Metabolic Reprogramming in the Tumor Microenvironment With Immunocytes and Immune Checkpoints

Yaolin Xu1, Lijie He1, Qiang Fu2

  • 1Department of Oncology, The People's Hospital of China Medical University/The People's Hospital of LiaoNing Province, Shenyang, China.

Frontiers in Oncology
|December 3, 2021
PubMed

Immune checkpoint inhibitors (ICIs), Ipilimumab, Nivolumab, Pembrolizumab and Atezolizumab, have been applied in anti-tumor therapy and demonstrated exciting performance compared to conventional treatments. However, the unsatisfactory response rates, high recurrence and adaptive resistance limit their benefits. Metabolic reprogramming appears to be one of the crucial barriers to immunotherapy. The deprivation of required nutrients and altered metabolites not only promote tumor progression but also confer dysfunction on immune cells in the tumor microenvironment (TME). Glycolysis plays a central role in metabolic reprogramming and immunoregulation in the TME, and many therapies targeting glycolysis have been developed, and their combinations with ICIs are in preclinical and clinical trials. Additional attention has been paid to the role of amino acids, lipids, nucleotides and mitochondrial biogenesis in metabolic reprogramming and clinical anti-tumor therapy. This review attempts to describe reprogramming metabolisms within tumor cells and immune cells, from the aspects of glycolysis, amino acid metabolism, lipid metabolism, nucleotide metabolism and mitochondrial biogenesis and their impact on immunity in the TME, as well as the significance of targeting metabolism in anti-tumor therapy, especially in combination with ICIs. In particular, we highlight the expression mechanism of programmed cell death (ligand) 1 [PD-(L)1] in tumor cells and immune cells under reprogramming metabolism, and discuss in detail the potential of targeting key metabolic pathways to break resistance and improve the efficacy of ICIs based on results from current preclinical and clinical trials. Besides, we draw out biomarkers of potential predictive value in ICIs treatment from a metabolic perspective.

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