ArticleGynecologic oncology reports2025
Malignant Brenner tumor with extensive clear cell features: A valuable diagnostic lesson learned from molecular tumor profiling and AI-based tumor differential tool.
Article in Gynecologic oncology reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Malignant Brenner tumor (MBT) with extensive clear cell features mimicking an ovarian clear cell carcinoma (CCC) is exceedingly rare. This case report discusses the diagnostic challenges associated with this unusual histologic finding and highlights the value of molecular tumor profiling and artificial intelligence (AI)-based tools in tumor diagnostics. Case Summary: A 55-year-old woman presented with a 17.7 cm complex left ovarian mass, which was initially diagnosed as ovarian clear cell carcinoma on the frozen and permanent H&E sections. The subsequent next-generation sequencing (NGS) and an AI-based tumor differential tool predicted an 88 % match of urothelial origin for the ovarian tumor driven by strong expression of GATA3, uroplakin 2, and AMACR, while assigning 0 % match to ovarian CCC. The molecular and histologic discordance prompted pathologic re-evaluation. On the additional sections submitted from the ovarian tumor, a small component of benign Brenner tumor was identified adjacent to the tumor with extensive clear cell features. In addition, both the tumor cells exhibiting clear cell features and the benign Brenner tumor showed positive expression of urothelial markers by immunohistochemistry. The diagnosis was amended to MBT with extensive clear cell features. The NGS data was reviewed and showed the ovarian tumor harbored CDKN2A/B loss and a molecular triple phenotype (MDM2 amplification/TP53 wild-type/TERT wild-type), supporting the diagnosis of MBT and disfavoring metastatic urothelial carcinoma. Conclusion: MBT should be considered in the differential diagnosis of ovarian neoplasms with clear cell features. Extensive tumor sampling combined with careful evaluation of the histologic and immunohistochemical features and molecular analysis is the key to accurate diagnosis. AI-based tumor differential tools are valuable adjuncts to tumor diagnostics when investigated with other pathological and clinical findings.
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