Beyond Glycolysis: Targeting Non‐Glycolytic Metabolic Pathways in Brain Tumors for Therapeutic Innovation: A Narrative Review

ABSTRACT

Background and Aims

Metabolic reprogramming is a hallmark of brain tumors, extending beyond the classical Warburg effect. While glycolysis has been extensively studied, gliomas and pediatric high‐grade brain cancers demonstrate remarkable metabolic plasticity. This review aims to highlight non‐glycolytic metabolic pathways that sustain tumor growth, contribute to therapy resistance, and offer translational potential in neuro‐oncology.

Methods

We conducted a comprehensive synthesis of recent preclinical and translational studies focusing on non‐glycolytic metabolic dependencies in brain tumors. Particular emphasis was placed on fatty acid oxidation (FAO), amino acid metabolism, mitochondrial dynamics, and immune metabolic interfaces.

Results

Emerging evidence indicates that FAO supports ATP synthesis and redox balance under hypoxic conditions. Glutaminolysis and serine/glycine metabolism maintain nucleotide and antioxidant pools essential for tumor survival. Mitochondrial fusion–fission dynamics and Complex I mutations enhance oxidative phosphorylation (OXPHOS) adaptability. Targeting these metabolic nodes, individually or in combination, reduces tumor growth, reverses drug resistance and sensitizes tumors to radiotherapy and immunotherapy. Additionally, the tryptophan–kynurenine–AHR axis contributes to immune evasion, underscoring the interplay between metabolism and tumor immunology.

Discussion

Non‐glycolytic metabolism represents an emerging frontier for precision neuro‐oncology. The integration of metabolic inhibitors with conventional or immune‐based therapies shows promise in preclinical models. However, overcoming metabolic plasticity and therapeutic resistance will require patient stratification, blood–brain barrier penetrant inhibitors, and biomarker‐guided clinical trials. These insights underscore the need to translate metabolic vulnerabilities into clinically actionable strategies.

Conclusion

Non‐glycolytic metabolic pathways, including lipid, nucleotide, and amino acid metabolism, offer promising therapeutic targets to overcome tumor survival and therapy resistance in brain tumors. However, despite encouraging preclinical evidence, the clinical development of such targeted metabolic therapies remains in its early stages.

Summary

• Brain tumors exploit non‐glycolytic metabolic pathways beyond glycolysis.

• FAO, amino acid metabolism, and mitochondrial dynamics sustain tumor survival.

• Targeting these pathways reduces growth and reverses therapy resistance.

• The tryptophan–kynurenine–AHR axis links metabolism to immune evasion.

• Non‐glycolytic metabolism offers novel targets for precision neuro‐oncology.

1. Introduction

Metabolic reprogramming is now strongly established as a hallmark of cancer. It reflects the ability of malignant cells to alter nutrient utilization and energy production to support uncontrolled growth, survival under stress, and immune evasion [1]. While the Warburg effect, first described in the 1920s, remains a foundational concept, it represents only one facet of the complex metabolic landscape in tumors. This phenomenon is characterized by aerobic glycolysis and has historically guided therapeutic strategies aiming to disrupt glucose metabolism. However, accumulating evidence reveals that many cancers, particularly brain tumors, exhibit profound metabolic plasticity that enables them to bypass glycolytic inhibition and exploit alternative pathways for bioenergetic and biosynthetic needs [2].

Glioblastoma (GBM), the most lethal primary brain tumor in adults, along with high‐grade pediatric CNS malignancies such as medulloblastoma and diffuse intrinsic pontine glioma (DIPG), exemplify this metabolic adaptability. These tumors flourish in oxygen and nutrient‐deprived niches, often adopting a hybrid metabolic profile that includes glycolysis, oxidative phosphorylation (OXPHOS), fatty acid oxidation (FAO), and amino acid metabolism. Their ability to switch between these pathways in response to therapeutic pressure or environmental stress contributes to both tumor progression and resistance to conventional treatments [3, 4].

Moreover, the tumor microenvironment (TME) plays a critical role in shaping metabolic behavior. Crosstalk between tumor cells and stromal components such as immune cells, astrocytes, and endothelial cells further amplifies metabolic heterogeneity. For instance, lactate produced by glycolytic tumor cells can be recycled by neighboring cells via the reverse Warburg effect, while immune cells within the TME may compete for key metabolites like glutamine and tryptophan, influencing both tumor growth and immune suppression [5].

Given this complexity, a narrow focus on glycolysis is no longer sufficient to capture the full metabolic landscape of brain tumors. There is an urgent need to investigate non‐glycolytic metabolic pathways not only to deepen our understanding of tumor biology but also to uncover novel therapeutic targets. This review addresses that need by synthesizing current evidence on non‐glycolytic metabolic dependencies and assessing their relevance for translational research in neuro‐oncology.

