Marisa Huang1, Hung-Yuan Li2, Hsiao-Wei Liao1,3, Ching-Hung Lin4,5, Chin-Yi Wang1, Wen-Hung Kuo6, Ching-Hua Kuo1,2,7. 1. School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan. 2. Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan. 3. The Metabolomics Core Laboratory, Center of Precision Medicine, National Taiwan University, Taipei, Taiwan. 4. Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan. 5. Department of Medical Oncology, National Taiwan University Cancer Center Hospital, Taipei, Taiwan. 6. Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan. 7. Department of Pharmacy, National Taiwan University Hospital, Taipei, Taiwan.
Abstract
RATIONALE: Breast cancer is one of the most common cancers among women and its associated mortality is on the rise. Metabolomics is a potential strategy for breast cancer detection. The post-column infused internal standard (PCI-IS)-assisted liquid chromatography/tandem mass spectrometry (LC/MS/MS) method has been demonstrated as an effective strategy for quantitative metabolomics. In this study, we evaluated the performance of targeted metabolomics with the PCI-IS quantification method to identify women with breast cancer. METHODS: We used metabolite profiling to identify 17 dysregulated metabolites in breast cancer patients. Two LC/MS/MS methods in combination with the PCI-IS strategy were developed to quantify these metabolites in plasma samples. Detection models were built through the analysis of plasma samples from 176 subjects consisting of healthy volunteers and breast cancer patients. RESULTS: Three isotope standards were selected as the PCI-ISs for the metabolites. The accuracy was within 82.8-114.16%, except for citric acid and lactic acid at high concentration levels. The repeatability and intermediate precision were all lower than 15% relative standard deviation. We have identified several metabolites that indicate the presence of breast cancer. The area under the receiver operating characteristics (AUROC) curve, sensitivity and specificity of the linear combinations of metabolite concentrations and age with the highest AUROC were 0.940 (0.889-0.992), 88.4% and 94.2% for pre-menopausal woman, respectively, and 0.828 (0.734-0.922), 73.5% and 85.1% for post-menopausal women, respectively. CONCLUSIONS: The targeted metabolomics with PCI-IS quantification method successfully established prediction models for breast cancer detection. Further study is essential to validate these proposed markers.
RATIONALE: Breast cancer is one of the most common cancers among women and its associated mortality is on the rise. Metabolomics is a potential strategy for breast cancer detection. The post-column infused internal standard (PCI-IS)-assisted liquid chromatography/tandem mass spectrometry (LC/MS/MS) method has been demonstrated as an effective strategy for quantitative metabolomics. In this study, we evaluated the performance of targeted metabolomics with the PCI-IS quantification method to identify women with breast cancer. METHODS: We used metabolite profiling to identify 17 dysregulated metabolites in breast cancerpatients. Two LC/MS/MS methods in combination with the PCI-IS strategy were developed to quantify these metabolites in plasma samples. Detection models were built through the analysis of plasma samples from 176 subjects consisting of healthy volunteers and breast cancerpatients. RESULTS: Three isotope standards were selected as the PCI-ISs for the metabolites. The accuracy was within 82.8-114.16%, except for citric acid and lactic acid at high concentration levels. The repeatability and intermediate precision were all lower than 15% relative standard deviation. We have identified several metabolites that indicate the presence of breast cancer. The area under the receiver operating characteristics (AUROC) curve, sensitivity and specificity of the linear combinations of metabolite concentrations and age with the highest AUROC were 0.940 (0.889-0.992), 88.4% and 94.2% for pre-menopausal woman, respectively, and 0.828 (0.734-0.922), 73.5% and 85.1% for post-menopausal women, respectively. CONCLUSIONS: The targeted metabolomics with PCI-IS quantification method successfully established prediction models for breast cancer detection. Further study is essential to validate these proposed markers.
Authors: Alex Ap Rosini Silva; Marcella R Cardoso; Luciana Montes Rezende; John Q Lin; Fernando Guimaraes; Geisilene R Paiva Silva; Michael Murgu; Denise Gonçalves Priolli; Marcos N Eberlin; Alessandra Tata; Livia S Eberlin; Sophie F M Derchain; Andreia M Porcari Journal: Int J Mol Sci Date: 2020-05-20 Impact factor: 5.923