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中华妇幼临床医学杂志(电子版) ›› 2023, Vol. 19 ›› Issue (04) : 403 -409. doi: 10.3877/cma.j.issn.1673-5250.2023.04.005

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子宫内膜癌患者淋巴管间隙浸润预测因素研究现状
韩春颖, 王婷婷, 李艳艳, 朴金霞()   
  1. 吉林省肿瘤医院妇瘤三科,长春 130012
  • 收稿日期:2023-01-08 修回日期:2023-07-01 出版日期:2023-08-01
  • 通信作者: 朴金霞

Current research status on predictors of lymphatic vascular invasion in patients with endometrial carcinoma

Chunying Han, Tingting Wang, Yanyan Li, Jinxia Piao()   

  1. Department of Gynecology and Oncology-3, Jilin Provincial Cancer Hospital, Changchun 130012, Jilin Province, China
  • Received:2023-01-08 Revised:2023-07-01 Published:2023-08-01
  • Corresponding author: Jinxia Piao
  • Supported by:
    Science and Technology Development Plan Project of Jilin Province(20200403096SF)
引用本文:

韩春颖, 王婷婷, 李艳艳, 朴金霞. 子宫内膜癌患者淋巴管间隙浸润预测因素研究现状[J/OL]. 中华妇幼临床医学杂志(电子版), 2023, 19(04): 403-409.

Chunying Han, Tingting Wang, Yanyan Li, Jinxia Piao. Current research status on predictors of lymphatic vascular invasion in patients with endometrial carcinoma[J/OL]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2023, 19(04): 403-409.

淋巴管间隙浸润(LVSI)状态,是影响子宫内膜癌(EC)患者的预后因素之一。目前对LVSI状态,主要依靠手术切除组织标本的组织病理学检测结果进行判断,尚具有一定局限性。关于LVSI状态预测EC患者预后的相关研究的分子水平检测,包括DNA及RNA与相关蛋白检测,这些均有助于预测EC患者的LVSI状态。根据EC患者临床数据开发的LVSI风险预测模型,如影像学数据及肿瘤标志物等相关预测模型,均可有助于临床判断LVSI状态,从而预测EC患者预后。笔者拟就目前关于EC患者LVSI状态的分子预测、免疫组织化学预测及LVSI状态风险预测模型的最新研究进展现状进行阐述,旨在为临床对EC患者的诊断及治疗方案制定提供参考。

Lymphatic vascular infiltration (LVSI) is one of the prognostic factors for patients with endometrial cancer(EC), but LVSI mainly depends on pathological analysis of surgical specimens, which has certain limitations. In recent years, preliminary progress has been made in the prediction of LVSI, such as molecular level detection, including DNA, RNA and related protein detection, which can help to predict LVSI status. Predictive models developed from clinical data can also aid in clinical judgment LVSI in patients with EC. The author intends to review the latest research progresses on molecular prediction, immunohistochemistry prediction, and related risk model prediction of LVSI status in patients with EC, with the aim of providing reference for clinical diagnosis and treatment planning of EC.

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