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Metabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression. ​

Literature Information ​

PMID26321679
JournalCell
Impact Factor42.5
JCR QuartileQ1
Publication Year2015
Times Cited1691
Keywordstumor microenvironment, metabolic competition, T cells, glycolysis, cancer progression
Literature TypeJournal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S.
ISSN0092-8674
Pages1229-41
Issue162(6)
AuthorsChih-Hao Chang, Jing Qiu, David O'Sullivan, Michael D Buck, Takuro Noguchi, Jonathan D Curtis, Qiongyu Chen, Mariel Gindin, Matthew M Gubin, Gerritje J W van der Windt, Elena Tonc, Robert D Schreiber, Edward J Pearce, Erika L Pearce

TL;DR ​

This study reveals that tumors metabolically restrict T cells by consuming glucose, which reduces their mTOR activity and IFN-γ production, thereby facilitating tumor growth. Importantly, checkpoint blockade therapies can restore glucose availability in the tumor microenvironment, enhancing T cell glycolysis and function, highlighting a crucial link between tumor metabolism and T cell hyporesponsiveness in cancer.

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tumor microenvironment · metabolic competition · T cells · glycolysis · cancer progression

Abstract ​

Failure of T cells to protect against cancer is thought to result from lack of antigen recognition, chronic activation, and/or suppression by other cells. Using a mouse sarcoma model, we show that glucose consumption by tumors metabolically restricts T cells, leading to their dampened mTOR activity, glycolytic capacity, and IFN-γ production, thereby allowing tumor progression. We show that enhancing glycolysis in an antigenic "regressor" tumor is sufficient to override the protective ability of T cells to control tumor growth. We also show that checkpoint blockade antibodies against CTLA-4, PD-1, and PD-L1, which are used clinically, restore glucose in tumor microenvironment, permitting T cell glycolysis and IFN-γ production. Furthermore, we found that blocking PD-L1 directly on tumors dampens glycolysis by inhibiting mTOR activity and decreasing expression of glycolysis enzymes, reflecting a role for PD-L1 in tumor glucose utilization. Our results establish that tumor-imposed metabolic restrictions can mediate T cell hyporesponsiveness during cancer.

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Primary Questions Addressed ​

  1. How do different metabolic pathways in tumors influence T cell functionality and overall immune response?
  2. What specific mechanisms can be targeted to enhance T cell glycolysis in the tumor microenvironment?
  3. How does the interaction between tumor cells and immune cells vary across different types of cancers in terms of metabolic competition?
  4. What are the potential therapeutic implications of restoring glucose levels in the tumor microenvironment for cancer treatment?
  5. How do checkpoint inhibitors like CTLA-4 and PD-1 antibodies alter the metabolic landscape of tumors to enhance T cell activity?

Key Findings ​

Research Background and Objectives ​

The immune system's T cells often fail to effectively combat cancer, which may be attributed to insufficient antigen recognition, chronic activation, or suppression by other immune cells. This study aims to explore the metabolic interactions between tumors and T cells, particularly focusing on how tumor glucose consumption affects T cell functionality and tumor progression.

Main Methods/Materials/Experimental Design ​

The research utilized a mouse sarcoma model to investigate the metabolic restrictions imposed by tumors on T cells. Key experimental approaches included:

  • Tumor Model: A mouse sarcoma model was used to simulate cancer conditions.
  • Metabolic Assessment: The glucose consumption of tumors was measured to assess its impact on T cell metabolism.
  • T Cell Functionality: Evaluated T cell mTOR activity, glycolytic capacity, and IFN-γ production in response to tumor glucose levels.
  • Checkpoint Blockade Therapy: Investigated the effects of antibodies against CTLA-4, PD-1, and PD-L1 on restoring T cell function and glucose availability in the tumor microenvironment.
  • Glycolysis Enhancement: Conducted experiments to enhance glycolysis in an antigenic "regressor" tumor to determine its effect on T cell-mediated tumor control.

