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Altered metabolism in cancer: insights into energy pathways and therapeutic targets

Abstract

Cancer cells undergo significant metabolic reprogramming to support their rapid growth and survival. This study examines important metabolic pathways like glycolysis, oxidative phosphorylation, glutaminolysis, and lipid metabolism, focusing on how they are regulated and their contributions to the development of tumors. The interplay between oncogenes, tumor suppressors, epigenetic modifications, and the tumor microenvironment in modulating these pathways is examined. Furthermore, we discuss the therapeutic potential of targeting cancer metabolism, presenting inhibitors of glycolysis, glutaminolysis, the TCA cycle, fatty acid oxidation, LDH, and glucose transport, alongside emerging strategies targeting oxidative phosphorylation and lipid synthesis. Despite the promise, challenges such as metabolic plasticity and the need for combination therapies and robust biomarkers persist, underscoring the necessity for continued research in this dynamic field.

Graphical Abstract

Introduction

Cancer remains one of the leading causes of morbidity and mortality worldwide. Despite significant advancements in our understanding and treatment of cancer, the complexity and adaptability of malignant cells continue to pose ongoing challenges [1, 2]. One of the hallmark features of cancer cells is their altered metabolism, which supports rapid growth and survival in hostile environments [3, 4]. The study of cancer metabolism dates back to the early 20th century, when Otto Warburg first observed that cancer cells preferentially utilize glycolysis for energy production, even in sufficient oxygen – a phenomenon now known as the Warburg effect [5]. Warburg’s discovery was revolutionary, challenging the prevailing belief that oxidative phosphorylation in mitochondria was the primary energy source for all cells, including cancerous ones. Over the decades, subsequent research has expanded our understanding of the metabolic reprogramming in cancer cells, revealing a complex network of altered pathways that contribute to tumorigenesis and cancer progression.

The metabolic reprogramming in cancer cells is not limited to enhanced glycolysis. It encompasses a range of alterations in various metabolic pathways, including increased glucose uptake and lactate production even under aerobic conditions (aerobic glycolysis) [6], dependency on glutamine for anaplerosis and biosynthesis (glutaminolysis) [3], enhanced lipogenesis and altered fatty acid oxidation (lipid metabolism) [3], and changes in the metabolism of amino acids like serine and glycine [3]. Despite the emphasis on glycolysis, many cancer cells still rely on mitochondrial respiration for survival and proliferation. These alterations are driven by oncogenes and tumor suppressor genes, which rewire cellular metabolism to meet the demands of rapid cell division, resist cell death, and adapt to hypoxic conditions within the tumor microenvironment (TME) [7].

At the molecular level, several key regulators orchestrate the metabolic reprogramming in cancer cells. Oncogenes such as MYC and RAS promote anabolic processes and increase the uptake and utilization of nutrients [8]. When lost, tumor suppressor genes like TP53 and LKB1 can enhance glycolysis and biosynthetic pathways [9, 10]. Hypoxia-inducible factors (HIFs) induce the expression of glycolytic enzymes and glucose transporters in response to low oxygen levels [11, 12]. The AMP-activated protein kinase (AMPK) acts as a cellular energy sensor and regulator, balancing energy supply and demand [13, 14], while the mTOR signaling pathway promotes protein synthesis and cell growth, integrating signals from nutrients and growth factors [15].

Recognizing altered metabolism as a cancer hallmark has opened new avenues for therapeutic intervention [16, 17]. Targeting metabolic pathways offers the potential to disrupt the energy supply and biosynthetic processes essential for tumor growth [18, 19]. Some promising therapeutic strategies include inhibitors of glycolysis that target key glycolytic enzymes such as hexokinase and lactate dehydrogenase, glutamine antagonists that inhibit glutamine uptake or metabolism, lipid metabolism inhibitors that target fatty acid synthesis and oxidation pathways, and mitochondrial metabolism modulators that disrupt mitochondrial function and oxidative phosphorylation. Clinical trials are exploring these and other metabolic targets to develop effective treatments with minimal toxicity to normal cells.

This review aims to provide a detailed and integrated overview of the current understanding of altered metabolism in cancer. It explores key energy pathways, including glycolysis, oxidative phosphorylation, glutaminolysis, and lipid metabolism, highlighting their roles and regulatory mechanisms in cancer cells. The review also examines the regulation of these pathways by oncogenes and tumor suppressors, epigenetic modifications, and microenvironmental factors. Furthermore, it discusses therapeutic targets in cancer metabolism, including glycolysis inhibitors, oxidative phosphorylation, glutaminase, and lipid metabolism. Finally, it addresses challenges and future directions in overcoming metabolic plasticity, developing combination therapies, and identifying biomarkers for metabolic targeting, aiming to inform the development of novel therapeutic approaches.

Metabolic reprogramming in cancer

Cancer cells exhibit profound alterations in their metabolism, supporting their rapid growth, survival, and ability to adapt to diverse and often hostile environments. Herein, we shed light on two critical aspects of metabolic reprogramming in cancer: the Warburg effect and additional metabolic pathways that extend beyond this well-known phenomenon.

The Warburg effect is one of cancer cells’ most well-characterized metabolic alterations. Warburg observed that cancer cells favor glycolysis for energy production, even with adequate oxygen [20]. This preference for glycolysis over oxidative phosphorylation, despite its lower efficiency in ATP production, is a hallmark of many types of cancer [21].

In normal cells, glycolysis is typically followed by oxidative phosphorylation in the mitochondria under aerobic conditions, yielding up to 36 molecules of ATP per glucose molecule [22]. In contrast, glycolysis alone produces only 2 ATP molecules per glucose molecule. However, cancer cells compensate for this inefficiency by upregulating glucose transporters and glycolytic enzymes, leading to an increased glycolytic flux [22, 23]. This metabolic reprogramming supports rapid cell proliferation by providing both ATP and metabolic intermediates for biosynthetic processes, such as nucleotide and lipid synthesis.

Various oncogenic signals and mutations in tumor suppressor genes drive the Warburg effect. For instance, activating oncogenes like MYC and RAS enhances glycolytic enzyme expression [24], while mutations in tumor suppressors like TP53 and PTEN further promote glycolysis [25, 26]. Additionally, HIFs, which are stabilized in low oxygen conditions commonly found in tumors, increase the expression of glycolytic enzymes and glucose transporters, further reinforcing the Warburg effect [24].

While the Warburg effect is central to cancer metabolism, it is not the sole metabolic alteration observed in cancer cells. Several other metabolic pathways are reprogrammed to support the unique demands of tumor growth and survival. Glutaminolysis highlights cancer cells’ dependence on the amino acid glutamine, serving as a key nitrogen donor for nucleotide and amino acid biosynthesis and replenishing tricarboxylic acid (TCA) cycle intermediates. Enzymes such as glutaminase (GLS) are frequently upregulated, indicating potential therapeutic targets [27, 28]. Alterations in lipid metabolism, including enhanced de novo lipogenesis and changes in fatty acid oxidation, provide essential components for membrane biogenesis and additional energy sources. Despite the Warburg effect suggesting a reduced reliance on oxidative phosphorylation, many cancer cells still utilize mitochondrial respiration to meet energy demands and support biosynthetic pathways, playing crucial roles in apoptosis regulation and reactive oxygen species (ROS) production [29]. Beyond glutamine, other amino acids like serine and glycine are critical, with the serine-glycine-one-carbon (SGOC) metabolism pathway supporting nucleotide synthesis and redox balance. Enzymes such as serine hydroxymethyltransferase (SHMT) and glycine decarboxylase (GLDC) are often upregulated, underscoring their importance in cancer metabolism [29, 30].

While the Warburg effect has been widely studied, it is important to consider the interconnectedness of metabolic pathways such as glutaminolysis, lipid metabolism, and SGOC metabolism, which cancer cells utilize to meet their biosynthetic and energy demands. Targeting single pathways, like inhibiting GLS in glutaminolysis, has shown potential in certain cancers, but a combined therapeutic approach could yield better results. For example, combining glycolysis inhibitors with mitochondrial respiration inhibitors could cut off cancer cells’ access to multiple energy sources. Moreover, further research into how cancer cells switch between these pathways in response to treatments is crucial, as understanding this metabolic plasticity may reveal new vulnerabilities.

Metabolic synthetic lethalities in cancer

Metabolic synthetic lethality refers to the concept where the combination of a genetic mutation and a metabolic vulnerability leads to cancer cell death, while each factor alone does not. In cancer, this approach exploits the specific metabolic dependencies of tumor cells to induce selective cell death. Tumor cells often have altered metabolic pathways that can create unique vulnerabilities [31, 32].

Metabolic synthetic lethality offers a promising strategy for targeting tumors with specific genetic alterations, particularly those affecting the TCA cycle. This approach capitalizes on the unique metabolic dependencies created by mutations in key TCA cycle enzymes, leading to vulnerabilities that can be therapeutically exploited. Among the enzymes frequently mutated in various cancers are succinate dehydrogenase (SDH), fumarate hydratase (FH), and isocitrate dehydrogenase (IDH). These mutations result in profound metabolic alterations that create therapeutic opportunities. Understanding how these mutations influence tumor metabolism is crucial for developing targeted treatments.

SDH mutations are genetic alterations that lead to the accumulation of succinate, disrupting the TCA cycle and causing metabolic imbalances in tumor cells. Mutations in SDH result in the accumulation of succinate, which profoundly alters tumor metabolism and creates several vulnerabilities. One significant adaptation in SDH-deficient tumors is an increased reliance on glycolysis for energy production. This heightened glycolytic activity represents a potential therapeutic target; inhibitors of glycolytic enzymes or glucose transporters may selectively affect these tumors [33, 34]. For example, in SDH-deficient tumors, which rely heavily on glycolysis due to TCA cycle impairment, WZB117, a GLUT1 inhibitor, can effectively reduce glucose uptake, decrease intracellular ATP, downregulate glycolytic enzymes, and inhibit tumor growth, making it a promising candidate for enhancing treatment outcomes and sensitizing tumors to other therapies [35]. Additionally, to compensate for the disrupted TCA cycle, SDH-mutant cells often become heavily dependent on glutamine metabolism. Targeting enzymes involved in glutamine utilization, such as glutaminase, could selectively impair these cancer cells. For instance, studies indicate that SDHB knockout cells exhibit heightened sensitivity to GLS-1 inhibitors, suggesting that targeting this enzyme could selectively impair the growth of SDH-mutant tumors [36, 37]. Moreover, the accumulation of succinate and subsequent disruptions in cellular redox balance can lead to increased oxidative stress. Therapeutic strategies that further elevate reactive oxygen species levels might overwhelm the oxidative stress tolerance of these cells, leading to selective cell death.

