Yixin Li
Yunmei Zhang3,4
Yan Nie- 1Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- 2Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- 3Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- 4Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- 5Guangdong Provincial Key Laboratory of Cancer Pathogenesis and Precision Diagnosis and Treatment, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Shanwei, China
Metabolic reprogramming is not only one of the malignant characteristics of tumor cells, but also commonly seen in a variety of immune cells in tumor microenvironment(TME), which massively promotes tumor-body immune interaction. Immunometabolic editing is a dynamic, co-evolutionary process wherein adaptive metabolic reprogramming in the TME, driven by tumor-immune crosstalk during immunoediting, critically shapes anti-tumor immune response and governs immune evasion. Studies of metabolic pathways linked to anti-tumor immune process and discoveries of important therapeutic targets are conducive to the development of targeted immunometabolic intervention to enhance the body’s anti-tumor immune response and improve the efficacy of tumor immunotherapies. This review summarizes metabolic characteristics of the TME, highlights immunometabolic editing during cancer evolution, and discusses mechanisms by which tumor immunotherapies modulate tumor immunometabolism to identify potential therapeutic targets.
1 Introduction
Metabolic reprogramming is a hallmark of cancer, where tumor-induced alterations in metabolic pathways regulate diverse immune cell functions to achieve immunosuppression. Specifically, tumor cells rewire metabolic circuits (e.g., glycolysis, glutaminolysis) to compete for nutrients in the tumor microenvironment (TME), thereby impairing effector T cell function while promoting immunosuppressive populations like myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) (1, 2). The metabolic interaction between tumor cells and immune cells and how these cells adapt to the TME by forming corresponding metabolic phenotypes are the key factors that determine tumor immune response, immune escape or immunotherapy. From an evolutionary and integrative perspective, we here propose the concept of Immunometabolic Editing—a dynamic and reciprocal process in the TME wherein metabolic competition and crosstalk throughout the immunoediting cascade drive the selection of tumor variants with specific metabolic profiles, while simultaneously shaping the functional fate of immune infiltrates. This co-evolution ultimately determines immunological control versus tumor escape.
Therefore, targeting key nodes in tumor immunometabolism and synergizing with existing immunotherapies has emerged as a promising frontier to overcome resistance and enhance therapeutic efficacy. By addressing the metabolic demands of immune cells (3), such strategies synergistically enhance immunotherapy efficacy (4). This integrated approach offers novel therapeutic avenues to overcome metabolic immunosuppression and potentiate antitumor immune responses, as evidenced by preclinical and clinical advances in metabolic modulators and nanomedicine-based delivery systems (5).
In this review, we will first give an overview of metabolic properties in tumor microenvironment. We will also highlight the process of immunometabolic editing, presenting metabolic alterations of tumor cells, immune cells, as well as stromal cells in the TME, and summarize how they support cancer evolution. Last but not least, we will illustrate mechanisms of tumor immunotherapies underlying tumor cell metabolism regulation, technological frontiers in dissecting tumor immunometabolism, and propose promising therapeutic targets in tumor immunometabolism.
2 Metabolic properties in tumor microenvironment
The metabolic interplays between tumor cells and stromal components within the TME exist throughout the entire process of tumor evolution. Tumor cells exhibit a distinct metabolic phenotype characterized by aerobic glycolysis (Warburg effect), even under normoxic conditions, to prioritize biomass synthesis over ATP efficiency. This metabolic shift supports rapid cell proliferation by generating glycolytic intermediates for nucleotides, amino acids, and lipids (6). Enhanced lactate dehydrogenase (LDH) activity in tumor cells further drives lactate production, acidifying the TME and promoting immunosuppression (7). Stromal cells, particularly cancer-associated fibroblasts (CAFs), adopt a “reverse Warburg effect”, engaging in aerobic glycolysis to secrete lactate, pyruvate, and glutamine, which would be exploited by tumor cells for oxidative phosphorylation and anabolic pathways (8–10). This metabolic symbiosis sustains tumor growth while depleting glucose reserves, creating a nutrient-deprived TME (11).
