Pre-treatment risk assessment of women with endometrial cancer: differences in outcomes of molecular and clinical classifications in the Slovenian patient cohort

子宫内膜癌女性治疗前风险评估:斯洛文尼亚患者队列中分子分型和临床分型结果的差异

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Abstract

BACKGROUND: The aim of this study was to evaluate changes in prognostic risk profiles of women with endometrial cancer by comparing the clinical risk assessment with the integrated molecular risk assessment profiling. PATIENTS AND METHODS: This prospective study recruited patients with biopsy proven endometrial cancer treated at the University Medical Centre Maribor between January 2020 to February 2021. Patient clinical data was assessed and categorized according to the currently valid European Society of Gynaecological Oncology, European SocieTy for Radiotherapy and Oncology, and European Society of Pathology (ESGO/ESTRO/ESP) guidelines on endometrial cancer. Molecular tumour characterization included determination of exonuclease domain of DNA polymerase-epsilon (POLE) mutational status by Sanger sequencing and imunohistochemical specimen evaluation on the presence of mismatch repair deficiencies (MMRd) and p53 abnormalities (p53abn). RESULTS: Fourty-five women were included in the study. Twenty-two tumours were of non-specific mutational profile (NSMP) (56.4%), 13 were classified as MMRd (33.3%), 3 were classified as p53abn (7.7%) and 1 was classified as POLE mutated (2.6%). Six tumours (15.4%) had multiple molecular classifiers, these were studied separately and were not included in the risk assessment. The clinical risk-assessment classified 21 women (53.8%) as low-risk, 5 women (12.8%) as intermediate risk, 2 women as high-intermediate risk (5.1%), 10 women (25.6%) as high risk and 1 patient as advanced metastatic (2.6%). The integrated molecular classification changed risk for 4 women (10.3%). CONCLUSIONS: Integrated molecular risk improves personalized risk assessment in endometrial cancer and could potentially improve therapeutic precision. Further molecular stratification with biomarkers is especially needed in the NSMP group to improve personalized risk-assessment.

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