FH mutations cause fumarate accumulation, leading to distinct metabolic dependencies and vulnerabilities. One notable consequence is the upregulation of heme synthesis, as FH-mutant cells attempt to manage excess fumarate. Targeting heme oxygenase-1 (HO-1), which is involved in heme degradation, has shown potential in selectively targeting FH-deficient tumors [38, 39]. Another vulnerability arises from the dependency of some FH-deficient cells on argininosuccinate synthase to handle excess fumarate. Inhibiting this enzyme could provide a synthetic lethal approach. Additionally, like SDH-deficient tumors, FH-deficient cells often exhibit impaired oxidative phosphorylation and increased reliance on glycolysis [38, 39]. Combining glycolysis inhibitors with other agents could be a potent strategy against tumors. For example, recent studies demonstrated that combining arsenic trioxide (ATO) with HO-1 inhibitors enhances cytotoxicity, induces apoptosis, and modulates autophagy via an ROS-dependent mechanism in pancreatic ductal adenocarcinoma (PDAC) cells [40], while simultaneously targeting HO-1 and σR proteins with novel hybrid compounds shows enhanced antiproliferative activity in DU145 prostate and U87MG glioblastoma cells, highlighting promising strategies for developing more effective and less toxic anticancer therapies [41].

Moreover, mutations in IDH lead to the production of 2-hydroxyglutarate (2-HG), which induces distinctive metabolic changes in tumors. One major alteration is NAD + depletion, a consequence of altered metabolic pathways. IDH-mutant tumors are particularly sensitive to further NAD + depletion, suggesting that targeting NAD + salvage pathways could selectively impair these cells [42, 43]. Such as, treatment with NAMPT inhibitors resulted in significant reductions in intracellular NAD + levels and induced cell death specifically in IDH1/2-mutant cancer cell lines. The depletion of NAD + activated the energy sensor AMPK, triggered autophagy, and ultimately led to cytotoxicity in these cancer cells. This demonstrates a clear therapeutic strategy: by inhibiting NAMPT, which is already compromised in IDH1-mutant cells, it is possible to selectively target and kill these cancer cells while sparing normal cells that do not share this metabolic vulnerability [44, 45]. Furthermore, many IDH-mutant tumors become dependent on glutamine as a source of α-ketoglutarate to produce 2-HG [43, 46]. Targeting glutamine metabolism in these cancers could therefore be an effective therapeutic strategy. Additionally, IDH mutations can alter lipid metabolism, affecting lipid synthesis and fatty acid oxidation. Exploiting these metabolic changes through inhibition of key lipid metabolism enzymes might offer further therapeutic opportunities [43].

Overall, metabolic synthetic lethality offers a promising approach for cancer treatment by targeting the unique metabolic dependencies caused by TCA cycle mutations, enabling greater selectivity and reduced toxicity to normal cells. This strategy also has the potential to overcome resistance to conventional therapies and enhance efficacy when combined with targeted treatments or immunotherapies. Moreover, identifying specific TCA cycle mutations as biomarkers can help tailor therapies to patients most likely to benefit, making this approach a significant advancement in developing personalized and more effective cancer treatments.

Key energy pathways

Glycolysis

Glycolysis, the central metabolic pathway that converts glucose into pyruvate, plays a pivotal role in the altered metabolism of cancer cells [47, 48]. This process, fundamental to normal and malignant cells, has been extensively studied for its implications in cancer biology and therapeutic targeting. In cancer, glycolysis operates under significantly different dynamics than normal cells, often called the Warburg effect.

Cancer cells undergo significant metabolic alterations to support rapid growth and proliferation [49, 50]. One of the most notable changes is the upregulation of glucose transporters, particularly GLUT1, which enhances glucose influx into the cells [51, 52]. For example, a recent study has reported that GLUT1 is highly expressed in lung adenocarcinoma (LUAD), and its elevated levels are associated with poor patient survival. Functional studies have demonstrated that GLUT1 plays an oncogenic role in LUAD, as its knockdown results in decreased cell proliferation, colony formation, migration, and invasion while also inducing apoptosis in LUAD cells. Mechanistically, GLUT1 interacts directly with phosphorylated epidermal growth factor receptor (p-EGFR), preventing EGFR protein degradation via ubiquitin-mediated proteolysis [53]. These findings suggest that targeting GLUT1 could be a promising therapeutic strategy. Notably, combining GLUT1 inhibitors with EGFR-tyrosine kinase inhibitors (TKIs) like Gefitinib may enhance therapeutic efficacy in treating LUAD [53]. This increased glucose uptake is the foundation for 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) imaging, a common technique used in cancer diagnosis. In addition to increased glucose uptake, cancer cells exhibit an enhanced glycolytic flux. This is characterized by higher glycolysis rates than normal cells, facilitated by upregulating key glycolytic enzymes such as hexokinase II [23]. Despite the presence of oxygen, cancer cells preferentially convert pyruvate to lactate via lactate dehydrogenase A (LDHA) [51], rather than oxidizing it in the mitochondria. This phenomenon, known as the Warburg effect, is a hallmark of cancer metabolism.

Various factors regulate the switch to glycolysis in cancer cells. Oncogenes such as HIF-1α, c-Myc, and Akt are known to promote glycolysis [51], whereas tumor suppressors like p53 act to suppress it. The loss of p53 in cancer cells often promotes a glycolytic phenotype [51]. For instance, HIF-1α is a key regulator of cellular response to hypoxia and promotes glycolysis through several mechanisms: it increases the expression of glucose transporters GLUT1 and GLUT3, enhancing glucose uptake; upregulates nearly all glycolytic enzymes, including hexokinases (HK1 and HK2), phosphofructokinases (PFKL and PFKP), and pyruvate kinase M (PKM); and enhances the expression of lactate dehydrogenase A (LDHA) and monocarboxylate transporter 4 (MCT4), facilitating lactate production and export. Additionally, HIF-1α reduces oxidative phosphorylation by promoting mitophagy and decreasing mitochondrial biogenesis [54]. While c-Myc directly activates the transcription of many glycolytic enzyme genes and cooperates with HIF-1α to enhance the transcription of key glycolytic enzymes such as hexokinase 2 (HK2) and pyruvate dehydrogenase kinase 1 (PDK1). This collaboration between c-Myc and HIF-1α leads to additive increases in glucose uptake and lactate production [55]. Furthermore, activation of signaling pathways like PI3K/Akt/mTOR enhances glycolysis, contributing to the metabolic reprogramming observed in cancer cells. For example, Akt activation increases glucose uptake by inhibiting thioredoxin-interacting protein (TXNIP), leading to higher expression of glucose transporters GLUT1 and GLUT4 on the cell surface [56]. It enhances glycolytic enzyme activity by phosphorylating and activating key enzymes such as hexokinase 2 (HK2) and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase (PFKFB2), promoting glycolysis [56]. The PI3K/Akt pathway shifts metabolism towards aerobic glycolysis, making cancer cells dependent on glucose [56]. Akt also regulates metabolism through transcription factors by activating mTORC1 and inhibiting FOXO, and it may influence mitochondrial function to sustain TCA cycle flux [57]. Additionally, the pathway causes long-term metabolic reprogramming and interacts with other signaling pathways like HIF-1α to modulate glucose metabolism, contributing to the complex metabolic changes in cancer cells [58].

Targeting glycolysis offers a promising avenue for cancer therapy, aiming to exploit the metabolic vulnerabilities of cancer cells. Several strategies are being explored, including inhibition of glycolytic enzymes, targeting glucose transporters, and exploiting lactate production. Hexokinase inhibitors like 2-deoxyglucose (2-DG) disrupt glycolysis and induce cell death in cancer cells [52, 59]. Small molecules that promote the tetrameric, active form of PKM2 can shift metabolism away from glycolysis towards oxidative phosphorylation, inhibiting cancer cell proliferation [59, 60]. Inhibitors of GLUT1 can restrict glucose uptake, starving cancer cells of their primary energy source [52, 59]. Moreover, inhibiting LDHA blocks the conversion of pyruvate to lactate, accumulating toxic levels of pyruvate and disrupting redox balance [59, 61]. Agents that neutralize the acidic tumor microenvironment can impair cancer cell invasion and enhance immune cell activity [59, 62]. Combining glycolysis inhibitors with conventional therapies such as chemotherapy, radiation, or immunotherapy may enhance overall efficacy by concurrently targeting multiple cancer cell survival mechanisms. Figure 1 illustrates the glycolytic pathway in cancer cells, highlighting key steps, regulatory roles of oncogenes and tumor suppressors, the Warburg effect, reduced reliance on mitochondrial metabolism, potential therapeutic targets, and the clinical relevance of glycolytic metabolites as biomarkers and in 18 F-FDG PET imaging (Fig. 1).

