Nunes Sofia C, Sousa Joana, Silva Fernanda, Silveira Margarida, Guimarães António, Serpa Jacinta, Félix Ana, Gonçalves Luís G
iNOVA4Health, NOVA Medical School, Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria 130, 1169-056 Lisboa, Portugal.
Instituto Português de Oncologia de Lisboa Francisco Gentil (IPOLFG), Rua Prof Lima Basto, 1099-023 Lisbon, Portugal.
Metabolites. 2023 Sep 1;13(9):989. doi: 10.3390/metabo13090989.
Ovarian cancer is the major cause of death from gynecological cancer and the third most common gynecological malignancy worldwide. Despite a slight improvement in the overall survival of ovarian carcinoma patients in recent decades, the cure rate has not improved. This is mainly due to late diagnosis and resistance to therapy. It is therefore urgent to develop effective methods for early detection and prognosis. We hypothesized that, besides being able to distinguish serum samples of patients with ovarian cancer from those of patients with benign ovarian tumors, H-NMR metabolomics analysis might be able to predict the malignant potential of tumors. For this, serum H-NMR metabolomics analyses were performed, including patients with malignant, benign and borderline ovarian tumors. The serum metabolic profiles were analyzed by multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) methods. A metabolic profile associated with ovarian malignant tumors was defined, in which lactate, 3-hydroxybutyrate and acetone were increased and acetate, histidine, valine and methanol were decreased. Our data support the use of H-NMR metabolomics analysis as a screening method for ovarian cancer detection and might be useful for predicting the malignant potential of borderline tumors.
卵巢癌是妇科癌症死亡的主要原因，也是全球第三大常见的妇科恶性肿瘤。尽管近几十年来卵巢癌患者的总体生存率略有提高，但治愈率并未改善。这主要是由于诊断较晚和对治疗产生耐药性。因此，迫切需要开发有效的早期检测和预后方法。我们假设，除了能够区分卵巢癌患者与良性卵巢肿瘤患者的血清样本外，氢核磁共振代谢组学分析或许还能够预测肿瘤的恶性潜能。为此，我们对患有恶性、良性和交界性卵巢肿瘤的患者进行了血清氢核磁共振代谢组学分析。通过多变量统计分析，包括主成分分析（PCA）和正交偏最小二乘判别分析（OPLS-DA）方法，对血清代谢谱进行了分析。确定了一种与卵巢恶性肿瘤相关的代谢谱，其中乳酸、3-羟基丁酸和丙酮增加，而乙酸盐、组氨酸、缬氨酸和甲醇减少。我们的数据支持将氢核磁共振代谢组学分析用作卵巢癌检测的筛查方法，并且可能有助于预测交界性肿瘤的恶性潜能。
