Metabolic reprogramming in cancer: signaling pathways and therapeutic targets

Abstract

Metabolism is a general term for an ordered series of chemical reactions used to maintain life, and the maintenance of normal cellular activities cannot be separated from metabolism, which is the most basic feature of life. However, metabolic alterations have a dual role. In normal cells, metabolic dysregulation predisposes them to impaired energy acquisition, senescence and even apoptosis. In contrast, metabolic remodeling in tumor cells is advantageous for cancer cell growth and proliferation, driving tumor development and becoming a hallmark of cancer. The inherent heterogeneity and plasticity of many tumor cells themselves are often accompanied by unique alterations in energy metabolism that allow them to survive even in harsh environments where resources are scarce. Notably, tumor cells do not operate in isolation; their metabolic reprogramming is tightly intertwined with metabolic crosstalk and collaborative adaptations involving other components within the tumor microenvironment. Among these metabolic pathways, glycolysis remains the dominant metabolic pathway driving tumor growth and microenvironmental remodeling, even under oxygen-sufficient conditions. Additionally, amino acid, lipid, and polyamine metabolism have been identified as a metabolic regulators that support cancer cell growth, influencing the fate and function of other cells in the microenvironment through metabolite exchange. Targeting cancer metabolism and its interactions with the microenvironment has thus emerged as a promising strategy for treating various malignancies. This article systematically reviews the redistribution of metabolic activities during cancer progression, encompassing both cell-autonomous metabolic reprogramming and microenvironment-mediated metabolic synergy and adaptation. The aim is to provide novel insights and therapeutic strategies for the comprehensive treatment of cancer.

Graphical Abstract

This review provides a comprehensive and systematic overview of the major modes of metabolic remodeling in cancer, including glucose, glutamine, lipid, and polyamine metabolism; investigates the metabolic crosstalk between cancer cells and the microenvironment; and provides potential therapeutic strategies based on metabolic pathways. This study contributes to a deeper understanding of the metabolic heterogeneity and uniqueness of metabolism in cancer and promotes anticancer therapies based on metabolic modalities

Introduction

Cancer has emerged as a major global health challenge in the 21st century, with the number of new cases projected to reach 35 million by 2050 [1, 2]. Notably, lung, breast, colorectal, prostate, and gastric cancers collectively account for more than half of all newly diagnosed cancer cases worldwide [2]. Persistent driving forces, such as smoking, aging, and other multifactorial risks, are responsible for this increasing incidence [3]. However, this severe situation, although traditional cancer treatment methods have made significant progress driven by technology and research, numerous factors such as drug resistance and tumor heterogeneity, have prevented some cancer patients from benefiting. In particular, for patients with advanced cancer, the current treatment options encounter major challenges; thus, new treatment strategies are urgently needed.

Metabolic reprogramming represents a critical hallmark of tumor cells. Unlike normal cells, cancer cells systematically rewire their metabolic pathways to fulfill the heightened bioenergetic and biosynthetic demands required for sustained proliferation, invasion, metastasis, and adaptation to microenvironmental stress [4]. More than a century ago, the groundbreaking work of Otto Warburg revealed that tumor cells preferentially metabolize glucose to lactate via the glycolytic pathway even under oxygen-sufficient conditions, rather than engaging in efficient mitochondrial oxidative phosphorylation. This reprogramming of energy metabolism (the Warburg effect) not only overturns conventional theories of the cellular energy supply but also highlights the central role of metabolic dysregulation in tumorigenesis and progression [5]. Decades of subsequent research have improved our understanding of tumor metabolic reprogramming. These metabolic networks, encompassing nutrient sensing, signal transduction, and gene expression regulation, collectively drive tumor initiation and development.

The metabolic alterations in tumors encompass all stages of cellular-metabolite interactions [6]. For instance, tumor cells increase the uptake and utilization of glucose and glutamine to supply biosynthetic precursors and ATP. Depending on nutrient availability in the microenvironment, tumor cells can dynamically adjust their metabolic requirements, switching to various alternative carbon and nitrogen sources, such as accelerating the uptake and conversion of polyamines. Moreover, they maintain the redox balance by enhancing the flux through the pentose phosphate pathway (PPP) and accelerating serine/glycine metabolic flux and one-carbon unit production [7]. Furthermore, tumor cells exploit the accumulation of specific metabolites to directly influence gene expression and malignant phenotypes, thereby establishing a “metabolism-epigenetics-transcription” regulatory circuit. These changes may be driven by mutations in oncogenes and tumor suppressor genes, which reprogram cellular metabolism to systematically meet the multifaceted biological demands of tumor cells, such as rapid proliferation, apoptosis resistance, and adaptation to microenvironmental stress including hypoxia and nutrient deprivation [8, 9].

Metabolic reprogramming in tumors is the result of intricate interactions between cancer cells and other components within the tumor microenvironment (TME) [10]. The TME constitutes a complex ecosystem comprising cancer cells, fibroblasts, immune cells, endothelial cells, and the extracellular matrix [11]. Recent research has revealed that the relationship between the TME and tumor metabolic reprogramming is not one of simple causality but rather forms a dynamic, bidirectional, and self-reinforcing vicious cycle [12, 13]. Cancer cells adapt to and remodel the TME through metabolic reprogramming, while factors such as hypoxia, nutrient deprivation, and metabolic waste accumulation within the TME further drive the selection of cancer cells with more adaptable metabolic phenotypes. For instance, the substantial amount of lactate produced by glycolysis in tumor cells inhibits the immune-killing functions of natural killer (NK) cells and effector T cells while simultaneously selecting for tumor cells that are more tolerant to acidic conditions. These cells typically exhibit more active glycolysis and proton extrusion capabilities [14, 15]. Concurrently, metabolic signals such as the arginine-spermine axis associated with tumor cells can induce the activation and phenotypic transformation of immunosuppressive cells, accelerating the degree of immune suppression in the microenvironment. Moreover, stromal cells within the microenvironment can support tumor growth by providing metabolic substrates (such as glutamine and fatty acids [FAs]) or recycling metabolic waste (such as lactate), thereby forming a metabolic symbiotic network [16, 17]. This dynamic interplay not only enhances the survival adaptability of tumors but also increases their metabolic plasticity. Particularly under stress conditions such as hypoxia or nutrient deprivation, this metabolic synergy intensifies, driving tumors to exhibit more aggressive and treatment-resistant phenotypes.

Given the critical role of metabolic reprogramming in tumor growth and its interdependent relationship with the TME, targeting metabolites and related pathways has emerged as a highly promising anticancer strategy. This approach includes inhibiting transporters and key metabolic enzymes to reduce nutrient uptake and utilization, as well as decreasing the production and release of metabolites such as lactate to remodel the TME. Additionally, targeting metabolic adaptability aims to sensitize tumors to existing therapies. Corresponding clinical trials are currently investigating the efficacy, safety, and therapeutic outcomes of combination regimens involving these targeted inhibitors, with the goal of achieving synergistic antitumor effects and broader clinical benefits.

This review systematically summarizes the characteristics of metabolic reprogramming in cancer cells, covering key pathways such as glucose, glutamine, lipid, and polyamine metabolism. It delves into the roles of metabolic intermediates, key metabolic enzymes, and related signaling pathways in promoting tumor progression, while evaluating their potential as therapeutic targets. This article further focuses on the role of tumor metabolites in regulating the TME, elucidating how metabolic reprogramming influences immune cell function, shapes an immunosuppressive microenvironment, and mediates therapeutic resistance. Finally, we outline intervention strategies targeting tumor metabolism, aiming to provide a theoretical foundation and translational directions for the development of novel anticancer therapies.

Glucose metabolism in cancer

Aerobic Glycolysis and key metabolic enzymes

Carcinogenesis is a very complex process. Unlike normal cells, which rely primarily on oxidative phosphorylation for energy production, most tumor cells preferentially utilize aerobic glycolysis (the Warburg effect) to convert large amounts of glucose into lactate and export it from the cell, even under conditions of a sufficient oxygen supply [18]. This metabolic reprogramming not only provides tumor cells with a rapid means of generating ATP but also supplies essential carbon skeletons, NADPH, and other biosynthetic precursors crucial for key biological processes such as growth, proliferation, and angiogenesis. Furthermore, through mechanisms such as acidification of the microenvironment, this metabolic shift fosters an immunosuppressive environment favorable for tumor survival, thereby significantly increasing the invasive and metastatic potential of tumor cells [19]. The glycolytic pathway plays a central regulatory role in cancer metabolism, including the regulation of several key metabolic enzymes [20]. As the gateway for glucose influx into cells, the upregulation of glucose transporters (GLUTs) is a hallmark of many cancer types. Different GLUT isoforms play specific roles in tumor metabolic reprogramming because of their distinct affinities and regulatory mechanisms [21]. For example, GLUT1 provides a basal, sustained, and high-rate of glucose uptake, serving as the primary transporter to meet the basic energetic and biosynthetic demands of cancer cells. It is commonly upregulated in most cancers, including breast [22], liver [23], prostate [24], pancreatic [25], and lung [26] cancers, and is regulated by oncogenes such as Myc, Kras, and yes-associated protein (YAP). High expression of forkhead box D1 (FOXD1), which is closely related to a poor prognosis for patients with pancreatic cancer, promotes the upregulation of GLUT1 expression and glucose uptake in cancer cells by activating the transcription of solute carrier family 2 member 1 (SLC2A1) and the lncRNA HOXA11-AS, which aggravate the malignant behavior of cancer cells [27]. Moreover, GLUT1 expression levels are strongly correlated with the malignant grade and poor prognosis of patients with breast cancer, as confirmed in breast cancer cell models [28, 29]. Studies have shown that GLUT2, which has a relatively low affinity for glucose, is specifically upregulated in liver cancer and colorectal cancer, consistent with the metabolic characteristics of their tissues of origin [30, 31]. In contrast, GLUT3, whose affinity for glucose is relatively high, confers a strong competitive advantage to cancer cells under harsh microenvironmental conditions such as hypoxia and nutrient deprivation, directly supporting tumor growth, invasion, and therapy resistance [32]. For instance, elevated GLUT3 expression is observed not only in thyroid cancer [33] and glioblastoma [34] but also across a range of aggressive tumors such as triple-negative breast cancer [35] and head and neck squamous cell carcinoma [36], where it is significantly associated with a poor prognosis for patients. This heterogeneity in GLUT isoform expression, dictated by tumor diversity, reveals the metabolic strategies employed by cancer cells to adapt to varying survival pressures, thereby offering promising molecular targets for the development of novel anticancer therapies targeting specific isoforms or particular tumor microenvironmental niches.

Hexokinase 2 (HK2) is a key driver of increased glycolysis rates and is upregulated in a variety of cancers [37]. High HK2 expression not only activates glycolytic bypass pathways, including the PPP, serine synthesis pathway and hexosamine biosynthesis pathway, but also results in the production of pyruvate, which becomes an important raw material for the synthesis of amino acids and lipids [38]. Moreover, HK2 is closely related to the survival of patients with breast cancer and mediates the immunosuppression of breast cancer cells through the upregulation of programmed death ligand-1 (PD-L1) expression [39]. Pyruvate kinase (PK) is the last key enzyme that catalyzes the glycolysis process, converting phosphoenolpyruvate to pyruvate. PK has four subtypes, PKL, PKR, PKM1 and PKM2, among which the PKM2 subtype is generally overexpressed in various cancer cells [40]. Studies have shown that the highly efficient expression of PKM2 and lactate dehydrogenase (LDHA) in pancreatic cancer cells leads to the conversion of most pyruvate to lactate. The large amount of lactate that is produced is then excreted extracellularly to participate in the formation of the acidic TME, which contributes to the enhancement of immunosuppression and leads to worse clinical outcomes. In particular, these cells highly express the monocarboxylate transporter MCT4 on their plasma membrane, which transports intracellularly accumulated lactate into the microenvironment, accelerating glycolytic flux [41, 42]. In bladder cancer, PKM2 promotes growth, proliferation and cisplatin resistance of cancer cells. Moreover, the m5C modification of the PKM2 mRNA has become a key link in the glycolytic metabolism of bladder cancer in a hypoxic environment and is therefore a potential target for bladder cancer therapy [43, 44]. However, Dayton et al. used PKM2-/- mice and observed that the stable presence of PKM2 can prevent spontaneous hepatocellular carcinoma. These contradictory results highlight the multiple effects of PKM2 on metabolism in cancer [45]. A precise understanding of the metabolic regulation of PKM2 is important for the selection of therapeutic targets in cancer.

Activation of aerobic glycolysis-related bypass pathways

Increased glycolysis simultaneously activates multiple self-associated bypass pathways, among which the PPP provides the raw material for purine and pyrimidine nucleotide synthesis and maintains redox homeostasis for cancer cell growth, which largely depends on the activity of glucose-6-phosphate dehydrogenase (G6PD), as it catalyzes the first step of the glucose-6-phosphate shift to the PPP [46]. Moreover, inhibition of phosphofructokinase (PFK-1) and PKM2 can drive glycolytic flux toward the PPP, which may also be a major factor involved in the widespread overexpression of PKM2 in cancer cells because of the low catalytic efficiency of PKM2 compared with that of PKM1 [47]. An analysis of transcriptomic and metabolomic data suggests that pancreatic cancer cells in acidic environments tend to increase the rate of PPP metabolism (NADPH and ribulose 5-phosphate synthesis pathway), which may be associated with negative feedback regulation of lactate. Increased activity of the PPP promotes the survival and development of cancer cells in an acidic environment by mediating the AMP-activated protein kinase (AMPK)/ YAP/matrix metallopeptidase 1 (MMP1) signaling axis [48]. As a tumor suppressor gene, P53 is involved in metabolic regulation and can promote the output of glucose to glycogen and thus the consumption of glucose [49]. Moreover, P53 can induce conformational changes in G6PD, and the inactivation of P53 in cancer cells removes the restriction of G6PD activity, thereby increasing PPP flux and macromolecular biosynthesis [50]. Transketolase (TKT), a nonoxidative metabolic enzyme in the PPP pathway, regulates the cellular levels of ribose-5-phosphate and NADPH. Its activity significantly influences the distribution of glucose between glycolysis and the PPP [51]. Upon the inhibition of TKT to modulate PPP flux and nucleotide synthesis, cancer cell proliferation is markedly affected, and resistance to cisplatin and paclitaxel can be mitigated. Common inhibitors currently include oroxylin A [52] and oxythiamine (OT) [53]. Several studies have shown that targeted inhibitors of PPP metabolism can sensitize cancer cells to ionizing radiation, confirming the potential value of agents targeting the PPP as radiotherapy sensitizers [54, 55].

As another key bypass of glycolysis, serine is catalyzed by serine hydroxymethyltransferase (SHMT, including cytosolic SHMT1 and mitochondrial SHMT2) to provide one‑carbon units for the folate cycle, thereby driving nucleotide synthesis. This process is coupled with the generation of NADPH and supplies essential precursors (glycine and cysteine) for the synthesis of the antioxidant glutathione (GSH), thereby collectively establishing a robust antioxidant defense network together with PPP. Particularly under hypoxic stress, the one‑carbon metabolism mediated by SHMT2 and mitochondrial methylene-tetrahydrofolate dehydrogenase 2 (MTHFD2) enhances mitochondrial antioxidant capacity [56]. Furthermore, when the key glycolytic enzymes PKM1/2 are inhibited, the glucose flux to serine is upregulated, but the content of pyruvate produced by glycolysis does not decrease. These results are attributed to the maintenance of metabolic homeostasis in cancer cells by phosphoglycerate dehydrogenase (PHGDH)-mediated serine biosynthesis cysteine catabolism, which are upregulated in a variety of cancers, including esophageal, lung and liver cancers, and are associated with cell proliferation, metastasis, and chemoresistance [57–59]. The hexosamine biosynthesis pathway (HBP) fully integrates metabolites such as glucose, glutamine, acetyl-CoA and UTP to provide substrates for the glycosylation of cancer cell proteins and lipids. Glutamine-fructose-6-phosphate transaminase 1/2 (GFPT1/2) is the first key rate-limiting enzyme in the HBP process; it is overexpressed in prostate cancer and breast cancer, and can escape immune killing by enhancing protein glycosylation and reducing lymphocyte infiltration, which may be closely related to the stable expression of the PD-L1 protein [60, 61]. These results confirm the necessity of targeting bypass pathways to improve the efficacy of cancer immunotherapy.