Fig. 1
figure 1

This figure illustrates glycolysis as a key energy pathway in cancer cells, highlighting the pathway's steps from glucose to pyruvate, including all intermediate metabolites and enzymes (e.g., hexokinase, phosphofructokinase, pyruvate kinase). The roles of oncogenes and tumor suppressors in regulating glycolysis are indicated. The Warburg effect is highlighted by showing increased glycolytic flux and lactate production despite the presence of oxygen, with pyruvate diverted to lactate dehydrogenase instead of mitochondria. The contrast between glycolysis and oxidative phosphorylation in mitochondria is depicted, indicating the reduced reliance on mitochondrial metabolism in cancer cells. Potential therapeutic targets within the glycolytic pathway are showed, and suggestions for combining glycolytic inhibitors with other treatments are included. The clinical relevance is emphasized by showing how glycolytic metabolites or enzyme levels can serve as biomarkers for cancer diagnosis, with reference to 18F-fluorodeoxyglucose (FDG) PET imaging used for detecting high glycolytic activity in tumors

Oxidative phosphorylation

Oxidative phosphorylation (OXPHOS) is a fundamental metabolic pathway for ATP production through the mitochondria’s electron transport chain (ETC). Despite the prominence of the Warburg effect, which describes cancer cells’ preference for glycolysis even under aerobic conditions, OXPHOS remains crucial in many cancers and plays an important role in the progression of cancer and could be a potential therapeutic target (Fig. 2). While many cancer cells exhibit increased glycolysis, they often maintain functional OXPHOS. For example, leukemias and lymphomas can maintain functional OXPHOS despite their glycolytic activity, and similar observations are seen in pancreatic ductal adenocarcinoma, where OXPHOS remains active in this aggressive cancer type. Some melanomas, particularly the high OXPHOS subtype, exhibit increased OXPHOS alongside glycolysis, and endometrial carcinoma cells can also persist with active OXPHOS [63]. This dual capability allows cancer cells to adapt to varying environmental conditions, such as oxygen and nutrient availability fluctuations. OXPHOS serves as an additional ATP source when insufficient glycolysis occurs, ensuring a continuous energy supply essential for rapid cell division and growth [64, 65]. For example, acute myeloid leukemia (AML) cells demonstrate this dual metabolic capability [66, 67]. While many cancer cells primarily rely on glycolysis (the Warburg effect), AML cells, particularly leukemic stem cells (LSCs), strongly prefer OXPHOS [66, 68]. This metabolic flexibility allows AML cells to adapt to different microenvironments and resist chemotherapy. For instance, studies have shown that chemotherapy-resistant AML cells have enhanced mitochondrial respiration capacity. These cells, characterized by a low SoNar ratio, primarily reside in the vascular niche and are enriched with functional leukemia-initiating cells. The SoNar-low AML cells demonstrate higher levels of oxidative phosphorylation, contributing to their resistance to cytosine arabinoside (Ara-C), a common chemotherapy drug [66]. Furthermore, research has found that treatment-resistant AML LSCs can maintain OXPHOS even under challenging conditions [67]. This metabolic adaptation allows them to survive and potentially lead to disease relapse. The ability to switch between glycolysis and OXPHOS enables these cells to thrive in various oxygen and nutrient conditions within the bone marrow microenvironment [67, 69]. This dual metabolic capability in AML cells highlights the importance of targeting glycolysis and OXPHOS in developing more effective treatments. Cancer cells’ ability to switch between glycolysis and OXPHOS, known as metabolic flexibility, is vital for survival [70]. This adaptability supports cancer cells in hostile microenvironments, including hypoxia and nutrient scarcity [71]. For instance, cancer cells may rely more on OXPHOS during metastasis to meet their energy demands. This metabolic flexibility is a key factor in the resilience and aggressiveness of cancer cells [72].

Fig. 2
figure 2

This figure illustrates the role of Oxidative Phosphorylation (OXPHOS) in cancer metabolism, detailing key components, alterations, and therapeutic targets. The figure depicts the mitochondrial structure, including the electron transport chain (ETC) complexes I-IV and ATP synthase (Complex V), highlighting the flow of electrons from NADH and FADH2 to oxygen, producing water and ATP via chemiosmosis and the proton gradient. The figure also shows common cancer-associated alterations, such as the Warburg effect, mitochondrial dysfunction, and increased reactive oxygen species (ROS) production. Mutations in mtDNA genes can disrupt electron flow, leading to increased ROS production, which damages cellular components like DNA, proteins, and lipids, promoting further mutations and cancer progression. These mutations can also activate oncogenic signaling pathways such as NF-κB and HIF-1α. The bottom panel emphasizes therapeutic strategies, including ETC complex inhibitors, agents affecting mitochondrial biogenesis, and ROS modulation

Furthermore, mitochondrial dynamics and function are often altered in cancer cells. Proteins like Drp1 (dynamin-related protein 1) and Mfn1/2 (mitofusins) regulate mitochondrial fission and fusion processes, affecting OXPHOS efficiency [73, 74]. Additionally, cancer cells may enhance mitochondrial biogenesis through factors like PGC-1α (peroxisome proliferator-activated receptor gamma coactivator 1-alpha) to boost their OXPHOS capacity. These adaptations ensure that mitochondria meet proliferating cancer cells’ increased energetic and biosynthetic demands [74, 75].

Moreover, key oncogenes and tumor suppressors modulate OXPHOS in cancer. For example, c-Myc enhances mitochondrial biogenesis and respiration, supporting rapid cell growth [74, 75]. Conversely, mutations in tumor suppressors like p53 can disrupt mitochondrial function and OXPHOS, contributing to tumor metabolic reprogramming. These genetic alterations highlight the complex regulation of OXPHOS in cancer and its contribution to tumorigenesis.

Hypoxia-inducible factors (HIFs) are transcription factors activated under low oxygen conditions, playing a critical role in reprogramming cellular metabolism [76, 77]. HIF-1α typically promotes glycolysis and suppresses OXPHOS by inducing pyruvate dehydrogenase kinase (PDK), which inhibits the entry of pyruvate into the tricarboxylic acid (TCA) cycle [78, 79]. However, HIF-2α has been shown to maintain OXPHOS in certain cancer contexts, illustrating the complexity of metabolic regulation under hypoxic conditions [12]. For example, one study demonstrated that HIF-1α primarily regulates VEGF expression in response to hypoxia and IGF-I in MCF-7 cells, while HIF-2α plays a dominant role in driving VEGF and other target gene expression in renal carcinoma cells with VHL loss. The findings also revealed a reciprocal relationship between HIF-1α and HIF-2α, where silencing HIF-2α enhances HIF-1α–mediated VEGF expression under hypoxic conditions. Additionally, the small-molecule inhibitor NSC-134,754 was shown to effectively reduce both HIF-1α and HIF-2α protein levels and VEGF expression, presenting a promising therapeutic strategy for targeting the HIF pathway in cancers [80]. In contrast, another study focusing on gastric cancer found that HIF-1α, but not HIF-2α, dimerizes with HIF-1β to regulate the expression of angiogenesis and glucose metabolism-related target genes, such as VEGF, in response to hypoxia. This emphasizes the critical role of HIF-1α in early-stage gastric cancer development and highlights important insights into the HIF pathway’s role in tumor progression, offering potential targets for therapeutic intervention [81].

OXPHOS is also implicated in cancer cell invasion and metastasis [63, 64]. Mitochondrial ATP production supports the energy-intensive processes of cell migration and invasion. Additionally, reactive oxygen species (ROS) generated by OXPHOS can activate signaling pathways that promote metastatic behaviors. OXPHOS in mitochondria is a major source of ROS in cells, as electron transport can lead to electron leakage and partial oxygen reduction, forming superoxide anions that convert to other ROS like hydrogen peroxide [82]. ROS are crucial signaling molecules at moderate levels, activating pathways in cancer progression and metastasis [83]. They can trigger several pro-metastatic signaling cascades, including the NF-κB pathway [84], which regulates genes related to cell survival, proliferation, and metastasis, and MAPK pathways that influence cell proliferation, survival, and migration [82]. Additionally, ROS can activate the PI3K-Akt pathway, promoting cell survival and metastasis [84]. ROS enhance cell motility and invasion by increasing the expression and activity of matrix metalloproteinases (MMPs), which degrade the extracellular matrix [82, 84]. They also induce epithelial-mesenchymal transition (EMT), endowing cancer cells with a more invasive phenotype, and stimulate the production of pro-angiogenic factors like VEGF, facilitating new blood vessel formation to support metastasis [83, 84]. Moreover, ROS contributes to anoikis resistance, allowing cancer cells to survive in circulation, establish metastases at distant sites, and aid in forming pre-metastatic niches in distant organs, creating environments conducive to secondary tumor establishment [85]. This highlights the role of OXPHOS in energy production and in facilitating cancer progression and metastasis [86, 87].

Similarly, cancer stem cells (CSCs) rely on OXPHOS for their metabolic flexibility and survival in diverse tumor microenvironments. CSCs are a subpopulation of cancer cells within a tumor that can self-renew, differentiate into various cell types, and drive tumor growth and recurrence. This metabolic flexibility allows CSCs to switch between glycolysis and OXPHOS, aiding survival in various tumor microenvironments and supporting therapy resistance. Furthermore, enhanced mitochondrial biogenesis and effective ROS management, regulated by key signaling pathways such as PI3K/AKT/mTOR and AMPK, further support the reliance of CSCs on OXPHOS for their mitochondrial function and energy metabolism [88, 89]. The reliance on OXPHOS makes CSCs resistant to conventional therapies targeting glycolysis-dependent cells, while their ability to enter quiescence and undergo EMT enhances their resilience and metastatic potential [90, 91]. Targeting OXPHOS in CSCs is an emerging strategy to eradicate these resilient cell populations and improve therapeutic outcomes.

Several agents targeting OXPHOS are under investigation, including metformin [92], phenformin [93], and IACS-010759 [94]. These inhibitors reduce ATP production, induce energetic stress, and selectively kill cancer cells with high OXPHOS dependence. Combining OXPHOS inhibitors with other treatments, such as glycolysis inhibitors or conventional chemotherapies, can enhance anti-tumor efficacy. This dual inhibition approach exploits the metabolic flexibility of cancer cells, pushing them beyond their energetic limits. Moreover, mitochondrial uncouplers, such as 2,4-dinitrophenol (DNP), dissipate the proton gradient across the mitochondrial membrane, reducing ATP synthesis and increasing metabolic stress [95, 96]. These agents show potential in preclinical models, though their use requires careful dosing due to potential toxicity [97, 98]. The development of safer and more effective mitochondrial uncouplers could provide another avenue for targeting OXPHOS in cancer.

