Metabolomic biomarkers for benign conditions and malignant ovarian cancer: Advancing early diagnosis

• Published in: Clinica chimica acta 2024-06, Vol.560, p.119734-119734, Article 119734
• Main Authors: Zhang, Wenjia, Lai, Zhizhen, Liang, Xiaoyue, Yuan, Zhonghao, Yuan, Yize, Wang, Zhigang, Peng, Peng, Xia, Liangyu, Yang, XiaoLin, Li, Zhili
• Format: Article
• Language: English
• Subjects: Adult; Aged; Biomarker; Biomarkers, Tumor - blood; Chromatography, High Pressure Liquid; Early Detection of Cancer; Early-diagnosis; Female; Humans; Machine learning; Metabolomics; Middle Aged; Ovarian cancer; Ovarian Neoplasms - blood; Ovarian Neoplasms - diagnosis; Ovarian Neoplasms - metabolism; Tandem Mass Spectrometry
• ISSN: 0009-8981; 1873-3492
• DOI: 10.1016/j.cca.2024.119734

•Three metabolites panel serves as new biomarkers for early ovarian cancer detection.•The panel surpasses CA125 in benign conditions vs. malignant ovarian cancer diagnosis.•Glycerophospholipid pathways play vital roles in ovarian cancer progression. Ovarian cancer (OC) is a major global cause of death among gynecological cancers, with a high mortality rate. Early diagnosis, distinguishing between benign conditions and early malignant OC forms, is vital for successful treatment. This research investigates serum metabolites to find diagnostic biomarkers for early OC identification. Metabolomic profiles derived from the serum of 60 patients with benign conditions and 60 patients with malignant OC were examined using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). Comparative analysis revealed differential metabolites linked to OC, aiding biomarker identification for early-diagnosis of OC via machine learning features. The predictive ability of these biomarkers was evaluated against the traditional biomarker, cancer antigen 125 (CA125). 84 differential metabolites were identified, including 2-Thiothiazolidine-4-carboxylic acid (TTCA), Methionyl-Cysteine, and Citrulline that could serve as potential biomarkers to identify benign conditions and malignant OC. In the diagnosis of early-stage OC, the area under the curve (AUC) for Citrulline was 0.847 (95 % Confidence Interval (CI): 0.719–0.974), compared to 0.770 (95 % CI: 0.596–0.944) for TTCA, and 0.754 for Methionine-Cysteine (95 % CI: 0.589–0.919). These metabolites demonstrate a superior diagnostic capability relative to CA125, which has an AUC of 0.689 (95 % CI: 0.448–0.931). Among these biomarkers, Citrulline stands out as the most promising. Additionally, in the diagnosis of benign conditions and malignant OC, using logistic regression to combine potential biomarkers with CA125 has an AUC of 0.987 (95 % CI: 0.9708–1) has been proven to be more effective than relying solely on the traditional biomarker CA125 with an AUC of 0.933 (95 % CI: 0.870–0.996). Furthermore, among all the differential metabolites, lipid metabolites dominate, significantly impacting glycerophospholipid metabolism pathway. The discovered serum metabolite biomarkers demonstrate excellent diagnostic performance for distinguishing between benign conditions and malignant OC and for early diagnosis of malignant OC.