Mapping the Human Metabolome for Functional Metabolomics

In recent years, significant efforts have been focussed into understanding metabolic reprograming in cancer with the hope of discerning context-specific biology that is exploitable for either for diagnosis or treatment. While some generalized phenomena such as the ‘Warburg Effect’ have been identified, the metabolic landscape of cancer is highly heterogeneous, as tumors from the same sub-type can exhibit vastly different metabolic profiles, which can influence disease progression and response to treatments. As research begins to study how generalized treatments fail for specific patients and cancers, we need to understand what makes specific cancer lineages unique, in order to identify potential vulnerabilities with a greater level of precision. While other ‘omics fields have quantified the expression of genes, transcripts and proteins of hundreds of tissue and cell types, our understanding of the metabolic composition of human cells remains rudimentary, and only a limited number of highly targeted metabolite maps of cancer cell lines currently exist. Our work focuses on addressing this limitation by systematically mapping the metabolomes of a broad range of human cell lines including patient derived cancer cell lines using large scale LC-MS-based metabolomics and lipidomics analyses. With hundreds of mapped metabolites, these maps have yielded valuable insights into the metabolites that are highly specific to individual cell types and diseases (i.e. biomarkers) as well as cancer-selective metabolic vulnerabilities and ‘choke-points’ for specific cancer lineages, leveraging existing drugs and chemical inhibitors with wide therapeutic windows.