Kit-based plasma metabolomics in a large-scale cohort - Application to cancer biomarker discovery

8th Munich Metabolomics Symposium
Applications of clinical metabolomics in oncology and cardiovascular diseases
Virtual event November 12th, 2021
Part 1 - Oncology & Immunology
Organized by Helmholtz Zentrum Munich, Technical University Munich, and biocrates
Prof. Dr. Eiji Hishinuma
Tohoku University, Sendai, Japan
Abstract:
Metabolomics is thought to be a good reflection of human phenotypic changes and has contributed greatly to the identification of biomarkers. However, the use of it in clinical practice is very rare. Therefore, it is particularly critical to reveal metabolomic profiles in vivo by utilizing large-scale cohort studies for the identification of disease biomarkers. Tohoku Medical Megabank Organization (ToMMo) stores many kinds of specimens obtained from large-scale cohort studies in the biobank and metabolome analysis is performed by using the plasma specimens. Until now, we have conducted several thousand plasma metabolome analysis using mass spectrometry. The results have been published in our database, Japanese Multi Omics Reference Panel (jMorp; jmorp.megabank..... In addition, Advanced Research Center for Innovations in Next-Generation Medicine (INGEM) was established and patient-derived specimens from Tohoku University Hospital are stored in the clinical biobank. Here, in this presentation, we would like to discuss the results of our research on the analysis of ToMMo plasma specimens using the Wide-Target Metabolome Analysis Kit and the evaluation of the quantitative values obtained. Moreover, we also performed plasma metabolome analysis on cancer specimens stored in INGEM clinical biobank with the same kit. Compared to the large cohort samples, plasma metabolome profiles were different in various cancer patients. Furthermore, we found that prognostic biomarkers that associated with high-risk patients. Thus, our research demonstrated that plasma metabolome analysis is useful not only for cancer diagnosis, but also for predicting prognosis and evaluating of chemotherapy response with the variation of metabolites.