Predictive value of IGF2BP2 for endometrial cancer recurrence: a multicenter study

Area of Science:

• Oncology
• Genetics
• Biomarkers

Background:

• Endometrial cancer (EC) recurrence poses a significant clinical challenge.
• Identifying reliable prognostic factors is crucial for personalized treatment strategies.
• IGF2BP2 has emerged as a potential biomarker in various cancers.

Purpose of the Study:

• To develop and validate a prognostic model for predicting postoperative recurrence-free survival (RFS) in endometrial cancer (EC) patients.
• To assess the predictive value of Insulin-like Growth Factor 2 Binding Protein 2 (IGF2BP2) in combination with clinicopathological parameters.
• To establish a nomogram-based tool for quantitative risk stratification.

Main Methods:

• Retrospective multicenter study involving 860 endometrial cancer patients (545 training, 315 validation).
• Univariate and multivariate Cox regression analyses to identify independent prognostic factors for RFS.
• Development and validation of a nomogram incorporating identified factors, with evaluation using AUC and calibration curves.

Main Results:

• Multivariate analysis identified FIGO stage, myometrial invasion depth, histologic type, CA125, p53 status, lymphovascular space invasion, and IGF2BP2 expression as independent predictors of RFS.
• The integrated nomogram model demonstrated excellent performance in predicting 1-, 3-, and 5-year RFS.
• The model showed superior discriminative ability (AUC = 0.884) compared to single-parameter models.

Conclusions:

• The developed nomogram integrating IGF2BP2 and clinicopathological parameters accurately predicts RFS in EC patients.
• This tool offers a quantitative framework for prognostic assessment and risk stratification.
• Further prospective validation is recommended for clinical implementation.