Recent studies have highlighted the significance of non‐glycolytic metabolic pathways in sustaining brain tumor growth and therapy resistance. These alternative routes, including fatty acid oxidation, amino acid metabolism, and mitochondrial dynamics play critical roles in tumor survival and progression. Despite their relevance, these pathways remain underrepresented in current neuro‐oncology reviews, leaving a gap in the literature that this work aims to address [3].

This review aims to find emerging findings on non‐glycolytic metabolic dependencies in brain tumors, with a particular focus on their mechanistic roles and therapeutic implications. By evaluating these pathways and their translational potential, we seek to provide a comprehensive framework for future research and clinical innovation in neuro‐oncology.

1.1. Fatty Acid Oxidation (FAO) in Brain Tumors

FAO is a highly efficient energy‐generating process in which fatty acids are broken down in the mitochondria in order to produce energy (primarily in the form of acetyl‐CoA, NADH, and FADH²), especially during periods of high energy demand or low glucose availability. This process is usually seen during prolonged exercise or fasting [6]. Now, when it comes to glucose‐deprived microenvironments of tumor cells, they usually adapt by upregulating FAO. Here, FAO is a critical metabolic process, which particularly, under hypoxic and nutrient‐stressed conditions such as brain tumor (glioblastoma), contributes to tumor progression and therapeutic resistance. The mechanism of FAO includes the mobilization of stored lipids, their transportation into mitochondria, and subsequent breakdown via β‐oxidation to produce acetyl CoA. This acetyl CoA fuels the tricarboxylic acid (TCA) cycle, supporting ATP synthesis and sustaining cellular proliferation. More precisely, the acetyl CoA fuels the Krebs cycle that generates ATP to support cellular growth and functions. Moreover, this metabolic pathway promotes the increase of lipid synthesis, FAO, lipid uptake and lipid storage. In this way, FAO plays a critical role in the progression of tumors by serving as one of the effective energy sources. However, extracellular TME factors (hypoxia, nutritional alterations, and acidosis) and continuous oncogenic events directly alter the lipid metabolic phenotype in tumor cells [7]. When it comes to glioblastoma stem cell survival and proliferation, these metabolic alterations such as glutamine metabolism and fatty acid synthesis (FAS) play a vital role. Glioblastoma multiforme (GBM), also known as grade IV astrocytoma, is a type of brain tumor which invades the nearby brain tissue, but usually does not spread to other distant organs. It is one of the aggressive and fast‐growing brain tumors. Now, a highly coordinated metabolic program has shifted from FAS to catabolism in glioblastoma multiforme in which FAO emerged as a key metabolic node as per some integrative analyses. Because of the diverse microenvironment present in this tumor, metabolic reprogramming likely plays a significant role during glioma‐genesis, which enables the cells to proliferate and adapt. Glioblastoma multiforme, being a heterogeneous tumor, includes hypoxia, angiogenesis, alternating nutrient gradients, and necrosis. Enhanced FAO increases the rate of breakdown of fatty acids into carbon substrates with tumorigenesis. NADH and FADH² acetyl CoA generated in the Krebs cycle provide the electron gradient. This electron gradient causes ATP synthesis during oxidative phosphorylation, as per some recent investigations. Therefore, FAO plays a role in this tumor via energy production [8]. See Figure 1 for the mechanism of FAO in tumor progression.

Figure 1.

Mechanism of FAO in tumor progression [9].

When FAO inhibitors are combined with anti‐tumor drugs, the drug resistance of cancer cells to drugs can be reversed. This enhances the effectiveness of tumor therapy according to some pre‐clinical studies. This is one of the examples of how some existing therapies for cancer are correlated with metabolic reprogramming especially when FAO is involved. More precisely, metabolic reprogramming of FAO is crucial for the growth, proliferation, and metastasis of cancer cells, and tumor resistance is induced by alteration of FAO. This mechanism includes enhancing DNA damage repair, changing apoptosis signaling pathways, mediating tumor cell immune evasion, and promoting autophagy of tumor cells [9]. Metabolically, cancer cells are adaptive to the nutrient microenvironment and changing oxygen levels. Some combinatorial strategies do show some promising effects, such as the combination of FAO and a glycolytic inhibitor. For instance, when FAO is targeted in glioblastoma, it alleviates the immunosuppressive tumor microenvironment by reducing the tumor growth in the syngeneic murine models of lung and colon cancer. Moreover, glycolytic inhibitor dichloroacetate (DCA) induces apoptosis in glioblastoma multiforme. Again, DCA has synergistic effects on the growth and survival of glioblastoma multiforme induced by mitochondrial oxidative stress, via sensitizing glioblastoma multiforme to radiation. Glucose metabolism and reactive oxygen species (ROS) are bidirectionally linked. As a result, this dual blockade of the FAO pathways and glycolysis supposedly inhibits glioblastoma multiforme tumor growth by enhancing chemoradiation‐induced ROS (Figure 2) [10].