Lactate regulation and epigenetic modifications

Unlike normal cells, tumor cells continuously refine their metabolic patterns to increase their adaptability to a constantly changing microenvironment characterized by hypoxia, low pH, nutrient scarcity, electrolyte imbalance, and oxidative stress. Lactate accumulation represents a major outcome of this metabolic reprogramming [62]. In addition to glycolysis, glutamine can fuel lactate production via its catabolic pathway, providing tumor cells with an auxiliary lactate-generating route that supports their highly glycolytic phenotype [63]. Consequently, the traditional perception of lactate as a mere metabolic waste product has shifted to a multifunctional signaling molecule and energy carrier, playing complex regulatory roles within the TME.

As a key metabolic enzyme for lactate production, LDHA (LDH5) is overexpressed in most cancers and has high affinity and catalytic efficiency in the conversion of pyruvate to lactate [64]. LDHA expression is directly regulated by transcription factors such as c-Myc and hypoxia-inducible factor 1 (HIF-1), with the latter further increasing lactate production by blocking pyruvate entry into mitochondria [65, 66]. Additionally, post translational modifications of LDHA, such as phosphorylation and acetylation, are closely associated with cancer progression and drug resistance [67, 68]. In colorectal cancer, adenylate kinase 6 (hCINAP) binds to LDHA and promotes its phosphorylation at tyrosine residue 10, leading to an overactive Warburg effect and reduced cellular reactive oxygen species (ROS) levels, thereby conferring metabolic advantages for the invasion of colorectal cancer stem cells [69]. At the transport level, lactate achieves dynamic intracellular-extracellular and intercellular exchange through the MCT family (such as MCT1 and MCT4), a process mediated by factors such as pH, lactate concentration gradients, and cellular redox reactions [70]. Research has indicated that lactate that has accumulated within cancer cells is transported extracellularly by the monocarboxylate transporter MCT4, which not only facilitates the acceleration of glycolytic flux but also increases the acidity of the TME and promotes angiogenesis [71]. Moreover, cancer cells in some tumors rely on oxidative phosphorylation as the dominant metabolic pathway (oxidative cancer cells), and some cancer cells rely mainly on glycolysis (glycolytic cancer cells). These oxidative cancer cells expressing MCT1 uptake lactate secreted by glycolytic cancer cells expressing MCT4, using it as an oxidative fuel and preserving the glucose required by glycolytic cancer cells. This “metabolic symbiosis” accelerates cancer progression [72]. In oxygen-rich regions, LDHB catalysis in oxidative cancer cells results in the conversion of lactate to pyruvate, which then enters the TCA cycle together with NADH via the malate‒aspartate shuttle. In particular, in non-small cell lung cancer (NSCLC) and metastatic breast cancer, the contribution of lactate to the TCA cycle even exceeds that of glucose [73, 74]. Furthermore, elevated lactate levels accelerate metabolic remodeling and functional state transitions among diverse cell types within the TME, contributing to the maintenance of the malignant phenotype of cancer cells, as elaborated in the following Sect [75].

Similarly, as an epigenetic regulator, lactate can directly participate in the regulation of gene expression through histone lactylation, a process that is dynamically modulated by enzymes such as acetyltransferase p300 and histone deacetylases (HDACs) [76, 77]. Particularly in tumor cells with active glycolysis, accumulated lactate stabilizes and increases the activity of proglycolytic transcription factors such as HIF-1α and c-Myc, as well as the expression of their downstream target genes, via lactylation, thereby forming a self-reinforcing positive feedback loop that further entrenches the glycolytic phenotype of tumors [78, 79]. In various cancer types, lactylation further couples with other epigenetic mechanisms to jointly drive tumor progression. For example, in colorectal cancer, the methyltransferase 1 (METTL1)-mediated m7G modification of the PKM mRNA increases PKM2 expression, promoting glycolysis and lactate accumulation. The accumulated lactate, in turn, upregulates METTL1 expression via histone H3K9 lactylation, establishing another positive feedback axis. This regulatory circuit concurrently increases the expression of the immune checkpoint molecule poliovirus receptor (PVR, CD155), thereby further promoting immune evasion in addition to metabolic reprogramming [80]. Similar mechanisms have also been observed in malignancies such as gastric cancer and glioblastoma, underscoring the critical role of lactylation in tumor progression [81, 82]. Based on the mechanisms described above, targeting key nodes involved in lactate production and modification has emerged as a highly promising therapeutic strategy. Inhibiting LDHA to reduce lactate synthesis, or developing modulators of p300/HDACs to interfere with the dynamic balance of lactylation has the potential to simultaneously disrupt the metabolic dependency and epigenetic remodeling capabilities of tumors, thereby providing new avenues for combination therapies targeting multiple pathways. Changes in glucose metabolism and related signaling pathways in cancer are shown in Fig. 1.

Fig. 1.

Changes in glucose metabolism and related signaling pathways in cancer. Cancer cells significantly enhance glucose uptake and glycolytic flux by upregulating the expression of glucose transporters and the activity of key glycolytic enzymes (e.g., HK2, PKM2 and LDHA). This metabolic reprogramming not only efficiently converts glucose into lactate and ATP but also activates multiple metabolic branches such as the pentose phosphate pathway, serine synthesis pathway, and hexosamine biosynthesis pathway, providing essential precursors for the synthesis of macromolecules, including nucleic acids, proteins, and lipids required for tumor cell proliferation. In addition, the substantial amount of lactate generated by tumor cell glycolysis is extruded into the tumor microenvironment via MCT4, where it serves as a metabolic substrate utilized by stromal cells, immune cells, and other components, thereby reshaping the microecology. Meanwhile, intracellular lactate can function as an epigenetic regulator, modulating the transcription of relevant genes through mechanisms such as lactylation. This process helps sustain and reinforce the glycolytic phenotype of tumor cells, establishing a positive feedback loop that continuously drives malignant tumor progression. HK2, hexokinase 2; PKM2, pyruvate kinase 2; LDHA, lactate dehydrogenase A; MCT4, monocarboxylate transporter 4; G6PD, glucose-6-phosphate dehydrogenase; TKT, transketolase; PPP, pentose phosphate pathway; PHGDH, phosphoglycerate dehydrogenase; SHMT, serine hydroxymethyltransferase; PDH, pyruvate dehydrogenase. PDK, pyruvate dehydrogenase kinase, HDACs, histone deacetylases

Cancer treatment strategies targeting glucose metabolism

Aerobic glycolysis, a metabolic pathway that is preferentially utilized by the majority of cancer cells, accelerates energy acquisition and the supply of biosynthetic precursors. Interventions targeting this pathway can, to some extent, inhibit cancer progression. These interventions include inhibiting GLUTs to restrict glucose uptake by cancer cells, specifically targeting key rate-limiting enzymes to reduce glycolytic flux, and blocking lactate production and efflux through inhibition of the LDHA or MCT4. These interventions have shown significant antitumor potential in preclinical studies and are expected to become a promising direction for future combination therapies in cancer treatment.

GLUT transporters, which serve as the gateway for glucose entry into cancer cells, has become a primary target of interest for cancer therapy. In particular, GLUT1 is a major glucose transporter protein that mediates a series of tumor metabolic reprogramming events by supporting glycolysis. Previous studies have shown that GLUT1 contributes to epidermal growth factor receptor (EGFR) - tyrosine kinase inhibitor (TKI) resistance by mediating glucose metabolism. High levels of GLUT1 are associated with shorter survival, especially in lung cancer patients with EGFR mutations. The sensitivity of cancer cells to EGFR-TKI treatment was improved by the use of the GLUT1 inhibitor WZB117, suggesting that strategies targeting the GLUT1-EGFR axis have the potential to be effective approaches for the treatment of lung cancer [26]. Other inhibitors targeting GLUT1 include BAY-876, STF-31, fasentin, KL-11,743, and silybin, which have entered phase I clinical trials (NCT00487721). These drugs can have anticancer activity through the inhibition of glucose uptake. Another antiglycolytic strategy involves targeting the rate-limiting enzyme of glycolytic metabolism, HK2. 2-Deoxy-D-glucose (2-DG), a glucose analog, enters cancer cells and competes with glucose-6-phosphate for HK2, whereby the phosphorylation of 2-DG to 2-DG-P blocks glycolysis and leads to ATP depletion and oxidative stress, resulting in anticancer effects [83]. Nonetheless, 2-DG is ineffective as a single agent to exert anticancer effects, including in clinical trials related to pancreatic and prostate cancer [84, 85]. Several studies have begun to explore the efficacy of 2-DG in combination therapy. The phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling is a major pathway that activates glycolytic metabolism in B-cell non-Hodgkin lymphoma (B-NHL). The combination of the PI3K and mTOR inhibitor PF-04691502 with 2-DG promoted the transformation of B-NHL cell metabolism from aerobic glycolysis to oxidative respiration and enhanced the toxic effect on B-NHL cells [86]. Furthermore, the combination of 2-DG with cisplatin has been shown to increase cytotoxicity in head and neck cancer [87]. Other targeted HK2 inhibitors include lonidamine (LND) [88], GEN-27 [89], and some natural compounds, such as resveratrol and astragalin [90, 91]. PFK-158, the first specific 6-phosphofructo-2-kinase (PFKFB3) inhibitor, has shown broad antitumor activity in a variety of human and preclinical models, and the clinical value of PFK-158 in patients with advanced pancreatic cancer has been reported in a related multicenter clinical trial (NCT02044861) [92]. In addition, PFKFB3 activity is specifically inhibited by 3-(3-pyridinyl)-1-(4-pyridinyl)-2-propen-1-one (3PO) and its derivative 1-(4-pyridinyl)-3-(2-quinolinyl)-2-propen-1-one (PFK15). The administration of 3PO inhibits glucose uptake, lactate production, and ATP production in Jurkat T-cell leukemia cells [93]. Moreover, PFK15 inhibits glucose uptake and promotes apoptosis in Lewis lung cancer cells in vitro and in vivo [94]. Through the catalytic action of PKM2, phosphoenolpyruvate is converted to pyruvate, which is the hub connecting glycolysis and oxidative phosphorylation, and inhibitors targeting PKM2 have become the focus of research. Compounds such as benserazide, TT-232, vitamin K5, and Compound 3 reduce glycolytic activity in tumors by inhibiting PKM2 [95]. Nevertheless, targeting PKM2 alone does not achieve good efficacy in the treatment of cancer; rather, PKM2 inhibition promotes tumor growth in some cancer models [45, 96].

Although the aforementioned strategies have shown significant antitumor efficacy in preclinical models and can produce synergistic effects when combined with chemotherapy or radiotherapy, their clinical translation still faces substantial challenges. These challenges primarily arise from tumor metabolic heterogeneity, the activation of compensatory pathways, and potential systemic toxicity. Consequently, future efforts should focus on developing more selective inhibitors, identifying biomarkers capable of predicting the therapeutic response, and exploring their integration into precision-based combination treatment regimens. Targeting the glycolytic pathway, particularly as a component of combination therapy, remains a highly promising research direction in the field of cancer treatment. The development of inhibitors targeting key enzymes involved in glycolysis and related mechanisms of action are summarized in Table 1.

Table 1.

Summary of studies on the development of inhibitors targeting key enzymes involved in Glycolysis metabolism and related mechanisms of action

Target key enzymes of metabolism	Inhibitors	Type of study	In vivo/ in vitro	Mechanism of action	References
GLUT1	WZB117	Preclinical	In vitro	Inhibits GLUT1 to increase sensitivity of lung cancer cells to EGFR-TKI therapy	[26]
	BAY-876	Preclinical	Both	Inhibits GLUT1 to block RB1 expression and glycolysis in breast cancer	[97]
	STF-31	Preclinical	In vitro	Inhibits the growth and invasion of thyroid cancer and improves the therapeutic effect of lenvatinib	[98]
	Fasentin	Preclinical	In vitro	Inhibits glucose uptake and growth in glioblastoma	[99]
	KL-11,743	Preclinical	Both	Specifically blocks glucose metabolism and triggering an acute collapse of the NADH pool and significant accumulation of aspartate	[100]
	Silybin (NCT00487721)	Phase II	-	Inhibits GLUT1 expression and glucose uptake	[101]
HK2	2-DG (NCT00096707)	Phase I	-	Inhibits HK2 and competes with glucose to inhibit glycolysis	[102]
	Lonidamine	Preclinical	In vitro	Improves the sensitivity of meningioma to the treatment of AKT inhibitor AZD5363. Inhibition of glycolysis	[103]
	Gen-27	Preclinical	Both	Inhibits HK2 and the interaction between HK-2 and VDAC	[89]
	Resveratrol	Preclinical	Both	Inhibits glycolysis and enhances the sensitivity of liver cancer to sorafenib	[90]
	Astragalin (ASG)	Preclinical	Both	Inhibits the expression of HK2 by increasing miR-125b. Inhibits liver cancer glycolysis and promotes oxidative phosphorylation and ROS production	[91]
	Benserazide	Preclinical	Both	Reduces glucose uptake, lactate production, and ATP production levels in colorectal cancer cells by inhibiting HK2	[104]
	Chrysin	Preclinical	Both	Inhibits liver cancer glycolysis and lactate production	[105]
	Matrine	Preclinical	Both	Inhibits the expression of HK2 mediated by c-Myc. Combines application with lonidamine to improve anti-cancer effect leukemia cells apoptosis	[106]
PFKFB3	PFK-158 (NCT02044861)	Phase I	-	Inhibits glucose uptake and promotes apoptosis of cancer cells	[92]
	3PO	Preclinical	Both	Inhibits glucose uptake and decreases intracellular concentrations of Fru-2,6-BP, lactate, ATP, NAD+, and NADH	[93]
PKM2	Benserazide	Preclinical	Both	Inhibits glycolysis and promote oxidative phosphorylation. Inhibition of melanoma cell growth and metastasis	[107]
	TT-232	Preclinical	In vitro	Promotes the nuclear translocation of PKM2 and programmed cell death	[108]
	Vitamin K3/K5	Preclinical	In vitro	Inhibits glycolysis process	[109]
	Compound 3	Preclinical	In vitro	Inhibits glycolysis process and induces lung cancer cell death	[95]
LDHA	FX11	Preclinical	Both	Inhibits glycolysis. Induces autophagy in thyroid cancer by activating AMPK signaling pathways	[110]
	Oxamic acid sodium	Preclinical	In vitro	Inhibits lactate production. Promotes the migration of esophageal cancer cells by activating ERK1/2 signals	[111]
	GSK2837808A	Preclinical	Both	Inhibits the formation of L-2 hydroxy-glutaric acid (L-2HG)	[112]
MCTs	α-cyanocinnamic acid (α-CHCA)	Preclinical	In vitro	Inhibits MCT1/2 activity and lactate transport	[113]
	AZD3965 (NCT01791595)	Phase I	-	Inhibits MCT1 activity and lactate transport	[114]
	Syrosingopine	Preclinical	In vitro	Inhibits the activity of MCT1 and MCT4. Induces high intracellular lactate levels	[115]
	AR-C155858	Preclinical	Both	Inhibits MCT1 activity and lactate transport	[116]
G6PD	6-aminonicotinamide (6-AN)	Preclinical	In vitro	Inhibits lactate production and glucose depletion, alters mitochondrial potential and redox balance. Induces endoplasmic reticulum stress	[117]
	G6PDi-1	Preclinical	Both	Inhibits the production of NADPH	[118]
	Polydatin	Preclinical	Both	Inhibits the shunt of glucose flux to the PPP pathway	[119]
	Dehydroepiandrosterone (DHEA)	Preclinical	Both	Inhibits G6PD and NADPH levels and promotes ROS production	[120]
	RRx-001	Preclinical	Both	Induces redox imbalance and apoptosis	[121]
TKT	Oroxylin A	Preclinical	Both	Inhibits TKT expression and induces accumulation of nonoxidative PPP substrates	[52]
	Oxythiamine	Preclinical	Both	Suppresses the PPP pathway by inhibiting TKT	[53]
PHGDH	NCT-503	Preclinical	Both	Promotes ROS stress and DNA damage	[122]
	CBR-5884	Preclinical	In vitro	Induces ROS and decreases the NADPH/NADP + ratio	[123]