These metabolic interplays also have an impact on immunoactivity. First of all, tumor cells’ hyperactive glycolysis exhausts extracellular glucose, impairing effector T cell functions and fostering immune evasion. Glucose deprivation in tumor-infiltrating lymphocytes (TILs) suppresses mTOR signaling, diminishes glycolytic flux, and impairs interferon-gamma (IFN-γ) transcriptional output, culminating in a progressive impairment of immune effector functions (12). Elevated lactate (10–40 mM) acidifies the TME (pH ~6.5–6.9), inhibiting cytotoxic T lymphocyte (CTL) activity and promoting lipid synthesis via SLC5A12-mediated uptake in stromal cells (13, 14). Also, the elevated extra-cellular lactate levels within the TME may impair the efflux capacity of glycolytically active dendritic cells, thereby contributing to progressive intracellular lactate retention (15). On the other hand, low oxygen gradients within the TME activate HIF-1α, which upregulates glycolytic enzymes like glucose transporters (GLUT1) or hexokinase 2 (HK2), and PDK1 to suppress mitochondrial pyruvate utilization, redirecting carbon flux toward lactate (16). Hypoxia also induces lipid droplet formation in tumor-associated macrophages (TAMs), driving M2 polarization and immune suppression (17). Tumor cells and stromal cells exhibit increased lipid storage via upregulated enzymes of de novo lipogenesis and lipid scavenging. Lipid-rich TAMs adopt pro-tumor phenotypes through PI3K-γ/STAT6 signaling, while lipid droplets in cancer cells enhance chemoresistance and metastasis (18–20). These metabolic adaptations create a feed-forward loop: hypoxia and acidosis reinforce glycolytic flux, lactate sustains lipid biosynthesis, and lipid-laden stromal cells further compromise antitumor immunity. Targeting these pathways—e.g., inhibiting HIF-1α, LDHA, or fatty acid oxidation—may disrupt TME-driven immunosuppression and improve therapeutic outcomes (21, 22). More details of metabolic properties in the TME are demonstrated in Table 1.
Table 1. An overview of metabolic reprogramming of tumor cells.
3 Immunometabolic editing during cancer evolution
3.1 Metabolic reprogramming in tumor immune response
The metabolic interplay between tumor cells and immune cells during antitumor immune responses profoundly shapes immunoediting process and therapeutic efficacy. Effector immune cells exert anti-tumor activity and consume nutrients such as glucose and arginine, creating localized metabolic stress that can directly eliminate tumor cells or inhibit their growth, herein referred to as metabolic elimination. Recent advances highlight that immune cell metabolic reprogramming is dynamically regulated by activation states and TME constraints, exhibiting distinct patterns across immune subsets (23, 24) The overview of metabolic reprogramming is illustrated in Figure 1.
Figure 1. Metabolism of immune cells is distinguishably reprogrammed in the TME. The reprogrammed metabolism of immune cells exhibits stage-specific divergence between activation states and differentiation phases, with preferential engagement of distinct pathways to fulfill diverse functional demands. Conversely, systemic metabolic conditions and microenvironmental metabolites exert significant influence on immune cell phenotypes and effector functions. (Created with figdraw.com).
Naïve T cells rely on oxidative phosphorylation (OXPHOS) for energy, but upon activation, effector T cells undergo metabolic reprogramming toward aerobic glycolysis and glutaminolysis to meet biosynthetic demands for proliferation and cytokine production (23, 24). However, in the TME, tumor cells outcompete T cells for glucose via upregulated GLUT1, leading to CD8+ T cell exhaustion and impaired glycolytic flux (23, 25). Recent studies reveal that enhancing mitochondrial metabolism (e.g., via PGC-1α) or targeting adenosine/PD-L1 pathways can reinvigorate T cell function (26). Additionally, glutamine restriction in the TME disrupts T cell differentiation, but pharmacologic inhibition of tumor glutaminase (GLS1) enhances CTL infiltration and anti-tumor responses (27).