Figure 2.

Mechanism of FAO in tumor microenvironment [11].

2. Amino Acid Metabolism: Glutamine, Serine, and Beyond

2.1. Glutamine Metabolism

Glioblastoma is an aggressive and high‐grade malignancy originating from abnormal cell growth in the brain and needing metabolic reprogramming to further support the growth of the tumor. This metabolic reprogramming is associated with various different metabolic pathways, and glutaminolysis is one of them. Glutaminolysis is reported to fuel the TCA cycle and support nucleotide biosynthesis. This process is associated with mitochondrial pathway activation and can be targeted therapeutically in the case of glioblastoma as well. It also illustrates that the levels of mitochondria‐related proteins such as COX1, COX2, and DRPI are correlated with each other as well as with the glutaminolysis‐related proteins (GLDH and GLS1). On the other hand, the inhibition of glutaminolysis (via GSL1 or GLDH) in cell lines with high GLDH and GLS1 expression suppresses the growth of the brain tumor [12]. Therefore, it can be said that mitochondrial‐dominant glioblastomas are also glutaminolysis dominant, which creates a subtype distinction that could be exploited therapeutically. In mesenchymal subtype glioblastoma, especially GLUD1 and GPT2 are downregulated. This allows glutamate accumulation for glutathione (GSH) synthesis, which further enhances antioxidant defenses and overall tumor survival. On the contrary, in lower grade astrocytomas with IDH1 mutations, GLUD1 and GPT2 are upregulated further diverting glutamate towards energy metabolism and reducing GSH, making cells more vulnerable to oxidative stress [13]. Furthermore, GDH1 is reported to connect glutamate to α‐ketoglutarate in the mitochondria, which is significant for glioblastoma cell proliferation and brain tumor growth even when there is an abundance of glucose [14]. These findings also indicate that glioblastoma does not solely depend on glycolysis, but rather relies on glutaminolysis via GDH1 to further feed the TCA cycle and support the biosynthesis and redox balance.

2.2. Combination Therapy Exploiting Glutamine Metabolism

In a recent study, it was established that GBM cells resist treatment with antipsychotic drug Pimozide by upregulating the consumption of glutamine. This elevation of glutamine is completed as Pimozide activates SREBP‐1, which increases the activation of ASCT2 (a glutamate transporter), forming a feedforward loop. The loop results in an increase of glutamate uptake, which further results in more ammonia release and, lastly, SREBP‐1 activation. Pharmacological targeting of ASCT2 or glutaminase, when combined with pimozide, disrupts this loop, resulting in significant mitochondrial damage and oxidative stress, ultimately causing GBM cell death both in vitro and in vivo [15]. Recent evidence highlights the heterogeneity of glutamine utilization in GBM. It was discovered that transcriptionally distinct GBM clusters, which were characterized by variable glutamine metabolism, were associated with changes in prognosis, oncogenic signaling, immunological microenvironment, and treatment sensitivity. Functionally, the combination of dihydroartemisinin (DHA) and the glutaminase inhibitor CB839 caused disruptions in glutamine metabolism, increased the accumulation of reactive oxygen species, promoted apoptosis, and inhibited migration in GBM cells exhibiting significant preclinical efficacy [16].

In a study, it was revealed that PCTK1 (PCTAIRE kinase 1) enhances brain metastasis by reprogramming glutamine metabolism. Overexpression of this PCTK1 in breast cancer cells accelerates brain colonization and correlates with elevated expression of glutaminase genes (GLS, GLS2) in brain tumor data sets. PCTK1‐expressing cells outperform controls in terms of proliferation under low‐nutrient circumstances with physiological glutamine levels, but PCTK1 knockdown limits growth and decreases GLS expression [17]. These results lead to PCTK1 and glutamine metabolism as possible combinatorial treatment targets by indicating that PCTK1 enhances tumor fitness in the brain microenvironment through glutamine metabolic adaptation.

Inhibiting glutaminase (GSL) through siRNA or the small molecule BPTES preferentially slows the proliferation of glioma cells harboring mutant IDH1, compared to wild‐type counterparts. GLS inhibition increased glycolytic intermediates while decreasing intracellular glutamate and α‐ketoglutarate (α‐KG). Additionally, exogenous α‐KG supplementation was able to restore the growth inhibition in mutant IDH1 cells, indicating their dependence on glutaminase‐driven α‐KG synthesis. Furthermore, this study highlights glutaminase as a prospective metabolic target by demonstrating that IDH1‐mutant gliomas are particularly susceptible to disruption of glutamine catabolism [18].