Abbreviations: GLUT1 Glucose transporter type 1, EGFR Epidermal growth factor receptor, RB1 RB transcriptional corepressor 1, NADH Nicotinamide adenine dinucleotide, HK2 Hexokinase2, VDAC Voltage dependent anion channel 1, PFKFB3 6-phosphofructo-2-kinase/Fructose-2,6-Biphosphatase 3, PKM2 Pyruvate kinase 2, AMPK Adenosine 5‘-monophosphate (AMP)-activated protein kinase, LDHA Lactate dehydrogenase A, MCTs Monocarboxylate transporters, G6PD Glucose-6-phosphate dehydrogenase, ROS Reactive oxygen species, TKT Transketolase, PHGDH Phosphoglycerate dehydrogenase

Amino acid metabolism in cancer

The uptake and metabolism of amino acids represent another critical metabolic pathway, in addition to glycolysis, that sustains the malignant growth of tumors. This process not only provides essential carbon and nitrogen sources for the synthesis of macromolecules such as nucleic acids, lipids, and proteins but also directly activates multiple signaling pathways that drive tumor proliferation, survival, and metastasis [124, 125]. Among the amino acids, glutamine, the most abundant free amino acid in the body, not only serves as a precursor for protein synthesis but also participates in processes such as anaplerosis of the tricarboxylic acid cycle, nitrogen supply, and glutathione synthesis. These functions directly sustain the energy metabolism, biosynthesis, and redox homeostasis of cancer cells [126, 127]. Therefore, a thorough elucidation of amino acid metabolism pathways, particularly glutamine metabolism, is essential for overcoming resistance to glycolysis-targeted cancer therapies and developing novel combination treatments.

Glutamine metabolism and signal transduction

Glutamine transport and usage

Glutamine is a key amino acid that supports cellular proliferation and plays a central role in anabolic metabolism. The carbon skeleton of its molecular structure can serve as a precursor, directly contributing to the synthesis of FAs and other nonessential amino acids. Simultaneously, the nitrogen atoms provided by the amino group in its side chain are directly involved in the synthesis of purine and pyrimidine nucleotides, thereby fulfilling the demands of nucleic acid biosynthesis [127, 128]. Exogenous glutamine is transported into cells by various glutamine transporters (SLC1A5, SLC38A1 and SLC38A2) on the plasma membrane to participate in the synthesis of nucleotides and nonessential amino acids in the cytoplasm [129]. Glutamine taken up by cancer cells undergoes a critical branching of its metabolic pathway within the cytoplasm. One portion is directly utilized for the synthesis of hexosamines, nucleotides, and various non-essential amino acids. The other portion is deaminated by glutaminase (GLS) in the cytoplasm to produce glutamate. This resulting glutamate can then be transported into the mitochondria, where it participates in the TCA cycle or other biosynthetic reactions [130]. The metabolizing enzyme GLS, which initiates the first step in glutamine catabolism, is overexpressed in a variety of cancers and is regulated by multiple oncogenic signaling pathways [131]. For example, sirtuin 5 (SIRT5), a mitochondrial NAD+-dependent lysine deacetylase, stabilizes GLS by desuccinylating lysine residue K164 and thus mediates the smooth progression of glutamine metabolism in breast cancer [132]. In colorectal cancer, tumor cells upregulate the expression of SLC1A3 and GLS by modulating the YTH N6-methyladenosine RNA binding protein 1 (YTHDF1)-GID complex subunit 8 homolog (GID8) signaling pathway, thereby increasing glutamine uptake and catabolism and ultimately supporting sustained tumor proliferation and survival [133]. The glutamate produced during the glutamine metabolism is further converted into α-ketoglutarate (α-KG) through glutamate dehydrogenase 1 (GLUD1), transaminases such as glutamate-oxaloacetate transaminase (GOT), glutamate-pyruvate transaminase (GPT), and phosphoserine transaminase (PSAT) and subsequently participates in the TCA cycle. Citrate produced in the cycle is exported to the cytoplasm and cleaved into acetyl-CoA and oxaloacetate, supplying essential precursors for the synthesis of lipids, amino acids, and other substances. This metabolic model provides cancer cells with high-throughput TCA cycle flux and metabolites, a level that cannot be achieved solely through glucose metabolism [134]. Particularly under hypoxic conditions or mitochondrial dysfunction, the level of α-KGDH-catalyzed α-KG production of succinate is reduced in cancer cells (standard TCA cycle reaction). These changes in substrate levels drive the isocitrate dehydrogenase (IDH)-mediated reductive carboxylation of α-KG to produce isocitrate and citrate, which are then transported out of the mitochondria to participate in the synthesis of biomolecules such as lipids and amino acids [135]. In addition to α-KG, glutamine can also be converted into alanine, aspartate, and serine, with serine serving as a precursor for glycine synthesis [136]. Notably, in pancreatic cancer cells, upregulated uncoupling protein 2 (UCP2) facilitates the transport of aspartate, which is produced from glutamine catabolism, from the mitochondria to the cytoplasm for NADPH generation. Silencing UCP2 significantly inhibits cancer cell proliferation, highlighting UCP2 as a potential therapeutic target [137]. These findings demonstrate that glutamine metabolism provides critical biosynthetic precursors and energy support for the rapid proliferation of cancer cells. Moreover, under glucose-limited conditions, it exhibits remarkable metabolic adaptability by replenishing the TCA cycle and supplying substrates for amino acid synthesis, effectively compensating for the metabolic deficiencies caused by insufficient glucose availability. The highly synergistic and complementary dynamic network formed between glutamine metabolism and glucose metabolism collectively maintains the metabolic homeostasis of cancer cells.

Regulation of carcinogenic factors

Glutamine is among the most highly consumed amino acids in cancer cells. Its extensive uptake and metabolism serve as a metabolic foundation for the rapid proliferation of tumor cells and the synthesis of macromolecules. This process is directly regulated by multiple key oncogenic signaling pathways [138]. For instance, c-Myc, as a proto-oncogene, increases glutamine uptake and its conversion to glutamate in prostate cancer and lymphoma cells by upregulating the expression of SLC1A5 and GLS, thereby promoting glutamine catabolism [139]. Furthermore, in a c-Myc+/− hepatocellular carcinoma cell model, SLC1A5 mRNA expression levels were significantly reduced by approximately 20–30%, accompanied by an approximately 40% decrease in glutamine uptake. These findings suggest that c-Myc may influence the metabolic dependence of hepatocellular carcinoma cells on glutamine by regulating SLC1A5 expression [140]. Additionally, c-Myc can transcriptionally upregulate the expression of the cystine/glutamate antiporter SLC7A11, facilitating the export of intracellular glutamate from the cell while promoting the uptake of extracellular cystine. The imported cystine is rapidly reduced to cysteine within the cell, which serves as a key substrate for synthesizing the antioxidant glutathione [141]. GLUD1 is a critical enzyme in glutamate catabolism and is overexpressed in various cancer cells, promoting cancer cell proliferation, metastasis, and drug resistance. Mechanistically, multiple oncogenic signals, such as Myc and mTORC1, are involved in the activation of GLUD1, which is often accompanied by increased expression of other glutamine metabolism enzymes, such as GLS [142–144]. Moreover, the activation of mTORC1 signaling plays a role in glutamine metabolism in pancreatic cancer cells by stabilizing glutamine synthetase (GS) and preventing its ubiquitination and proteasomal degradation, thereby regulating glutamine synthesis under nutrient-limited conditions [145].

Moreover, the activation of the oncogene Kras enhances the addiction of cancer cells to glutamine. In particular, in colorectal cancer, Kras drives the catabolism of glutamine into glutamate and increases its mitochondrial import by upregulating key genes involved in glutamine metabolism, such as GLS and the mitochondrial glutamate transporter SLC25A22. SLC25A22 is also considered a potential target for overcoming the immunosuppressive microenvironment in Kras-mutant colorectal cancer [146, 147]. However, in pancreatic cancer cell lines, the atypical glutamine metabolism mediated by the oncogene Kras relies on the activity of GOT. Glutamine-derived aspartate is converted to oxaloacetate by GOT, which subsequently undergoes oxidative decarboxylation to produce pyruvate. This process increases the NADPH/NADP ratio, thereby maintaining the redox balance and promoting tumor cell resistance to platinum-based drugs [148, 149]. Additionally, Mutations in the tumor suppressor gene TP53 are prevalent in the majority of cancers. Its functional loss leads to a reprogramming of the metabolic network, promoting an abnormal increase in the metabolic flux from α-KG to succinate. The resulting decrease in the α-KG/succinate ratio inhibits the activity of α-KG-dependent dioxygenases, leading to a reduction in 5-hydroxymethylcytosine (5hmC) level, epigenetic dysregulation, and ultimately driving tumor cell dedifferentiation and enhanced adaptability [150]. Furthermore, the HIF-1α gene plays a critical role in glutamine metabolism in tumors by stimulating the expression of SLC7A11, promoting the exchange of glutamine and cystine, increasing glutathione levels within tumor cells, and preventing the accumulation of ROS [151]. Collectively, the existing evidence indicates that multiple oncogenic signaling pathways, such as c-Myc, Kras, and HIF-1, directly regulate key processes in glutamine metabolism, thereby driving the tumor dependence on glutamine. Therefore, targeting specific metabolic nodes driven by oncogenes has become a forefront in translational cancer research, with its core strategy focusing on precise intervention against the metabolic vulnerabilities determined by tumor genotypes. As the efficacy of single-agent metabolic inhibitors is often limited by metabolic plasticity, developing rational combination therapies based on the coordinated targeting of oncogenic signaling and its downstream metabolic dependencies holds promise for systematically overcoming resistance and achieving more durable therapeutic benefits in tumors with specific genetic backgrounds.

Noncanonical pathways of glutamine metabolism and signal transduction

In tumor metabolism, glutamine is utilized primarily by canonical and noncanonical pathways [152]. The canonical glutamine metabolic pathway is involved mainly in the TCA cycle, providing energy and biosynthetic precursors for cancer cells. It serves as the “main route” for glutamine metabolism in most tumors, with key regulatory enzymes including GLS and GLUD1 [153]. However, under conditions such as hypoxia, mitochondrial dysfunction, or Kras-activated tumors, cancer cells employ GOT2 to metabolize glutamate into aspartate and α-KG. Mitochondrial aspartate is subsequently transported to the cytoplasm, where it is metabolized by GOT1 into oxaloacetate. The latter is reduced to malate by malate dehydrogenase (MDH), followed by oxidative decarboxylation catalyzed by malic enzyme 1 (ME1), generating pyruvate, CO₂, and NADPH. This process constitutes the noncanonical glutamine metabolic pathway, which supports macromolecule synthesis and maintains redox homeostasis [154].

Studies have shown that in pancreatic cancer, Kras gene knockout or the use of the selective monoamine receptor antagonist ziprasidone can directly target and inhibit GOT1 expression, thereby disrupting glutamine metabolism and affecting NADPH generation. This process leads to elevated levels of ROS and disrupts the redox balance [155, 156]. Furthermore, the inhibition of GOT1 increases the sensitivity of cancer cells to 5-fluorouracil and doxorubicin, which is associated with GOT1-induced NADPH production [157, 158]. Moreover, in colorectal cancer cells, GOT2 expression is activated by the HIF-1α-SOX12 signaling axis, promoting asparagine biosynthesis. The inhibition of this signaling axis reduces cancer cell proliferation [159]. Through catalysis mediated by GOT2, glutamine is converted into aspartate, which is subsequently utilized by asparagine synthetase to generate asparagine [160]. Notably, when glutamine is depleted, asparagine increases the activity of GS, thereby increasing glutamine levels again [161]. Additionally, aspartate produced by cancer cells participates in the activation and proliferation of CD8 + T cells. An insufficient aspartate supply leads to mitochondrial metabolic dysfunction, inhibition of mTOR signaling, and reduced expression of cytotoxic molecules such as granzyme B (GZMB) and IFN-γ, ultimately impairing T-cell cytotoxicity. These findings highlight the potential value of targeting GOT2 for alleviating cancer-induced immunosuppression [162]. Based on these findings, cancer cells dynamically regulate the flux between the two pathways according to their genetic background (e.g., Kras status) and microenvironmental conditions (e.g., oxygen levels and nutrient availability) to maximize survival advantages. Therefore, simultaneously targeting both pathways or combining these strategies with other therapies represents an effective approach to overcoming resistance driven by metabolic plasticity.

Cross-regulation between redox homeostasis and the TME

Glutamine, a key node in cellular metabolism, is being increasingly recognized for its multifunctional roles in maintaining redox homeostasis and supporting biosynthesis. In addition to contributing to reducing power through the generation of NADPH via noncanonical pathway, glutamine-derived glutamate is also a critical metabolite involved in glutathione synthesis [163]. It is exchanged with extracellular oxidized cystine via the cystine/glutamate antiporter. The imported cystine is rapidly reduced to cysteine, which then combines with glutamate derived from the metabolic flux of glutamine and glycine. Through catalysis mediated of glutamate cysteine ligase (GCL) and glutathione synthetase (GSS), these components are synthesized into glutathione. An adequate glutathione pool not only maintains the intracellular redox balance but also provides essential reducing power for cancer cells, supporting their sustained biosynthetic demands and proliferative activity [164]. Furthermore, glutathione increases cancer cell resistance to chemotherapeutic agents such as cisplatin, a process associated with the regulation of IDH2/HIF-1α signaling [165]. Moreover, the competitive consumption of glutamine by tumor cells, along with the release of its metabolites, profoundly influences immune cells and stromal cells within the TME. Specifically, through the high expression of glutamine transporters and key metabolic enzymes, tumor cells preferentially take up and utilize glutamine from the microenvironment, thereby establishing metabolic competition with immune cells such as T cells and NK cells. This competition results in impaired glutathione synthesis and increased accumulation of ROS in immune cells, ultimately leading to their functional suppression and diminished immune responsiveness [166]. Additionally, glutamine deprivation promotes the migration and invasion of CAFs, thereby driving tumor epithelial cells toward nutrient-rich areas. This glutamine-driven invasion of CAFs can be blocked by modulating TRAF6- and p62-dependent glutamine activity [167]. Furthermore, α-KG, a derivative of glutamine metabolism, binds to oxoglutarate receptor 1 (OXGR1) on macrophages, triggering MAPK signaling and suppressing MHC-II antigen presentation, thereby promoting immune evasion and tumor progression [168]. In summary, this metabolic pattern reveals how tumor cells leverage metabolic reprogramming to convert their survival advantages into dominance over the microenvironment. A deeper understanding of this cross-regulatory network is crucial for developing combination therapies that simultaneously target tumor cells and activate antitumor immunity.