Glutaminolysis

Glutaminolysis is a metabolic process that converts glutamine to glutamate and subsequently to α-ketoglutarate, which can enter the tricarboxylic acid (TCA) cycle to produce energy and support biosynthetic processes. This pathway is particularly important in cancer metabolism (Fig. 3), as many cancer cells exhibit an increased dependence on glutamine, making it a critical fuel source for their growth and survival [99].

Fig. 3
figure 3

This figure illustrates glutaminolysis as a Key Energy Pathway in Cancer. Glutamine is transported into cancer cells and converted to glutamate by glutaminase (GLS). Glutamate is further converted to α-ketoglutarate (α-KG), entering the TCA cycle to support energy production. Glutaminolysis also replenishes TCA cycle intermediates and produces biosynthetic precursors for macromolecule synthesis. Additionally, it generates NADPH to maintain redox balance. Key enzymes in this pathway are potential therapeutic targets for cancer treatment

Glutaminolysis begins with the uptake of glutamine, an abundant amino acid in the body, into the cell [100]. Once inside, glutamine is converted to glutamate by the enzyme glutaminase (GLS). Glutamate can then be further converted to α-ketoglutarate by either glutamate dehydrogenase (GDH) or transaminases. α-Ketoglutarate enters the TCA cycle, contributing to the production of ATP and providing intermediates for synthesizing nucleotides, amino acids, and lipids [101, 102]. This metabolic pathway is particularly active in rapidly proliferating cells, including cancer cells, which require a constant supply of these biosynthetic precursors.

Cancer cells often exhibit altered metabolism to support their rapid growth and proliferation. One of these alterations is an increased reliance on glutamine, making glutaminolysis a critical pathway in cancer metabolism. Glutamine provides a carbon source for the TCA cycle and nitrogen for synthesizing nucleotides and amino acids, essential for DNA replication and protein synthesis [100]. This contribution to the TCA cycle supports energy production and the synthesis of other metabolic intermediates [103]. Simultaneously, the nitrogen atoms in glutamine are utilized in the biosynthesis of nucleotides, the building blocks of DNA and RNA, and other amino acids [104]. For example, in rapidly dividing cells like cancer cells or immune cells responding to infection, glutamine is often consumed at high rates to support the increased demand for nucleotide synthesis during DNA replication and amino acid production for protein synthesis [105]. This makes glutamine a critical nutrient for cell growth, proliferation, and survival, particularly when rapid cell division or protein production is required.

Glutaminolysis supports cancer cell survival under various stress conditions, such as nutrient deprivation and hypoxia. By providing intermediates for the TCA cycle, glutaminolysis helps maintain cancer cells’ energy balance and redox status. For example, in renal cell carcinoma and glioblastoma cells, which exhibit a high dependency on glutamine. Under conditions of nutrient deprivation, these cancer cells increase the expression of glutamine transporters like SLC1A5, facilitating enhanced uptake of glutamine. Once inside the cell, glutamine is converted to glutamate by glutaminase, and subsequently, glutamate can be transformed into α-KG through the action of glutamate dehydrogenase (GLUD). This α-KG then enters the TCA cycle, replenishing its intermediates and sustaining energy production necessary for cell survival and growth during stress conditions [29, 106]. Additionally, cancer cells often rely on glutaminolysis to support their metabolic needs. The conversion of glutamine to α-KG not only fuels the TCA cycle but also contributes to the synthesis of nucleotides and amino acids, which are vital for cellular functions and proliferation. This metabolic adaptation allows cancer cells to thrive even when oxygen levels are low, demonstrating the importance of glutaminolysis in maintaining their viability under adverse conditions [100, 107].

Many cancer cells exhibit what is known as “glutamine addiction,” where they become highly dependent on glutamine for their growth and survival [108]. This phenomenon is driven by the activation of oncogenes such as MYC, which upregulate glutamine transporters and enzymes involved in glutaminolysis. For example, MYC increases the expression of glutaminase, enhancing the conversion of glutamine to glutamate and subsequently fueling the TCA cycle and biosynthetic processes [108]. This metabolic reprogramming towards increased glutaminolysis provides cancer cells with a growth advantage but also creates a vulnerability. Targeting glutamine metabolism can selectively impair the growth of glutamine-dependent cancer cells while sparing normal cells that are less reliant on this pathway.

The dependence of many cancers on glutaminolysis presents a potential target for therapeutic intervention. Inhibitors of glutaminase, such as CB-839, have shown promise in preclinical and clinical studies by reducing the proliferation of cancer cells and enhancing the efficacy of other anticancer therapies. These inhibitors block the conversion of glutamine to glutamate, disrupting the supply of α-ketoglutarate to the TCA cycle and reducing the production of ATP and biosynthetic precursors. Furthermore, combining glutaminase inhibitors with other metabolic inhibitors or conventional therapies could provide a more effective approach to cancer treatment. For instance, targeting glutaminolysis and glycolysis can simultaneously disrupt the two major metabolic pathways in cancer cells, leading to metabolic stress and cell death. Additionally, therapies that induce oxidative stress, such as radiation or certain chemotherapeutics, may be more effective when combined with glutaminase inhibitors, as cancer cells become more susceptible to oxidative damage when their antioxidant defenses are compromised. For example, in pre-clinical studies, CB-839 demonstrated significant antiproliferative effects in the triple-negative breast cancer (TNBC) cell line HCC-1806 by markedly reducing glutamine consumption, glutamate production, and levels of several tricarboxylic acid cycle intermediates, as well as decreasing oxygen consumption and glutathione levels. However, CB-839 showed limited activity in the estrogen receptor-positive cell line T47D. The sensitivity of TNBC cells to CB-839 was associated with their reliance on extracellular glutamine for growth, elevated intracellular levels of glutamate and glutamine, and higher expression of GAC. Additionally, CB-839 exhibited notable antitumor efficacy in xenograft models, including a patient-derived TNBC model and the basal-like HER2(+) cell line JIMT-1, both as a single agent and in combination with paclitaxel [109]. Moreover, another study evaluated the effects of CB-839 on radiation sensitivity using human HNSCC cell lines and xenograft models. The combination of IR and CB-839 significantly reduced cell survival, spheroid size, and tumor growth compared to either treatment alone. Additionally, CB-839 decreased the oxygen consumption rate/extracellular acidification rate ratio in CAL-27 and HN5 cells and increased oxidative stress and DNA damage in irradiated CAL-27 cells. These findings suggest that combining IR with CB-839 enhances the anti-tumor response in HNSCC, supporting further clinical investigation of this combination therapy [110].

Lipid metabolism

Lipid metabolism, a crucial cellular process, involves lipids’ synthesis, degradation, and utilization. In cancer, lipid metabolism is often reprogrammed to meet malignant cells’ high energy demands and rapid growth rates (Fig. 4). This metabolic reprogramming is a hallmark of cancer, enabling tumor cells to sustain their proliferative capabilities, evade apoptosis, and adapt to the tumor microenvironment [111, 112].

Fig. 4
figure 4

This figure illustrates the comprehensive pathways of lipid metabolism in cancer cells, highlighting key processes such as lipid uptake, storage, fatty acid synthesis, β-oxidation, and cholesterol metabolism. Lipid uptake involves lipoprotein lipase (LPL), fatty acid transporters (FAT/CD36, FABP), and the formation of lipid droplets. Fatty acid synthesis is detailed from the conversion of citrate to acetyl-CoA, catalyzed by enzymes including ATP citrate lyase (ACLY), acetyl-CoA carboxylase (ACC), and fatty acid synthase (FASN), with regulation by stearoyl-CoA desaturase (SCD). The figure also depicts fatty acid oxidation (β-oxidation) within mitochondria and peroxisomes, mediated by carnitine palmitoyltransferase I (CPT1) and acyl-CoA dehydrogenases (ACAD). Cholesterol metabolism is shown, which can lead to the progression of cancer. Additionally, potential therapeutic targets and inhibitors, such as FASN and CPT1 inhibitors, are marked, underscoring their relevance in cancer treatment

Cancer cells exhibit significant alterations in lipid metabolism compared to normal cells. These changes include increased de novo lipogenesis [113], enhanced fatty acid uptake [112], and altered fatty acid oxidation [114]. De novo lipogenesis, the process by which cells synthesize fatty acids from non-lipid precursors, is upregulated in many cancers. Key enzymes involved in this pathway, such as ATP citrate lyase (ACLY), acetyl-CoA carboxylase (ACC), and fatty acid synthase (FASN), are often overexpressed in tumor cells. This results in an abundant supply of fatty acids essential for membrane biogenesis, energy production, and the synthesis of signaling molecules. For example, in breast cancer, DNL is essential for sustaining the membrane composition and energy needs of rapidly proliferating tumor cells. Luminal subtypes rely heavily on DNL for fatty acid replenishment, while basal-like receptor-negative cancers tend to use exogenous fatty acids more. This metabolic shift is driven by various genomic and proteomic changes that influence lipogenic enzyme expression and activity [115, 116]. Inhibiting enzymes involved in DNL, such as FASN, has been shown to reduce tumor growth and enhance chemotherapy sensitivity, highlighting DNL as a promising target for therapeutic intervention [117, 118].

Furthermore, fatty acid uptake is also elevated in cancer cells, facilitated by overexpression of fatty acid transport proteins (FATPs) and CD36, a scavenger receptor involved in lipid uptake [119, 120]. This allows cancer cells to scavenge extracellular fatty acids, providing an additional energy source and building blocks for membrane synthesis. Furthermore, the process of fatty acid oxidation (FAO), which breaks down fatty acids to generate ATP, is often reprogrammed in cancer cells. While some cancers increase FAO to meet their energy demands, others decrease it to divert fatty acids toward lipid synthesis pathways [121].

