Table Info

Table 1.

Drugs for targeted metabolism combined with immunotherapy

Drug	Targeted metabolism	Mechanism	Appropriate immunotherapy	Reference
Bicarbonate	Glycolysis	Directly increase pH value	Anti-PD-1/L1/CTLA-4 treatment	[107]
Diclofenac	Glycolysis	Inhibit lactate transporter protein	Anti-PD-1/L1 treatment	[108]
CB839	Glutaminolysis	Inhibit GLS activity	CAR-T cell therapy	[69]
JHU083	Glutaminolysis	Inhibit GLS activity	Anti-PD-1/L1 treatment	[119]
V-9302	Glutaminolysis	Inhibit glutamine transporter protein	Anti-PD-1/L1 treatment	[120]
Glycolytic metabolite phosphoenolpyruvate (PEP)	Glycolysis	Sustaining NFAT signaling and T cell effector functions, and its enhancement in the TME has been shown to boost T cell activity	Anti-PD-1/L1 treatment	[109]
Methionine supplementation	Methionine metabolism	Improved the expression of H3K79me2 and STAT5 in T cells, and this was accompanied by increased T cell immunity	Anti-PD-1/L1 treatment	[117]
Chemotherapeutic prodrug (TH-302)	Hypoxia-inducible factor	This approach reduces myeloid cell-mediated suppression and enhances the infiltration of effector T cells	Anti-PD-1/L1 treatment	[116]
Arachidonic acid	Lipid metabolism	IFN-γ in combination with arachidonic acid induces immunogenic tumor ferroptosis, serving as a mode of action for CD8⁺ T cell mediated tumor killing	Anti-PD-1/L1 treatment	[125]
Avasimibe	Lipid metabolism	Inhibition of ACAT1, a crucial enzyme involved in cholesterol esterification, resulted in enhanced effector functions and increased proliferation of CD8⁺ T cells, while having no significant effect on CD4⁺ T cells	Anti-PD-1/L1 treatment	[124]

GLS: glutaminase; IFN-γ: interferon gamma; ACAT1: acyl-CoA acyltransferase 1; NFAT: nuclear factor of activated T-cells; TME: tumor microenvironment

Declarations

Author contributions

LCG: Data curation, Visualization, Investigation, Writing—original draft, Writing—review & editing. MPK: Supervision, Investigation. SCC: Conceptualization, Methodology, Software. BCO: Methodology, Writing—review & editing, Validation. VPB: Data curation, Validation, Investigation, Writing—review & editing.

Conflicts of interest

Luis Cabezón-Gutiérrez reports he received payment for presentations of Roche, Astra Zeneca, Brystol Myers Squibb, Merck Serono, Ipsen Pharma, Grunenthal, Kyowa Kirin, Pfizer and Eisai and received support for attending meetings from Roche, Merck. Eli Lilly, Bristol-Myers Squibb and Nutricia. Vilma Pacheco-Barcia reports receiving grants as awards from Merck, FSEOM, and Pfizer, as well as payments for presentations from Merck, Eli Lilly, Eisai, and Pierre Fabre. She has also received support for attending meetings from Roche, Eli Lilly, Bristol-Myers Squibb, Merck, Amgen, Merck Sharp & Dohme, and Nutricia. Additionally, she participated in advisory boards for Advanced Accelerator Applications (a Novartis company) and Nutricia. Sara Custodio-Cabello has received honoraria (outside of this submitted study) from Fresenius, Astellas Pharma, Merck and Abbott and received support for attending meetings from Pierre-Fabre and Amgen. Magda Palka-Kotlowska has received payment for presentations of Pfizer, Devon, Pharmamar, and Esteve and received support for attending meetings from Pfizer and Novartis. Beatriz Chacón-Ovejero have no conflicts of interest to declare. All the authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publication

Not applicable.

Availability of data and materials

Not applicable.

Funding

Not applicable.

Copyright

Publisher’s note

Open Exploration maintains a neutral stance on jurisdictional claims in published institutional affiliations and maps. All opinions expressed in this article are the personal views of the author(s) and do not represent the stance of the editorial team or the publisher.

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