Immune cell metabolism in cancer: From mechanistic circuits to immunotherapy optimization

The metabolic state of an immune cell is not incidental to its function: it is a primary determinant of whether an anti-tumor response succeeds or collapses. Mechanistic research over the past decade has established that T cell activation, effector differentiation, memory formation, and exhaustion are each supported by distinct bioenergetic and biosynthetic programs. Glycolysis drives acute effector function, while oxidative phosphorylation and fatty acid oxidation sustain long-lived memory populations and, paradoxically, also fuel immunosuppressive regulatory subsets. In myeloid cells, metabolic switches centered on succinate accumulation, itaconate production, cGAS-STING pathway activation, and arginine metabolism govern whether macrophages and dendritic cells promote or restrain anti-tumor immunity. These immune cell-intrinsic metabolic programs, distinct from the metabolic competition imposed on immune cells by the tumor microenvironment, are increasingly recognized as critical and modifiable determinants of how patients respond to checkpoint inhibitors, adoptive cell therapies, and cancer vaccines.The maturation of metabolomics, stable-isotope fluxomics, single-cell transcriptomics, and proteomics now provides the tools to analyze these cellular programs with mechanistic precision and clinical relevance. Integrating these diverse data layers through computational network modeling offers a tractable path from basic immune cell biology to patient stratification and therapeutic design.This Research Topic aims to consolidate mechanistic, translational, and computational research on immune cell-intrinsic metabolic programs as determinants of anti-tumor immunity and immunotherapy response. We seek to connect discoveries in cellular immunometabolism to clinically measurable outcomes, and to identify metabolic intervention strategies that can enhance the efficacy of existing immunotherapy modalities, including checkpoint inhibitors, CAR-T and CAR-NK therapies, tumor-infiltrating lymphocyte therapies, and cancer vaccines.We welcome original research, reviews, mini-reviews, methods, and perspective articles. Submissions may use experimental, clinical, or computational approaches. Areas of interest include, but are not limited to:• Metabolic reprogramming in T cells, NK cells, macrophages, and dendritic cells during anti-tumor immune responses, covering glycolysis, oxidative phosphorylation, fatty acid oxidation, amino acid catabolism, and one-carbon metabolism.• Metabolic checkpoints that govern T cell exhaustion, functional reinvigoration, and durable memory formation in the context of checkpoint blockade.• Innate immune metabolic reprogramming, including cGAS-STING pathway activation, macrophage polarization via succinate and itaconate metabolism, and the role of myeloid cell bioenergetics in tumor immune surveillance.• Metabolomics and fluxomics approaches to characterize metabolic flux dynamics and heterogeneity in tumor-infiltrating immune cell populations.• Multi-omics integration (metabolomics, proteomics, transcriptomics) for identifying immune cell metabolic signatures predictive of response or resistance to cancer immunotherapy.• Metabolic conditioning of adoptive cell therapies, including strategies to maintain CAR-T and CAR-NK cell persistence, effector function, and resistance to TME-imposed metabolic stress.• Pharmacological interventions that target immune cell metabolic pathways to enhance immunotherapy efficacy.• Computational and machine learning approaches for modeling immunometabolic networks and enabling patient stratification by immune metabolic phenotype. Topic editors: Dilinaer Wusiman, Erika Adriana Eksioglu, Stefano Cavalieri Source: https://www.frontiersin.org/research-topics/83510/immune-cell-metabolism-in-cancer-from-mechanistic-circuits-to-immunotherapy-optimization