Toward Biology-Driven Surveillance After Endometrial Cancer Treatment: A Molecular–Clinical Framework Integrating Recurrence Phenotype

Background: Current post-treatment surveillance strategies for endometrial cancer rely predominantly on clinical stage and histological grade, without integration of molecular tumor biology. Molecular classification has revealed profound biological heterogeneity across endometrial cancer subtypes, including differences in recurrence patterns, prognosis, and treatment responsiveness, yet surveillance strategies have not been systematically adapted to reflect this heterogeneity. Objective: To propose a biology-driven surveillance framework for endometrial cancer that integrates molecular subtype, clinicopathological risk factors, and recurrence phenotype. Methods: This narrative review and conceptual framework synthesizes evidence from cohort studies, molecular classification analyses, international guidelines, and the literature addressing recurrence patterns and treatment responsiveness across molecular subtypes of endometrial cancer. Results: We propose a three-tier surveillance model stratifying patients into low-, intermediate-, and high-risk groups. The framework integrates molecular subtype with clinicopathological modifiers and expected recurrence phenotype. Within the no specific molecular profile (NSMP) subtype, CTNNB1 mutation status is incorporated as a primary modifier, assigning CTNNB1-mutated tumors to the intermediate-risk group regardless of estrogen receptor (ER) status. In CTNNB1 wild-type NSMP tumors, ER expression functions as a secondary modifier, allowing identification of a biologically low-risk subgroup. L1CAM expression is considered a high-risk modifier within NSMP. The framework also accounts for differences in the therapeutic modifiability of recurrence, including the role of immunotherapy in mismatch repair-deficient tumors. Conclusions: Uniform post-treatment surveillance does not reflect the biological diversity of endometrial cancer. The proposed framework provides a biologically grounded approach to surveillance that aligns follow-up intensity with recurrence phenotype and therapeutic opportunities. This model may serve as a conceptual basis for prospective studies evaluating personalized surveillance strategies in endometrial cancer.