This review establishes that PTMs are the central processing units of oncogenic metabolic reprogramming

The gap

Evidence profile

Sourced from the future work of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 3 journals. Those papers have been cited 13 times in total.

Supporting evidence — 4 representative gaps

• Post-translational modifications in metabolic reprogramming: implications for metabolic therapy and immunotherapy in cancer (2026) · Signal Transduction and Targeted Therapy · doi

  This review establishes that PTMs are the central processing units of oncogenic metabolic reprogramming. They function as a universal molecular language, translating upstream oncogenic signals and microenvironmental cues into precise metabolic commands across all core pathways—glucose, lipid, amino acid, and nucleotide metabolism. Beyond flux control, PTMs directly couple metabolic activity to cell fate determination, locking in aggressive phenotypes through metabolite-derived epigenetic remodeling. Furthermore, they extend their reach into the TME, 1. De Martino, M., Rathmell, J. C., Galluzzi, L. & Vanpouille-Box, C. Cancer cell metabolism and antitumour immunity. Nat. Rev. Immunol. 24, 654–669 (2024). 2. Tzouanas, C. N. et al. Hepatic adaptation to chronic metabolic stress primes tumorigenesis. Cell 189, 435–460.e28 (2026). 3. Lee, J. M., Hammarén, H. M., Savitski, M. M. & Baek, S. H. Control of protein stability by post-translational modifications. Nat. Commun. 14, 201 (2023). 4. Chen, Y. et al. O-GlcNAcylation determines the translational regulation and phase separation of YTHDF proteins. Nat. Cell Biol. 25, 1676–1690 (2023). 5. Yang, Z. et al. Lactylome analysis suggests lactylation-dependent mechanisms of metabolic adaptation in hepatocellular carcinoma. Nat. Metab. 5, 61–79 (2023).

  generalfuture work
  Keywords: metabolic cell ptms oncogenic metabolism control adaptation translational review establishes central processing units reprogramming function
• Immune checkpoints and immunoregulation in metabolic diseases and cancers: pathological mechanisms and therapeutic potential (2026) · Signal Transduction and Targeted Therapy · doi

  The crosstalk between the immune and metabolic systems is pivotal in maintaining organismal homeostasis. Evidently, immune check- point molecules play fundamental in broad biological functions, including endocrine and metabolic processes. Although numerous literature reports have elaborated on the impact of the interaction between metabolism and immunity on health and disease state, especially in cancer development, there is a lack of systematic summation of immunity and typical metabolic diseases, particularly focusing on immune checkpoints. In this review, we delineate the current understanding of the interactions between key immune checkpoints and three prevalent metabolic diseases, including obesity, diabetes, and thyroid disorders. Mechanistically, these checkpoints modulate disease progression through transcrip- tional regulation, signaling pathway engagement, and immune microenvironment immune checkpoint inhibitors has been associated with metabolic-related immune adverse events, such as endocrine toxicity and hypothyr- oidism, highlighting their metabolic regulatory roles (Fig. 6). remodeling. Clinically, the use of These findings position immune checkpoints as critical nodes in immune-metabolic homeostasis, offering transformative insights for therapeutic development. Future research should prioritize the design of metabolic disease-specific clinical trials with enhanced safety monitoring protocols to evaluate checkpoint modulation, coupled with the development of multiomics biomarker panels for precise patient stratification and treatment response prediction. The implementation of precision medicine frameworks that integrate immunological and metabolic profiling data will be crucial, as will the development of rational combination therapies simultaneously targeting checkpoint and metabolic pathways. The integration of artificial intelligence with multiomics data promises to uncover novel therapeutic targets, while breakthroughs in this interdisciplinary field may establish new treatment paradigms for metabolic diseases with cancer or autoimmune comorbidities. ACKNOWLEDGEMENTS This study was supported by the National Natural Science Foundation of China (82372598), the Science and Technology Innovation Program of Hunan Province (2022RC3072), the Natural Science Foundation of Hunan Province (2024JJ3048 and 2025JJ30046), and the Natural Science Foundation of Hunan Province for Youth Foundation (2025JJ60587). We also thank Biorender.com for creating all the figures that have obtained publication licensing rights in the manuscript. AUTHOR CONTRIBUTIONS Yongguang Tao designed the review. Yongguang Tao, Desheng Xiao, and Shuang Liu revised the manuscript. Minmin Xiang drafted and revised the manuscript, the tables, and the figures. All authors have read and approved the review.

  generalfuture work
  Keywords: metabolic immune development checkpoints science foundation disease diseases review checkpoint natural hunan province manuscript homeostasis
• Metabolic Adaptations in Cancer Progression: Optimization Strategies and Therapeutic Targets (2025) · Cancers · cited 13× · doi