NK cells depend on glycolysis and OXPHOS for cytotoxicity. In hypoxic TME, mitochondrial dysfunction impairs NK cell effector functions, while lactate acidosis downregulates NKG2D receptor expression, reducing tumor cell recognition (28). Recent studies propose metabolic interventions such as LDH inhibitors to mitigate lactate toxicity or ROS scavengers like NAC to restore mitochondrial integrity, thereby enhancing NK-mediated tumor lysis (26). Notably, tissue-resident NK subsets exhibit unique metabolic dependencies on fatty acid oxidation (FAO), suggesting context-specific targeting opportunities (29).
Neutrophils undergo dynamic metabolic reprogramming during tumor immune surveillance, shifting between anti-tumor (N1) and pro-tumor (N2) phenotypes (30). Activated neutrophils primarily utilize glycolysis for ATP production and NETosis, facilitated by HIF-1α under hypoxia (31). This supports ROS generation via PPP for cytotoxic functions (32). Tumor-associated neutrophils (TANs) exhibit enhanced OXPHOS and FAO, particularly in immunosuppressive N2 states. This metabolic shift supports survival in nutrient-depleted TME and facilitates arginase-1-mediated T-cell suppression (32).
Macrophage polarization (M1/M2) is tightly linked to metabolic reprogramming. Pro-inflammatory M1 macrophages utilize glycolysis and broken TCA cycles, accumulating succinate to stabilize HIF-1α and drive IL-1β production. In contrast, anti-inflammatory M2 macrophages depend on OXPHOS and FAO, supported by enhanced glutamine metabolism and α-ketoglutarate (α-KG)-dependent epigenetic remodeling (33).
By redefining the metabolic landscape of the TME, immune cells either drive anti-tumor elimination or succumb to suppression, implying metabolic reprogramming as a critical axis for therapeutic intervention in overcoming immune evasion.
3.2 Metabolic reprogramming in tumor immune evasion
Immune pressure selects for tumor cell clones that has evolved superior metabolic fitness to survive in a metabolically hostile landscape or that can impose immunosuppressive metabolic constraints on immune cells, leading to metabolism-dominant immune escape. Emerging evidence highlights that tumor-derived metabolites and nutrient competition synergistically impair effector immune cell function while promoting immunosuppressive cell infiltration, thereby facilitating immune evasion during tumor development.
Tumor cells generate immunosuppressive metabolites through dysregulated glycolysis and amino acid metabolism. Lactate accumulation directly inhibits CTL proliferation and IFN-γ production (27). Lactate not only acidifies the TME but also directly suppresses NK-cell cytotoxicity and dendritic cell (DC) maturation, while enhancing Treg suppressive activity via FOXP3 and monocarboxylate transporter-1 (MCT-1) up-regulation (34). Glutamine deprivation in bladder cancer triggers EGFR/MEK/ERK/c-Jun signaling, elevating PD-L1 expression and impairing T-cell responses (35). Conversely, pharmacologic inhibition of glutaminase (e.g., JHU083) reprograms T-cell metabolism toward OXPHOS, enhancing antitumor immunity in preclinical models (36). Notably, tumor-derived kynurenine—a product of tryptophan catabolism via indoleamine 2,3-dioxygenase (IDO)—induces Treg differentiation while suppressing CD8+ T cell effector functions, creating a tolerogenic niche (29, 30).
Glucose and glutamine depletion in the TME starve effector T cells, triggers T cell exhaustion, characterized by upregulated PD-1 and CTLA-4 expression, which synergizes with PD-L1 overexpression on tumor cells to amplify immune checkpoint signaling (32, 33). Glucose deprivation impairs T-cell function by suppressing the mTOR signaling pathway. Limited glucose availability inhibits mTORC1, a crucial regulator of T-cell differentiation and effector functions (37). This suppression curtails T-cell proliferation and cytokine production, thereby weakening the anti-tumor immune response (38). Separately, glutamine deprivation can promote immune evasion by upregulating PD-L1 expression. This process is mediated through the activation of the EGFR/MEK/ERK/c-Jun signaling cascade (39, 40). The transcription factor c-Jun, activated downstream of EGFR and ERK, directly binds to the PD-L1 promoter, enhancing its expression and thus facilitating tumor escape from immune surveillance (41, 42). Recent studies reveal that mitochondrial dysfunction in CD8+ T cells—driven by tumor-induced oxidative stress—exacerbates metabolic insufficiency, impairing OXPHOS and perpetuating exhaustion (37, 38). Chronic antigen exposure and hypoxic stress in the TME induce mitochondrial fragmentation and bioenergetic failure in T cells. Exhausted T cells exhibit depolarized mitochondria, reduced OXPHOS, and impaired FAO, which are critical for sustaining effector functions (34). Furthermore, tumor-derived extracellular vesicles containing mitochondrial DNA (mtDNA) can paradoxically foster immune tolerance by activating the cGAS-STING pathway in stromal cells, increasing PD-L1 expression (43).