Other amino acid metabolic pathways and signal transduction

In addition to glutamine metabolism, metabolic changes in other amino acids, such as nonessential amino acids glycine and serine and the essential amino acids leucine and arginine, are also involved in cancer progression [169]. A study has shown that serine, whether derived from external sources or produced as an intermediate in glucose metabolism, can serve as a substrate for conversion into glycine by SHMT. This process provides one-carbon units for the synthesis of nucleotides, proteins, and lipids [170]. However, when serine is available, neither restricting exogenous glycine intake nor depleting the endogenous glycine cleavage system can inhibit the proliferation of cancer cells, indicating that nucleotide synthesis and cancer cell growth are supported by serine rather than glycine consumption [171]. In a hypoxic environment, c-Myc-mediated transcriptional upregulation of serine synthesis-related metabolic enzymes promotes serine biosynthesis and cancer cell growth [172]. Moreover, the p53 analog p73 can also promote serine synthesis to combat nutritional stress during cancer progression by increasing GLS2 expression [173]. Proline metabolism can maintain cellular redox homeostasis and is closely related to cancer aggressiveness. Studies have shown that ORAOV1 increases the intracellular proline concentration and subsequently reduces ROS production by binding to pyrrolin-5-carboxylate reductase (PYCR) in esophageal squamous cell cancer (ESCC), thereby increasing tumorigenicity and tumor growth [174]. Moreover, under nutrient-deprived conditions, pancreatic cancer cells can utilize multiple pathways, including macropinocytosis, to take up collagen I and IV proteins. Proline derived from these collagens is converted into glutamate and α-KG by proline oxidase (PRODH1), which helps maintain the TCA cycle and provides precursors for biosynthesis [175]. Changes in amino acids metabolism and related signaling pathways in cancer are shown in Fig. 2.

Fig. 2.

Changes in glutamine metabolism and related signaling pathways in cancer. Exogenous glutamine can enter cancer cells through various transporter proteins (SLC1A5, SLC38A1, and SLC38A2). Through the actions of metabolic enzymes such as GLS and GLUD1, glutamine is converted into α-KG, which subsequently participates in the TCA cycle. On the one hand, the catabolic metabolism of glutamine in mitochondria results in the production of α-KG, which enters the TCA cycle and subsequently provides raw materials for the synthesis of fatty acids and amino acids; on the other hand, glutamate can be converted to serine, which can then be catalyzed by SHMT to produce glycine, which participates in GSH synthesis. In addition, glutamate produced by glutamate metabolism can be exchanged with extracellular cysteine via the xCT system, promoting GSH synthesis and defending against oxidative stress. SLC1A5, solute carrier family 1 member 5; GLS, glutaminase; GLUD1, glutamate dehydrogenase 1; IDH, isocitrate dehydrogenase; GOT2, glutamic-oxaloacetic transaminase 2; mTOR, mammalian target of rapamycin; SHMT, serine hydroxymethyltransferase; GSH, glutathione; PSAT, phosphoserine aminotransferase; GPT, glutamate pyruvate transaminase; PYCR, pyrroline-5-carpoxylate reductase; PRODH1, proline dehydrogenase 1; GSS, glutathione synthetase; GCL, glutamate cysteine ligase

Cancer treatment strategies targeting glutamine metabolism

Numerous cancers, including lung and prostate cancer, depend on a considerable supply of exogenous glutamine to maintain their metabolic requirements. Since glutamine transporters are pivotal for nutrient acquisition from glutamine, the development of inhibitors targeting these proteins markedly influence disease progression. SLC1A5 (ASCT2), a sodium-dependent neutral amino acid transporter protein belonging to the SLC1 family, has emerged as a new anticancer target because of its high affinity for glutamine. Studies have shown that the inhibition of glutamine uptake by blocking ASCT2 with L-γ-glutamyl-p-nitroanilide (GPNA) significantly enhanced the inhibitory effect of cetuximab on gastric cancer proliferation in vitro and in vivo, and targeting ASCT2 to inhibit glutamine uptake may be a promising strategy to improve the inhibitory effect of cetuximab on advanced gastric cancer [176]. The inhibitory effect of GPNA on ASCT2 plays a certain role in the treatment of lung [177], pancreatic [178], and breast [179] cancers. Compared with that of GPNA, the inhibitory effect of V-9302 against ASCT2 was greater. V-9302, a competitive small-molecule antagonist of transmembrane glutamine flux, leads to reduced cancer cell growth and proliferation, increased cell death, and increased oxidative stress through the pharmacological blockade of ASCT2, and these activities together promote antitumor responses in vitro and in vivo [180]. Moreover, specific antibodies targeting ASCT2 (KM4008, KM4012, and KM4018) have been shown to inhibit glutamine-dependent growth of gastric and colorectal cancer cells, confirming their anticancer efficacy and showing promise for advancement into clinical trials [181]. Other types of glutamine transporters such as SLC38A1 and SLC38A2-related inhibitors, are being developed because SLC38A1 and SLC38A2 replace the function of ASCT2 in some cancer types, especially in ASCT2 (-/-) cancers [182]. The deamination of glutamine to glutamate, catalyzed by GLS, serves as the first and rate-limiting step in glutamine catabolism, making it an attractive anticancer target. GLS1 functions as the primary isoform under most conditions, while GLS2 can be induced under specific contexts such as p53 activation, partially compensating for GLS1 activity and thereby adding complexity to its therapeutic targeting [183]. Currently, research on inhibitors targeting GLS1 is more advanced, with BPTES and CB-839 serving as representative small-molecule compounds in this field. Notably, in BRAF-mutant thyroid cancer, knocking down STAG2 expression significantly increases the antitumor efficacy of BPTES, providing compelling evidence for the potential of combination therapy strategies [184]. Another specific GLS1 inhibitor, CB-839, has not shown adverse effects in preclinical studies. However, CD-839 does not exert significant antitumor effects on pancreatic cancer cells, suggesting that monotherapy led to metabolic adaptation in cancer cells [185]. Therefore, a series of clinical trials of combination therapies are under way, including cabozantinib in combination with CB-839 for advanced renal cell carcinoma (NCT03428217); palbociclib combined with CB-839 for Kras-driven pancreatic cancer, NSCLC, and colorectal cancer (NCT03965845); CB-839 in combination with chemotherapy (carboplatin and pemetrexed) for NSCLC (NCT04265534); and nivolumab in combination with CB-839 for melanoma (NCT02771626). The pro-cancer effect of GLUD1 on various cancers suggests that it is also a potential target for cancer therapy. GLUD1-targeted inhibitors, including the purine analogs R162 and epigallocatechin gallate (EGCG) exert potent anticancer effects on cancers such as colorectal cancer, lung cancer, and gliomas. The application of R162 significantly improved the antitumor efficacy of docetaxel in NSCLC [142]. These studies suggest that targeting glutamine metabolism alone does not significantly benefit cancer patients and that combinations with other regimens are a potential strategy for the treatment of cancer. The development of inhibitors targeting key enzymes involved in glutamine metabolism and related mechanisms of action are summarized in Table 2.

Table 2.

Summary of studies on the development of inhibitors targeting key enzymes involved in glutamine metabolism and related mechanisms of action

Target key enzymes of metabolism	Inhibitors	Type of study	In vivo/ in vitro	Mechanism of Action	References
ASCT2	gamma-L-Glutamyl-p-Nitroanilide (GPNA)	Preclinical	In vitro	Inhibits the uptake of glutamine by lung cancer cells	[177]
	V-9302	Preclinical	Both	Inhibits glutamine transport and leucine uptake	[180]
	KM4008, KM4012, and KM4018	Preclinical	Both	Inhibits glutamine transport	[181]
GLS1	BPTES	Preclinical	Both	Inhibits glutamine metabolism	[184]
	CB-839 (NCT03428217)	Phase II	-	Inhibits glutamate production	[186]
	JHU-083	Preclinical	Both	Inhibits glutamine metabolism	[187]
	IPN60090 (NCT05039801)	Phase I	-	Inhibits glutamine metabolism	[188]
GLUD1	R162	Preclinical	Both	Inhibits α-KG production and ROS accumulation	[142]
	EGCG	Preclinical	In vitro	Binding to ADP activation site inhibits GLUD1 activity	[189]
GOT1	Adapalene	Preclinical	In vitro	Inhibits GOT1 activity and ovarian cancer growth	[190]
	Aspulvinone O	Preclinical	Both	Inhibits glutamine metabolism and pancreatic cancer growth	[191]
	iGOT1-01	Preclinical	In vitro	Inhibits GOT1 activity	[192]

Abbreviations: ASCT2 Alanine-serine-cysteine transporter 2, GLS1 Glutaminase 1. GLUD1 Glutamate dehydrogenase 1, EGCG Epigallocatechin gallate, α-KG α-ketoglutarate, ROS Reactive oxygen species, GOT1 Glutamic oxaloacetic transaminase 1

Lipid metabolism in cancer

Overview of lipid metabolism in cancer

Compared with that in normal cells, metabolic reprogramming in cancer cells is evident not only through the activity of classic pathways such as glucose and glutamine metabolism but also through the systematic reprogramming of lipid metabolism. This multidimensional and adaptive metabolic remodeling spans various stages, including de novo lipid synthesis, exogenous uptake, storage, and catabolism, collectively supporting the sustained energy and biosynthetic demands of cancer cells during rapid proliferation, survival, invasion, and distant metastasis [193]. Under the often hypoxic and nutrient-deprived conditions of the TME, lipid metabolic reprogramming provides cancer cells with critical metabolic flexibility. For instance, cancer cells increase exogenous lipid uptake by upregulating the expression of the FA transporter CD36 while relying on the increased expression of enzymes such as fatty acid synthase (FASN) to drive endogenous FA de novo synthesis, thereby maintaining lipid homeostasis. This abnormal activation of lipid metabolism not only supports membrane biogenesis and signaling molecule synthesis but is also closely linked to the malignant biological behaviors of tumors, including accelerated proliferation, an enhanced metastatic capacity, and the development of therapeutic resistance, thereby profoundly influencing tumor progression and the patient prognosis [194, 195]. The following sections delve into various dimensions, such as lipid uptake and synthesis, to systematically elucidate the mechanisms and roles of changes in lipid metabolism in tumor development.

Cholesterol metabolism and LDLR

The acquisition of exogenous lipids is important for the synthesis of cholesterol and FAs, where cholesterol maintains the integrity and fluidity of the cell membrane and affects the composition of membrane microstructures [196]. Tumor cells often reshape cholesterol metabolism by adjusting cholesterol uptake, synthesis, transport, transformation, and efflux to meet the demands for energy and substances required for rapid growth [197]. As a single transmembrane receptor, the low-density lipoprotein receptor (LDLR) plays an important role in maintaining the homeostasis of intracellular cholesterol metabolism, in which exogenous cholesterol is internalized into the low-density lipoprotein (LDL) and taken up by the cell after binding to the LDLR on the cytosolic membrane [198]. Previously, LDLR was thought to be a major source of risk for cardiovascular diseases such as atherosclerosis, but recent studies have shown that LDLR is involved in cancer signaling and malignant progression, including that of colorectal, prostate, lung, and breast cancers [199]. Guillaumond et al. demonstrated that LDLR is overexpressed at all stages of pancreatic cancer progression and is strongly associated with an increased risk of cancer recurrence. The blockade of LDLR decreases the proliferation and colony formation potential of pancreatic cancer cells and reduces the activation of the ERK1/2 survival pathway. In addition, LDLR silencing sensitizes cancer cells to chemotherapeutic agents and enhances chemotherapy-promoted tumor regression [200]. Moreover, LDLR promotes the proliferation and invasion of renal cell carcinoma cells by activating the EGFR signaling pathway [201]. In glioblastoma, LDLR relies on EGFRvIII mediated activation of PI3K-SREBP-1 signaling to promote tumor survival [202]. These studies suggest that the regulation of cholesterol metabolism by targeting LDLR will become a novel adjuvant strategy for the treatment of some cancers.

De Novo FA synthesis and molecular regulation

Unlike normal cells, cancer cells initiate and sustain de novo FA synthesis even in the presence of exogenous lipids, to meet the demands for membrane biogenesis, energy storage, and signal transduction required for their rapid proliferation [203]. Acetyl-CoA is a limiting factor in lipid synthesis because it is a key substrate for FA and cholesterol synthesis. In addition to the oxidative decarboxylation of glycolytic pyruvate in mitochondria, acetyl-CoA can be obtained by β-oxidation of FAs, catabolism of branched-chain amino acids (leucine and isoleucine) and oxidative decomposition of ketone bodies [204, 205]. In addition, under conditions of hypoxia or nutrient deficiency, cancer cells can also use acetyl-CoA synthetase (ACSS) to obtain acetate, even when it results in the loss of a molecule of ATP. Three subtypes of ACSS have been identified, of which ACSS1 and ACSS3 are located mainly in the mitochondria, while ACSS2 is found mainly in the cytoplasm and nucleus of most cancer cells. The inhibition of ACSS2 significantly inhibits tumor formation and growth, highlighting the critical role of acetate in lipid synthesis and utilization in cancer [206]. In pancreatic cancer, the ACSS2-mediated Zrt- and Irt-like protein 4 (ZIP4) signaling pathway reshapes metabolic activity by increasing the macropinocytosis of cancer cells and is positively associated with a poor prognosis [207]. Increased levels of O-GlcNAc transferase (OGT) in glioblastoma promote ACSS2 Ser-267 phosphorylation and subsequent acetyl-CoA production by regulating cyclin-dependent kinase 5 (CDK5), and targeting the OGT/CDK5/ACSS2 pathway may be an approach to modify the metabolic dependence of brain tumors [208].

In the presence of acetyl-CoA carboxylase (ACC), cytoplasmic acetyl-CoA is carboxylated to malonyl coenzyme A, which is further converted to FA by FASN, and both of these key enzymes are transcriptionally regulated by sterol regulatory element binding proteins 1 and 2 (SREBP1/2) [209]. ACC1 is highly expressed in a variety of cancers, including NSCLC and prostate cancer [210, 211]. In colorectal cancer, circCAPRIN1 interacts with STAT2 to promote colorectal tumor progression and lipid synthesis by increasing ACC1 expression [212]. However, studies have shown that in breast cancer, ACC1 expression is decreased, whereas ACC1 phosphorylation levels are increased. This process is mediated by leptin and TGFβ signaling-related TGFβ-activated kinase (TAK) 1, which subsequently promotes the production of acetyl-CoA and increases the acetylation level of the Smad2 transcription factor, ultimately inducing breast cancer metastasis and epithelial-mesenchymal transition (EMT). Furthermore, ACC1 deficiency exacerbates tumor recurrence following primary tumor resection in mice [213]. Collectively, these findings demonstrate that alterations in ACC1 expression levels and activity states, such as phosphorylation, serve as critical regulatory nodes in modulating lipid metabolic programs and influencing malignant behaviors across different tumor types. Moreover, FASN is closely associated with tumor recurrence and poor prognosis across multiple cancer types. Inhibition of FASN not only reduces FA synthesis but also leads to the accumulation of malonyl-CoA, which in turn suppresses fatty acid oxidation (FAO). This dual metabolic disruption ultimately induces cell cycle arrest and apoptosis in tumors [214]. A large amount of preclinical evidence has shown that lipid metabolism is active in pancreatic tumors induced by Kras, which is often manifests as the upregulation of FASN expression, subsequently enhancing de novo FA synthesis and energy metabolism and reducing lipid peroxidation levels by removing unsaturated FAs to promote self-progression [215, 216]. An in-depth exploration revealed that FASN is regulated by the expression of phospholipase A2 group IIA (PLA2G2A). The inhibition of PLA2G2A by an siRNA or the pharmacological action of tanshinone I led to decreased FASN expression, which was accompanied by reduced lipid synthesis and impaired mitochondrial oxidative phosphorylation, providing a potential targeted therapeutic strategy for eliminating Kras-driven pancreatic cancer cells [217]. Bian et al. identified the upregulation of FASN induced by EGFR/ERK signaling as important for proliferation and the reversal of apoptosis in pancreatic cancer [218]. Studies have shown that cancer patients with high expression of FASN have a poor prognosis and shorter overall survival, and high FASN expression is strongly associated with a poor chemotherapy response and immunosuppression [219, 220]. Unlike the de novo synthesis of FA, FA transport is more prominent in animal models in vivo, especially the uptake and transport of long-chain FA, which partially explains the insignificant anticancer effect of FASN inhibitors in vivo [221]. The combination of FA transporter protein inhibitors with FASN inhibitors may be an effective strategy to modulate lipid metabolism in pancreatic cancer.

