Gynecology and Obstetrics Unit, Department of Neuroscience, Reproductive Sciences and Dentistry, School of Medicine, University of Naples Federico II, Naples, Italy.
Department of Medicine, Surgery and Dentistry, "Scuola Medica Salernitana", Neuroscience Section, University of Salerno, Baronissi, Italy.
Acta Obstet Gynecol Scand. 2020 Sep;99(9):1135-1146. doi: 10.1111/aogs.13847. Epub 2020 Apr 9.
Endometrial cancer (EC) is the most common gynecological malignancy in the developed world. The prognosis of EC strongly depends on tumor stage, hence the importance of improving diagnosis. Metabolomics has recently appeared as a promising test for a non-invasive diagnosis of several diseases. Nevertheless, no metabolic marker has been approved for use in the routine practice. We aimed to provide an overview of metabolomics findings in the diagnosis of EC.
A systematic review was performed by searching eight electronic databases from their inception to October 2019 for studies assessing metabolomics in EC diagnosis. Extracted data included characteristics of patients and EC, serum concentration of metabolites in women with and without EC and its association with EC diagnosis, tumor behavior and pathological characteristics.
Six studies with 732 women (356 cases and 376 controls) were included. Several metabolites were found able to predict the presence of EC, tumor behavior (progression and recurrence) and pathological characteristics (histotype, myometrial invasion and lymph vascular space invasion).
Metabolomics might be suitable for a non-invasive diagnosis and screening of EC, offering the possibility to predict tumor behavior and pathological characteristics. Further studies are necessary to validate these results.
子宫内膜癌(EC)是发达国家最常见的妇科恶性肿瘤。EC 的预后强烈依赖于肿瘤分期,因此提高诊断水平非常重要。代谢组学最近作为一种非侵入性诊断多种疾病的有前途的检测方法出现。然而,还没有代谢标志物被批准用于常规临床实践。我们旨在提供代谢组学在 EC 诊断中的研究结果的概述。
通过从创建到 2019 年 10 月在八个电子数据库中进行系统检索,评估了评估 EC 诊断中代谢组学的研究。提取的数据包括患者和 EC 的特征、EC 患者和非 EC 患者血清代谢物浓度及其与 EC 诊断、肿瘤行为和病理特征的相关性。
纳入了 6 项共 732 名女性(356 例病例和 376 例对照)的研究。发现了几种代谢物能够预测 EC 的存在、肿瘤行为(进展和复发)和病理特征(组织类型、肌层浸润和淋巴血管空间浸润)。
代谢组学可能适合 EC 的非侵入性诊断和筛查,提供了预测肿瘤行为和病理特征的可能性。需要进一步的研究来验证这些结果。