Concurrently, metabolite gradients actively reshape the immune landscape. Lactate and adenosine promote M2 macrophage polarization and Treg expansion via HIF-1α stabilization, while hypoxic regions secrete chemokines like CCL22 or CXCL12 to attract MDSCs (39, 40). These cells further deplete arginine and cysteine, metabolites essential for T cell receptor signaling and glutathione synthesis, respectively (41). Notably, tumor cholesterol esterification generates lipid rafts enriched in PD-L1, simultaneously enhancing immune checkpoint expression and recruiting lipid-dependent Tregs (31).
This metabolic reprogramming extends across the immune repertoire. While Teff and NK cells experience suppressed cytotoxicity and metabolic flexibility due to lactate accumulation, microenvironmental acidosis, and nutrient deprivation (44), suppressive populations like Tregs and MDSCs thrive on FAO and OXPHOS, leading to their expansion (34). In premetastatic niches, neutrophils utilize mitochondrial fatty acid metabolism to overcome glucose limitations, promoting immunosuppressive ROS production and disrupting nuclear factor of activated T cells (NFAT) signaling (34). Additional mechanisms include mitochondrial ROS accumulation in TAMs, which promotes M2 polarization and reinforces immunosuppression (36), along with AMPK signaling inhibition in γδ T cells due to a dominant Warburg effect, leading to impaired anti-tumor activity (35).
Metabolic-immune crosstalk also varies across malignancies. In melanoma, intratumoral heterogeneity correlates with reduced immune cytolytic activity and resistance to checkpoint inhibitors, partly due to metabolic subclones evading immune surveillance (45). Non-small cell lung cancers (NSCLC) with KRAS mutations exhibit distinct IL-17A-driven inflammatory profiles, which are modulated by glutamine metabolism and mitochondrial ROS, influencing therapeutic responses (46).
Collectively, these intertwined metabolic alterations—encompassing nutrient deprivation, mitochondrial damage, and metabolite-driven signaling—create a profoundly immunosuppressive milieu. Targeting these pathways to restore metabolic fitness in cytotoxic cells, such as with LDHA inhibitors or IL-15 to restore OXPHOS in NK cells, not only underscores metabolic reprogramming as a central mechanism in immune evasion, but also represents a promising therapeutic strategy to reverse immune dysfunction (47).
3.3 Underappreciated metabolic roles of stromal cells
Within the TME, stromal cells, particularly CAFs, orchestrate an immunosuppressive landscape through profound metabolic alterations. Firstly, CAFs contribute significantly to a lactate-rich milieu by enhancing glycolytic flux and engaging in metabolic symbiosis with cancer cells (48). Elevated extracellular lactate directly impairs CTL function by disrupting their proliferation, cytokine production, and cytotoxic capacity (49). Secondly, stromal cells prominently express ectonucleotidases like CD39 and CD73, which convert pro-inflammatory extracellular ATP into potent immunosuppressive adenosine (50, 51). This accumulation of adenosine subsequently engages A2A receptors on T cells, effectively curbing their activation and effector functions (50, 52). Furthermore, competition for essential nutrients like glutamine further restricts available resources for infiltrating immune cells. Collectively, these metabolic activities create a hostile environment that fosters immune evasion and presents a significant barrier to the efficacy of cancer therapies. Targeting these stromal-driven metabolic pathways is therefore under active clinical investigation as a strategy to reinvigorate anti-tumor immune responses (53).