Exogenous lipid intake

In addition to de novo lipid synthesis, cancer cells also utilize exogenous lipids to meet their bioenergetic and biosynthetic demands for malignant proliferation, depending on tumor tissue heterogeneity, microenvironmental signals, and nutrient availability [222]. The uptake of exogenous lipids involves the participation of various transport molecules, including CD36, the fatty acid transport protein family (FATP/SLC27), and fatty acid-binding proteins (FABPs) [223]. These molecules have been shown to be closely associated with cancer development and a poor prognosis. Among these proteins, CD36 has garnered significant attention in cancer research. As a transmembrane protein belonging to scavenger receptor class B, CD36 recognizes multiple ligands, including lipid-related ligands (such as long-chain FAs) and protein-related ligands (such as thrombospondin and collagen types I and IV) [224]. Specifically, in HER2 + breast cancer cells, increased CD36 expression promotes FA uptake to compensate for the reduced FA synthesis caused by HER2 inhibition and enhances cancer cell resistance to lapatinib [225]. Additionally, CD36 reprograms FA metabolism by increasing FA uptake while inhibiting FAO through AMPK-dependent signaling, thereby maintaining stemness characteristics in liver cancer [226]. Furthermore, high CD36 expression accelerates lipid accumulation in gastric, colorectal, and prostate cancers [227]. This metabolic compensation becomes particularly evident when FASN is inhibited, suggesting that the combined inhibition of FASN and CD36 exerts a synergistic effect on suppressing cancer cell proliferation [228]. FABPs, as critical regulators of lipid metabolism, facilitate lipid uptake and transport by binding to lipids to increase their solubility. Specifically, FABP5 promotes lipolysis and FA synthesis, leading to increased FA levels in cervical cancer cells. FA subsequently activates the NF-κB signaling pathway, promoting lymph node metastasis, which can be regulated by miR-144-3p under hypoxic conditions [229]. However, in the TME, endoplasmic reticulum stress induces the downregulation of transgelin 2 (TAGLN2)-FABP5 signaling, which inhibits FA uptake by T cells and consequently leads to T-cell dysfunction. The overexpression of TAGLN2 in T cells significantly increases their antitumor capacity [230]. Additionally, FABP4 is upregulated in various cancers, such as breast and ovarian cancer, confirming its potential as a novel biomarker [231]. These findings highlight the flexible coordination between exogenous lipid uptake and endogenous lipid synthesis, profoundly reflecting the metabolic adaptability of cancer cells to maintain survival and progress in response to microenvironmental challenges. Understanding the regulatory networks underlying these metabolic patterns and the specific metabolic preferences of individual tumors is important for developing precise metabolic therapies and designing effective combination treatment strategies. Changes in lipid metabolism and related signaling pathways in cancer are shown in Fig. 3.

Fig. 3.

Changes in lipid metabolism and related signaling pathways in cancer. Lipid metabolism in cancer includes the uptake and conversion of FAs and cholesterol. FA transporters are overexpressed in cancer. FAs that are consumed in large quantities undergo FAO by the key enzymes ACSLs and CPT1/2, providing a large amount of nutrients for the invasion, proliferation and chemotherapy resistance of cancer cells. Endogenous acetate and acetyl-CoA can also be converted to fatty acids under different conditions. Cholesterol metabolism mainly involves endogenous lipid synthesis, exogenous lipid uptake, exocytosis, and esterification, ultimately providing steroids and bile acids for cancer cell metabolism. FAs, fatty acids; FAO, fatty acid oxidation; ACSLs, acyl-CoA synthetase long-chains; CTP1/2, carnitine palmitoyltransferase 1/2; ACSS2, acyl-CoA synthetase short chain family member 2; ACC, acetyl-CoA carboxylase; FASN, fatty acid synthase; SCD, stearoyl-CoA desaturase; STARD, StAR related lipid transfer domain; HMGCR, HMG-CoA reductase; SQLE, squalene epoxidase; ACAT1/2, acetyl-CoA acetyltransferase 1/2

Cancer therapeutic strategies targeting lipid metabolism

Cancer cells accelerate lipid metabolism to meet the energy requirements for malignant progression. Therefore, large numbers of preclinical studies and clinical trials targeting lipid metabolism are being conducted. LDLR is a key metabolic enzyme through which cancer cells take up cholesterol, and the development of LDLR inhibitors has become important for the restriction of lipid metabolism in cancer. Amlotinib, a multitargeted tyrosine kinase inhibitor (TKI), is a member of a therapeutic class of drugs for advanced lung cancer that reduces cholesterol uptake by inhibiting LDLR expression and the AMPK/mTOR pathway. However, increased cholesterol synthesis in cancer cells reduces the efficacy of amlotinib, suggesting that the inhibition of cholesterol uptake alone is ineffective at mitigating cancer progression [232]. 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase (HMGCR) is a rate-limiting enzyme in the cholesterol biosynthesis pathway that converts HMG-CoA to mevalonate, which is overexpressed in several cancer types, including colorectal and liver cancer [233, 234]. Given the pivotal role of HMGCR reductase in cancer cell lipid metabolism, drug development targeting this pathway has emerged as a major direction in cancer therapy. For example, statins have a higher affinity for HMGCR, which can competitively inhibit the reduction of HMG-CoA to mevalonate, thereby reducing the amount of cholesterol synthesis. These drugs include mevastatin, pravastatin and simvastatin. Studies have shown that the use of statins improves the overall survival of patients with multiple myeloma [235] and metastatic pancreatic cancer [236]. A meta-analysis of more than 1 million cancer patients revealed that statin use reduced all-cause and cancer-specific mortality by 30% and 40%, respectively [237]. Paradoxically, statins do not significantly improve the overall survival of some patients with cancer and even increase the risk of prostate cancer and melanoma [238, 239]. These different results may vary depending on the type of drug, mode of administration, or duration. Furthermore, cancer cells accelerate the conversion of cholesterol into bile acids and steroids to mitigate the toxic effects caused by cholesterol accumulation. Targeting 3β-hydroxysteroid dehydrogenase type 7 (HSD3B7) with celastrol can disrupt this metabolic pathway, thereby reversing malignant progression and improving patient survival rates. Comprehensively regulating cholesterol-related metabolic networks is crucial for effectively harnessing anticancer effects [240]. ACSS2 depletion inhibits the growth of a variety of cancers and is another potential therapeutic target in lipid metabolism. In particular, during hypoxic stress, the upregulation of ACSS2 expression accelerates the uptake and utilization of acetate by cancer cells for the synthesis of acetyl-CoA. Targeted-ACSS2 inhibitors include AD-5584, AD-8007 [241], and the recently discovered compounds VY-3-249 [242] and VY-3-135 [243]. Compared with VY-3-249, VY-3-135 displays a more favorable profile with superior solubility, stability, and efficacy, demonstrating strong potential for advancement into clinical trials. Furthermore, FAO provides substantial energy for various oxidative tumors, thereby driving tumor progression, stemness, and therapeutic resistance [244]. The use of trimetazidine to target the mitochondrial trifunctional fatty acid oxidation enzyme (MTP) disrupts the physical interaction between MTP and respiratory chain complex I while inhibiting oxidative phosphorylation, thereby inducing a redox imbalance and energy crisis in cancer cells [245]. The development of inhibitors targeting key enzymes involved in lipid metabolism and related mechanisms of action are summarized in Table 3. However, due to the continuous supply of cholesterol and lipid precursors from dietary sources, solely inhibiting endogenous lipid synthesis in tumors often yields limited anticancer efficacy. Therefore, the exploration of more effective therapeutic strategies requires simultaneous intervention in both lipid synthesis and catabolism in cancer. Additionally, given the significant metabolic heterogeneity among different tumor types, a viable future approach is to combine lipid metabolism-targeting strategies with existing conventional therapies (such as chemotherapy and radiotherapy) and emerging treatments such as immunotherapy. These combination regimens with synergistic effects on multiple mechanisms hold as promise as important potential strategies for overcoming tumor resistance and increasing therapeutic efficacy.

Table 3.

Summary of studies on the development of inhibitors targeting key enzymes involved in lipid metabolism and related mechanisms of action

Target key enzymes of metabolism	Inhibitors	Type of study	In vivo/ in vitro	Mechanism of Action	References
LDLR	Anlotinib	Preclinical	Both	Inhibits the uptake of cholesterol by cancer cells	[232]
HMGCR	Statins (NCT00335504; NCT05586360)	Phase II	-	Inhibits cholesterol synthesis. Inhibits angiogenesis and promotes apoptosis	[236]
ACSS2	AD-5584; AD-8007	Preclinical	Both	Inhibits the production of acetyl-CoA and lipid storage	[241]
	MTB-9655	Phase I	-	Inhibits the production of acetyl-CoA	[243]
	VY-3-249; VY-3-135	Preclinical	Both	Inhibits acetate metabolism	[246]
ACCs	TOFA	Preclinical	Both	inhibits the production of malonyl-CoA. Inhibits the proliferation of ovarian cancer cells and induces apoptosis	[247]
	ND-646	Preclinical	Both	Inhibits the synthesis and growth of FAs	[248]
	Soraphen A	Preclinical	In vitro	Reduces FA synthesis and increases FAO in prostate cell lines	[249]
FASN	TVB-3166	Preclinical	In vitro	Induces endoplasmic reticulum stress inhibits the expression of ERα in breast cancer	[250]
	Cerulenin	Preclinical	In vitro	Targeting FASN/APP signals inhibits the aggressiveness and tumorigenicity of cancer stem cells	[251]
	Orlistat	Preclinical	Both	Inhibits lipid synthesis. Promotes lipid peroxidation	[252]
	IPI-9119	Preclinical	Both	Inhibits FA synthesis and induces apoptosis in prostate cancer	[253]
	TVB-2640 (NCT02223247)	Phase I	-	Inhibits lipid metabolism	[254]
	Omeprazole	Preclinical	In vitro	Inhibits the expression of FASN and ACLY to reduce lipid levels	[255]
	Triclosan; C75	Preclinical	In vitro	Inhibits lipid synthesis	[256]
ACLY	BMS-303,141	Preclinical	Both	Inhibits FA and cholesterol synthesis. Activates of p-eIF2α/ATF4/CHOP axis to promote apoptosis of HCC cells	[257]
	SB-204,990; NDI-091143	Preclinical	In vitro	Inhibits lipid synthesis and induces caspase-3 activation and apoptosis	[258]
	Bempedoic acid	Preclinical	Both	Inhibits acetyl-CoA production and CXCR1 transcription	[259]

Abbreviations: LDLR Low density lipoprotein receptor, HMGCR 3-hydroxy-3-methylglutaryl-CoA reductase, ACSS2 Acetyl-CoA synthetase 2, ACC Acetyl CoA carboxylase, FASN Fatty acid synthase, APP Amyloid beta precursor protein, ACLY ATP citrate synthase, eIF2α eukaryotic initiation factor-2α, AFT4 Activating transcription factor 4, CHOP C/EBP homologous protein, HCC Hepatocellular carcinoma, CXCR1 C-X-C motif chemokine receptor 1

Polyamine metabolism in cancer

Overview of polyamine metabolism in cancer

Nucleotide metabolism, represented by DNA metabolism, and epigenetic regulation both depend on one-carbon metabolism to maintain genome integrity, and one-carbon metabolism provides sufficient amount of methyl groups for nucleotide, amino acid, and lipid synthesis, of which methionine cycle-dependent polyamine synthesis is important for cancer cell growth and development [260–262]. Changes in polyamine metabolism constitute prominent metabolic remodeling in cancer. Unlike those in normal cells, the levels of polyamines, such as putrescine, spermidine, and spermine, are increased in many cancers, and these compounds can bind to various negatively charged molecules and participate in tumorigenesis, autophagy, metastasis, and immune escape [263]. High levels of polyamine pools are maintained by increased biosynthesis, transport, and inhibition of catabolism, with the involvement of numerous oncogenes (Myc, Jun, Fos, and Kras) [264]. Studies have shown that various pancreatic cancer cell lines preferentially degrade glutamine to provide nitrogen for polyamine synthesis. This dependency is related to arginine depletion in the TME and is driven by mutant Kras [265]. In addition, activation of the c-Myc pathway is among the major drivers of the dysregulation of polyamine metabolism-related cancers, including ovarian [266], colorectal [267], and bladder [268] cancers. Moreover, the WNT signaling cascade is an important factor that mediates the activation of Myc/ornithine decarboxylase (ODC) signaling [269]. PPAR-gamma co-activator-1 (PGC1)-α is an important regulator of the aggressiveness of prostate cancer cells and can reduce the expression of Myc and ODC, thereby significantly reducing intracellular polyamine levels and metastasis characteristics [270]. Deficiency of 5’-methyladenosine phosphorylase (MTAP), a key enzyme in polyamine metabolism in tumors, can accelerate the accumulation of 5’-deoxy-5’methylthioadenosine (MTA) in the TME, ultimately reducing the maturation of dendritic cells and the activation of T cells. This remodeling of polyamine metabolism exacerbates immunosuppression in tumors [271]. In colorectal cancer, the overexpression of Fos, Jun, and methionine adenosyltransferase 2 (MAT2) accelerates polyamine accumulation, thereby supplying the polyamines required for the sustained proliferation of cancer cells [272].

