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Background: Optimal management for endometrial cancer in patients with clinically negative lymph nodes is still under debate. Several prediction models for lymphatic dissemination of early-stage endometrial cancer have been developed. However, external validation is rare, and decision curve analysis has hardly been applied for these models.Objective: To develop and validate a nomogram to predict lymph node metastasis of presumed stage I and II endometrial cancer.Study Design: The prediction nomogram was developed by using multivariable logistic regression with data for 700 EC patients who underwent initial surgery from 2006 to 2017 at Peking University People's Hospital (training dataset), Beijing. External validation was performed in 727 eligible patients from Fudan University Shanghai Cancer Center (validation dataset), Shanghai.Results: For the 700 women in the training dataset, the lymph node metastasis rate was 8.0% (56/700). Lymphovascular space invasion, histological grade, cervical stromal invasion, and myometrial invasion were independent prognostic factors in the training dataset. We generated a nomogram based on these pathological factors. To determine the clinical usefulness of our nomogram, we compared it with the Mayo criteria. For our nomogram, the area under the receiver operating characteristic curve (AUC) was 0.85 as compared with 0.63 for the Mayo criteria. In the validation dataset, the AUC was 0.78 as compared with 0.57 for the Mayo criteria. The nomogram was well-calibrated in both the training and validation datasets. At a 10% probability threshold, our nomogram decreased almost 29 unnecessary lymphadenectomies per 100 patients than the Mayo criteria without missing more metastatic disease.Conclusion: We developed a nomogram to predict lymph node metastasis in patients with early-stage endometrial cancer in China. This prediction model may help clinicians in decision-making for patients with early-stage endometrial cancer, especially for the patient with incomplete surgery, reducing overtreatment, and medical costs.

Diabetes is closely related to the occurrence of endometrial cancer (EC) and its poor prognosis. However, there is no effective clinical treatment for EC patients with diabetes (patientEC+/dia+). To explore new therapeutic targets, Ishikawa is cultured with high glucose (IshikawaHG) mimicking hyperglycemia in patientEC+/dia+. Subsequently, it is discovered that IshikawaHG exhibits glucose metabolic reprogramming characterized by increased glycolysis and decreased oxidative phosphorylation. Further, pyruvate dehydrogenase kinase 1 (PDK1) is identified to promote glycolysis of IshikawaHG by proteomics. Most importantly, JX06, a novel PDK1 inhibitor combined metformin (Met) significantly inhibits IshikawaHG proliferation though IshikawaHG is resistant to Met. Furthermore, a reduction‐sensitive biodegradable polymer is adopted to encapsulate JX06 to form nanoparticles (JX06‐NPs) for drug delivery. It is found that in vitro JX06‐NPs have better inhibitory effect on the growth of IshikawaHG as well as patient‐derived EC cells (PDC) than JX06. Additionally, it is found that JX06‐NPs can accumulate to the tumor of EC‐bearing mouse with diabetes (miceEC+/dia+) after intravenous injection, and JX06‐NPs combined Met can significantly inhibit tumor growth of miceEC+/dia+. Taken together, the study demonstrates that the combination of JX06‐NPs and Met can target the cancer metabolism plasticity, which significantly inhibits the growth of EC, thereby provides a new adjuvant therapy for patientsEC+/dia+.