ReviewFrontiers in oncology2026
Molecular classification of endometrial cancer in fertility-sparing-treatment: toward a personalized clinical approach.
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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Authors and funding
6 authors.
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Abstract
Molecular classification has emerged as a promising tool to improve patient selection and prognostic stratification in fertility sparing treatment (FST) for endometrial cancer (EC). Although FST is currently considered a valid option for carefully selected patients with early stage, low grade endometrioid EC, recurrence rates remain substantial and conventional clinicopathologic criteria inadequately capture tumor biological heterogeneity. Current evidence suggests that NSMP tumors represent the most favorable subgroup for FST, showing the highest complete response rates and lowest recurrence rates, likely due to preserved estrogen and progesterone receptor signaling. In contrast, MMRd/MSI H and p53abn tumors demonstrate poorer oncologic outcomes, reduced sensitivity to progestin therapy, and higher recurrence rates. Although POLEmut tumors are associated with excellent prognosis after standard surgical management, this advantage does not clearly translate into superior outcomes during hormonal treatment. Additional biomarkers, including hormone receptor expression, PI3K/AKT/mTOR pathway alterations, and ARID1A, CTNNB1, and ESR1 mutations, may further refine prediction of treatment response within molecular subgroups. Despite its clinical potential, the widespread implementation of molecular classification remains limited by economic and infrastructural barriers, including restricted access to sequencing technologies. Future prospective studies are needed to validate molecular guided fertility sparing strategies and to integrate molecular profiling with additional predictive biomarkers in order to optimize individualized management of young women with EC.
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