Lipids serve not only as energy sources but also as critical signaling molecules in cancer. Lipid signaling pathways, mediated by molecules such as phosphoinositides, sphingolipids, and eicosanoids, play pivotal roles in cell proliferation, survival, migration, and invasion [111, 113]. For instance, the PI3K/Akt pathway, frequently activated in cancer, is heavily influenced by lipid signaling. Activation of PI3K catalyzes the production of phosphatidylinositol (3,4,5)-trisphosphate (PIP3), a lipid second messenger that recruits and activates Akt, promoting cell survival and growth [122].

Furthermore, sphingolipid metabolism is also intricately linked to cancer progression [123, 124]. Sphingolipid metabolism refers to the biochemical processes involved in synthesising, breaking down, and regulating sphingolipids, a lipid class that plays crucial roles in cell membrane structure and signaling. This pathway involves various enzymes and intermediates, such as ceramide and sphingosine, and is essential for cell growth, differentiation, apoptosis, and responses to stress. Ceramide, a central molecule in sphingolipid metabolism, can induce apoptosis, while its metabolites, sphingosine-1-phosphate (S1P) and ceramide-1-phosphate (C1P), promote cell proliferation and survival [125, 126]. The balance between these opposing lipid signals is often disrupted in cancer, favoring tumor growth and resistance to cell death [113].

The TME, composed of cancer cells, stromal cells, immune cells, and extracellular matrix, plays a crucial role in cancer progression and metastasis. Lipid metabolism within the TME is highly dynamic and contributes to the metabolic crosstalk between different cell types. Cancer-associated fibroblasts (CAFs) and adipocytes within the TME can supply fatty acids to cancer cells, supporting their metabolic needs. Additionally, hypoxic conditions within the TME can induce lipid droplet formation in cancer cells, serving as energy reservoirs that can be mobilized during periods of metabolic stress [114]. As, in a mouse model of gastric cancer, lipid aggregation in tumor-associated macrophages (TAMs) upregulated the expression of phosphoinositide 3-kinase (PI3K-γ) and promoted TAM polarization to the M2 phenotype. This lipid metabolism in TAMs is closely associated with immunosuppression and chemotherapy resistance [127]. Immune cells within the TME, such as TAMs, also exhibit altered lipid metabolism. TAMs can undergo metabolic reprogramming to support tumor growth and suppress anti-tumor immunity. For instance, TAMs often rely on FAO and exhibit increased lipid uptake, which can promote their pro-tumoral functions. Targeting the lipid metabolic pathways in these cells represents a potential therapeutic strategy to modulate the TME and enhance anti-tumor immunity [114].

Given the critical role of lipid metabolism in cancer, targeting lipid metabolic pathways offers promising therapeutic opportunities [128]. Inhibitors of key enzymes involved in de novo lipogenesis, such as FASN inhibitors, have shown potential in preclinical models [129]. Targeting fatty acid uptake and FAO are also being explored as therapeutic strategies. For instance, inhibitors of CD36 and FAO have demonstrated anti-tumor effects in various cancer models [130]. Furthermore, strategies to disrupt lipid signaling pathways, such as PI3K/Akt inhibitors and modulators of sphingolipid metabolism, are under investigation. Combining lipid metabolism-targeting therapies with conventional treatments, such as chemotherapy and immunotherapy, may enhance therapeutic efficacy and overcome resistance.

Regulation of metabolic pathways

Oncogenes and tumor suppressors

In cancer, metabolic pathways can be regulated through various mechanisms, including oncogenes, tumor suppressor genes, epigenetic modifications, and microenvironmental factors (Fig. 5). Cancer involves genetic alterations and significant metabolic changes [131, 132]. The deregulation of metabolic pathways is a hallmark of cancer, heavily influenced by the activities of oncogenes and tumor suppressors [133]. Understanding how these genes regulate metabolism is crucial for developing targeted cancer therapies.

Fig. 5
figure 5

The figure illustrates the regulatory landscape of metabolic pathways in cancer, highlighting key influences from oncogenes (e.g., MYC, RAS) and tumor suppressor genes (e.g., p53, PTEN). Epigenetic modifications (DNA methylation, histone marks) are shown in the figure with its regulatory role. Microenvironmental factors such as hypoxia, nutrient availability (glucose, glutamine), and immune interactions are illustrated to impact metabolic adaptations in cancer cells. Interactions and feedback loops between these regulatory elements are represented, emphasizing how oncogene activation may enhance glycolysis and alter mitochondrial function, and how epigenetic silencing affects metabolic enzyme expression

Oncogenes are mutated or overexpressed versions of normal genes, known as proto-oncogenes, that drive uncontrolled cell growth and proliferation [134, 135]. Several oncogenes are known to alter metabolic pathways to support the high energy and biosynthetic demands of rapidly proliferating cancer cells. For example, the MYC oncogene, a transcription factor, upregulates genes involved in glycolysis, glutaminolysis, and nucleotide biosynthesis. MYC enhances the expression of glucose transporters and glycolytic enzymes while stimulating glutamine metabolism, which feeds into the TCA cycle and supports biosynthesis [136, 137]. Similarly, the RAS family of proteins activates pathways like PI3K/AKT and MAPK, which enhance glucose uptake, glycolysis, lipid biosynthesis, and macromolecular synthesis, all crucial for cell growth and proliferation [138]. The PI3K/AKT pathway, a major regulator of cellular metabolism, promotes glucose uptake and glycolysis by upregulating glucose transporters and glycolytic enzymes [139]. Activated AKT enhances protein synthesis and inhibits apoptosis through mTOR signaling [140]. Another key player, HIF-1α, stabilizes under hypoxic conditions typical of tumors and increases the expression of glycolytic enzymes and glucose transporters, promoting anaerobic glycolysis. HIF-1α also upregulates vascular endothelial growth factor (VEGF), enhancing tumor angiogenesis and oxygen supply [141]. These oncogenes collectively shift cellular metabolism towards increased glycolysis, glutaminolysis, and lipid biosynthesis, supporting cancer cells’ rapid growth and energy demands.

In contrast, tumor suppressors are genes that inhibit cell growth and proliferation, acting as a defense against cancer [142, 143]. They often counteract the effects of oncogenes and maintain cellular homeostasis. The tumor suppressor p53, for example, is a transcription factor known as the “guardian of the genome.” It responds to cellular stress and DNA damage by inducing cell cycle arrest, apoptosis, and senescence [144]. p53 also regulates metabolism by inhibiting glycolysis and promoting OXPHOS [145]. It activates the expression of TIGAR, which lowers glycolysis and enhances the pentose phosphate pathway, providing antioxidant defense [146].

AMP-activated protein kinase (AMPK) is another critical tumor suppressor, acting as a cellular energy sensor activated by low ATP levels [147, 148]. AMPK inhibits anabolic processes and promotes catabolic processes to restore energy balance [149]. It inhibits mTOR signaling, reduces protein synthesis, and enhances fatty acid oxidation and glucose uptake [150]. LKB1, a tumor suppressor, activates AMPK and several other kinases involved in cellular metabolism, promoting oxidative metabolism and inhibiting mTOR, thereby reducing cell growth and proliferation [151].

The balance between oncogenes and tumor suppressors determines the metabolic phenotype of a cell [152]. In cancer cells, oncogenes are often upregulated or mutated, leading to enhanced glycolysis, glutaminolysis, and biosynthesis [21]. Conversely, tumor suppressors are often inactivated, removing their inhibitory effects on metabolism and allowing uncontrolled cell growth [153]. Targeting metabolic pathways influenced by oncogenes and tumor suppressors presents a promising approach to cancer therapy. For instance, glycolysis inhibitors, such as 2-deoxy-D-glucose, can starve cancer cells of energy, while glutaminase inhibitors can reduce the supply of TCA cycle intermediates [154]. AMPK activators can restore metabolic balance and inhibit cancer cell growth [155]. Therefore, understanding the metabolic regulation by oncogenes and tumor suppressors can lead to the development of personalized cancer therapies aimed at specific metabolic vulnerabilities of cancer cells. This approach holds promise for more effective and targeted treatments, potentially improving outcomes for cancer patients.

Epigenetic modifications

Epigenetic modifications are fundamental in regulating metabolic pathways in cancer, significantly influencing cancer progression, adaptation, and survival [156, 157]. These modifications, including DNA methylation, histone modifications, and non-coding RNAs, modulate gene expression without altering the underlying DNA sequence [157, 158]. The complex relationship between epigenetic changes and metabolic reprogramming is pivotal for the aggressive nature of cancer cells [159].

DNA methylation, the addition of a methyl group to the 5-carbon of cytosine residues within CpG dinucleotides, typically leads to gene silencing. This modification can silence key metabolic genes, affecting pathways such as glycolysis, the tricarboxylic acid (TCA) cycle, and lipid metabolism. For instance, the hypermethylation of genes regulating HIF-1α can enhance its stability and activity, promoting the glycolytic phenotype known as the Warburg effect, which is common in cancer cells [160]. Additionally, DNA methylation can regulate genes involved in glutaminolysis, crucial for providing intermediates for the TCA cycle and biosynthesis in rapidly proliferating cancer cells [161].

Histone modifications also play a significant role in cancer metabolism. Histones, the protein components of chromatin, undergo various post-translational modifications, including acetylation, methylation, phosphorylation, and ubiquitination, which influence chromatin structure and gene expression. Histone acetylation, mediated by histone acetyltransferases (HATs) and histone deacetylases (HDACs), generally leads to an open chromatin structure and active transcription [162]. Acetylation of histones at promoters of glycolytic genes enhances their expression, while HDACs can repress genes involved in lipid metabolism, affecting lipid synthesis and oxidation [163]. Similarly, histone methylation can either activate or repress transcription depending on the specific amino acid residues methylated and the number of methyl groups added [164]. This modification can regulate the expression of enzymes involved in the TCA cycle, impacting energy production, biosynthetic precursor availability, and one-carbon metabolism, crucial for nucleotide biosynthesis and methylation reactions [164].

