The description below is taken from the R01 version of the FOA.
The overall goal of this FOA is to encourage research grant applications to (a) generate a mechanistic understanding of the metabolic processes that support robust anti-tumor immune responses in vivo, (b) determine how the metabolic landscape of the tumor microenvironment affects immune effector functions, and (c) then use this information to manipulate (reprogram) the metabolic pathways used by the tumor, the immune response, or both to improve cancer immunotherapy.
This FOA utilizes the Research Project Grant (R01) mechanism., which supports research applications that propose to investigate novel scientific ideas, model systems, tools, agents, targets, and technologies that have the potential to substantially move the field forward. This FOA runs in parallel with an FOA of similar scientific scope, PAR-16-229, which utilizes the Exploratory/Developmental Grant (R21) mechanism
One the critical pathways that enables growth and survival of cancer cells is the ability to reprogram metabolism from primarily oxidative phosphorylation (OxPhos) observed in normal resting cells to aerobic glycolysis (Warburg metabolism). This reprogramming is associated with an increase in glucose receptor expression, glucose uptake, diversion of glycolytic intermediates to various biosynthetic pathways required for tumor cell growth, and the export of lactate and other metabolites that alters the metabolic landscape of the tumor microenvironment. Similarly, reprogramming of lipid metabolism in tumor cells can contribute to cell survival and clonal expansion. Metabolic changes in the tumor can also deprive tumor-infiltrating immune cells of essential nutrients and metabolites required for effective responses to the tumor, contributing to immunosuppression in the tumor microenvironment. Recent advances in immunology have demonstrated that lymphocytes undergo a similar reprogramming to Warburg metabolism to meet the demands of clonal expansion following antigen stimulation. Whereas naïve T cells generate ATP through OxPhos to maintain basic cellular functions (ion transport, membrane maintenance, and protein turnover), following exposure to antigen they switch to Warburg metabolism. Altered regulation of lipid metabolism in lymphocytes upon activation can also have critical and pleiotropic effects on cell fate and function. Such inter-connected metabolic shifts are thought to play critical roles in lymphocyte activation, clonal expansion, lineage differentiation and acquisition of effector functions, and generation of long-lived memory T cells capable of self-renewal. The presence of memory cytotoxic T cells in tumors is associated with an optimum anti-tumor immune response, suggesting that manipulating metabolic pathways to generate more memory CTL could dramatically enhance anti-tumor immune responses.
However, in order to capitalize on these advances to improve cancer immunotherapy we need to understand more fully how metabolic pathway choice affects lymphocyte differentiation into specific effector subsets and how the immune system is affected by the altered metabolic landscape of the tumor microenvironment in which the nutrient/metabolite pools and environmental conditions (such as hypoxia and acidosis) have been dramatically altered by the metabolic state of the tumor. At present we don’t fully understand the similarities, differences, and functional consequences of the metabolic pathways utilized by activated immune cells and cancer cells that would guide the development of novel metabolic interventions to improve immunotherapy.
Critical needs for future studies include developing (a) approaches to reprogram the metabolic qualities of anti-tumor immune cells (either ex vivo or in vivo) to improve immunotherapy (homing, persistence and/or effector function), and/or (b) approaches that target cancer cell metabolic pathways to impair cancer cell survival without compromising endogenous anti-tumor immunity.
Applicable research directions could include, but not be limited to, the following:
Major Challenges and Opportunities:
- Assess the crosstalk between the different metabolic platforms that may be operating in any given cell and integrate those assessments to generate a more complete metabolic profile at the single cell level.
- Generate a better understanding of metabolites as signaling molecules in transcription that effect cellular differentiation.
- Determine the relationship between metabolism and self-renewal capacity.
- Clarify how specific metabolites affect various immune states such as activation, anergy,
- development of long-lived memory cells versus short-lived effector cells, and homing to their proper niche.
- Elucidate how the metabolic environment (or nutrient repertoire) in normal tissues, immune tissues, and in the setting of pathology (in tumors) affects immune cell development and/or effector function.
- Delineate the consequences of metabolic interventions on immune cell growth and effector functions.
Tools and Technologies:
- New instrumentation and novel approaches are needed to parse the metabolic heterogeneity of tissues in situ.
- Improved methods and approaches need to be developed to assess how the metabolic
- characteristics of the tumor microenvironment affect the anti-tumor immune response.
- Computational models to better understand which metabolic pathways are hard-wired and when perturbed lead to cell death and which are flexible and can be experimentally manipulated need to generated.
- Development of small molecule inhibitors of glycolysis, FAO, and other metabolic pathways for therapeutic intervention is needed.
- The ability to perform comprehensive analysis of the metabolic heterogeneity (metabolic flux/metabolomics) of different immune subsets and a full description of the functional consequences of differential utilization of metabolic pathways in supporting immune cell differentiation is needed.
Deadlines: standard dates and standard AIDS dates apply
URLs:
R01 version – http://grants.nih.gov/grants/guide/pa-files/PAR-16-228.html
R21 version – http://grants.nih.gov/grants/guide/pa-files/PAR-16-229.html
Filed Under: Funding Opportunities