Role of Fibroblast Glutamate Metabolism in Immunosuppression in Pancreatic Cancer

About This Grant

ABSTRACT Pancreatic ductal adenocarcinoma (PDAC) has a dismal 5-year survival rate of <10%, driven in large part by a unique tumor microenvironment (TME) characterized by an intense fibrotic and inflammatory reaction, orchestrated by cancer associated fibroblasts (CAFs) and immunosuppressive immune cells. CAFs, among the most prominent cell types in PDAC, influence tumorigenesis by secreting extracellular matrix (ECM), metabolites, and cytokines. While CAFs ultimately promote cancer progression, complete removal of CAFs and their ECM from tumors has proven detrimental to patients. Therefore, understanding how to inhibit functions that promote tumorigenesis, without eliminating CAFs, is critical to develop effective targeted stromal therapies that complement standard of care regimens. Functionally, CAFs support tumor growth by inhibiting anti-tumor natural killer (NK) and CD8+ T cells and by supplying metabolites that fuel cancer cell proliferation. We recently linked glutamate/glutamine-cycling enzymes to immunosuppressive cytokine production in CAFs: ablating these enzymes restored anti-tumor immune killing of PDAC cells, while glutamate supplementation enhanced CAF immunosuppression. This led us to postulate that a CAF-derived glutamate metabolite drives immune suppression in the TME. We now show that gamma aminobutyric acid (GABA), a glutamate-derived metabolite, is present in PDAC patient tumor interstitial fluid (TIF), and that CAFs synthesize GABA de novo and express both the biosynthetic enzymes and receptors needed to produce and respond to it. Furthermore, it is known that T and NK cells possess GABA receptors, and blockade of GABA signaling in mouse models of PDAC significantly reduced tumor burden. Thus, we hypothesize that CAFs are a major source of GABA in the TME, that GABA is a driver of immunosuppression through paracrine effects on immune cells, and that GABA imparts an immunosuppressive program in CAFs, in an autocrine manner. In an innovative approach, we will address these hypotheses using a physiologically relevant 3D culturing system, state of the art murine models of PDAC, spatial transcriptomics, metabolomics, and multiplex ELISAs to uncover how gain or loss of function of GABA signaling in normal fibroblasts and CAFs alters immunosuppression and tumor growth. Murine models are essential for this study because GABAergic paracrine signaling between CAFs, cancer cells, and immune cells cannot be fully recapitulated in vitro, and syngeneic and genetically engineered PDAC models are required to assess how manipulating GABA signaling alters tumor burden and anti-tumor immunity in an intact TME. Additionally, we have a novel IRB approved protocol to study this phenomenon in patients, using patient matched plasma, TIF, and the same tissue after fluid isolation. Our long-term goal is to develop prognostic/diagnostic profiles from metabolites, cytokines, immune cell infiltrates, and target spatial transcriptomes using a novel computational pipeline that can be done as a simple blood test to find cancer early.