2.3. Serine/Glycine Pathways

De novo metabolism of serine and glycine has recently been recognized as a significant non‐glycolytic vulnerability in brain tumors and metastatic lesions. The microenvironment within the brain is deficient in free serine and glycine, leading metastatic cancer cells to depend on de novo serine synthesis driven by PHGDH for nucleotide generation and proliferation. In several preclinical models, brain metastases were decreased by genetic or pharmacologic PHGDH inhibition [19]. Due to suppression within the cerebral microenvironment, the extracellular serine and glycine are limited, hence prompting tumor cells to upregulate the serine synthesis pathway (SSP) with phosphoglycerate dehydrogenase as its rate‐limiting enzyme. Therefore, this pathway supports nucleotide biosynthesis, maintains the redox balance, and provides one‐carbon units that are essential for growth in the cerebral microenvironment.

Functional studies confirm that both primary brain tumors and brain metastases depend on PHGDH activity under serine‐poor conditions, and along with that, genetic or pharmacological inhibition of PHGDH markedly inhibits the tumor growth, thereby suggesting a therapeutic opportunity specific to the brain microenvironment. Translational advances now include the repositioning of homoharringtonine (HHT), identified as a direct PHGDH inhibitor, which reduces serine flux and tumor progression in neuroblastoma models both in vivo and in vitro, highlighting the possibilities of targeting SSP pharmacologically [20].

Clinically, inhibiting the serine–glycine–one‐carbon network is likely to be most effective when given in combination therapies, for example, with DNA‐damaging agents, radiotherapy, or agents that further restrict nutrient supply [9]. However, penetration of the blood–brain barrier, adaptive metabolic rewiring, and the creation of molecules that activate PHGDH's enzymatic and non‐enzymatic capabilities will be necessary for the combination therapy to succeed. Significant phases toward translation include ongoing medicinal chemistry research and testing in brain models that are physiologically relevant.

2.4. Other Amino Acids

Beyond the metabolism of glutamine and serine, tryptophan catabolism represents an important non‐glycolytic pathway in the case of brain tumors. Gliomas frequently utilize indoleamine‐2,3‐dioxygenase 1 (IDO1) enzyme to degrade extracellular tryptophan while generating immunosuppressive metabolites such as kynurenine [21]. The aryl hydrocarbon receptor (AHR), which is activated by these metabolites, influences the tumor microenvironment by enhancing cell survival, suppressing anti‐tumor immunity, and promoting resistance to treatment. This dual effect, nutrient depletion and immunomodulation, illustrates how amino acid metabolism supports tumor microenvironment beyond bioenergetics. Accordingly, inhibitors of IDO1, tryptophan‐metabolic enzymes, and AHR signaling are being explored as therapeutic strategies in the management of glioma.

3. Therapeutic Strategies

3.1. Patient Subtype Stratification

Dividing brain tumors into subtypes and selecting the right patients for each treatment appears to be a promising strategy. Many studies on glioblastoma heterogeneity show that only tumors that highly express genes related to glutaminolysis respond well to glutaminase inhibitors. For example, a study shows that glioma stem cell (GSC) lines with high glutaminase (GLS) expression were more sensitive to glutaminase inhibitors such as CB839 and C968 [22]. Apart from that, in another study, researchers grouped GBM tumors by their glutamine metabolism, where combinational therapy of CB839 with DHA synergistically reduced glutamine metabolism and separately triggered apoptosis, ROS accumulation, and impaired migrative capacity in GBM cells. This finding suggests that using biomarkers to stratify patients, such as GSL1, GLDH expression, and glutamine‐metabolism signatures, can help in determining the right patients.

3.2. Combination Therapies

Combination therapies are equally important because monotherapy that targets only one metabolic node may frequently result in suboptimal efficacy. Combining CB‐839 (a GLS inhibitor) with other metabolic stressors or conventional therapy may potentiate effects in glioblastoma conditions [23]. Metabolic studies conducted after GLS inhibition reveal that in the presence of inhibitors, the results described an accumulation of Gln and lower levels of TCA cycle intermediates and aspartate, reflecting metabolic rewiring and potential vulnerabilities for combination targeting.

3.3. Targeting Immune Modulation

Another translational approach is to target immunological modulation, as the tryptophan → kynurenine → AHR axis is frequently linked to tumor immune evasion. A recent study illustrates that elevated factors, such as YKL‐40 upregulate IDO1 or TDO2 in coordination with kynurenine. This further implies the establishment of an inhibitory tumor immune microenvironment that leads to tumor immune evasion [24]. This emphasizes why metabolic inhibitors should be used in combination with IDO/TDO or AHR antagonists. In fact, the evaluation of IDO/TDO inhibitors highlights the fact that these enzymes are active drug developers and important modulators of tumor immunity (Figure 3) [25].

Figure 3.

Targeting the tryptophan–kynurenine–AHR axis pathway for tumor immune suppression. Note: This figure was drawn by the author.