The following flowchart summarizes the technical route of the study:

Mermaid diagram

Key Results and Findings ​

  • Tumor glucose consumption was found to metabolically restrict T cells, resulting in reduced mTOR activity, glycolytic capacity, and IFN-γ production.
  • Enhancing glycolysis in antigenic tumors could negate the protective effects of T cells against tumor growth.
  • Checkpoint blockade antibodies (CTLA-4, PD-1, PD-L1) were shown to restore glucose levels in the tumor microenvironment, thereby enabling T cell glycolysis and enhancing IFN-γ production.
  • Direct blocking of PD-L1 on tumors was found to inhibit glycolysis by reducing mTOR activity and the expression of glycolytic enzymes.

Main Conclusions/Significance/Innovation ​

The study establishes that metabolic restrictions imposed by tumors play a crucial role in T cell hyporesponsiveness during cancer progression. It highlights the importance of tumor glucose utilization in modulating T cell activity and suggests that enhancing T cell glycolysis through checkpoint blockade therapies could be a promising strategy to improve anti-tumor immunity. This research contributes to the understanding of the metabolic interplay between tumors and the immune system, potentially guiding future therapeutic approaches.

Research Limitations and Future Directions ​

  • Limitations: The study primarily used a mouse model, which may not fully replicate human cancer biology. Additionally, the specific mechanisms by which enhanced glycolysis influences T cell function warrant further investigation.
  • Future Directions: Future research could explore the detailed molecular pathways involved in tumor-induced metabolic restrictions, the role of other nutrients besides glucose, and the efficacy of combining metabolic interventions with existing immunotherapies in clinical settings. Further studies should also evaluate the implications of these findings in various types of cancers beyond sarcomas.

References ​

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  5. Programmed death ligand 1 expression and tumor-infiltrating lymphocytes in glioblastoma. - Anna Sophie Berghoff;Barbara Kiesel;Georg Widhalm;Orsolya Rajky;Gerda Ricken;Adelheid Wöhrer;Karin Dieckmann;Martin Filipits;Anita Brandstetter;Michael Weller;Sebastian Kurscheid;Monika E Hegi;Christoph C Zielinski;Christine Marosi;Johannes A Hainfellner;Matthias Preusser;Wolfgang Wick - Neuro-oncology (2015)
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Literatures Citing This Work ​

  1. Nutrient Competition: A New Axis of Tumor Immunosuppression. - Madhusudhanan Sukumar;Rahul Roychoudhuri;Nicholas P Restifo - Cell (2015)
  2. Tumour immunology: An exhausting metabolic competition. - Sarah Seton-Rogers - Nature reviews. Cancer (2015)
  3. Beyond Genomics: Multidimensional Analysis of Cancer Therapy Resistance. - Mary Philip;Andrea Schietinger - Trends in immunology (2015)
  4. Immunometabolism: Cellular Metabolism Turns Immune Regulator. - Róisín M Loftus;David K Finlay - The Journal of biological chemistry (2016)
  5. Costimulation Endows Immunotherapeutic CD8 T Cells with IL-36 Responsiveness during Aerobic Glycolysis. - Naomi Tsurutani;Payal Mittal;Marie-Clare St Rose;Soo Mun Ngoi;Julia Svedova;Antoine Menoret;Forrest B Treadway;Reinhard Laubenbacher;Jenny E Suárez-Ramírez;Linda S Cauley;Adam J Adler;Anthony T Vella - Journal of immunology (Baltimore, Md. : 1950) (2016)
  6. Cholesterol metabolites and tumor microenvironment: the road towards clinical translation. - Laura Raccosta;Raffaella Fontana;Gianfranca Corna;Daniela Maggioni;Marta Moresco;Vincenzo Russo - Cancer immunology, immunotherapy : CII (2016)
  7. Glycolysis and EZH2 boost T cell weaponry against tumors. - Glenn R Bantug;Christoph Hess - Nature immunology (2016)
  8. Immunometabolism governs dendritic cell and macrophage function. - Luke A J O'Neill;Edward J Pearce - The Journal of experimental medicine (2016)
  9. The Warburg Effect: How Does it Benefit Cancer Cells? - Maria V Liberti;Jason W Locasale - Trends in biochemical sciences (2016)
  10. Genetics and biology of pancreatic ductal adenocarcinoma. - Haoqiang Ying;Prasenjit Dey;Wantong Yao;Alec C Kimmelman;Giulio F Draetta;Anirban Maitra;Ronald A DePinho - Genes & development (2016)

... (1681 more literatures)

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