A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses

To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts. Metabolomic profiling was performed on an initial set of sera from 101 serous and nonsero...

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Published in:Clinical cancer research Vol. 28; no. 21; p. 4669
Main Authors: Irajizad, Ehsan, Han, Chae Y, Celestino, Joseph, Wu, Ranran, Murage, Eunice, Spencer, Rachelle, Dennison, Jennifer B, Vykoukal, Jody, Long, James P, Do, Kim Anh, Drescher, Charles, Lu, Karen, Lu, Zhen, Bast, Robert C, Hanash, Sam, Fahrmann, Johannes F
Format: Journal Article
Language:English
Published: United States 01.11.2022
Subjects:
Algorithms
Biomarkers, Tumor
CA-125 Antigen
Carcinoma, Ovarian Epithelial
Female
Humans
Neoplasms, Glandular and Epithelial
Ovarian Neoplasms - pathology
Proteins - metabolism
WAP Four-Disulfide Core Domain Protein 2
ISSN:1557-3265, 1557-3265
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Summary:To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts. Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed. A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76-0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84-0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84-0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P < 0.001) with improved specificity (0.89 vs. 0.78; one-sided P < 0.001) for early-stage ovarian cancer compared with ROMA alone. A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.
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ISSN:1557-3265
1557-3265
DOI:10.1158/1078-0432.CCR-22-1113