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Updated: Jun 13, 2025

Heterotypic Three-dimensional In Vitro Modeling of Stromal-Epithelial Interactions During Ovarian Cancer Initiation and Progression
Published on: August 28, 2012
Biomolecular Classification in Endometrial Cancer: Onset, Evolution, and Further Perspectives: A Critical Review
Valentina Bruno1, Martina Betti2,3, Jessica Mauro4
1Gynecologic Oncology Unit, Department of Experimental Clinical Oncology, Istituto di Ricovero e Cura a Carattere Scientifico Regina Elena National Cancer Institute, 00128 Rome, Italy.
Abstract:
Since the new guidelines for endometrial cancer risk classification have been published, many reviews have proposed a critical re-evaluation. In this review, we look back to how the molecular classification system was built and its evolution in time to highlight the major flaws, particularly the biases stemming from the inherent limitations of the cohorts involved in the discoveries. A significant drawback in some cohorts is the inclusion criteria, as well as the retrospective nature and the notably sparse numbers, especially in the POLEmut (nonsynonymous mutation in EDM domain of POLE) risk groups, all of which impact the reliability of outcomes. Additionally, a disregard for variations in follow-up duration leads to a non-negligible bias, which raises a substantial concern in data interpretation and guideline applicability. Finally, according to the results that we obtained through a re-analysis of the confirmation cohort, the p53abn (IHC positive for p53 protein) subgroup, which is predominant in non-endometrioid histology (73-80%), loses its predictivity power in the endometrioid cohort of patients. The exclusion of non-endometrioid subtypes from the cohort led to a complete overlap of three molecular subgroups (all except POLEmut) for both overall and progression-free survival outcomes, suggesting the need for a more histotype-specific approach. In conclusion, this review challenges the current ESGO/ESTRO/ESP guidelines on endometrial cancer risk classification and highlights the limitations that must be addressed to better guide the clinical decision-making process.
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