelial tumors and evaluate GLUT-1 expression as a diagnostic tool for distinguishing tumors in the ovary.

Materials and Methods

This descriptive-analytical cross-sectional study analyzed 69 pathological samples of patients diagnosed with ovarian epithelial tumors who underwent oophorectomy. Immunohistochemical staining was performed using GLUT-1 antibody. The intensity of cell membrane staining and the proportion of positive neoplastic cells were graded to score immunostaining. Chi-square/Fisher’s exact test was used to analyze the data. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), and staining accuracy for GLUT-1 in distinguishing borderline from invasive tumors were calculated by standard methods (P < 0.05).

Results

In all benign tumors, GLUT-1 staining was negative. In addition, weak staining intensity was observed in 38.5% of borderline tumors, and 96% of invasive tumors had strong staining intensity (P < 0.001). Strong GLUT-1 staining was found in 94.7% of Papillary Serous Carcinoma, 9/1% of Borderline Serous tumors, 100% of Brenner tumors, and clear cell carcinoma. The results demonstrated a high diagnostic value of GLUT-1 expression intensity in differentiating between borderline and malignant ovarian epithelial tumors (Accuracy: 97.10, Sensitivity: 96%, Specificity: 97.73).

Conclusion

Overall, GLUT-1 expression could help distinguish benign from borderline, especially borderline from malignant ovarian epithelial tumors. Thus, it seems that it provides useful prognostic information, particularly for the borderline category.

Language:
English
Published:
Journal of Disease and Diagnosis, Volume:12 Issue: 2, Apr 2023
Pages:
63 to 69
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