Polyamine synthesis and molecular regulation

Ornithine derived from the urea cycle is the main raw material for polyamine synthesis, which is partly dependent on the breakdown of arginine. Moreover, elevated serum arginase 1 (ARG1) levels are frequently observed in the serum of cancer patients, and are positively correlated with a poor prognosis [273]. As the first polyamine molecule synthesized de novo in mammals, the formation of putrescine is mediated by ODC, one of the key rate-limiting enzymes for polyamine synthesis, which is regulated by various genes, such as increased levels of ARG1 and ornithine aminotransferase (OAT) and decreased levels of ODC antizyme (OAZ) and spermidine/spermine-N1-acetyltransferase (SAT1) [274]. The expression of ODC is regulated by the transcription factor Myc. In malignant tumors such as neuroblastoma and breast cancer, Myc often leads to excessive tumor proliferation through an ODC-dependent increase in polyamine levels. The Myc-ODC axis provides a promising target for the treatment of Myc-driven cancers, such as neuroblastoma. In a p48Cre/+-LSL-KrasG12D/+ mouse model, the proliferation of tumor cells was accompanied by a significant increase in ODC activity, and difluoromethylornithine (DMFO) treatment resulted in significant decreases in ODC, ARG1, spermine synthase (SMS), and spermidine synthase (SRM) expression and an increase in OAZ expression, which inhibited tumor progression [275, 276]. Moreover, following the injection of pancreatic cancer cells with knockout of OAT and ODC1 (encoding ODC protein) into immunodeficient mice, the resulting tumor volume showed no significant difference compared to that in control mice. This indicates that the observed metabolic alteration operates independently of immune-related mechanisms [277]. Putrescine and decarboxylated S-adenosylmethionine (dcSAM) are catalyzed by SRM to produce spermidine. Furthermore, dcSAM provides a propylamine group for the synthesis of spermine through the action of SMS. Additionally, spermidine can also be generated through the degradation of spermine. SBP-101 (diethyl dihydroxyhomospermine) is a spermine analog that inhibits pancreatic cancer progression by affecting the activity of the polyamine-metabolizing enzyme ODC and depleting intracellular polyamine pools [278]. The interconversion between polyamines depends on the function of key enzymes such as spermine oxidase (SMOX), acetylpolyamine oxidase (PAOX), spermidine/spermine-N1-acetyltransferase (SSAT), SRM, and SMS [279]. Accumulated spermine can be oxidized to spermidine by SMOX, accompanied by the production of 3-acetylaminopropanal and H₂O₂. Additionally, through the action of SSAT, spermine can be used to generate N1-acetylspermine and N1-acetylspermidine, which act as substrates for PAOX and are converted to spermidine and putrescine. The above process often induces the production of a large number of ROS, leading to oxidative stress [280]. SSAT is encoded by the SAT1 gene. Changes in the SSAT content are tightly regulated by polyamine levels and link polyamine metabolism to lipid and glucose metabolism by affecting the acetyl-CoA and ATP contents [281]. In addition, each aminopropylation reaction in the process of producing spermidine from putrescine or spermine from spermidine uses one molecule of S-adenosylmethionine (AdoMet) to generate MTA, and these reactions prevent the production of excessive polyamine levels. MTA is converted by MTAP into adenine and 5-methylthioribose-1-phosphate, an important salvage pathway for maintaining ATP and methionine levels [282]. Many solid tumors and hematological malignancies lack MTAP, and thus inhibitors of purine synthesis and methionine deprivation may be potential therapeutic strategies for MTAP-deficient tumors [283].

Input and efflux of polyamines

In addition to polyamine synthesis and catabolism, the level of the intracellular polyamine pool is equally dependent on the regulation of the polyamine transport system (PTS), which includes the uptake and export of polyamines. However, unlike those in bacteria and unicellular eukaryotes, PTS in mammals has not yet been clearly investigated [284]. At present, only a few proteins, such as ATPase cation transporting 13A2 (ATP13A2) and ATP13A3, have been shown to function in polyamine transport, among which ATP13A2 is considered to be the main transport protein involved in lysosomal polyamine export [285]. In addition, members of the SLC superfamily, the largest family of membrane transporters, including SLC22A4 (OCTN1) and SLC18B1 (VPAT), have been demonstrated to play a key role in the transport of polyamines [286, 287]. Moreover, SLC3A2 affects polyamine uptake in neuroblastoma by reducing spermidine uptake and utilization and thus delaying tumor development in neuroblastoma-prone mice [288]. Furthermore, SLC6A14 is considered among the major transporters involved in arginine transport and is significantly overexpressed in colorectal cancer [289]. Researchers examining polyamine export have not proposed specific molecules or related mechanisms. The most studied and controversial target is SLC3A2, which can mediate the export of spermidine, spermine, and putrescine in colonic epithelial cells, as well as the extracellular release of the polyamine metabolic intermediate N1-acetylspermidine in liver cancer cells [290, 291]. However, in some cancers, such as gliomas [292] and neuroblastomas [293], SLC3A2 is an important transporter for polyamine uptake. The extent to which blocking polyamine transport can suppress cancer cells’ demand for polyamine metabolism remains unknown. Consequently, an in-depth exploration of key targets and mechanisms involved in polyamine transport, synthesis, and degradation processes may provide potential therapeutic approaches to improve the prognosis and management of cancer. Changes in polyamine metabolism and related signaling pathways in cancer are shown in Fig. 4.

Fig. 4.

Changes in polyamine metabolism and related signaling pathways in cancer. The accumulation of polyamines is involved in the proliferation, invasion and metastasis of cancer. Exogenous glutamine and spermidine are taken up by cancer cells and progressively generate putrescine, spermidine and spermine, which are driven by oncogenes such as Myc and Kras. In this process, a large amount of ROS will be produced, leading to oxidative stress. Additionally, cancer cells can induce macrophages to polarize towards the M2 phenotype and inhibit the proliferation and activation of CD8 + T cells by delivering polyamines into the TME. OAT, ornithine aminotransferase; ARG1/2, arginase 1/2; ODC, ornithine decarboxylase 1; PAOX, polyamine oxidase; SPDS, spermidine synthase; SRM, spermidine synthase; SSAT, spermidine/spermine N1-acetyltransferase; SMS, spermine synthase; MTAP, methylthioadenosine phosphorylase; MAT1/2A, methionine adenosyltransferase 1/2A; ROS, reactive oxygen species; PTS, polyamine transport system

Cancer treatment strategies targeting polyamine metabolism

The uptake and utilization of polyamines by cancer cells indicate that targeting polyamine metabolism is a reasonable strategy for cancer therapy. Both the synthetic utilization and the transport of polyamines have been shown to interfere with cancer progression. ODC is a key rate-limiting enzyme in the polyamine synthesis pathway and is upregulated in most cancers. Many in vivo and in vitro studies have shown that ODC is an effective target for inhibiting cancer progression. As an effective, highly specific, and irreversible inhibitor of ODC, DFMO can inhibit tumor growth by promoting the consumption of putrescine and spermidine [294]. DFMO has been shown to exert a cancer-suppressing effect on some solid tumors, such as breast cancer, colon cancer, and melanoma [295, 296]. In a randomized phase III clinical trial in patients with anaplastic glioma, DFMO combined with PCV (procarbazide, lomustine, and vincristine) improved overall survival compared with PCV alone [297]. A phase III study comparing the efficacy and safety of DFMO in combination with lomustine versus lomustine alone in patients with recurrent/progressive anaplastic astrocytoma following radiotherapy and temozolomide chemotherapy is also underway (NCT02796261). However, the consumption of polyamines could not prevent the compensatory increase in polyamine transport; thus, DFMO alone could not achieve a good anticancer effect, and the combination of DFMO with polyamine transport inhibitors may be a more promising treatment strategy. Burns et al. developed a polyamine transport inhibitor, d-Lys(C16acyl)-Spm-(11), which is a lipophilic lysine-spermine conjugate that combined with DFMO, effectively depletes polyamine levels in cancer cells, inhibits tumor growth and reduce the probability of recurrence in tumor-bearing mice [298]. Furthermore, in numerous cancers, including lymphoma, colorectal cancer, pancreatic cancer, and breast cancer, treatment strategies combining DFMO with other polyamine transport inhibitors, such as AMXT 1501 and Trimer PTI, are more effective at inhibiting cancer cell proliferation and enhancing anticancer effects than monotherapy [299–301]. Moreover, inhibiting the interconversion between polyamines is key part of targeting polyamine metabolism. SMOX and PAOX are key enzymes responsible for polyamine breakdown and potential therapeutic targets. In the multiple intestinal neoplasia (Min) mouse model, the enterotoxigenic bacterium Bacteroides fragilis (ETBF) accelerated the formation and development of colon tumors by inducing SMOX upregulation and exacerbating inflammation, resulting in increased ROS levels and DNA damage. The use of the polyamine oxidase inhibitor MDL 72,527 reduced chronic intestinal inflammation and tumorigenicity, confirming the potential value of targeting polyamine metabolism for cancer treatment and prevention [302]. However, in already formed cancer tissues or cells, the application of the SMOX inhibitor JNJ-9350 and the PAOX inhibitor MDL 72,527 prevented ODC1 inhibition and glutamine deprivation inhibited cancer cell growth and induced cell death pathways associated with ROS production [303]. Therefore, targeted treatment or combination therapy for different stages of tumor formation or different metabolic characteristics should be developed in the future. The development of inhibitors targeting key enzymes involved in polyamine metabolism and the related mechanisms of action are summarized in Table 4.

Table 4.

Summary of studies on the development of inhibitors targeting key enzymes involved in polyamine metabolism and the related mechanisms of action

Target key enzymes of metabolism	Inhibitors	Type of study	In vivo/ in vitro	Mechanism of Action	References
ODC	DFMO (NCT02796261)	Phase III	-	Promotes the consumption of putrescine and spermidine and inhibits tumor growth	[297–299]
	SBP-101 (NCT05254171)	Phase II/III	-	Inhibits ODC activity and polyamine synthesis, depletion of polyamine levels	[278]
	N-ω-chloroacetyl-l-ornithine (NCAO)	Preclinical	In vitro	Inhibits ODC activity and tumor proliferation	[304]
	1-amino-oxy-3-aminopropane (APA)	Preclinical	In vitro	Competitively bound to ornithine ODC inhibits the production of putrescine	[305]
	Curcumin	Preclinical	In vitro	Inhibits ODC activity and induces ROS production	[306]
SMOX/ PAOX	MDL 72,527	Preclinical	Both	Reduces chronic intestinal inflammation, proliferation and tumorigenesis	[302]
	C9-4/ C13-4	Preclinical	Both	Inhibits spermidine and putrescine production	[307]
AdoMetDC	SAM486A	Phase II	-	Inhibits polyamine biosynthesis	[308]
	MDL 73,811	Preclinical	In vitro	Inhibits spermidine and spermidine synthesis	[309]
	Methylglyoxal bis-guanylhydrazone (MGBG)	Clinical	-	Inhibits polyamine synthesis and mitochondrial function	[310]
	CGP 48,664	Preclinical	In vitro	inhibits spermine and spermidine production. Increases putrescine levels in cancer cells	[311]
SSAT	Indomethacin	Preclinical	In vitro	Promotes SAT1 transcription and induces polyamine degradation and cycle arrest in cancer cells	[312]
	PG-11,047 (NCT 00705653)	Phase I	-	Improves SSAT activity and promotes polyamine catabolism	[313]
	DENSPM; BESpm	Preclinical	In vitro	Promotes SSAT activity	[314, 315]
Polyamine transporter	AMXT-1501	Preclinical	In vitro	inhibits SLC3A2 activity. Improves the anti-cancer effect of lorlatinib	[293]
	Trimer PT	Preclinical	Both	Improves the inhibition of polyamine synthesis by DFMO and activates anti-tumor immune responses	[301]

Abbreviations: ornithine decarboxylase 1; DFMO Eflornithine, SMOX Spermine oxidase, PAOX Polyamine oxidase, ROS Reactive oxygen species, SSAT Spermidine/spermine-N1-acetyltransferase, SLC3A2 Solute carrier family 3 member 2

Metabolic crosstalk between cancer cells and the TME

Metabolic changes and related signaling pathways in the TME

The microenvironment is the direct ecological niche for tumor growth and development. The relationships between tumors and the microenvironment are often thought of as “seed” and “soil” [316]. This dynamic ecosystem comprises a variety of cells, including immune cells and fibroblasts, each of which exhibit distinct metabolic patterns that collectively shape the metabolic landscape of the tumor [317]. Under stress conditions such as hypoxia and nutrient deprivation, tumor cells remodel their own metabolism to sustain growth. Simultaneously, other cells in the microenvironment undergo adaptive metabolic reprogramming in response [318]. For example, cancer-associated fibroblasts (CAFs) can supply metabolic substrates to tumors through the “reverse Warburg effect”, while regulatory T cells and tumor-associated macrophages (TAMs) assist tumors in evading immune surveillance and promoting invasion and metastasis by competitively consuming nutrients such as glucose and amino acids or secreting immunosuppressive metabolites (e.g., lactate) [319]. This interplay of metabolic cooperation and competition forms a critical foundation for treatment resistance in tumors and explains why most conventional therapies struggle to achieve durable efficacy. Therefore, determining how metabolites regulate tumor progression and the immunosuppressive state of the TME, as well as systematically elucidating the effects of metabolic networks on the functions of various microenvironmental components, is crucial for understanding the regulatory mechanisms in cancer and developing novel combination therapeutic strategies.

Fibroblasts

As the most abundant stromal component in the TME, CAFs form the central hub of the intercellular signaling network, with their functions and phenotypes exhibiting high heterogeneity [320]. CAFs are major regulators of tumor metabolic remodeling and affect cancer cell growth, drug resistance and immune escape through multiple metabolic pathways, such as glucose, amino acid and lipid metabolism [321]. However, the metabolic crosstalk between cancer cells and CAFs is still unclear and needs to be further explored.

Metabolic crosstalk between CAFs and tumor cells is known as the “reverse Warburg effect”; namely, CAFs promote the expression of MCT4 and HIF-1α, followed by increased glycolytic activity and lactate secretion [322]. Excessive uptake of lactate provides cancer cells with metabolic precursors and fuels their growth. Undoubtedly, this process is beneficial for oxidative cancer cells. Compared with normal fibroblasts, CAF-related metabolism significantly changes from oxidative phosphorylation to aerobic glycolysis, which is associated with decreased activity of IDH3α. Specifically, the downregulation of IDH3α suppresses prolyl hydroxylase 2 (PHD2) activity and HIF-1α protein stabilization by reducing the effective level of α-KG. Subsequent HIF-1α accumulation promotes glycolysis by increasing glucose uptake and upregulating the expression of glycolytic enzymes. Concurrently, HIF-1α inhibits oxidative phosphorylation by upregulating NADH dehydrogenase (ubiquinone)-1α subcomplex 4-like 2 (NDUFA4L2) [323]. In the microenvironments of breast cancer and pancreatic cancer, the expression of the key glycolytic enzymes PKM2 and LDHA in CAFs is increased [324, 325]. In addition, stromal caveolin-1 (Cav-1) deficiency is a biomarker of a poor prognosis for patients with breast cancer. The loss of Cav-1 in CAFs results in the overactivation of the TGFβ signaling pathway and subsequently induces oxidative stress and increased autophagy/mitochondrial autophagy and glycolysis [326]. Another important feature of CAF metabolism is increased glutamine synthesis and secretion. In ovarian cancer, CAF-derived glutamine is taken up by cancer cells and converted to glutamate catalyzed by glutaminase to support the TCA cycle [327]. Furthermore, CAF-derived exosomes, which carry acetic acid, lipids, amino acids, or TCA intermediates, are taken up by pancreatic cancer cells via macropinocytosis and are associated with the inhibition of mitochondrial oxidative phosphorylation and increased compensation of glycolysis. Moreover, the inhibition of electron transport chains by exosomes significantly increases the reductive carboxylation of glutamine biosynthesis in cancer cells [328]. Alanine produced by pancreatic stellate cells through autophagy-mediated catabolism of proteins is a substitute carbon source for the TCA cycle of pancreatic cancer, which facilitates the synthesis of nonessential amino acids and lipids in cancer cells. This metabolic pattern reduces the dependence of tumor cells on nutrients such as glucose and glutamine, which are limited in the pancreatic cancer microenvironment [329]. The level of branched-chain amino acids (BCAAs) is associated with an increased risk of cancer. CAFs increase the expression of branched-chain amino acid transaminase 1 (BCAT1) under the influence of cancer cells, and the subsequent increase in the breakdown of BCAAs provides a large amount of the metabolic product branched-chain α-ketoacid (BCKA) for cancer cells to maintain de novo protein synthesis and the TCA cycle [330].

