4.1 Medicine 

Expression Patterns of CDK4 and Cyclin D1 in Uterine Stromal Tumors and Sarcomas: Diagnostic and Prognostic Implications

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Uterine stromal tumors encompass a histologically and clinically heterogeneous group of neoplasms ranging from benign endometrial stromal nodules (ESN) to low-grade and high-grade endometrial stromal sarcomas (LG-ESS and HG-ESS). Reliable markers for diagnostic stratification and prognostic assessment remain limited.
This study aimed to evaluate the immunohistochemical expression of CDK4 and Cyclin D1 in uterine stromal tumors and assess their association with tumor grade, hormonal receptor status, proliferation index, and disease-free survival. A total of forty-five uterine stromal tumors were retrospectively analyzed, including 15 cases each of ESN, LG-ESS, and HG-ESS. Immunohistochemical staining for CDK4, Cyclin D1, CD10, estrogen receptor (ER), progesterone receptor (PR), and Ki67 was performed using Leica antibodies. CDK4 and Cyclin D1 expressions were quantified using the H-score method. Correlations between marker expression, clinicopathological parameters, and disease-free survival (DFS) were statistically analyzed. A progressive increase in CDK4 and Cyclin D1 H-scores was observed from ESN to LG-ESS and HG-ESS (p < 0.001). Hormonal receptor expression and diffuse CD10 staining decreased significantly with increasing tumor grade (p < 0.001). CDK4 and Cyclin D1 H-scores showed a strong inverse correlation with ER/PR expression and a positive correlation with Ki67 index. Disease recurrence occurred exclusively in sarcoma cases, predominantly in HG-ESS. High CDK4 (H-score >150) and Cyclin D1 (H-score >200) expression, negative or focal CD10 expression, ER/PR negativity, and Ki67 index >50% were significantly associated with reduced DFS. CDK4 and Cyclin D1 overexpression are associated with higher tumor grade, loss of hormonal receptor expression, increased proliferative activity, and poor disease-free survival in uterine stromal tumors. These markers may serve as potential indicators of tumor aggressiveness and could be integrated into diagnostic and prognostic assessment protocols.

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