Non-coding RNAs, including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), are also key players in the post-transcriptional regulation of gene expression in cancer metabolism [165]. miRNAs can degrade mRNA or inhibit its translation, affecting various metabolic pathways [166]. For example, miRNAs can target mRNAs of enzymes in glycolysis and gluconeogenesis, altering glucose uptake and utilization [167]. They can also modulate the expression of key enzymes in lipid biosynthesis and breakdown, influencing lipid availability and membrane synthesis. For example, microRNA-195 inhibits breast cancer cell proliferation, invasion, and metastasis by targeting FASN, HMGCR, ACACA, and CYP27B1 [168]. On the other hand, lncRNAs can act as scaffolds, guides, or decoys for chromatin-modifying complexes, impacting gene expression related to amino acid metabolism and redox balance, which are essential for the metabolic needs of cancer cells [169].

The integration of epigenetic modifications and metabolic pathways in cancer is complex and dynamic [170, 171]. Cancer cells often undergo metabolic reprogramming to meet their increased energy and biosynthetic demands, and epigenetic modifications can facilitate this reprogramming by altering the expression of metabolic enzymes and pathways [152]. For instance, the Warburg effect is supported by the epigenetic silencing of mitochondrial genes and the activation of glycolytic genes, enabling cancer cells to rely on glycolysis for energy production even in the presence of oxygen [172]. Moreover, metabolites themselves can influence epigenetic modifications [173]. For example, α-ketoglutarate, a TCA cycle intermediate, acts as a cofactor for DNA and histone demethylases, linking metabolism directly to epigenetic regulation [174]. S-adenosylmethionine (SAM), a methyl donor for DNA and histone methylation, and NAD+, required for the activity of sirtuins (a class of HDACs), exemplify the direct connection between metabolic intermediates and epigenetic modifications [175].

The therapeutic implications of targeting epigenetic modifications in cancer metabolism are profound. Epigenetic therapies, such as DNA methyltransferase inhibitors (e.g., 5-azacytidine) and HDAC inhibitors (e.g., vorinostat), can reactivate silenced metabolic genes and disrupt the metabolic adaptations of cancer cells [157, 176]. Combining epigenetic drugs with metabolic inhibitors can enhance therapeutic efficacy by targeting the metabolic vulnerabilities of cancer cells [159, 177]. Such as, studies have explored the combination of the histone deacetylase inhibitor vorinostat with different agents in cancer treatment. In one phase I study, vorinostat was safely administered up to 400 mg once daily or 300 mg twice daily with carboplatin and paclitaxel in 28 patients with advanced solid malignancies, demonstrating promising activity [178]. Another phase I study investigated vorinostat combined with pazopanib or ixazomib in patients with metastatic TP53 mutant solid tumors. Results showed that the pazopanib and vorinostat combination yielded significantly higher clinical benefit rates (45% vs. 3.4%; p < 0.001), longer median progression-free survival (3.5 months vs. 1.7 months; p = 0.002), and longer median overall survival (12.7 months vs. 7.3 months; p = 0.24) compared to ixazomib and vorinostat. These findings suggest that antiangiogenesis-based therapy with pazopanib may offer superior clinical outcomes [179]. Additionally, epigenetic modifications can serve as biomarkers for cancer diagnosis, prognosis, and treatment response, providing insights into the metabolic state and potential therapeutic targets in cancer [156, 157]. One example of epigenetic modifications serving as biomarkers in cancer is the role of DNA methylation in CRC. In CRC, specific patterns of DNA methylation, such as hypermethylation of the MLH1 gene promoter, are associated with microsatellite instability (MSI), which is a hallmark of certain CRC subtypes. The presence of MSI can help diagnose and prognosticate CRC, as well as guide treatment decisions [180]. For instance, MSI-high tumors are often more responsive to immune checkpoint inhibitors [181, 182]. Thus, DNA methylation status not only aids in the diagnosis and prognosis of CRC but also provides valuable information for selecting targeted therapies, illustrating how epigenetic modifications can offer insights into cancer’s metabolic state and therapeutic strategies.

Microenvironmental factors

The TME is a complex and dynamic network surrounding cancer cells, composed of various cellular and non-cellular components that significantly influence cancer progression and metastasis [183]. This microenvironment includes stromal cells such as fibroblasts, immune cells like macrophages and lymphocytes, endothelial cells forming blood vessels, and the extracellular matrix (ECM) [184]. Each component interacts with cancer cells through biochemical and mechanical signals, creating a niche that supports tumor growth and resistance to therapies [185].

One of the critical elements in the TME is CAFs, which secrete growth factors, cytokines, and ECM components that facilitate tumor cell proliferation, invasion, and angiogenesis [186]. CAFs also contribute to the remodeling of the ECM, providing structural support for tumor expansion and creating barriers to immune cell infiltration [187]. Similarly, immune cells within the TME can adopt pro-tumorigenic roles [188]. For example, TAMs often display an M2-like phenotype that promotes tissue repair and immunosuppression, aiding in tumor immune evasion [189].

Hypoxia, a common feature of solid tumors due to aberrant vasculature, further complicates the TME [190]. Hypoxic conditions stabilize HIFs, which activate a transcriptional program that promotes angiogenesis, metabolic reprogramming, and EMT [191]. This adaptation enables cancer cells to survive in low-oxygen conditions and increases their metastatic potential [192]. Additionally, the acidic and nutrient-depleted environment of the TME results from altered metabolic activity of cancer cells, influencing the behavior of surrounding stromal and immune cells [193].

The interplay between metabolic pathways and the TME further emphasizes the complexity of cancer metabolism. Nutrient availability, such as glucose and amino acids, in the TME influences the metabolic state of cancer and stromal cells. Moreover, metabolic byproducts like lactate can modulate immune cell function, creating an immunosuppressive microenvironment that favors tumor progression [194]. For example, in CRC, tumor cells undergo metabolic changes that alter the availability of nutrients like glucose and amino acids in the TME. This reprogramming leads to an increased reliance on aerobic glycolysis, commonly referred to as the Warburg effect, where cancer cells preferentially convert glucose to lactate even in the presence of oxygen. This process not only supports rapid tumor growth but also results in the accumulation of lactate in the TME, creating an acidic environment that can suppress immune responses [195, 196]. Targeting these metabolic adaptations presents a promising strategy for cancer therapy, aiming to disrupt the metabolic flexibility of cancer cells and sensitize them to conventional treatments.

Inhibitors for targeting cancer metabolism

Glycolytic inhibitors

Cancer cells often exhibit altered metabolism, characterized by increased glucose uptake and glycolysis, even in the presence of oxygen. This metabolic reprogramming supports rapid cell proliferation and survival. Consequently, targeting glycolysis has emerged as a potential therapeutic strategy in cancer treatment. Various glycolytic inhibitors have been developed to exploit the dependence of cancer cells on this pathway [197]. Table 1 provides an overview of glycolytic inhibitors, their clinical trial phases, status, conditions studied, and respective study periods (Table 1).

Table 1 Overview of inhibitors that target glycolysis directly or indirectly

Hexokinase inhibitors, such as 2-Deoxy-D-glucose (2-DG) and Lonidamine, play a crucial role in disrupting the initial steps of glycolysis. 2-DG is a glucose analog that competes with glucose for phosphorylation by hexokinase, the enzyme responsible for the first step of glycolysis [198]. This competition impairs ATP production, leading to cancer cell death [199]. Lonidamine specifically inhibits hexokinase II (HKII), which is often overexpressed in cancer cells, thereby reducing glycolytic flux and inducing apoptosis [200]. Combination therapies involving these agents offer hope for improving cancer treatment outcomes. For example, the combination of 2-Deoxy-glucose (2-DG) with different therapeutic approaches has yielded contrasting outcomes in cancer therapy. The pairing of 2-DG with fenofibrate (FF) shows significant potential by synergistically inducing energy and endoplasmic reticulum (ER) stress in tumors, leading to energy depletion, inhibition of mTOR, and cancer cell death, highlighting a promising avenue for clinical development [201]. However, the combination of 2-DG with a ketogenic diet (KD) has resulted in significant dose-dependent toxicity, causing acute thrombocytopenia, interstitial pneumonia, and rapid mortality in treated mice, while being well tolerated on a standard diet [202]. Similarly, lonidamine has shown limited cytotoxicity on its own but significantly enhances the efficacy of various chemotherapeutic agents, such as 5-fluorouracil, methotrexate, etoposide, cisplatin, and mitomycin C, in both mouse and human fibrosarcoma cell lines. Its enhancement of drug effectiveness is time- and concentration-dependent, suggesting its potential role in combination therapies to improve cancer treatment outcomes. By targeting energy metabolism pathways, including monocarboxylate transporter (MCT) and mitochondrial pyruvate carrier (MPC) inhibition, lonidamine selectively targets tumors without causing common side effects like alopecia and myelosuppression [203]. Furthermore, it has shown promising synergistic effects when used alongside physical therapies such as radiotherapy, hyperthermia, and photodynamic therapy [204]. This suggests that combination therapies with hexokinase inhibitors like 2-Deoxy-D-glucose (2-DG) and lonidamine can enhance cancer treatment effectiveness. While 2-DG shows promise when paired with fenofibrate, it can cause severe toxicity with a ketogenic diet. Lonidamine enhances the efficacy of various chemotherapeutic agents and physical therapies, offering potential in multidrug strategies, though outcomes depend on the specific combinations used.

Moreover, inhibitors of phosphofructokinase, such as 3-PO, target a rate-limiting enzyme in glycolysis. 3-PO (3-(3-Pyridinyl)-1-(4-pyridinyl)-2-propen-1-one) was initially thought to inhibit PFKFB3, rather than phosphofructokinase-1 (PFK-1) [205, 206]. However, recent research has revealed that 3-PO does not directly bind to or inhibit PFKFB3 [206]. Instead, it reduces glycolytic activity in cancer cells by a different mechanism. 3-PO accumulates lactic acid inside cells, leading to a decrease in intracellular pH and the subsequent inhibition of glycolytic enzymes [206]. This inhibition of glycolysis can impair cancer cell growth and survival [205], but it is not due to the direct inhibition of PFK-1 or PFKFB3 as previously thought [207]. In contrast, koningic acid is a selective inhibitor of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), disrupting the glycolytic pathway, reducing ATP production, and promoting apoptosis in some cancer cells. While 3-PO and koningic acid affect glycolysis, they do so through different mechanisms and target distinct enzymes within the pathway [207].

