Histopathological and Bioinformatic Analysis of the IL-6/STAT3 Signaling Pathway in Ovarian Neoplasms.

&lt;b&gt;Background and Objective:&lt;/b&gt; Ovarian cancer is a highly lethal gynecologic malignancy, often diagnosed at advanced stages due to nonspecific symptoms. The IL-6/STAT3 pathway promotes tumor progression, chemoresistance and poor prognosis. Therefore, this study aimed to evaluate the histologic patterns of ovarian tumors based on the WHO 2020 classification and investigate the role of the IL-6/STAT3 pathway in ovarian cancer progression. &lt;b&gt;Materials and Methods:&lt;/b&gt; A retrospective observational study was conducted using 2,309 ovarian biopsy specimens collected between 2016 and 2025 and classified according to the 2020 WHO Classification of Female Genital Tumours. Histopathological data were analyzed using descriptive statistics and the chi-square test (p<0.05). Bioinformatic analyses of TCGA gene expression data were performed using DESeq2 for differential expression analysis and Kaplan-Meier and Cox regression analyses to evaluate the prognostic significance of the IL-6/STAT3 signaling pathway. &lt;b&gt;Results:&lt;/b&gt; Surface epithelial tumors were the most common ovarian neoplasms (74.08%), followed by germ cell tumors (12.56%). Mucinous ovarian tumors were the predominant epithelial subtype. A significant association between age and malignancy was observed (p<0.001). STAT3 expression was significantly increased in the low-grade group (p = 0.022), while IL-6 expression was not statistically significant. &lt;b&gt;Conclusion:&lt;/b&gt; Ovarian tumors showed diverse histopathological features and STAT3 dysregulation may contribute to ovarian carcinoma prognosis. Integrating histopathological and molecular analysis may improve diagnostic and prognostic assessment.