  The development of cancer requires the modulation of key cellular metabolic pro- cesses, enabling malignant cells to adapt to environmental conditions for their growth and survival. Metabolic reprogramming in tumor cells alters the utilization of glucose, fatty acids, and amino acids, affecting their requirement for specific nutrients. The TCA cycle highlights the metabolic role of certain a.a.s., such as Gln, in cancer progression. Glutamine contributes to ATP production and anabolic processes by entering the TCA cycle as α-ketoglutarate, thereby supporting the energy generation, redox balance, and biosynthesis required for tumor growth. This metabolic dependency becomes especially critical when cancer cells metastasize, requiring adaptation to differing resource availability between the primary tumor site and the new microenvironment. Cancer’s adaptability is driven by the high metabolic plasticity of malignant cells, which rapidly modulate their metabolism and simultaneously reshape their environment to suit their needs. For in- stance, Gln deprivation increases cancer cells’ reliance on alternative nutrients such as Asp, asparagine, BCAAs, or glucose. Conversely, prolonged inhibition of glycolysis may cause cancer cells to activate AMPK (AMP-activated protein kinase) signaling pathways, leading to upregulation of glutamine metabolism and/or increased fatty acid utilization (including β-oxidation, uptake, and storage), thereby promoting survival under glucose deprivation. In addition to that, in response to low oxygen levels, cancer cells induce the expression of glycolytic enzymes and GLUT1, which triggers autophagy and simultane- ously helps them avoid apoptosis. These metabolic adaptations may explain some of the inconsistencies frequently observed in experimental findings. Metabolic phenotypes tend to vary according to the tissue of origin, tumor microenvironment, stage (primary versus metastatic tumors), and mutational differences. The metabolic flexibility of tumors, driven by real-time adjustments in metabolite levels, enzymatic fluxes, and the directionality of existing metabolic pathways, poses a significant obstacle to the development of effective cancer therapy. Understanding the role of various nutrients in tumor growth is a promising area of research that holds great potential for enhancing cancer treatment by strategically manipulating nutrient availability. The fight against cancer, therefore, requires the develop- ment of new therapeutic strategies that take into account and exploit the potential of the metabolic reprogramming of cancer cells. Achieving this goal demands a comprehensive understanding of the metabolic profiles across different cancer types. Specific alterations, for example in a.a. metabolism, differ between tumor types and are shaped by numerous factors, including intrinsic cellular characteristics and components of the tumor microenvironment. This metabolic diversity underscores a major challenge in oncology: the het

  generalfuture work
  Keywords: cancer metabolic cells tumor growth glucose nutrients microenvironment metabolism development requires cellular malignant survival reprogramming
• Immunometabolic programming of macrophages and tumor-associated macrophages: metabolic pathways shaping polarization, immune regulation, and disease outcomes (2026) · Frontiers in Immunology · doi

  Macrophage immunometabolism has moved from a descriptive concept to a mechanistic framework that explains how immune phenotypes are established, stabilized, and reshaped by tissue context. In this context, tumor-associated macrophages provide a particularly informative model because their metabolic states are continuously shaped by tumor-derived metabolites, hypoxia, and nutrient competition within the tumor microenvironment. The evidence synthesized in this review supports a central conclusion: macrophage polarization and function are constrained by metabolic circuitry, particularly glucose flux and mitochondrial respiration, lipid uptake and signaling, cholesterol balance, and amino acid– derived immunoregulatory metabolites. Within tumors, TAMs exemplify this principle because the tumor microenvironment imposes hypoxia and nutrient limitation while providing abundant metabolites such as lactate, lipid mediators, and tryptophan- or arginine-derived products that bias macrophages toward immunosuppressive programs. These metabolic shifts amplify checkpoint signaling, impair cytotoxic lymphocyte activity through nutrient deprivation, and promote angiogenesis, invasion, and matrix remodeling, collectively shaping clinical outcomes. An important emerging theme is that immunometabolism also governs macrophage survival and immunological outputs through regulated cell death pathways. Ferroptosis provides a particularly compelling bridge between metabolism and immunity: iron handling, lipid composition, antioxidant capacity, and mitochondrial redox status converge to determine ferroptotic sensitivity, while ferroptotic signals can remodel local inflammation and immune priming. Positioning ferroptosis within the broader immunometabolic landscape opens new opportunities to reprogram macrophages in cancer and beyond. Future work should prioritize four directions. First, macrophage metabolic states must be interpreted as context-dependent continua rather than fixed M1/M2 categories; integrating single-cell, spatial, and metabolic profiling will be essential to map functional states to nutrient landscapes in tissues. Second, mechanistic studies should resolve causal “metabolic checkpoints” that lock macrophages into suppressive versus protective trajectories, including lactate sensing, lipid droplet biology, cholesterol efflux pathways, and amino acid– linked epigenetic remodeling. Third, therapeutic development should shift from listing individual inhibitors toward strategy- driven combinations that co-target tumor metabolism and TAM programs, with rational pairing to checkpoint blockade, anti- angiogenic agents, and emerging macrophage-engineering approaches such as CAR-macrophages. Fourth, interspecies differences in nitric oxide biology, arginine metabolism, and mi t o c h o n d r i a l p r o g r a m s be t w e e n m o u s e an d h u m a n macrophages must be addressed with human tissue datasets and more predictive experimental systems to improve translation. Overall, bridging metabolic and immune pathways in macrophages provides a unifying explanation for macrophage plasticity and offers actionable therapeutic entry points. As immunometabolic targets mature, macrophage-focused metabolic interventions are likely to become key components of combination immunotherapy and precision approaches for macrophage- driven pathologies.

  generalfuture work
  Keywords: macrophage metabolic macrophages tumor nutrient lipid immune context particularly states derived metabolites within pathways metabolism

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