Abstract：
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.
CONCLUSIONS: 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.
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.
CONCLUSIONS: 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.
摘要：
目的：分子特征对于评估子宫内膜癌患者的复发风险和影响总生存期至关重要。此外,外科手术本身可以根据肿瘤的分子特征进行个性化。本研究旨在评估从宫腔镜检查期间收集的活检标本中获得可靠分子分类状态的可行性，以更好地调整适当的手术治疗。
方法：这个单中心，回顾性,对106例子宫内膜癌患者进行了活检，然后进行了根治性手术，同时进行分子研究。通过p53和错配修复蛋白的免疫组织化学染色确定分子分类，以及POLE的基因测序。
结果：总体而言，106名患者接受了分子调查，最终在99例患者（93.4％）中实现了这一目标。其中,对71例患者(67%)进行了术前子宫内膜活检,对28例患者(26.4%)的最终子宫标本进行了分子分析.大多数子宫内膜活检是使用Bettocchi宫腔镜进行的（66％）。7例患者（6.6%）无法进行分子分析，其中6例因样本不足，1例归因于粘膜内癌。分子研究结果表明,拷贝数低亚组是最常见的,在低风险类别中观察到5例“多分类器”。
结论：我们从活检样本中获得分子信息的经验强调了这种技术的可行性和有效性，甚至在小组织样本中。这种能力有助于确定患者的预后组，有利于及时决策，并为每个患者制定个性化策略。
方法：这个单中心，回顾性,对106例子宫内膜癌患者进行了活检，然后进行了根治性手术，同时进行分子研究。通过p53和错配修复蛋白的免疫组织化学染色确定分子分类，以及POLE的基因测序。
结果：总体而言，106名患者接受了分子调查，最终在99例患者（93.4％）中实现了这一目标。其中,对71例患者(67%)进行了术前子宫内膜活检,对28例患者(26.4%)的最终子宫标本进行了分子分析.大多数子宫内膜活检是使用Bettocchi宫腔镜进行的（66％）。7例患者（6.6%）无法进行分子分析，其中6例因样本不足，1例归因于粘膜内癌。分子研究结果表明,拷贝数低亚组是最常见的,在低风险类别中观察到5例“多分类器”。
结论：我们从活检样本中获得分子信息的经验强调了这种技术的可行性和有效性，甚至在小组织样本中。这种能力有助于确定患者的预后组，有利于及时决策，并为每个患者制定个性化策略。