Furthermore, targeting pyruvate kinase M2 (PKM2), an isoform expressed in cancer cells that promotes aerobic glycolysis, is another strategy [208]. Shikonin and TEPP-46 are notable PKM2 inhibitors. Shikonin disrupts the final step of glycolysis, reducing ATP production and causing cancer cell death [209]. TEPP-46, on the other hand, activates PKM2, shifting it from its less active dimeric form to the more active tetrameric form, thereby impairing cancer cell proliferation. For example, TEPP-46 was investigated as a potential treatment for triple-negative breast cancer (TNBC). PKM2 phosphorylation at S37 was associated with aggressive breast cancer phenotypes. TEPP-46 reduced PKM2 nuclear localization, inhibited tumor growth in a TNBC mouse xenograft model, and synergized with a CDK inhibitor to impair cell invasion and trigger cancer cell death [210].

Lactate dehydrogenase (LDH) inhibitors, such as galloflavin [211] and FX11 [212], prevent the conversion of pyruvate to lactate, a crucial step in glycolysis. By inhibiting LDH, these agents disrupt glycolysis, reducing lactate production and impairing cancer cell growth [212, 213]. These inhibitors are particularly effective in tumors with high glycolytic rates, where they can induce significant metabolic stress.

The mechanisms of action of glycolytic inhibitors encompass various aspects of cancer cell metabolism [52]. These inhibitors cause energy deprivation by reducing ATP production, which is essential for cancer cell survival [214]. They also inhibit biomass production by limiting intermediates for biosynthetic pathways, thus impairing cancer cell growth and proliferation [21]. Disrupting glycolysis can increase reactive oxygen species (ROS) levels, leading to oxidative stress and cell death [154]. Glycolytic inhibitors can also enhance the efficacy of other cancer treatments, such as chemotherapy and radiotherapy, by sensitizing tumors to conventional therapies [215].

Despite their potential, the clinical application of glycolytic inhibitors faces several challenges. Selective targeting of cancer cells without affecting normal cells is crucial to minimize toxicity [59, 60]. This is because normal cells also rely on glycolysis, making it difficult to target cancer cells specifically without harming healthy tissues. Cancer cells can develop resistance to glycolytic inhibitors through various mechanisms, such as upregulation of alternative metabolic pathways, necessitating combination therapies and biomarkers for resistance [59, 216]. For example, cancer cells may adapt by increasing oxidative phosphorylation or glutaminolysis when glycolysis is inhibited. Additionally, the potential toxicity and side effects of glycolytic inhibitors must be carefully managed, particularly in tissues with high glycolytic activity like the brain and muscles. These tissues rely heavily on glucose metabolism for their normal function, and inhibiting glycolysis could lead to serious side effects. Developing effective glycolytic inhibitors with suitable pharmacokinetic properties for clinical use remains a challenge. Many compounds that show promise in preclinical studies may not have the desired properties for use in humans, such as appropriate bioavailability or half-life. Furthermore, the complex interplay between cancer cell metabolism and the immune system needs to be considered when developing glycolytic inhibitors. Inhibiting glycolysis may affect immune cell function, potentially compromising the body’s natural defense against cancer.

Based on metabolic profiling of tumors, personalized medicine approaches can enhance therapeutic efficacy of glycolytic inhibitors by identifying patients most likely to benefit from these treatments. Understanding the metabolic heterogeneity of tumors is crucial for developing effective therapies. By addressing these challenges, glycolytic inhibitors can become a valuable addition to the arsenal of cancer treatments, offering new hope for patients with metabolic vulnerabilities in their tumors.

Glutaminase inhibitors

Cancer metabolism has been a focal point of research due to its critical role in the proliferation and survival of cancer cells. One of the central metabolic pathways by cancer cells is glutamine metabolism [106, 217]. Glutamine, a non-essential amino acid, becomes essential for the rapid growth and survival of cancer cells [106]. This is largely because glutamine serves as a carbon and nitrogen source for nucleotide and amino acid synthesis, which are crucial for the growth of proliferating cells [106, 217]. Glutamine serves as a precursor for various biosynthetic processes, including lipid synthesis and energy production through the TCA cycle [106]. The enzyme glutaminase, which converts glutamine to glutamate, is a key player in this metabolic pathway [106, 218]. Consequently, glutaminase inhibitors have emerged as promising therapeutic targets in cancer treatment (Table 2).

Table 2 Overview of glutaminase inhibitors

Glutaminase exists in two major isoforms in humans: GLS1 (kidney-type glutaminase) and GLS2 (liver-type glutaminase) [100, 219]. GLS1 is predominantly expressed in cancer cells, making it an attractive target for cancer therapy [219]. Inhibition of GLS1 disrupts the conversion of glutamine to glutamate, leading to a reduction in the production of key metabolites required for cell growth and survival [220, 221]. This, in turn, can induce cell death in glutamine-dependent cancer cells [221]. Several studies have demonstrated that glutaminase inhibitors can effectively suppress tumor growth in various cancer models, highlighting their potential as therapeutic agents [100, 220].

One of the most well-known glutaminase inhibitors is CB-839 (Telaglenastat), which selectively inhibits GLS1. Preclinical studies have shown that CB-839 can reduce tumor growth in multiple cancer types [110]. These findings have led to several clinical trials to evaluate the safety and efficacy of CB-839 in cancer patients. Early-phase clinical trials have reported promising results, with CB-839 demonstrating acceptable safety profiles and preliminary evidence of anti-tumor activity. These results have spurred further investigations into the combination of glutaminase inhibitors with other therapeutic agents to enhance their efficacy. For example, in a phase I clinical trial, telaglenastat is being investigated for its safety and efficacy when combined with radiation therapy (RT) and temozolomide (TMZ) in patients with untreated IDH mutant astrocytomas, where it depletes intracellular glutamate and enhances RT efficacy [222]. Similarly, in advanced renal cell carcinoma (mRCC), telaglenastat combined with everolimus demonstrated a favorable safety profile and improved progression-free survival (PFS) in patients previously treated with tyrosine kinase inhibitors (TKIs) and checkpoint inhibitors, suggesting the potential benefit of dual targeting glucose and glutamine metabolism in these cancers [223].

The combination of glutaminase inhibitors with other cancer therapies represents a promising approach to enhance treatment efficacy. Cancer cells often exhibit metabolic flexibility, allowing them to adapt to metabolic stress by switching to alternative pathways. Therefore, combining glutaminase inhibitors with other metabolic inhibitors or standard chemotherapies can create a synthetic lethality scenario, where the simultaneous targeting of multiple pathways overwhelms the cancer cells’ adaptive capacity. For example, combining CB-839 with inhibitors of the PI3K/AKT/mTOR pathway, which is often upregulated in cancer, can improve the therapeutic effects [106, 224].

Despite the promising potential of glutaminase inhibitors, several challenges remain. One major challenge is the heterogeneity of tumors and the metabolic plasticity of cancer cells. Not all tumors are equally dependent on glutamine metabolism, and some may develop resistance to glutaminase inhibition by activating alternative metabolic pathways. Therefore, identifying biomarkers that can predict which tumors are most likely to respond to glutaminase inhibitors is crucial for the successful implementation of this therapeutic strategy. Additionally, understanding the mechanisms underlying resistance to glutaminase inhibition will be essential for developing strategies to overcome resistance and improve patient outcomes.

Inhibitors of the tricarboxylic acid (TCA) cycle

The TCA cycle operates within the mitochondria, where it generates ATP, NADH, and FADH2 through the oxidation of acetyl-CoA derived from carbohydrates, fats, and proteins. These products are essential for the electron transport chain and oxidative phosphorylation. The cycle involves several key enzymes, including citrate synthase, aconitase, isocitrate dehydrogenase (IDH), alpha-ketoglutarate dehydrogenase, succinyl-CoA synthetase, succinate dehydrogenase (SDH), fumarase, and malate dehydrogenase. Dysregulation of these enzymes is often observed in various cancers, making them potential therapeutic targets [225, 226].

Succinate dehydrogenase (SDH), a component of both the TCA cycle and the electron transport chain, is another critical enzyme. Mutations in SDH genes are linked to hereditary paragangliomas, pheochromocytomas, and renal cell carcinoma [227]. Loss of SDH function leads to succinate accumulation, which inhibits alpha-ketoglutarate-dependent dioxygenases and stabilizes HIFs, promoting tumorigenesis [228, 229]. While direct inhibitors of mutant SDH are still under investigation, targeting the metabolic and signaling consequences of SDH loss [230], such as with HIF inhibitors, presents a potential strategy [231]. However, there is a scarcity of clinical trials for the inhibitors of the TCA cycle (Table 3).

Table 3 Overview of the tricarboxylic acid (TCA) cycle inhibitors

Similarly, mutations in fumarase (FH) are associated with hereditary leiomyomatosis and renal cell cancer [232]. Loss of FH activity results in fumarate accumulation, leading to effects similar to those seen with SDH mutations, including HIF stabilization and epigenetic changes. Direct targeting of FH-deficient tumors often involves exploiting the metabolic vulnerabilities and stress responses induced by fumarate accumulation [38].

Strategies for targeting the TCA cycle in cancer therapy include metabolic flux analysis, synthetic lethality, and combination therapies. Metabolic flux analysis, using stable isotope tracing, maps altered metabolic pathways in cancer cells to identify key vulnerabilities. Exploiting synthetic lethality involves targeting secondary pathways cancer cells rely on due to TCA cycle alterations, such as inhibiting glycolysis in tumors with impaired oxidative phosphorylation. Combination therapies pair TCA cycle inhibitors with treatments like chemotherapy, targeted therapies, or immunotherapy to enhance efficacy and overcome resistance. Challenges include ensuring selectivity to minimize toxicity to normal cells, developing cancer-specific delivery systems, identifying biomarkers for patient stratification, and addressing resistance mechanisms through continuous monitoring and combination strategies. More clinical trials are needed to evaluate the safety and efficacy of TCA cycle inhibitors across various cancer types and develop personalized treatments based on each tumor’s molecular context.