In addition to directly providing metabolites, CAFs regulate tumor metabolism through paracrine cytokine signaling. The deletion of focal adhesion kinase (FAK) in CAFs leads to increased activation of cytokine signaling pathways and the upregulation of the expression of C-C chemokine ligand (CCL)6, CCL11, CCL12 and pentraxin-3, which increase the activity of glycolysis processes in breast and pancreatic cancer cells [331]. In the ovarian cancer microenvironment, tumor cells can activate the TGF-β signaling pathway to induce the secretion of cytokines such as IL-6, IL-8, and CXCL10 by CAFs. These cytokines further promote the phosphorylation of phosphoglucomutase 1 (PGM1), thereby increasing glycogen catabolism in ovarian cancer cells and coordinately activating glycolysis and the PPP, which collectively drive tumor cell proliferation and metastasis [332]. Furthermore, the collagen fragments produced by CAFs can be taken up by pancreatic cancer cells, where they are converted to proline through the action of PRODH1 to support TCA cycle metabolism and cellular respiration [177]. Moreover, in head and neck squamous cell carcinoma, CAFs increase the stromal stiffness of the tumor niche by remodeling the biomechanical properties of the TME. This biomechanical alteration activates the YAP/TAZ‑dependent mechanotransduction pathway, further inducing the upregulation of downstream effector proteins, including GLS1, LDHA, and SLC1A3. Ultimately, this signaling cascade synergistically increases glycolysis and glutamine metabolism in cancer cells and accelerates glutamate‑aspartate exchange within the tumor niche [333].

In summary, the metabolic interaction network between stromal cells and tumor cells is highly intricate. Both the secretion of metabolites and the transmission of signals through different pathways jointly regulate nutrient uptake and metabolic reprogramming in tumor cells. Furthermore, CAFs exhibit distinct metabolic heterogeneity, making in depth multidimensional mechanistic research necessary. Such investigations are crucial not only for understanding tumor cells themselves but also for elucidating their significant effects on the function and fate of neighboring immune cell populations in the TME.

T lymphocytes

As a key mediator of adaptive immunity, the immune function of T lymphocytes is highly regulated by metabolic changes in the microenvironment. Upon stimulation with external antigens, T cells are activated and functionally differentiated in response to environmental information, including the cytotoxic effects of CD8 + T cells and immunosuppressive regulatory T (Treg) cells expressing forkhead box protein 3 (FOXP3) [334]. Determining the response of T cells to antigen stimulation is closely related to tumor immunotherapy. Although immune receptors and signaling factors determine the direction and type of the T-cell responses, cellular metabolism serves as the central regulatory hub for the T-cell survival, proliferation, and function, particularly within the TME. Therefore, targeting the metabolic reprogramming of effector T cells and Treg cells during tumor progression will be a critical strategy for future cancer therapies.

In the TME, the metabolic state of T cells is a critical determinant of the effective execution of antitumor functions. However, factors such as nutrient scarcity and metabolite deprivation disrupt intracellular metabolic and signaling pathways in T cells, ultimately leading to their functional impairment or exhaustion [335, 336]. Unlike resting T cells, activated T cells switch from oxidative phosphorylation to glycolysis and glutamine metabolism, which supplies the necessary energy and biosynthetic precursors for their own proliferation and effector functions. However, the killing effect of T cells on tumors is impaired. On the one hand, metabolically remodeled cancer cells are superior to T cells in terms of the uptake and utilization of glucose and glutamine, and the acidic microenvironment shaped by highly glycolytic cancer cells hinders the activation of T cells [337]. On the other hand, the PHD protein in T cells inhibits the killing effect of T cells on cancer cells by inhibiting HIF-driven glycolysis [338]. High expression of PD-L1 is a distinguishing feature of cancer cells, and high-intensity PD-L1 signaling induces reduced glycolysis, glutamine degradation and free FA metabolism in effector T cells. As shown in the study by Chang et al., anti-PD1 treatment led to the restoration of the glycolytic and cytotoxic functions of T cells to fight established cancer, suggesting that T-cell hyporesponsiveness in the TME may be due to metabolic restriction [339]. Although CD8 + T cells upregulate FA catabolic metabolism to provide energy and maintain their effector function under glucose- and glutamine-restricted conditions, lipid accumulation is detrimental to CD8 + T cells. In lipid-rich microenvironments, CD8 + T cells undergo significant transcriptional reprogramming, including the downregulation of very-long-chain acyl-CoA dehydrogenase (VLCAD), which exacerbates the accumulation of long-chain fatty acids (LCFAs) and very long-chain fatty acids (VLCFAs) that mediate lipid toxicity. Unlike cancer cells, CD4 + T cells or Treg cells, CD8 + T cells are unable to adapt to lipid-rich TMEs by shifting their metabolism from glycolysis to oxidative phosphorylation, and the accumulated lipids produce high levels of oxidative stress that ultimately inhibits cytotoxic functions [340].

As a specific immunosuppressive T-cell subpopulation, Treg cells are highly heterogeneous in terms of their metabolic characteristics. Compared with CD4 + T cells, Treg cells in the microenvironment exhibit more pronounced changes in glycolysis and mitochondrial metabolism, which are essential for self-function, self-tolerance, and immune homeostasis [341]. Unlike effector CD8 + T cells, FOXP3-expressing Treg cells within the TME actively suppress the expression of Myc and reduce glycolytic flux. Concurrently, these cells increase oxidative phosphorylation to sustain their functional activity under low-glucose conditions, a metabolic adaptation strategy that effectively alleviates nutrient competition with cancer cells [342, 343]. Moreover, lactate that accumulates in the microenvironment can also be taken up by Treg cells to increase PD-1 expression. High levels of PD-1 bind to the cancer cell ligand PD-L1 to increase and maintain FOXP3 expression on the surface of Treg cells, thus enhancing its own immunosuppressive function [344]. Furthermore, the proliferation and activation of Treg cells depend on anabolic processes, particularly lipid synthesis, during which key enzymes and transport proteins that coordinate FA metabolism, such as carnitine palmitoyltransferase 1 (CPT1), AMPK, liver kinase B1 (LKB1), and CD36, play indispensable roles [345, 346]. A recent study revealed the regulatory role of amino acid metabolism in Treg cell generation. Indoleamine 2,3-dioxygenase 1 (IDO1), an intracellular enzyme, is involved in the metabolism of the essential amino acid tryptophan in the kynurenine pathway, and IDO1 overexpression promotes the upregulation of PD-1 expression and the infiltration of Tregs [347]. Glutamate derived from glutamine metabolism serves as an essential metabolic substrate for Treg cells to maintain stable expression of their key transcription factor, FOXP3. This effect is specific, as supplementing glutamate alone in Treg cell cultures is sufficient to promote enhanced FOXP3 expression [348, 349]. In addition, essential amino acids including leucine, isoleucine and valine, are necessary for the proliferation of Treg cells [350]. Therefore, targeting T-cell metabolism or disrupting the metabolic balance between cytotoxic T cells and Treg cells may help enhance the antitumor immune response.

Macrophages

Cancer progression is highly dependent on the regulation of the TME. As some of the most abundant immune cells in this milieu, TAMs exert dual protumor and antitumor effects under the influence of multiple signaling stimuli [351, 352]. Decades of research have shown that immune metabolism serves as a determinant of macrophage function, regulating macrophage differentiation, mobilization, and antitumor responses [353]. In cancer, metabolites or signaling molecules in the microenvironment can also directly or indirectly reprogram macrophage metabolism to alter its function [354]. Positive modulation of macrophage metabolic programs profoundly affects cancer progression and tumor-targeted immune responses.

Classically activated (M1-type) and alternatively activated (M2-type) macrophages are often considered two distinct activation states of macrophages, although this division is oversimplified [355]. M1 macrophages are characterized by increased glycolytic activity and produce large amounts of NADPH via the PPP for the maintenance of redox homeostasis, whereas M2 macrophages are metabolically characterized by the TCA cycle and FAO. Moreover, glycolysis is necessary for the secretion of cytokines by M2 macrophages [356]. The metabolic heterogeneity of TAMs profoundly affects the survival, proliferation and invasion of cancer cells. High levels of lactate in the microenvironment directly regulate the polarization of macrophages, and this effect depends on the stable expression of HIF-1α, which induces the production of VEGF and the expression of M2 macrophage markers, including ARG1, found in inflammatory zone 1 (FIZZ1), macrophage galactose-C type lectin (MGL) 1 and MGL2 [357]. In breast cancer, the expression level of the macrophage surface sensor G protein-coupled receptor 132 (GPR132) is closely associated with the patient prognosis. Lactate secreted by cancer cells can bind to GPR132, subsequently activating downstream signaling pathways within macrophages and driving their polarization toward the M2 phenotype. Blocking GPR132 effectively reverses this polarization process [358]. Lactate accumulation also induces the transition of M1-type macrophages to M2-type macrophages through the modification of histone lactylation, which acts as a “lactate timer” [359].

α-KG derived from glutamine metabolism plays a key role in regulating macrophage phenotypic switching. On the one hand, a high α-KG/succinate ratio can inhibit HIF-1α expression and subsequent glycolytic metabolism in M1 macrophages; on the other hand, it promotes FAO in M2 macrophages and drives Jumonji domain-containing protein D3 (JMJD3)-dependent epigenetic reprogramming of M2-related genes. In this process, FAO provides an important energy source for the polarization of M2 macrophages [360]. Moreover, inhibition of GS activity in TAMs induces the polarization of M2-type TAMs toward the M1 type, accompanied by a decrease in glutamine levels and increase of succinic acid and accumulation of HIF-1α. GS gene deletion in tumor-bearing mouse macrophages can promote tumor vascular pruning, vascular normalization, accumulation of cytotoxic T cells and the inhibition of metastasis [361]. Lung cancer cell-derived succinic acid promotes the polarization of TAMs by activating the succinic acid receptor (SUCNR1), which leads to the migration, invasion and metastasis of cancer cells. These effects are mediated by the activation of the PI3K-HIF-1α signaling axis by SUCNR1 [362]. Moreover, the overexpression of IDO1 in tumor cells accelerates tryptophan catabolism, leading to increased production of kynurenine and activation of the aryl hydrocarbon receptor (AHR). This process ultimately drives the polarization of TAMs toward the M2 phenotype and suppresses T-cell responses [363]. Collectively, these studies suggest targeting the unique metabolic profile of M1 and M2 type macrophages. Direct targeting of cancer cell metabolism or targeting specific metabolic patterns to influence TAM phenotypic switching is a feasible approach for inhibiting tumor growth inhibition. The metabolic crosstalk and related signaling pathways between cancer cells and major components of the microenvironment are shown in Fig. 5.

Fig. 5.

Metabolic changes in immune cells and stromal cells in the TME. Metabolism in the TME is remodeled by fibroblasts and immune cells. Each cell type has its own unique metabolic pattern. Here, we describe the metabolic interactions of T cells, Treg cells, macrophages, and fibroblasts with cancer cells in the TME. The red upward-facing arrow (↑) indicates an increase, and the red downward-facing arrow (↓) indicates a decrease. TME, tumor microenvironment; MDSC, myeloid-derived suppressor cell; LDHA, lactate dehydrogenase; GS, glutamine synthetase; BCAT1, branched chain amino acid transaminase 1; ECM, extracellular matrix; BCAA, branched-chain amino acid; BCKA, branched-chain keto acid; SUCNR1, succinate receptor 1; FAO, fatty acid oxidation; IDO1, indoleamine 2,3-dioxygenase 1; PHD, prolyl hydroxylase; LCFAs, long-chain fatty acids; VLCFAs, very long-chain fatty acids

Combination therapeutic strategies targeting the TME in cancer

The complexity of cancer metabolism is reflected not only in its own metabolic heterogeneity and metabolic adaptability, but also in its interaction with the surrounding environment. For example, the availability of nutrients in the TME affects the metabolic status of cancer and stromal cells, while many metabolites, such as lactate, secreted by cancer cells further promote the formation of an immunosuppressive microenvironment. Therefore, enhancing the anticancer effect of immune cells by targeting the metabolic vulnerability of tumors or altering the metabolic program of immune cells to adjust to the pro-inflammatory state will be one of the approaches of cancer therapy, alone or in combination with other treatments. In this section, we discuss strategies to target the different metabolic modalities of tumor cells and immune cells.

Targeting metabolites

A restriction of glucose availability leads to changes in the composition of the immune microenvironment. For example, a low-glucose environment can induce FOXP3 expression and mediate the differentiation of effector T cells into Treg cells. Moreover, the acceleration of the glycolysis in cancer cells can relieve the inhibition of granulocyte colony-stimulating factor (G-CSF) and granulocyte-macrophage colony-stimulating factor (GM-CSF) in myeloid-derived suppressor cells (MDSCs) through AMPK-ULK1 and autophagy pathways, and the infiltration of MDSCs promotes tumor growth and metastasis and reduces the immune activity of T cells [364]. Therefore, modulating the metabolic patterns of CD8 + T cells in a nutrient‑restricted microenvironment to support their activation and function may serve as an effective anticancer strategy. This approach includes the use of pyruvate and acetate to sustain mitochondrial metabolism or the targeting of sarcosine dehydrogenase (SARDH) to promote sarcosine accumulation, both of which can enhance the immune function of T cells [365, 366]. Moreover, immune checkpoints, including PD-1, PD-L1 and CTLA-4, inhibit the uptake and utilization of glucose by T cells through signal transduction and promote lipolysis and lipid oxidation. Therefore, improving the metabolic status and effector function of T cells with corresponding checkpoint inhibitors is effective, as has been confirmed in some studies [367, 368]. Nevertheless, the effects of immune checkpoint inhibitors (ICIs) on other components of the microenvironment are worthy of further investigation. Engineered chimeric antigen receptor (CAR) T cells also represent a potential strategy for modulating T-cell metabolism. Adoptively transferred T cells can be genetically engineered to tailor their effector functions or memory characteristics. However, insufficient efficacy in solid tumors and limited persistence in vivo remain key constraints to their broader application. SLC2A1, the main glucose transporter on T cells, significantly affects glucose competition between T cells, cancer cells and peripheral immune cells. Therefore, the overexpression of SLC2A1 may effectively improve the metabolic adaptability and anticancer effect of CAR-T cells [369]. Moreover, supplementation of D-mannose in vitro can induce metabolic remodeling in T cells, enhance O-GlcNAc transferase (OGT)-mediated O-GlcNAcylation of β-catenin, and ultimately maintain their stemness characteristics and anti-tumor activity [370].

The availability of glutamine is inconsistent between cancer cells and immune cells. In particular, M2 macrophages in the TME rely on α-KG produced by glutamine metabolism to maintain their anti-inflammatory status. Moreover, glutamine metabolism accelerates the recruitment of MDSCs, which is more conducive to increasing the number of M2-type macrophages [371]. In the Lewis lung cancer microenvironment, pharmacological inhibition or genetic ablation of GS promotes an M1-like phenotype in macrophages, accompanied by decreased intracellular glutamine levels, increased succinate levels, enhanced glycolysis, and HIF-1α activation. These changes resulted in increased levels of T-cell recruitment and activation, and the inhibition of cancer angiogenesis and metastasis in a mouse tumor model [361]. Furthermore, within the nutrient-deprived TME, cancer cells can remodel the metabolic profile of CAFs by inducing metabolic stress, thereby promoting glutamine synthesis and providing essential nutritional support for their own proliferation and survival [327]. Particularly in breast cancer, exosomal miR-105 derived from tumor cells increases glutamine synthesis and secretion by CAFs in a Myc-dependent manner. This positive feedback loop reinforces metabolic symbiosis between cancer cells and other components of the TME. Therefore, a strategy that concurrently modulates metabolic pathways and disrupts intercellular communication represents a potential synthetic lethal approach, providing a novel direction for the systematic targeting of tumors and the improvement of therapeutic efficacy [372]. Moreover, CD36 is a key FA transporter in ovarian cancer, and cancer cells take up exogenous FAs via CD36 to maintain their energy requirements for growth and metastasis [373]. The inhibition of CD36 is not only an effective therapeutic strategy for ovarian cancer metastasis but also prevents the polarization of M2 macrophages, suggesting the dual therapeutic value of targeting CD36 [374]. Nevertheless, targeting nutrients alone does not seem to confer benefits because of exogenous nutrient uptake; thus, fully considering the inhibition of key steps of metabolic processes is advantageous for regulating the immune state of the microenvironment.

