Simplifying Cancer Complexity And Improving Clinical Success with Metabolomics: Part 2
By Dr. Kirk Beebe
Cancer continues to be a formidable disease with an overall success rate of bringing drugs to market of only 5-8%. This high failure rate is often attributed to a deficit between pre-clinical knowledge and clinical efficacy and illustrates the need for better translatability of preclinical research to the population of patients likely to benefit. Cancer is an extraordinarily complex disease involving, a heterogeneous mix of genetically mercurial cancer cells, stroma, and microenvironment across at least 200 different cancer types. Even with a specific cancer type, heterogeneity within patients impairs clinical development. Thus, the clinical challenges are substantial - to produce a meaningful regression or survival benefit based on targeting an important aspect or aspects of this complex biology.
Molecular targets are being explored for many cancers but preclinical models of cancer are frequently insufficient in translating promising therapies to clinical success. These therapies may be prone to resistance as well. Metabolomics is a key data stream that can address the critical need to fully understand the target’s environment to begin to unravel the basis of sensitivity and resistance. Thus, opportunities to identify the right drug combinations that will most likely work in concert with the molecularly targeted therapy.
There is a growing recognition that many cancer cells are metabolically rewired compared to normal cells1. This was first proposed by Otto Warburg in the 1920s where he speculated that aberrant metabolism could be the cause of many cancers2-4. These perturbed cells appear to gain metabolic flexibility and in some ways are metabolic “omnivores”5,6. Central to much of this rewiring, glycolytic enzymes are highly upregulated and/or dysregulated in cancer cells7. In addition many cancer cells are disproportionally dependent on glutamine metabolism. Although a focus of many investigators, a thorough understanding of their metabolic role in tumorigenesis remains mostly elusive7 and, given the metabolic derangements in tumorigenesis, metabolomics is primed to inform not only on the discrete biochemical differences but also on what those changes mean in the context of biology.