4 Metabolic regulation of tumor immunotherapies
Tumor immunotherapy is a treatment that recognizes and eliminates tumor cells by activating or enhancing the body’s immune system. In the past decade, breakthrough progress has been made in tumor immunotherapy. Immune checkpoint inhibitor(CTLA-4/PD-1 blockade), CAR-T cell therapy, and therapeutic cancer vaccines have markedly improved survival outcomes in malignancies by either reversing T-cell suppression or enabling tumor-specific cytotoxicity. Emerging strategies targeting immunosuppressive components of the TME and novel bispecific T-cell engagers (BiTEs) have effectively countered tumor immune evasion mechanisms (36). The efficacy of these immunotherapies is intrinsically linked to metabolic regulation within the tumor-immune ecosystem throughout immunometabolic editing process.
4.1 Cell type-specific immunometabolic regulation
Researchers emphasize the application of T cell metabolism reprogramming in precision immunotherapy. For instance, the cholesterol esterase ACAT1 is a key regulatory target for T cell metabolism. Inhibition of its activity can enhance the anti-tumor function of CD8+ T cells. This is because elevated cholesterol concentrations within the plasma membrane of CD8+ T lymphocytes potentiate T-cell receptor (TCR) clustering and signal amplification, concomitant with heightened efficacy in immunological synapse assembly (47). Moreover, mannose metabolism governs CD8+ T cell stemness and antitumor efficacy through OGT-mediated β-catenin O-GlcNAcylation, which sustains Tcf7-dependent epigenetic reprogramming to decouple proliferation from exhaustion, while D-mannose supplementation during in vitro expansion generates stem-like T cell products with enhanced therapeutic potential for adoptive immunotherapy (54).
Apart from T cell metabolism regulation, researchers explored strategies to enhance tumor immunotherapy through targeted macrophage metabolism, highlighting the role of PHGDH in reversing the TAM immunosuppressive phenotype. The PHGDH-catalyzed de novo serine biosynthesis pathway critically regulates the glutaminolysis by converting glutamate to α-KG. This metabolic shift is indispensable for amino acid-dependent mTORC1 signaling activation, thereby sustaining polarization of immunosuppressive M2-like macrophages and TAM expansion (55). Another study revealed the role of the cholesterol metabolizer CH25H and its metabolite 25-HC in inhibiting macrophage activation. 25-HC could promote tumor growth by upregulating the expression of Arg1, Il10, and Mrc1 of macrophages, thus providing a new metabolic target for tumor immunotherapy (56).
4.2 Metabolite-governed immunometabolic regulation
Metabolites such as lactate or cholesterol are regarded as potential targets. Reducing lactate production and accumulation by regulating lactic acid metabolism has been found to enhance the efficacy of immunotherapy. Since the expression of PD-L1 is regulated by high lactate levels in the TME, blocking the lactate-generating enzyme LDH-A can enhance the efficacy of anti-PD-1 treatment (57). Moreover, PCSK9 has been found to affect the anti-tumor immune response by regulating the surface LDLR expression of CD8+ T cells. Reduced LDLR expression may critically govern intracellular cholesterol homeostasis in CD8+ TILs, thereby contributing to dysregulated metabolic states within the TME (58). Researchers also explored the role of N6-methyladenosine RNA methylation as a metabolic reprogramming marker in the immune microenvironment, and proposed new immunotherapies regulating m6A modifications. It was reported that the enrichment of m6A within the 3′-UTR of PD-L1 mRNA, demonstrating that JNK signaling promotes immune escape in bladder cancer via METTL3-mediated m6A modification (59).
5 Tumor immunometabolism targeted therapeutic strategies
Therapeutic targeting of cancer metabolic reprogramming represents a paradigm shift in oncology, focusing on vulnerabilities spanning tumor-intrinsic pathways, immune cell modulation and microenvironmental interactions, within the framework of immuonmetabolic editing.
