TGFβ Drives Metabolic Perturbations during Epithelial Mesenchymal Transition in Pancreatic Cancer: TGFβ Induced EMT in PDAC

Simple Summary Pancreatic cancer is an aggressive disease with most patients diagnosed at late stages resulting in poor outcomes. While it is known that pancreatic tumor cells undergo epithelial to mesenchymal transition, the metabolic alterations accompanying that transition are not characterized. This study leveraged a metabolomics approach to understand the small molecule and biochemical perturbations that can be targeted for designing strategies for improving outcomes in pancreatic cancer. Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy wherein a majority of patients present metastatic disease at diagnosis. Although the role of epithelial to mesenchymal transition (EMT), mediated by transforming growth factor beta (TGF beta), in imparting an aggressive phenotype to PDAC is well documented, the underlying biochemical pathway perturbations driving this behaviour have not been elucidated. We used high-resolution mass spectrometry (HRMS) based molecular phenotyping approach in order to delineate metabolic changes concomitant to TGF beta-induced EMT in pancreatic cancer cells. Strikingly, we observed robust changes in amino acid and energy metabolism that may contribute to tumor invasion and metastasis. Somewhat unexpectedly, TGF beta treatment resulted in an increase in intracellular levels of retinoic acid (RA) that in turn resulted in increased levels of extracellular matrix (ECM) proteins including fibronectin (FN) and collagen (COL1). These findings were further validated in plasma samples obtained from patients with resectable pancreatic cancer. Taken together, these observations provide novel insights into small molecule dysregulation that triggers a molecular cascade resulting in increased EMT-like changes in pancreatic cancer cells, a paradigm that can be potentially targeted for better clinical outcomes.

Automated summary

Pancreatic cancer is an aggressive disease with poor outcomes due to late diagnosis. Metabolomics approach revealed metabolic changes that could potentially improve clinical outcomes.