Lastly, translation can be enhanced by utilizing small molecules and drug repurposing. PHGDH inhibitors made from pre‐existing medications or their derivatives provide a quicker route to reach clinical testing. These approaches can be used further in the case of brain tumors to reduce development time and risk.

4. Mitochondrial Dynamics and Oxidative Phosphorylation (OXPHOS)

4.1. Mitochondrial Plasticity in Tumors

There is impressive metabolic plasticity in brain tumors (gliomas and pediatric high‐grade gliomas), which alternate between glycolysis and OXPHOS in response to microenvironmental conditions such as oxygen availability, nutrient availability, and therapeutic stress. Hypoxia or nutrient deprivation can cause tumor cells to switch to glycolysis. However, during periods of oxygen supply or under certain forms of therapy pressure, they may switch to upregulate mitochondrial respiration to facilitate growth. As an illustration, diffuse intrinsic pontine glioma (DIPG) and other forms of pediatric brain tumors have been observed to increase mitochondrial Complex I gene expression in response to hypoxia signatures. This indicates that tumors may still seek to retain or re‐initiate OXPHOS even at low oxygen levels (Figure 4) [26].

Figure 4.

Targeting hypoxia to radiosensitize DIPGs [26].

The mitochondrial dynamics, such as fusion, fission, biogenesis, and mitophagy are important in permitting these changes. Mitochondrial functional integrity, efficient respiration, cristae preservation, and ATP production are more likely to be supported by fusion (mediated by proteins including MFN1, MFN2, OPA1). Mediated by DRP1 and FIS1, fission can promote the removal of damaged elements, stress adaptation, and distribute mitochondria in rapidly proliferating tumor cells. Mitochondrial fusion is relevant to the glioma stem‐like cells (GSCs) to ensure that they have high respiratory capacity and survival in an adverse microenvironment. It has been demonstrated that disruption of fusion/fission balance (such as over‐expression or inhibition of MFN2, OPA1, DRP1) can cause changes in tumor growth, stress sensitivity, and metastatic/invasive potential (Figure 5) [27].

Figure 5.

Mitochondrial dynamics and mitophagy in GBM cells [27].

4.2. mtDNA Mutations in Pediatric Brain Tumors and Complex I Mutations

The mutations of mitochondrial DNA (mtDNA) are becoming a well‐known issue in pediatric brain tumors. In pediatric brain tumors, a proteomic and mitochondrial genomic study identified variants in the mitochondrial genome (including the copy number, oxidative damage, and sequence variants of the mitochondrial genome) that are associated with tumor risk and behavior. As an example, locus changes (including 9952A, 10006G, 10398A, etc.) were linked to a higher risk of tumor development (with a higher tendency in the female children) [28]. The research also pointed to the fact that numeric changes in the amount of copy of the mitochondrial DNA and oxidative damage are combined with changes in protein expression (mitochondrial helicase, and so on) to affect the tumor phenotype [28].

Mutations in the genes coded by the mitochondrial DNA, especially the subunits of Complex I (NADH dehydrogenase), have been noted in gliomas and especially in the high grades of glioma, as well as in glioblastoma. Such mutations may cause dysfunction of Complex I, which not only reduces the efficiency of OXPHOS, but also competes with metabolic rewiring (e.g., increased dependence on glycolysis or other metabolic substrates) [29]. This group of Complex I mutations is also responsible for resistance to therapies, as cells defective in Complex I can produce less ROS during some stresses or utilize antioxidant systems, and thus avoid oxidative stress‐based therapies.

4.3. Therapeutic Targeting

Considering the key role of mitochondrial dynamics, mitochondrial DNA quality, and OXPHOS in brain tumor survival and resistance to therapy, several therapeutic approaches have been considered. Metformin (a biguanide) inactivates mitochondrial Complex I, causing a decline in the mitochondrial respiration rate, a drop in ATP generation, and the development of energetic and cell death stress in tumor cells [29]. In pediatric glioma models, metformin (and phenformin) inhibit the activity of mitochondrial Complex I, inhibit oxidative respiration, and sensitize tumors to hypoxia or other interventions. Moreover, CPI‐613 (also referred to as Devimistat) is a TCA cycle enzyme or pyruvate dehydrogenase (PDH) and a‐ketoglutarate dehydrogenase inhibitor and disrupts mitochondrial metabolic flux. CPI‐613 decreases TCA cycle metabolites in glioblastoma models, retarded the growth of tumors, and extends the life span of animals [30]. Importantly, those drugs or combinations that trigger mitochondrial ROS accumulation, membrane depolarization, or inhibit mitophagy can drive tumor cells beyond the limit of acceptable oxidative damage [30].

