Title |
Targeting Tumor Metabolism: A New Challenge to Improve Immunotherapy
|
---|---|
Published in |
Frontiers in immunology, February 2018
|
DOI | 10.3389/fimmu.2018.00353 |
Pubmed ID | |
Authors |
Soumaya Kouidhi, Farhat Ben Ayed, Amel Benammar Elgaaied |
Abstract |
Currently, a marked number of clinical trials on cancer treatment have revealed the success of immunomodulatory therapies based on immune checkpoint inhibitors that activate tumor-specific T cells. However, the therapeutic efficacy of cancer immunotherapies is only restricted to a small fraction of patients. A deeper understanding of key mechanisms generating an immunosuppressive tumor microenvironment (TME) remains a major challenge for more effective antitumor immunity. There is a growing evidence that the TME supports inappropriate metabolic reprogramming that dampens T cell function, and therefore impacts the antitumor immune response and tumor progression. Notably, the immunosuppressive TME is characterized by a lack of crucial carbon sources critical for T cell function and increased inhibitory signals. Here, we summarize the basics of intrinsic and extrinsic metabolic remodeling and metabolic checkpoints underlying the competition between cancer and infiltrating immune cells for nutrients and metabolites. Intriguingly, the upregulation of tumor programmed death-L1 and cytotoxic T lymphocyte-associated antigen 4 alters the metabolic programme of T cells and drives their exhaustion. In this context, targeting both tumor and T cell metabolism can beneficially enhance or temper immunity in an inhospitable microenvironment and markedly improve the success of immunotherapies. |
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Canada | 5 | 11% |
Switzerland | 3 | 7% |
Germany | 2 | 4% |
Venezuela, Bolivarian Republic of | 2 | 4% |
South Africa | 1 | 2% |
Mexico | 1 | 2% |
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Ireland | 1 | 2% |
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Scientists | 15 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
Geographical breakdown
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Unknown | 151 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 28 | 19% |
Student > Master | 20 | 13% |
Student > Bachelor | 13 | 9% |
Student > Doctoral Student | 5 | 3% |
Other | 17 | 11% |
Unknown | 37 | 25% |
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Immunology and Microbiology | 21 | 14% |
Medicine and Dentistry | 21 | 14% |
Agricultural and Biological Sciences | 18 | 12% |
Pharmacology, Toxicology and Pharmaceutical Science | 6 | 4% |
Other | 12 | 8% |
Unknown | 40 | 26% |