Diagnostic Potential of CD44, CD133, and VDR in Epithelial Ovarian Tumors: Association with Histopathology Parameters.

CD44、CD133 和 VDR 在卵巢上皮肿瘤中的诊断潜力:与组织病理学参数的关联

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作者:Jovanović LjubiÅ¡a, Å oÅ¡ić-Jurjević Branka, Ćirković Anđa, Dragičević Sandra, Filipović Branko, Milenković Svetlana, Dugalić Stefan, Gojnić-Dugalić Miroslava, Nikolić Aleksandra
Cancer stem cells (CSCs) significantly contribute to heterogeneity, malignancy, and therapy resistance in ovarian cancer. Recent studies emphasize the role of the vitamin D receptor (VDR) in regulating cell differentiation and stemness in various types of cancer. This study aims to determine the expression levels of CD44, CD133, and VDR in epithelial ovarian tumors (EOTs) and to compare these levels across different tumor types, including benign, atypical proliferative tumors, and five types of malignant phenotypes, in order to evaluate their potential as diagnostic tools for malignancy. Tissue samples from 218 patients diagnosed with EOT were analyzed. Clinical and histopathologic parameters were recorded. Quantitative immunohistochemical tissue microarray analysis was used to assess the expression levels of CD44, CD133, and VDR using two different scoring systems. Comparisons were made between benign tumors (n = 45), atypical proliferative tumors (n = 42), and ovarian carcinomas (n = 131), including high-grade serous (HGSC) and non-HGSC subtypes. Ovarian cancer, especially HGSC, showed a significantly higher expression of CD44 and VDR (p < 0.05) compared to atypical proliferative tumors and benign tumors. The expression of CD133 was highest in atypical proliferative tumors (p < 0.05). A moderate positive correlation was found between CD44, CD133, and VDR in all groups, with significant correlations with tumor grade and FIGO stage in ovarian cancer (p < 0.05). The increased expression of CD44 and VDR in aggressive ovarian cancer, along with elevated CD133 levels in atypical proliferative tumors, highlights the complexity of tumor biology. These markers may serve as valuable targets for the diagnosis of ovarian cancer.

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