5.1 Targeting metabolic pathways
Tumor cells prioritize glycolysis and glutaminolysis to fuel proliferation. Glutamine metabolism, catalyzed by GLS, supports nucleotide synthesis and redox balance. GLS inhibitors like CB-839 disrupt glutamine-to-glutamate conversion, elevating ROS and sensitizing tumors to chemotherapy in pancreatic and ovarian cancers (60). Similarly, glycolysis inhibitors such as 2-deoxyglucose (2-DG) target HK2, inducing ROS-mediated cell apoptosis (61). LDHA inhibitor FX11 suppresses lactate production, triggering oxidative stress and tumor regression in human lymphoma and pancreatic models (62). D-Mannose emerges as a promising modulator, countering T cell exhaustion by restoring metabolic balance. Mechanistically, D-mannose activates AMPK, leading to phosphorylation of PD-L1 at S195, which induces its abnormal glycosylation and proteasomal degradation (63). This degradation enhances T cell activation and cytotoxic killing (64). Preclinically, D-mannose synergizes with PD-1 blockade, significantly inhibiting triple-negative breast cancer (TNBC) growth and increasing CD8+ T cell infiltration, offering a strategy to overcome immunotherapy resistance (63). Adenosine accumulation within the TME potently suppresses T and NK cell function via the A2A receptor (A2AR). A2AR antagonists like CPI-444 block adenosine-mediated cAMP production and restore TCR signaling, IL-2, and IFN-γ production in T cells (65). Critically, CPI-444 demonstrates clinical activity as a single agent in renal cell carcinoma (RCC) patients, including those refractory to PD-1/PD-L1 blockade (66). Combining CPI-444 with anti-PD-L1 achieves synergistic tumor elimination in preclinical models, indicating its potential to reverse checkpoint inhibitor resistance (67, 68). Arginine metabolism is hijacked by tumors to “educate” immunosuppressive TAMs. Cancer cell-derived arginine fuels polyamine biosynthes in TAMs (69). Targeting this axis, the ornithine decarboxylase (ODC) inhibitor α-difluoromethylornithine (DFMO) disrupts myeloid-driven immunosuppression. DFMO impairs the suppressive function of MDSCs by reducing arginase activity and inhibiting the CD39/CD73-adenosine pathway (70). Furthermore, DFMO enhances anti-tumor CD8+ T cell infiltration and IFN-γ production, demonstrating its role in re-invigorating adaptive immunity (70).
5.2 Targeting metabolic enzymes and epigenetic regulators
Metabolic enzymes like pyruvate kinase M2 (PKM2) and GLUTs are pivotal in regulating metabolism in TME. PKM2 activators like TEPP-46 shift glycolysis toward oxidative phosphorylation, depleting biosynthetic intermediates and impeding cell growth (71). GLUT1 inhibitors (WZB117, BAY876) block glucose uptake in HCC and glioblastoma, synergizing with hypoxia-targeting agents (72). Similarly, researchers identified FTO as a demethylase that enhances glycolytic metabolism to evade immune surveillance. They developed Dac51, an FTO-inhibiting compound that disrupts tumor glycolysis and restores CD8+ T cell-mediated anti-tumor efficacy (48).