The substantial amount of lactate produced by glycolysis in tumors exacerbates the immunosuppressive state of the TME, which includes inhibiting T-cell activation and proliferation as well as promoting M2 macrophage polarization. Furthermore, lactate induces monocyte differentiation into dendritic (DC) cells, which is associated with the suppression of mTORC1 activity [375]. Given the highly acidic nature of the TME, neutralizing its acidity or increasing the local pH may serve as a potential strategy to increase the efficacy of cancer immunotherapy. The evidence suggests that buffering lactate with bicarbonate or the proton pump inhibitor esomeprazole improves the pH of the TME and ultimately increases the anticancer functions of T and NK cells [376]. Furthermore, in a mouse model of melanoma, the neutralizing effect of bicarbonate increased the efficacy of anti-PD-1 and anti-CTLA4 immunotherapy [377]. Therefore, targeting the pH of the TME is highly important for reshaping the immunosuppressive microenvironment and improving immunotherapy outcomes. In addition to the regulation of the acidic state of the TME, targeting lactate-related signals should also be a focus of attention. For example, a high lactate level activates GPR81 on immune cells, endothelial cells, and adipocytes, subsequently leading to angiogenesis, immune escape, and chemotherapy resistance [378]. GPR81 blockade leads to the downregulation of PD-L1 expression and inhibition of Treg production [379]. These findings provide a potential target for increasing the efficacy of cancer immunotherapy. Tryptophan degradation is an immune escape strategy that is common to many cancers. Many tumors expressing IDO1 and tryptophan-dioxygenase (TDO) suppress T-cell activation and promote Treg cell proliferation by depleting tryptophan in the TME and accelerating kynurenine accumulation [380]. LM10 is a TDO inhibitor that enhances tumor immune rejection and has virtually no toxic effects. Blocking TDO and IDO1 to improve the efficacy of cancer immunotherapy would be complementary. Pilotte et al. found that targeting both IDO1 and TDO eliminated 51% of tumors, as opposed to 32% for IDO1 and 35% for TDO alone [381].

Targeting the mTOR signaling pathway

mTOR is a serine/threonine protein kinase whose role in cell metabolism is closely related to the state and function of various immune cells. mTOR exists in two distinct catalytic subunit complexes, mTORC1 and mTORC2, which have different compositions and functions. Among them, mTORC1 plays a primary role in regulating metabolism by sensing various environmental signals, including growth factors, energy levels, oxygen, and nutrients [382]. In T cells, the downregulation of mTORC1 activity reduces glycolysis while promoting oxidative phosphorylation and FAO, thereby promoting the formation of memory CD8 + T cells and contributing to the establishment of long-lasting antitumor immunity [383]. A study of TP53 wild-type hepatocellular carcinoma has shown that, compared with monotherapy, the combination of the mTORC1 inhibitor everolimus with anti-PD-L1 antibodies significantly increases CD8 + T-cell infiltration and enhances tumor suppression [384]. Furthermore, the classic mTORC1 inhibitor rapamycin, when combined with Ad-Flt3L and Ad-TK/GCV, markedly enhances antiglioma cytotoxicity and improves memory T-cell function [385]. These results confirm that the regulation of mTORC1 activity is among the key mechanisms through which T cells exert their anticancer effects. Previous studies have also shown that mTOR signaling is involved in the polarization of macrophages. Chen et al. designed a double-targeted delivery liposome system for the codelivery of an mTOR inhibitor (rapamycin) and antiangiogenic drug (regorafenib). As a result, these liposomes effectively inhibited glycolysis and angiogenesis in tumors and repolarized M2 macrophages into the M1 state, thereby preventing tumor growth [386]. In conclusion, these results indicate that mTOR signaling is finely regulated in different immune cells in the TME, and more clear preclinical studies are needed to confirm its role in antitumor immunity.

Targeting AMPK

In a nutrient-deprived TME, a decrease in ATP production is accompanied by an increase in the AMP/ATP ratio. This metabolic stress induces AMPK activation, which drives cancer metabolism toward ATP-producing catabolic pathways and oxidative phosphorylation [387]. AMPK contributes to the metabolic remodeling in tumors and regulates the metabolic plasticity of various immune cell types in the TME, thus affecting antitumor immune response. In T cells, AMPK increases glutamine catabolism and mitochondrial oxidative phosphorylation, which contributes to nutrient utilization and the survival of effector/memory T cells [388]. Moreover, during CD8 + T-cell activation, AMPK is activated to maintain the ATP concentration and cell viability in the presence of low glucose availability [389]. In addition, increased AMPK activity coordinates the oxidative metabolism and proliferation of CD4 + T cells and serves as a potential candidate target for increasing the efficacy of CAR-T-cell therapy [390]. AMPK is also involved in molecular crosstalk between macrophages and cytokines. For example, AMPKα silencing increased the mRNA expression of TNF-α, IL-6 and cyclooxygenase-2 in LPS-induced macrophages [391]. Moreover, AMPKα-deficient macrophages and DCs exhibit enhanced inflammatory functions and antigen-presenting capacity through the increased production of inflammatory cytokines. This activity mediates the differentiation of CD4 + T cells into Th1 and Th17 subtypes, promoting the production of inflammatory factors such as IFN-γ and IL-17, and shifting their metabolic profile from oxidative phosphorylation to glycolysis [392]. AMPK can also impair MDSC activation and function by inhibiting the JAK-STAT, NF-κB, C/EBPβ, CHOP, and HIF-1α signaling pathways, thereby enhancing antitumor immunity [393, 394]. The most common drug targeting AMPK is metformin, which is the most widely used hypoglycemic agent for the treatment of patients with type 2 diabetes. Metformin increases the number of CD8 + T cells through the activation of AMPK, protecting them from apoptosis and preventing immune failure characterized by decreased secretion of IL-2, TNF-α and IFN-γ [395, 396]. Furthermore, several preclinical studies have shown that metformin in combination with PD-1 inhibitors inhibits the growth of cancer cells in mouse models of different tumor types and leads to a significant increase in the number of tumor-infiltrating CD8 + T cells [397, 398]. In another study, patients with NSCLC who are treated with both metformin and ICIs had better clinical outcomes (overall response rate (ORR), progression-free survival (PFS), and overall survival [OS]) [399]. These studies demonstrate the importance of targeting AMPK in combination with immunotherapy drugs for cancer treatment. Nevertheless, due to the diversity of metabolism in cancer and the complexity of the TME, the treatment of cancer needs to be based on multimodal combination therapy, which will be the focus of cancer treatment in the future.

Summary and prospects

In the past few decades, extensive research has been conducted on the pathogenesis of cancer, but has not stopped the increasing incidence and mortality of cancer. The rise and application of targeted therapy, chemotherapy, radiotherapy and immunotherapy cannot completely prevent the death and recurrence of cancer cells. New therapies are urgently needed to overcome the bottleneck of a cure for cancer. Metabolic reprogramming is a malignant hallmark of cancer. Changes in metabolism fulfill the requirements for energy and biomolecules for cancer cell proliferation and survival. Processes such as glycolysis, glutamine uptake and catabolism, FAO, and polyamine synthesis and utilization are key energy pathways that drive cancer development, highlighting opportunities for metabolism-targeted cancer therapies. In this review, we systematically elaborate on the uptake and utilization of key metabolic substrates such as glucose, glutamine, lipids, and polyamines by cancer cells. These processes are regulated by multiple factors, including dynamic changes in the TME, aberrant activation of oncogenic signaling, and remodeling of epigenetic modifications, which collectively highlight the heterogeneity and plasticity of metabolism in cancer. Further analysis of these metabolic regulatory networks will not only deepen our understanding of the mechanisms behind tumor metabolic reprogramming but also offer novel insights for developing targeted therapeutic strategies against cancer metabolism.

In-depth studies of metabolism in cancer have revealed that key enzymes, signaling pathways, and metabolic products dynamically regulate the evolution of cancer cells and their microenvironment, forming the core foundation of the complexity and heterogeneity of metabolism in cancer. Many preclinical studies have shown that solely targeting key metabolic enzymes or their associated signaling pathways often fails to achieve satisfactory antitumor outcomes. A critical explanation is the inability of such approaches to fundamentally restructure or disrupt the overall metabolic microenvironmental balance that sustains tumor growth, ultimately leading to the development of resistance via compensatory metabolic pathways. Furthermore, the high spatial and cellular heterogeneity of metabolic activity within tumors further complicates targeted therapy. The integrated application of multiomics technologies (e.g., single-cell RNA sequencing, integrated proteomics, single-cell metabolomics, and spatial omics) is critical for systematically dissecting intratumoral metabolic heterogeneity, identifying key metabolic subtypes, and revealing patterns of intercellular metabolic crosstalk to address this issue [400]. This approach facilitates the precise identification of critical metabolic vulnerabilities. Moreover, understanding the temporal dynamics of metabolic changes enables the design of intervention strategies tailored to specific metabolic states or cell cycle stages, which holds promise for reducing the risk of adaptive resistance and increasing the precision and durability of treatments.

In recent years, functional studies centered on metabolites have provided new insights for cancer treatment. For instance, the high-lactate TME has been shown to promote processes such as invasion, angiogenesis, chemotherapy resistance, and immunosuppression. Interventions targeting lactate production, transport, and metabolic pathways have become important strategies for improving therapeutic responses. Concurrently, combined strategies that integrate metabolism-targeting agents with immunotherapy, chemotherapy, or radiotherapy must be designed to systematically overcome metabolic plasticity and treatment resistance in tumors, with the goal of systematically disrupt the metabolic adaptability of tumors. Examples include the combined use of the glucose analog 2-DG with conventional chemotherapy, or the polyamine metabolism inhibitor DFMO in combination with the PCV regimen, both of which have demonstrated synergistic antitumor effects in preclinical and clinical studies, as presented in previous tables. However, the clinical translation of such combination strategies still faces multiple challenges, including drug toxicity, cumulative side effects, dosage selection, and timing of administration. Therefore, while metabolism-targeted combination therapies are being advanced, a systematic evaluation of their risk-benefit ratios is necessary to overcome the aforementioned limitations through rational design.

However, considering therapeutic strategies that target cancer cell metabolism alone is not sufficient because metabolic rewiring affects the composition, phenotype and function of cancer cells and microenvironmental components. On the one hand, cancer metabolism-related signals or metabolites affect the activation and function of microenvironmental antitumor immune cells (T cells and NK cells) in the TME, and on the other hand, cancer-associated stromal cells, such as CAFs, and immunosuppressive cells (M2 macrophages and MDSCs) reshape the local metabolic environment and oncogenic pathways, further promoting malignant tumor progression. These processes establish a vicious cycle wherein dysregulated metabolism and immunosuppression mutually reinforce each other, representing a key mechanism underlying the limited response rates observed with current immunotherapies. Targeting the metabolic differences between cancer cells and immune cells (especially effector T cells) in the TME and developing selective intervention strategies that suppress the metabolic advantages of cancer cells while relieving or bypassing the metabolic constraints on immune cells represent a highly promising research directions for improving current immunotherapy response rates and overcoming resistance. For example, the neutralization of the low-pH environment created by high lactate levels promotes the proliferation and activation of CD8 + T cells and NK cells, which is highly important for antitumor immunity. Moreover, dietary adjustments can also alter the metabolic state of the TME. For example, ketogenic diets reduce the level of lactate produced by cancer cells through the consumption of glucose, which further affects the polarization of macrophages and the proliferation of MDSCs. These effects suggest that ketogenic diets may increase the efficacy of cancer radiotherapy, chemotherapy, and immunotherapy [401]. Additionally, a high-fat diet can accelerate the progression of malignant tumors, whereas intermittent fasting or caloric restriction can increase the proportion of effector T cells in the TME, thereby enhancing antitumor immunity [402, 403]. Natural bioactive components in the diet al.so have anticancer potential. For instance, EGCG present in green tea and resveratrol present in grapes and peanuts have been shown to inhibit tumor progression by regulating the activity of enzymes involved in glucose, amino acid, and lipid metabolism (e.g., PKM2, PFK, and LDH) while also modulating the metabolic state of immune cells in the microenvironment. These compounds, which are characterized by their multitarget effects and low toxicity, are regarded as promising adjuvant strategies for cancer treatment. Furthermore, microorganisms (e.g., the gut microbiota and intratumoral microbiota) can profoundly influence metabolism in the TME through various mechanisms. For example, butyrate produced by the gut microbiota through the fermentation of dietary fiber promotes the differentiation and function of Treg cells, while certain bacteria can synthesize polyamines that suppress antitumor immune responses [404, 405]. By conducting in-depth analysis of the diet-microbiota-immunometabolism regulatory network, through targeted dietary modifications to adjust nutrient availability in the TME, reshaping the gut microbiota with probiotics or prebiotics to enhance immunometabolic activity, and combining immune checkpoint inhibitors with metabolism-targeted drugs, it may be possible to disrupt tumor metabolic adaptation and immune escape at a systemic level, thereby achieving personalized and precision therapy.

Nevertheless, the clinical application of current metabolism-targeting drugs remains limited by issues such as low bioavailability, poor solubility, and insufficient targeting specificity, preventing their antitumor efficacy from being fully realized. Moreover, the high complexity and heterogeneity of tumor metabolism, along with its close interaction with the TME, have collectively driven the evolution of treatment paradigms from single-agent approaches to multidimensional synergistic strategies. Given the tight coupling between the immunosuppressive TME and its unique metabolic reprogramming (e.g., high glucose consumption, elevated lactate levels, low pH, and hypoxia), interventions targeting metabolism (such as inhibiting lactate production or transport) can not only directly decrease the survival advantages of tumor cells but also significantly increase the function and tumor-infiltrating capacity of effector immune cells, such as CD8 + T cells. Moreover, the efficient activation of immune cells itself relies on specific metabolic support, further highlighting the synergistic potential between metabolic and immunomodulatory interventions. Future research must focus on developing intelligent nanodelivery systems (e.g., liposomes, polymeric nanoparticles, or metal-based nanoparticles) to achieve this synergistic effect. These systems should be capable of codelivering immunomodulatory drugs and metabolism-targeting agents at the right time, in the right space (e.g., within tumor foci or specific cell subpopulations), and at precise ratios. Such systems hold promise for maximizing synergistic therapeutic effects while minimizing off-target toxicity. Furthermore, delivery systems can be integrated with diagnostic imaging functions (e.g., MRI or fluorescent probes) to achieve theranostics, enabling real-time monitoring of the drug distribution, tumor metabolic dynamics, and treatment responses. These findings provide a basis for the timely adjustment of personalized treatment strategies, driving the advancement of tumor therapy toward dynamic and precise regulation.

In summary, based on the characteristic metabolic reprogramming of tumor cells, combination therapies that simultaneously target multiple metabolic pathways or synergize with other treatment modalities represent a systematic strategy to overcome the limitations of monotherapy, suppress tumor adaptation, and ultimately increase therapeutic efficacy. With the deepening understanding of metabolic complexity in tumors, advancements in biotechnology, and the emergence of more precise patient stratification strategies, metabolism-based combination therapy is likely to become an indispensable component of future comprehensive cancer treatment. This approach will provide a critical pathway toward achieving higher levels of precision in oncological therapeutics.

Authors’ contributions

S.D.; Writing-Original draft preparation, Supervision. T.L.; Supervision, Project administration, Funding acquisition.

Funding

This work was supported by National Natural Science Foundation of China (grant no. 81860519; 82160561), Science and Technology Research Project of Jiangxi Provincial Department of Education (grant no. GJJ2500103), and Youth Talent Research Development Program of the First Affiliated Hospital of Nanchang University (grant no. YFYPY202564).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

All authors have read and agreed to the published version of the manuscript.

Competing interests

The authors declare no competing interests.