Clinical OMICS

MAY-JUN 2019

Healthcare magazine for research scientists, labs, pathologists, hospitals, cancer centers, physicians and biopharma companies providing news articles, expert interviews and videos about molecular diagnostics in precision medicine

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20 Clinical OMICs May/June 2019 www.clinicalomics.com imental data "spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educa- tional resources." Just last fall, the University of California San Diego received a $12-million, four-year grant from the National Institutes of Health to expand the workbench. Other databases are being built, including the Genome Canada-funded Human Metabolome Database (HMD- B)—a comprehensive, openly accessible, online database of human small molecule metabolites—created by the Human Metabolome Project. In addition, the Biological Magnetic Resonance Data Bank (BMRD) collects, annotates, archives, and disseminates spectral and quantitative data derived from NMR spectroscopic investigations of biological macro- molecules and metabolites. Although the focus of these large resources is not can- cer, specifically, the growth of information will undoubt- edly have far reaching effects on the field as a whole. And, because metabolomics reaches deep into the nooks and crannies of all human physiology, gains in cancer metabolo- mics are sure to follow. "Contract research organizations (CROs) that conduct metabolomics (such as Metabolon) have improved over the past decade" said Chen Dai, Ph.D., a recently defended graduate student in Laurie Littlepage's lab at University of Notre Dame. Now, continued Dai, "we have a much more complete understanding of metabolism as a system, and much better databases with the spectra of thousands of metabolites, which allows for identification of more metabolites than ever before. Such advances in the tools has brought great discoveries, one of which is the discov- ery of oncometabolites." It is not only the detection of metabolites that is import- ant, but the tools that allow for the analysis of huge datasets which should facilitate the systematic study of metabolism. "Metabolism is notoriously complicated, and that complexity creates problems in research as altering one component can have unforeseen effects across many other pathways, which is really difficult to analyze" noted Dai. He adds that new tools "allow for the integration of metabolomics data with proteomics and transcriptomics data, presenting a systematic picture of the interactions and changes." (continued from previous page) Researchers are combining information from next-generation sequencing with metabolomics data to gain new insights in cancer. "Metabolism is notoriously complicated, and that complexity creates problems in research as altering one component can have unforeseen effects across many other pathways, which is really difficult to analyze." —Chen Dai, Ph.D., University of Notre Dame Monty Rakusen / Cultura / Getty Images

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