Epigenetic modifiers regulate metabolic genes. For example, HDAC4 deacetylates and activates GLS, promoting lung tumorigenesis, while HDAC inhibitors restore acetyl-CoA levels, normalizing histone acetylation and metabolic gene expression (73). DNMT inhibitors reverse methylation-induced silencing of tumor suppressors like PTEN, ameliorating PI3K/AKT-driven glycolytic flux (74). IDO1 and TDO2 are key immunosuppressive enzymes overexpressed in many cancers. They catalyze tryptophan degradation into kynurenine, depleting local tryptophan and accumulating immunosuppressive metabolites. This activates the GCN2 pathway in T cells and the AhR pathway, which promotes Treg differentiation while inhibiting effector T and NK cells (75). Epacadostat—a selective IDO1 inhibitor binding heme iron—effectively normalized plasma kynurenine levels in phase I trials, but monotherapy showed limited objective responses in solid tumors (76). Conversely, indoximod (a non-competitive IDO1 inhibitor modulating AhR/GCN2) combined with pembrolizumab achieved a 51% objective response rate (ORR) and 70% disease control rate (DCR) in advanced melanoma in a phase II trial. GLS1, the rate-limiting enzyme converting glutamine to glutamate, fuels tumor growth by replenishing TCA cycle intermediates and supporting biosynthesis. CB-839, an oral GLS inhibitor, demonstrated promising combinatorial efficacy: with cabozantinib in metastatic renal cell carcinoma (mRCC), it achieved a 50% ORR and 100% DCR in clear-cell subtypes (77). In myelodysplastic syndrome (MDS), CB-839 plus azacitidine induced marrow complete responses in 62.5% of patients, including those with TP53 mutations/complex karyotypes (78). Sirpiglenastat (DRP-104), a newer GLS inhibitor, is under evaluation with atezolizumab in advanced solid tumors (79). ARG1, expressed by MDSCs and TAMs, depletes arginine in TME, impairing T-cell receptor expression and proliferation. OATD-02, a dual ARG1/2 inhibitor, reverses TME immunosuppression and is undergoing trials in colorectal, renal, and lung cancers (80). Preclinically, L-norvaline (a non-competitive arginase inhibitor) enhances T-cell function and reduces microglial activation in murine models, though it remains investigational (81, 82). We have illustrated more therapeutic targets in Table 2.
Table 2. An overview of therapeutic targets in tumor immunometabolism.
5.3 Immune checkpoints and metabolic crossroads
PD-1/PD-L1 axis directly impairs CD8+ T cell metabolism. PD-1 signaling suppresses glycolysis and mitochondrial biogenesis via PGC-1α inhibition, blunting effector function. Conversely, lactate from tumor cells acidifies TME, upregulating PD-L1 expression and inducing Treg differentiation through MCT1-dependent lactate uptake, thereby dampening anti-tumor immunity (35, 83). Combining PD-1 blockade with LDHA inhibitors (FX11) or MCT1 inhibitors (AZD3965) reverses T cell exhaustion and enhances checkpoint efficacy (61, 62).
5.4 Tumor microenvironment modulation
HIF-1α upregulates GLUT1, LDHA, and CAIX, exacerbating glycolysis and acidification. HIF inhibitors normalize vascularization and glucose metabolism (84). CAIX inhibitors (e.g., SLC-0111) buffer pH and restore T cell cytotoxicity in cancer (85). Tumor cells outcompete T cells for glucose and glutamine. Glutamine blockade (CB-839) or adenosine receptor antagonists reverse CD8+ T cell suppression (60, 86). CAFs fuel tumor growth via “lactate shuttle” (MCT4-mediated export), while MCT4 inhibition disrupts this metabolic symbiosis (87).
6 Technological frontiers in dissecting tumor immunometabolism
Recent advancements in tumor immunology have shifted the paradigm from merely targeting immune checkpoints to a deeper interrogation of the metabolic cross-talk between cancer cells and the immune microenvironment. Single-cell multi-omics technologies have emerged as a cornerstone, enabling the dissection of cellular heterogeneity at unprecedented resolution. By integrating transcriptomic, proteomic, and spatial data, researchers can now map the intricate landscape of immune infiltration and identify specific metabolic signatures—such as cholesterol or branched-chain amino acid (BCAA) profiles—that correlate with therapeutic response (88, 89). This has led to the identification of actionable targets like DHCR7 and HMGCS1, demonstrating that metabolic reprogramming is not just a bystander effect but a critical driver of immune evasion.
Complementing these genomic approaches, hyperpolarized magnetic resonance imaging (HP-MRI) has revolutionized non-invasive metabolic phenotyping. By detecting real-time fluxes of labeled pyruvate into lactate, this technique allows clinicians to visualize tumor heterogeneity and monitor treatment-induced metabolic shifts without tissue destruction (90, 91). Furthermore, the integration of CRISPR-Cas9 screening with immunotherapy has unlocked new pathways; for instance, targeting enzymes involved in ferroptosis or nucleotide metabolism has been shown to sensitize tumors to immune checkpoint blockade, highlighting the potential of genetic engineering to overcome resistance mechanisms (92, 93). Finally, the development of metabolism-regulating nanocarriers represents a cutting-edge delivery strategy. These platforms exploit the TME to release drugs that simultaneously disrupt metabolic homeostasis and trigger immunogenic cell death, achieving spatiotemporal orchestration of therapy (94, 95).