4.4. Integrated Metabolic Networks and Crosstalk in Brain Tumors

The metabolic environment of brain tumors is much more complex than that based on glycolysis. Although the “Warburg effect” highlights the importance of aerobic glycolysis as a typical feature of most cancers, tumor cells tend to use other non‐glycolytic pathways and to dynamically respond by integrating them to promote survival, growth, and adaptation to stress [31]. This metabolic plasticity is augmented by a highly networked TCA cycle, glutamine and amino acid metabolism, lipid synthesis/oxidation, and pentose phosphate metabolism in brain tumors—glioblastoma. These metabolic pathways are interconnected and communicate with each other. So, if one pathway is blocked or inhibited, the others can adjust their function. This process allows the tumor cells to keep surviving and adapting to environmental changes [32]. It is an important consideration in the design of robust therapies to understand integrated metabolic networks and how they can crosstalk with each other. Here we consider two key aspects of that integration. One is how metabolic plasticity and redundancy enable tumor cells to avoid single pathway targeting, and the other is that the TME imposes external forces through hypoxia, nutrient gradients, and stromal tumor metabolic signaling. In brain tumors, such as glioblastomas, the connection between internal cancer cell metabolism and external TME signals forms a dynamic circuit that drives malignancy and limits treatment. Innovative treatments aimed at disabling tumor adaptability and enhancing clinical outcomes can be developed with integrated metabolic networks and their crosstalk [32].

4.5. Metabolic Plasticity and Redundancy

Tumor cells usually evade treatment by persistently changing the pathway they use to manage their energy. This process is known as metabolic plasticity [32]. Inhibition of one of the pathways (such as glycolysis) can cause tumor cells to increase OXPHOS, glutamine anaplerosis, fatty acid oxidation, or other carbon sources to sustain bioenergetics and biosynthesis (e.g., nucleotide, lipid) requirements [31]. This plasticity enables subsets of cells to adapt to metabolic changes imposed by therapy in brain tumors in which the metabolic heterogeneity is high. For example, the repression of glucose metabolism in glioma stem cells may result in an elevation of mitochondrial oxidative metabolism or amino acid catabolism as one of the compensation pathways [33].

The term metabolic redundancy refers to the fact that tumors often take advantage of parallel pathways that carry out the same or similar functions (e.g., generate NADPH, carbon skeletons, ATP). If one route is obstructed, alternative routes can serve as a backup. As an example, by inhibiting glycolytic enzymes, it can induce the pentose phosphate pathway, or serine/glycine metabolism, or glutaminolysis to stabilize redox and precursor levels. This prevents oxidative stress‐induced cell death [34]. In brain tumors, metabolic heterogeneity can allow the individual cell populations to use different substrates. Some cells can supply the TCA cycle by a pyruvate, others by glutamine or branched‐chain amino acids, resulting in internal redundancy [31].

When considering the therapeutic perspective, these characteristics are a significant setback because the ability to target a single specific enzyme or pathway frequently results in adaptive resistance. Study indicates that when one metabolic axis is restricted, another one is upregulated, which ultimately attenuates the effect. These redirect the flow of metabolites known as metabolic flux that leads to adaptive resistance [35]. Therefore, multi‐target approaches become crucial. Instead of a single metabolic enzyme, a combination of an inhibitor of glucose metabolism, glutaminolysis, OXPHOS, lipid metabolism, or redox may be effective. This can help minimize the risk of metabolic escape by this combinatorial targeting. In fact, recent preclinical models in glioma indicate that concomitant glycolysis and mitochondrial metabolism inhibition is more long‐lasting than either inhibition [33]. Additionally, synthetic lethal vulnerabilities (when redundancy is forcibly collapsed) can be used in combinatorial therapy. Indicatively, blocking both glutaminase and fatty acid oxidation at once can prevent it from redirecting metabolite flow into alternative pathways for survival, and this makes the treatment more effective [35].

4.6. Tumor Microenvironment (TME) Influence

The TME has strong control of tumor metabolism. The local environment during brain tumors is influenced by hypoxia, nutrient gradients, and immune and stromal cell interactions, which both limit or regulate metabolic fluxes. In solid tumors, hypoxia is widespread, particularly in poorly vascularized areas. Low oxygen triggers hypoxia‐inducible factor (HIF) signaling, which increases glycolytic genes and decreases mitochondrial oxidative metabolism. This favors the cells to be in the glycolysis and lactate‐producing state [36]. Nutrient gradients (e.g., glucose, amino acids) also limit the supply of substrates in the inner tumor areas, compelling them to adapt, such as autophagy, macropinocytosis, or extracellular metabolite scavenging [37]. In terms of brain tumors, the TME in the brain comprises local neural cells, which are astrocytes, microglia, and neurons, immune cells, extracellular matrix, and blood–brain barrier. These elements are in a continuous interaction with cancer cells and can affect their growth, invasion, and resistance to treatment. The TME of brain tumors is highly immunosuppressive, and it helps tumors to survive and evade immune response [38]. For example, tumor‐associated macrophages and microglia are very abundant in glioblastoma, and they play a role in tumor aggressiveness and drug resistance through facilitating inflammatory signaling pathways and immune suppression [39].

