ReviewFrontiers in oncology2026
Endometrial cancer molecular classification: research advances and clinical application.
Review in Frontiers in oncology, 2026. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors.
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Abstract
As research in molecular biology continues to advance, the classification of endometrial cancer has gradually shifted from traditional histology toward risk stratification based on the integration of molecular subtyping with clinicopathologic factors. Molecular subtyping has not only transformed our understanding of the biological heterogeneity of endometrial cancer but also provided new evidence for prognostic assessment and treatment selection. However, the maturity of clinical evidence and the translational therapeutic value vary across molecular subtypes. This review systematically summarizes the molecular characteristics and clinical significance of the POLE ultramutated(POLE-mut)subtype, mismatch repair deficient (dMMR) subtype, p53 abnormal (p53-abn) subtype, and no specific molecular profile (NSMP) subtype, with a focus on evaluating whether different molecular features can be further translated from risk stratification into specific treatment decisions. Centering on key issues such as de-escalated therapy for the POLE-mut subtype, the predictive value of immunotherapy for the dMMR subtype, intensified therapy for the p53-abn subtype, and further risk stratification of the NSMP subtype, this review analyzes the clinical basis and limitations of existing evidence and further discusses the challenges that tumors with multiple molecular features pose for classification and treatment decision making. Building on this, the paper compares how major international guidelines integrate molecular information with clinical and pathologic factors and analyzes real world implementation barriers such as testing standardization, result interpretation, and healthcare accessibility. Finally, it outlines the potential value of emerging technologies, including liquid biopsy, artificial intelligence, and multiomics, in dynamic risk assessment and precision therapy. This review aims to trace the continuum of evidence from molecular discovery to clinical action, clarifying which clinical decisions can be supported by existing molecular markers and identifying questions that current evidence cannot yet answer, thereby providing guidance for the precise application and clinical translation of molecular subtyping in endometrial cancer.
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