7 Concluding remarks and challenges
Metabolic reprogramming extends beyond the intrinsic alterations within tumor cells to profoundly reshape the metabolic landscape of TME. The immunometabolic editing landscape orchestrates microenvironmental immunosuppression by directly subverting the metabolic pathways essential for effector immune cells while concurrently fueling the activity and function of immunosuppressive populations (23, 96). This review synthesizes these advances to elucidate mechanistic links between immunometabolic editing and cancer pathology, offering a roadmap for next-generation therapeutic combinations.
The field of tumor immunometabolism still faces significant hurdles in clinical translation. The spatiotemporal metabolic heterogeneity within the TME, where divergent metabolic demands exist among immune cell subsets and tumor cells. This complexity renders single-target interventions insufficient; spatial metabolomics and real-time monitoring are needed to address dynamic shifts like hypoxia and nutrient competition (5). Balancing metabolic intervention toxicity remains critical, as targeting core pathways risks systemic toxicity in normal cells, necessitating precision drug design (97). The crosstalk between metabolites and immune signaling is inadequately mapped: metabolites like fumarate and PAGln modulate immune receptors through unclear multi-target mechanisms, requiring integrated multi-omics approaches (98). Additionally, synergistic mechanisms between metabolic checkpoints (IDO, GPR34) and classical immune checkpoints (PD-1) need more in-depth exploration for effective combination therapies (23). Clinical translation bottlenecks is another intractable issue, which exists in most strategies in preclinical stages. Reliable biomarkers (e.g., ADSL phosphorylation for STING response) lack large-scale validation (5). Pharmacokinetic limitations due to poor TME drug penetration and compensatory metabolic pathway activation further hinder the efficacy of anti-tumor therapies (99). Emerging tools like tumor-on-chip platforms and spatial metabolomics offer promise for resolving TME dynamics (100), but interdisciplinary efforts are still essential to overcome these barriers.
Author contributions
YL: Visualization, Writing – original draft, Writing – review & editing. YZ: Writing – review & editing, Formal Analysis, Funding acquisition. YN: Conceptualization, Funding acquisition, Supervision, Writing – review & editing. XC: Conceptualization, Funding acquisition, Supervision, Writing – review & editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This work was supported by grants from National Natural Science Foundation of China (82573594, 82473458, 82173054), Guangdong Provincial Key Laboratory of Cancer Pathogenesis and Precision Diagnosis and Treatment (2024B1212030002), Science and Technology Projects in Guangzhou (2025A03J4276), Postdoctoral Fellowship Program of CPSF (GZB20230902) and Guangdong Provincial Clinical Research Center for Breast Diseases (2023B110005).
Conflict of interest
The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Keywords: immune cells, metabolic reprogramming, stromal cells, tumor cells, tumor immunometabolism, tumor immunotherapy, tumour microenvironment (TME)
Citation: Li Y, Zhang Y, Nie Y and Chen X (2026) Immunometabolic editing of the tumor microenvironment: from reprogramming mechanisms to therapeutic vulnerabilities. Front. Immunol. 16:1678446. doi: 10.3389/fimmu.2025.1678446
Received: 02 August 2025; Accepted: 25 December 2025; Revised: 21 December 2025;
Published: 16 January 2026.
Edited by:
Adil Rasheed, Augusta University, United StatesReviewed by:
Jingjing Li, Shandong Second Medical University, ChinaCopyright © 2026 Li, Zhang, Nie and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yan Nie, bmlleWFuN0BtYWlsLnN5c3UuZWR1LmNu; Xueman Chen, Y2hlbnhtMjIzQG1haWwuc3lzdS5lZHUuY24=