4.7. Crosstalk Between Tumor and Stromal Cells via Metabolic Signaling

Stromal elements, such as astrocytes, microglia, endothelial cells, and cancer associated fibroblasts (CAFs) are involved in the metabolic interactions with tumor cells. This metabolic crosstalk may be through metabolite secretion (e.g., lactate, pyruvate, alanine) or through metabolite or mitochondrial transfer. A prime example is the reverse Warburg effect, where stromal cells switch to glycolysis and release lactate that is taken up and oxidized by tumor cells. Here, astrocytes and microglia are able to secrete metabolic substrates that nourish tumor cells in brain tumors. Moreover, the exchange of metabolites between tumor cells and stromal cells facilitates tumor survival and growth in a hypoxic and nutrient‐poor brain TME. For example, tumor associated macrophages (TAMs), which in gliomas can outnumber other immune cells, compete with tumor cells for glucose but also adjust to the adverse environment by enhancing glycolysis, fatty acid metabolism, and glutamine metabolism to maintain their immunosuppressive M2 phenotype. This restructuring of TAMs metabolism favors tumor immunity [40]. There is also the involvement of CAFs in metabolic crosstalk, whereby they secrete amino acids, lipids, and other metabolites, which are taken up by tumor cells and allow them to overcome nutrient deficiency. This exchange is accompanied by mechanisms such as macropinocytosis and metabolic recycling of the extracellular matrix constituents, which enable the tumor cells to survive in the face of environmental stresses [41].

5. Therapeutic Landscape and Clinical Translation

5.1. Preclinical Models and Trials

Recent years have seen developments in targeting FAO, amino acid metabolism, and mitochondrial reprogramming in brain tumors. It was found that GBM tissues overexpress FAO‐related genes, particularly CPT1A (carnitine palmitoyl transferase 1A), compared to the normal cortex. ATP production was reduced by synergistic cytotoxicity done with WTS assays; along with that, this combination also diminishes bioenergetics by increasing the rate of apoptosis. The stem cell frequency was lowered when the combination was given, as the stemness‐related proteins (CD133, Nestin, Sox2, PDPN, and Mis‐1) were decreased, and the genes that are associated (NOTCH1, POU5F1, PDPN, and NES) were downregulated. The invasiveness of the TSs (tumor spheres) was reduced as the complex combination therapy inhibited matrix invasion as well as reduced the invasiveness of the EMT (epithelial mesenchymal transition) markers. Therefore, combination therapy of Etomoxir (ETO) with Temozolomide (TMZ) was found to be more effective in suppressing the TCA cycle, ATP production, and GBM stemness and invasiveness than that of single treatments [42]. The potential benefits of metabolic therapies in the treatment of gliomas are being assessed by early‐phase clinical studies, such as trials using the PI3K/mTOR inhibitor Paxalisib in combination with metformin, along with a ketogenic diet in early stages of glioblastoma. Although this two‐stage cohort study is still in phase 2 of the clinical trial, the ultimate result may bring fruitful results. Pharmacological inhibition of glutaminase (GLS) effectively targets glioblastoma stem‐like cells (GSCs), a subpopulation implicated in therapeutic resistance and recurrence. Both compound 968 and CB839 suppressed GSC proliferation and clonogenicity, although only CB839 directly impaired GLS enzymatic activity and TCA cycle flux. Moreover, sensitivity to the treatment correlates with GLS protein expression, which was significantly upregulated in GSCs compared to neural stem cells [22]. These findings shed light on the therapeutic relevance of GLS inhibition and demonstrate the effectiveness of pharmaco‐metabolomics in refining drug specificity and translational potential. But in case of pediatric‐specific consideration, it still remains critical, given the specific mitochondrial and lipid reprograming in aggressive pediatric gliomas that influence both the efficacy and toxicity windows.

5.2. Biomarkers and Patient Stratification

The incorporation of strong biomarkers in patient selection and therapy monitoring is necessary for translational success in GBM. Circulating metabolites and extracellular vesicle cargo reflect GBM metabolic states as shown by recent metabolomic analysis, thereby opening up new possibilities for non‐invasive disease monitoring. EVs (extracellular vesicles) can be released by a variety of cells, including malignant cells, and their cargo consists of nucleic acids, proteins, and metabolites. Hence, they are considered as a reliable source for the identification of minimally invasive biomarkers for glioblastoma [43]. In particular, liquid biopsy is emerging as a useful tool to detect and quantify tumor‐derived substances released into various body fluids such as blood, CSF, saliva, and urine, as this article highlights [44]. This is particularly relevant in GBM, where repeated surgical sampling is impractical, and tumor heterogeneity complicates tissue‐based biomarkers.

