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Molecular classification of endometrial carcinoma on endometrial biopsy: an early prognostic value to guide
Stefano Restaino1,2, Alice Poli1,3, Martina Arcieri4
1Clinic of Obstetrics and Gynecology, 'Santa Maria della Misericordia' University Hospital, Azienda Sanitaria Universitaria Friuli Centrale, Udine, Italy.
Objective:
Molecular features are essential for estimating the risk of recurrence and impacting overall survival in patients with endometrial cancer. Additionally, the surgical procedure itself could be personalized based on the molecular characteristics of the tumor. This study aims to assess the feasibility of obtaining reliable molecular classification status from biopsy specimens collected during hysteroscopy to better modulate the appropriate surgical treatment.
Methods:
This monocentric, retrospective, observational study was conducted on 106 patients who underwent a biopsy procedure followed by radical surgery for endometrial cancer, with concurrent molecular investigation. The molecular classification was determined through immunohistochemical staining for p53 and mismatch repair proteins, along with gene sequencing for POLE.
Results:
Overall, 106 patients underwent molecular investigation, which was finally achieved on 99 patients (93.4%). Among these, the molecular analysis was conducted in 71 patients (67%) on the pre-operative endometrial biopsy and on the final uterine specimen in 28 patients (26.4%). Most of the endometrial biopsies were performed using Bettocchi hysteroscopy (66%). Molecular analysis was not possible in seven patients (6.6%), with six cases due to sample inadequacy and one case attributed to intra-mucosal carcinoma. The molecular results showed that the copy number low sub-group was the most common, and five cases of 'multiple classifiers' were observed in the low-risk category.
Conclusion:
Our experience in obtaining molecular information from biopsy samples underscores the feasibility and efficacy of this technique, even in small tissue samples. This capability helps define the prognostic group of patients, facilitates timely decision-making, and develops a personalized strategy for each patient.
