A major challenge in the development of cancer therapeutics is that cancerous cells share a lot in common with our healthy cells. Thus, it is difficult to find drugs that target cancerous cells but not our healthy cells. However, in contrast to the similarities between cancerous cells and healthy cells, the microenvironments of tumors and tissues are strikingly different. For example, healthy tissues are properly plumbed into the circulatory system and receive nutrients and oxygen that they need to efficiently function. In contrast, tumors have abnormal vasculature, which leaves the tumor strikingly impaired in nutrient delivery. We proposed that cancer cells may require adaptations to cope with altered nutrient availability in the tumor microenvironment (TME), which could be targeted with a wide-therapeutic window as cells in healthy microenvironments would not need such adaptations. Thus, the abnormal TME could provide additional specificity that would aid cancer therapeutic development. We previously performed a genetic screen of pancreatic cancer cells growing under tumor microenvironmental nutritional constraints to identify the genes that are required for pancreatic cancer cells to grow under these conditions. We found that pancreatic cancer cells under these conditions are extremely sensitive to loss of enzymes involved in the uptake and metabolism of fatty acids and the vitamin riboflavin. This suggests that targeting riboflavin or fatty acid metabolism could specifically impair the progression of pancreatic cancer. In this project, we will explore the underlying metabolic bases for why these pathways are conditionally essential in nutrient stressed cells.

First, we will identify the specific metabolic stressors that cause cells to rely on enhanced fatty acid/riboflavin/sphingolipid metabolism. Second, we will use cutting-edge metabolomics analyses to understand why the identified metabolic stressors alters pancreatic cancer reliance on these metabolic pathways. Lastly, we will use animal models of pancreatic cancer to understand the impact that targeting these pathways would have on tumor progression and host survival.

This project will utilize advanced CRISPR-based gene expression perturbations, GC- and LC-MS based metabolomics analysis, stable isotope-assisted analysis of metabolic flux and animal models of pancreatic cancer. There will be ample opportunities to learn the analytical chemistry involved in the metabolomics analysis as well as the multivariate statistical approaches used to analyze these data sets.

All software supplied by the lab.

AACR, Keystone