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

Issue link:

Contents of this Issue


Page 23 of 50

22 Clinical OMICs May/June 2019 tumor, the therapy will not be efficacious, leading to poor patient survival. Genetics cannot predict these findings, Fan said. Genomic screens are useful if the mutation has to do with the drug effects, but she finds that is not often the case as there are many examples where the environment determines the efficiency. Fan noted that we "need to put all of the omics together to tease apart a patient's complexity." Some researchers work to map out metabolic landscapes of specific can- cers. For example, recently published work in Cancer and Metabolism from the Littlepage Lab identified specific metabolic changes occurring during breast cancer, not only as com- pared to normal tissue but also as induced by multiple individual oncogenes. The team mapped out the metabolic landscapes of a few commonly used genetically engineered mouse models of breast cancer, a useful resource for peo- ple who use these models to mimic human breast cancer patients to understand the effect of oncogenes. "Learning how individual molecular alterations perturb the metabolic landscape is essential to our understanding of how altered metabolism can be utilized as a vulnerability and targeted with therapy," said Littlepage. The long and winding road The databases currently being built still are not broadly applicable in the clinic. In order to use metabolomics for diagnostics, and identifying a specific biomarker which cannot be detected with other, cheaper tools is necessary. Not only that, metabolomics is expensive and analysis can be time-consuming. So, a facility capable of quickly and cost-efficiently detecting the biomarker is also required. One researcher noted that it cost "over $20,000 for 36 sam- ples to run and analyze, and it took months to get the final data analyzed." Even after all of this, due to the various different sample preparation methods and separation tech- niques, there might be metabolites whose levels are biased and may need to be verified with other methods. Even if all of the data is absolutely accurate, there are still not nearly as many good metabolic biomarkers as there are genetic ones. Sample collection from patients is another important con- sideration of bringing metabolomics to the clinic. Despite the challenges that surround the sheer enormity of building a metabolomics database and other aspects of metabolomics, the researchers in the field see their work playing a role in advancing cancer treatment and diagnosis in the future. As Fiehn noted, it is "a long way to go from a cool idea to use as a standard in care." But, metabolomics is uniquely positioned as a readout of mechanism and func- tion. It can take many different studies to ascertain what a genetic mutation does and generations to see changes. However, in metabolomics, a change can be measured in minutes. With its many advantages and challenges, Fan said that "metabolomics is at that early stage—just like where genomics and proteomics started. But, we'll get there." (continued from previous page) Shankar Subramaniam, Ph.D., UCSD School of Medicine A mass spectrometer is a vital tool in metabolomics research. undefined / iStock / Getty Images

Articles in this issue

Links on this page

Archives of this issue

view archives of Clinical OMICS - MAY-JUN 2019