Therapeutic strategies in neuro‐oncology are rapidly evolving towards combined approaches that integrate nanomedicine with metabolic modulation, particularly for targeting the tumor microenvironment. Nanodrug delivery systems such as polymeric nanoparticles, lipid‐based carriers, and hyaluronic acid‐functionalized platforms have demonstrated enhanced penetration across the blood–brain barrier, further improving tumor selectivity and minimizing limitations of conventional glioblastoma therapies [45, 46, 47]. Combining these advanced delivery systems with hypoglycemic or metabolic modulators (e.g., metformin or glycolytic inhibitors) provides a synergistic approach to disrupt tumor bioenergetics. On the other hand, it is also reshaping the metabolic and immunological aspects of the tumor microenvironment, ultimately improving therapeutic effectiveness and overcoming resistance mechanisms.

In this particular context, EVs serve as a significant bridge between nanomedicine and tumor biology. Not only as biomarkers, but EVs are now also recognized as biocompatible nanocarriers with intrinsic targeting capabilities. This leads to efficient transport of proteins, nucleic acids, and chemotherapeutic agents across the blood–brain barrier [48, 49]. Recent studies also demonstrate that engineered EVs and hybrid nanoparticle EVs can significantly improve drug delivery efficiency, tumor targeting, and therapeutic response in glioblastoma cells [50]. Additionally, EVs also shape the tumor microenvironment by mediating intercellular communication, metabolic reprogramming, and immune modulation; hence, representing both therapeutic targets and delivery platforms [51]. Studies also show that tumor‐derived EVs can affect nanoparticle transport behavior, thus emphasizing the importance of considering the usage of EV‐nanoparticles in developing advanced therapeutic strategies [52].

These findings elaborate that nanodrug‐based delivery systems, metabolic interventions, and EV‐mediated mechanisms are well integrated within the sector of neuro‐oncology. This approach aligns with targeting both tumor metabolism and the microenvironment, which is essential for advancing the conventional glioblastoma treatment. From a clinical point of view, these advancements in the treatment strategies for neuro‐oncology may increase the adoption of combination therapies in the future. The combination therapies include the integration of nano‐formulated metabolic therapies, along with biomarker‐driven patient stratification by using EV‐based liquid biopsies. Integration and combinations like this could improve personalized treatment plans for every patient while optimizing drug delivery across the blood‐brain barrier, and enabling real‐time monitoring of therapeutic response in them.

6. Conclusion and Future Directions

For brain tumor survival and therapy resistance, non‐glycolytic pathways are crucial as they provide alternative sources of energy and essential macromolecules (for the rapid growth and proliferation of cells). These alternative metabolic routes, including lipid production, DNA synthesis, and amino acid metabolism, play an important role in the maintenance of tumors and resistance to chemotherapy. For instance, subtypes of glioma show the necessity of personalized treatment approaches by exhibiting specific metabolic profiles. Targeting metabolic characteristics of specific tumors and tailoring specific therapy according to that can play a great role in improving treatment outcomes [53]. Moreover, because of having interconnected pathways significant for cellular energy, homeostasis, and dysregulation linked to various diseases, FAO, mitochondrial dynamics, and amino acid metabolism can be offered as actionable targets. Especially in the case of cancer or tumor cells, FAO, as a core energy‐producing process within the mitochondria, can also be targeted to influence energy supply. Thus, lipid metabolism, nucleotide metabolism, and amino acid metabolism provide a decent therapeutic innovation for brain tumors by offering an alternative to the glycolytic pathways. In fact, some studies suggest that when it comes to reducing tumor proliferation and therapy resistance, the drugs which affect glucose, lipid, or nucleotide metabolism often show promising results [54]. There is strong evidence that combining metabolic inhibitors with chemotherapy or immunotherapy can significantly enhance their anti‐tumor efficacy in animal models. But drugs targeting these metabolic pathways are mostly at the preclinical stage currently [7]. In conclusion, the development of useful drugs targeting tumor metabolic pathways apart from glycolysis pathways, despite having a bright future, still has a long way to go.

Author Contributions

Iffat Islam Mayesha: conceptualization, writing – review and editing, supervision, and writing – original draft. Zubaier Ahmed: conceptualization, methodology, supervision, writing – review and editing, and writing – original draft. Ammarah Laaika Mohiuddin: writing – original draft and data curation. Faiza Fairuz Muskan: data curation, visualization, and writing – original draft. Saiful Islam: writing – original draft and data curation. Sharmin Jahan Sumaya: writing – original draft, data curation, and methodology.

Funding

The authors have nothing to report.

Ethics Statement

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Transparency Statement

The corresponding author, Zubaier Ahmed, affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Data Availability Statement

Data sharing is not applicable as no new data was generated, or the article describes entirely theoretical research.