Summary
Pancreatic ductal adenocarcinoma (PDAC) has a poor 5-year survival rate and lacks effective therapeutics. Therefore, it is of paramount importance to identify new targets. Using multi-plex data from patient tissue, three-dimensional co-culturing in vitro assays, and orthotopic murine models, we identified Netrin G1 (NetG1) and Netrin G1 ligand (NGL-1) as promoters of PDAC tumorigenesis. NetG1+ cancer-associated fibroblasts (CAFs) supported PDAC survival, through a NetG1/NGL-1 mediated effect on glutamate/glutamine metabolism. NetG1+ CAFs were intrinsically immunosuppressive and inhibited NK cell mediated killing of tumor cells. These functions were partially mediated by vesicular glutamate transporter 1 and glutamine synthetase. This study uncovered an important link between CAF driven metabolism and its immunosuppressive capacity, suggesting NetG1 and NGL-1 as potential targets in PDAC.
Significance PDAC is a devastating disease lacking effective therapies. A major hallmark of PDAC is desmoplasia, characterized by the expansion of CAFs and their extracellular matrix, creating a unique microenvironment that limits blood-supplied nutrition and is highly immunosuppressive. A better understanding of the role of CAFs in PDAC may lead to the identification of new targets for therapeutic intervention. Here, we uncovered two potential targets, NetG1 in CAFs and its binding partner NGL-1 in tumor cells. NetG1 in CAFs was important for the metabolic support of PDAC cells and for the intrinsic immunosuppressive capacity of CAFs, while NGL-1 in PDAC cells drove tumorigenesis. Our results helped clarify the role that CAFs play in PDAC, by defining CAF phenotypes through NetG1 expression. Finally, we established a link between CAF driven metabolism and their intrinsic immunosuppressive capacity. Thus, NetG1/NGL-1 axis mediates cell reciprocal and cell autonomous functions in PDAC, representing new attractive targets for this aggressive disease.
Footnotes
Significant Update: -Added detailed microarray pathways analyses -Added more human tissue data -Added human RNA expression database analyses -Added Kaplan-Meier Plots for OS based on human RNA expression databases -Performed a Tissue microarray and correlated stromal NetG1 and tumoral NGL-1 with patient overall survival -Generated NetG1 KD CAFs with CRISPRi as another method to validate observed findings in NetG1 KO CAFs -Added the effects of VGlut1 KD and GS inhibition in CAFs on the survival of PDAC cells in various co-culturing conditions (metabolic stress and NK killing) -added Glu/Gln addbacks to NetG1 KO CM and measured PDAC survival in 3D -Added mass spectrometry data of amino acid production, validating CON and NetG1 KO CAF glutamine and glutamate production -Added ELISA data for cytokine production of VGlut1 KD or GS inhibited CAFs -Added RNAseq comparing CON and NetG1 KO CAFs -Updated model in Figure 8 -Added discussion paragraph of clinical data analysis (mRNA databases and TMA)
Significant Update: -Added detailed microarray pathways analyses -Added more human tissue data -Added human RNA expression database analyses -Added Kaplan-Meier Plots for OS based on human RNA expression databases -Performed a Tissue microarray and correlated stromal NetG1 and tumoral NGL-1 with patient overall survival -Generated NetG1 KD CAFs with CRISPRi as another method to validate observed findings in NetG1 KO CAFs -Added the effects of VGlut1 KD and GS inhibition in CAFs on the survival of PDAC cells in various co-culturing conditions (metabolic stress and NK killing) -added Glu/Gln addbacks to NetG1 KO CM and measured PDAC survival in 3D -Added mass spectrometry data of amino acid production, validating CON and NetG1 KO CAF glutamine and glutamate production -Added ELISA data for cytokine production of VGlut1 KD or GS inhibited CAFs -Added RNAseq comparing CON and NetG1 KO CAFs -Updated model in Figure 8 -Added discussion paragraph of clinical data analysis (mRNA databases and TMA)
Significant Update: -Added detailed microarray pathways analyses -Added more human tissue data -Added human RNA expression database analyses -Added Kaplan-Meier Plots for OS based on human RNA expression databases -Performed a Tissue microarray and correlated stromal NetG1 and tumoral NGL-1 with patient overall survival -Generated NetG1 KD CAFs with CRISPRi as another method to validate observed findings in NetG1 KO CAFs -Added the effects of VGlut1 KD and GS inhibition in CAFs on the survival of PDAC cells in various co-culturing conditions (metabolic stress and NK killing) -added Glu/Gln addbacks to NetG1 KO CM and measured PDAC survival in 3D -Added mass spectrometry data of amino acid production, validating CON and NetG1 KO CAF glutamine and glutamate production -Added ELISA data for cytokine production of VGlut1 KD or GS inhibited CAFs -Added RNAseq comparing CON and NetG1 KO CAFs -Updated model in Figure 8 -Added discussion paragraph of clinical data analysis (mRNA databases and TMA)