Abstract SY13-03: Reprogramming tumor microenvironment metabolism to improve immunotherapy
Authors: Greg M. Delgoffe
Journal: Cancer Research (2019)

Abstract Advances in the immunotherapeutic treatment of cancer have resulted in unprecedented response rates in several of advanced indications. However, the reality is that the majority of patients who receive these immunotherapies will receive little or no benefit. Our inability to stimulate robust antitumor immunity in every patient likely stems from a lack of understanding of the regulation of the immune response at the tumor site. It is now generally appreciated that the tumor microenvironment imposes several barriers on the antitumor immune response. Aside from creating physical barriers and recruiting immunosuppressive cell populations, solid tumors especially create a distinct metabolic landscape that effectively deprives infiltrating immune cells from essential nutrients required for survival and function. Since its inception in 2014, my research program has aimed to identify the metabolic insufficiencies present in various tumor-infiltrating T cell subsets, develop models to understand the energetic contributions to T cell dysfunction in cancer, interrogate how metabolic heterogeneity in the patient population may predict immunotherapeutic response, and design novel combinatorial strategies employing metabolic ‘co-therapy’ to enhance the efficacy of immunotherapy in patients. We have found that tumor-infiltrating T cells suffer from severe metabolic deficiencies, and these metabolic defects impact the ability of these cells to infiltrate, recognize, and differentiate effectively in an immune response to cancer. Further, we have shown that metabolic reprogramming through genetic engineering, costimulatory immunotherapy, and pharmacologic rejuvenation has the potential to greatly improve response rates to cancer immunotherapy. One of our more exciting preclinical studies employed the type II diabetes drug metformin which can dramatically remodel the metabolism of the tumor microenvironment. This essentially creates a landscape that is much more permissive to T cell function, resulting in robust synergy with immunotherapy in mouse models. These exciting preclinical data served as the foundation for several clinical trials (one currently running here in Pittsburgh) combining this well-tolerated drug with immunotherapeutic checkpoint blockade. While the metabolic insufficiencies that T cells endure as a consequence of exhaustion occur consistently, what remains unclear is whether individual patient microenvironments are metabolically distinct from each other. In other words, do some patients harbor harsher environments than others, and, if so, are these patients more likely to progress on immunotherapies? To test this, we first interrogated the metabolic profile of a variety of human melanoma cell lines, which revealed that even in these cell lines that have been passaged for years in vitro, there was vast heterogeneity in both the degree and type of metabolic deregulation. Indeed, some cell lines were solely glycolytic, some were solely oxidative, and some deregulated both. By implanting these cell lines into immunodeficient animals we showed that increased oxidative metabolism was correlated to a tumors ability to generate a potent hypoxic environment. We next set out to systematically study the ‘immunometabolic’ status of patient microenvironments, with an initial focus on melanoma as these patients routinely receive checkpoint blockade immunotherapy in the first line. Working with our Melanoma Program we developed a workflow allowing for simultaneous immunologic profiling of TIL by flow whilst tumor cells from the same biopsy were assayed metabolically. Indeed, we found that the melanoma patient population carries the same metabolic heterogeneity: some patients had very energetic tumors while others had solely oxidative or glycolytic tumors. Profiling the T cells from these tumor biopsies showed that increased oxidative, but not glycolytic, metabolism was associated with decreased T cell function when stimulated ex vivo. Using a novel mouse model of melanoma, we next sought to reverse translate these findings, generating cell lines that lacked one gene in either the glycolytic or oxidative pathways. Implantation of these lines into immunocompetent B6 mice revealed similar findings to what was observed in the human population: deficiencies of tumor glycolytic metabolism had little to no effect on the immunologic profile of TIL, but tumor cells that lacked oxidative metabolism harbored less exhausted, more cytokine competent TIL. Furthermore, these tumors lacking oxidative metabolism were solely responsive to anti-PD1 therapy among those tested. Our data thus suggested it was the ability of tumors to sequester oxygen that created a barrier to checkpoint blockade immunotherapy. We thus sought to confirm this in patients, examining the metabolic profile of melanoma patients prior to initiation of anti-PD1 monotherapy. Indeed, patients with high tumor oxidative metabolism were more likely to progress on anti-PD1 therapy. Patients who had low tumor oxidative metabolism not only had increased overall survival on anti-PD1 therapy, but those responding patients had a longer duration of response. Finally, we confirmed that the product of tumor oxidative metabolism, hypoxia (measured by an immunohistochemistry stain in pre-treatment patient sections), could predict progression on anti-PD1 therapy. Our data highlight the importance of oxygen for the reinvigoration of antitumor T cell immunity by anti-PD1 therapy. Hypoxia represents a barrier of T cell infiltration and reinvigoration and thus can predict immunotherapeutic response. Further, we have linked tumor cell oxidative metabolism to the generation of a hypoxic environment, which suggests that tumor cell oxidation represents an attractive target to improve the immunotherapeutic treatment of cancer. Citation Format: Greg M. Delgoffe. Reprogramming tumor microenvironment metabolism to improve immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr SY13-03.