Fatty acid oxidation inhibitors

Cancer cells undergo significant metabolic reprogramming to support their rapid growth and proliferation. One critical metabolic pathway that these cells exploit is fatty acid oxidation (FAO), the process by which fatty acids are broken down in the mitochondria to generate energy. Targeting FAO can disrupt the energy supply and metabolic flexibility of cancer cells, potentially suppressing their growth. As a result, fatty acid oxidation inhibitors (FAO inhibitors) have emerged as promising therapeutic agents in cancer treatment [49, 118] (Table 4). For example, a recent study highlights the metabolic switch from glucose to fatty acid-dependent anabolic and energy metabolism in cisplatin-resistant cancer cells. It demonstrates that inhibition of FAO re-sensitizes these cells to cisplatin treatment, suggesting a combinational therapy of FAO inhibitors and platinum drugs as a potential strategy [233].

Table 4 Overview of the fatty acid oxidation inhibitors

FAO plays a pivotal role in cancer metabolism. While the reliance of cancer cells on glycolysis is well-documented, recent studies have highlighted the importance of FAO in cancer. FAO provides ATP, NADPH, and acetyl-CoA, all of which are crucial for maintaining cellular energy homeostasis, redox balance, and biosynthesis [234, 235]. The ATP generated through FAO supports the high energy demands of proliferating cancer cells, while NADPH helps maintain redox balance, protecting cells from oxidative stress [234, 235]. Additionally, acetyl-CoA produced from FAO is essential for fatty acid and cholesterol synthesis, necessary for membrane formation and signaling molecules [118, 236].

FAO inhibitors target various enzymes in the FAO pathway, reducing the availability of energy and essential metabolites for cancer cells. Key enzymes targeted by these inhibitors include Carnitine Palmitoyltransferase 1 (CPT1), Acyl-CoA Dehydrogenase (ACAD), and 3-Ketoacyl-CoA Thiolase (KAT) [234, 237]. CPT1, the rate-limiting enzyme in the transport of long-chain fatty acids into mitochondria, can be inhibited by drugs like etomoxir, blocking fatty acid entry and subsequent oxidation [118, 238]. ACAD inhibitors prevent the initial step of mitochondrial fatty acid β-oxidation, while KAT inhibitors halt the final step, leading to an accumulation of fatty acid intermediates [234, 237].

The therapeutic potential of FAO inhibitors in cancer treatment is significant. Cancer cells that heavily rely on FAO for energy and biosynthesis are particularly vulnerable to these inhibitors. By targeting FAO, these inhibitors can selectively kill cancer cells without affecting normal cells that rely more on glycolysis [239]. Moreover, FAO inhibitors can be used in combination with other cancer therapies to enhance their efficacy. For instance, combining FAO inhibitors with glycolysis inhibitors can target the metabolic flexibility of cancer cells, making it harder for them to adapt and survive. Furthermore, FAO inhibitors may help overcome drug resistance, which is often a significant challenge in cancer treatment. By targeting the metabolic adaptations that contribute to resistance, FAO inhibitors can improve the effectiveness of conventional therapies.

Examples of FAO inhibitors that have shown potential in cancer therapy include etomoxir, perhexiline, and ranolazine [240, 241]. Etomoxir and perhexiline are CPT1 inhibitors that have demonstrated anticancer activity, particularly against FAO-dependent tumors such as prostate cancer and leukemia [241]. Perhexiline, which inhibits both CPT1 and CPT2, has shown promising results in preclinical cancer studies. It has been found to inhibit proliferation and induce apoptosis in prostate cancer cell lines. Additionally, perhexiline combined with anti-androgen therapies like abiraterone or enzalutamide has demonstrated robust growth inhibition in prostate cancer cell models, including those resistant to enzalutamide [240]. Such as, a previous study highlights the therapeutic potential of co-targeting the androgen receptor (AR) axis and lipid oxidation in metastatic castration-resistant prostate cancer (mCRPC). Inhibition of carnitine palmitoyltransferase 1 A (CPT1A), a key enzyme in lipid oxidation, reduces prostate cancer growth and invasion, with the CPT1A isoform being more abundant in high-grade tumors. Combining CPT1A inhibition with the anti-androgen enzalutamide enhances its efficacy, including in enzalutamide-resistant models, by decreasing AKT activation and increasing AR sensitivity. Fat oxidation inhibitors, such as perhexiline, etomoxir, and ranolazine, in combination with enzalutamide, have shown robust growth inhibition in PCa cell models. Preclinical results further demonstrate significant tumor growth reduction with systemic combination treatment, suggesting that dual targeting of AR and lipid oxidation, including with perhexiline, may offer an effective strategy for mCRPC treatment [242]. It’s important to note that while these FAO inhibitors show promise in preclinical studies, their efficacy and safety in clinical cancer treatment still require further investigation.

Despite the promising potential of FAO inhibitors, several challenges remain. Achieving selectivity for cancer cells while sparing normal cells is a significant hurdle. FAO inhibitors need to be developed with a focus on selective targeting to minimize side effects. Additionally, cancer cells may develop resistance to FAO inhibitors through compensatory metabolic pathways. Understanding these resistance mechanisms will be crucial for developing combination therapies that can overcome them. Translating preclinical findings into clinical success also requires rigorous testing and validation in clinical trials.

Lactate dehydrogenase (LDH) inhibitors

Lactate dehydrogenase (LDH) inhibitors have emerged as a promising therapeutic strategy in cancer metabolism, targeting the altered metabolic pathways that are a hallmark of many malignancies. LDH is a key enzyme in the glycolytic pathway, catalyzing the conversion of pyruvate to lactate with concomitant regeneration of NAD+, a crucial step for maintaining glycolysis under anaerobic conditions [243, 244]. Cancer cells often exhibit increased glycolysis rates, even in the presence of oxygen [216, 245]. This metabolic reprogramming facilitates rapid proliferation and survival in the hypoxic TME [216, 245]. LDH inhibitors aim to disrupt this aberrant glycolytic flux, thereby reducing lactate production, acidification of the TME, and overall cancer cell survival [243, 246]. By inhibiting LDH, these agents can also impair the redox balance within cancer cells, leading to increased oxidative stress and apoptosis [246]. Additionally, targeting LDH can hinder the metabolic flexibility of cancer cells, making them more susceptible to other therapeutic interventions [243, 245]. Research and clinical trials are ongoing to optimize the efficacy and specificity of LDH inhibitors (Table 5), with some compounds showing promising preclinical results in reducing tumor growth and metastasis [243, 244]. For example, the pyrazole-based compound series (such as NCI-006) has been rigorously optimized, resulting in nanomolar IC50 values for lead compounds and demonstrated in vivo target engagement and efficacy with oral availability [216]. LDHB, another isoform of LDH, has also been identified as a potential target. LDHB plays a major role in the metabolic adaptability of cancer cells by controlling lysosomal activity and autophagy, enabling an oxidative phenotype [245]. Inhibition of both LDHA and LDHB could be therapeutically useful, as they participate in tumor-stroma metabolic interactions and the exchange of metabolic fuel. Moreover, combining LDH inhibitors like FX-11 with other agents such as DH348 (a CAIX inhibitor) significantly suppressed metastasis in prostate cancer models. Notably, FX-11 also showed synergy with immune checkpoint blockade (anti-PD-1) in pancreatic cancer models. These results suggest that addressing tumor acidity and lactate production could enhance the effectiveness of immunotherapy [247]. Thus, LDH inhibitors represent a novel and exciting avenue in the metabolic targeting of cancer therapy. However, challenges remain, including the need for improved potency, drug-like properties, and in vivo efficacy of natural product-derived LDH inhibitors. Future research should focus on integrating multiple disciplines, including natural product chemistry, medicinal chemistry, and pharmacology, to enhance the development of effective LDH inhibitors for cancer treatment.

Table 5 Overview of the lactate dehydrogenase (LDH) inhibitors

Glucose transport inhibitors

Glucose transport inhibitors are emerging as promising agents in the realm of cancer metabolism therapeutics, targeting the unique metabolic dependencies of cancer cells (Table 6). Cancer cells exhibit a heightened glycolytic rate, known as the Warburg effect, where they predominantly rely on glucose for energy production, even in the presence of oxygen. This metabolic reprogramming supports rapid cell proliferation and survival under adverse conditions. By inhibiting glucose transporters, specifically GLUT1, which is often overexpressed in various cancers, these inhibitors effectively starve cancer cells of their primary energy source [60, 216]. This leads to a reduction in ATP production, disruption of cellular homeostasis, and ultimately, cell death [216, 248]. Moreover, glucose transport inhibitors can synergize with other treatments, such as chemotherapy and radiotherapy, by further sensitizing cancer cells to these interventions [249, 250]. For example, recent studies investigated novel anti-cancer treatments through the application of phloretin in two distinct contexts. First, phloretin-based combinations were tested against hepatocellular carcinoma (HCC), where combination 1 involved inhibiting glycolysis with phloretin and gluconeogenesis with sodium meta-arsenite, while combination 2 involved inhibiting glycolysis with phloretin and inducing gluconeogenesis with dexamethasone. Both combinations significantly regressed malignant tissue in Swiss albino mice with induced HCC, demonstrating effective modulation of glucose metabolism as indicated by changes in GLUT2 and PEPCK expression. Molecular docking studies confirmed strong binding of the drugs to their targets [251]. In the second context, the synergistic effects of phloretin combined with radiotherapy (RT) were explored using a Lewis lung cancer (LLC) xenograft model. Phloretin enhanced RT efficacy, evidenced by increased survival rates, prolonged tumor growth delay, reduced glucose uptake, and higher apoptosis rates. The combination also reduced the proliferation index. These findings collectively suggest that phloretin-based treatments, whether targeting glucose metabolism or combined with RT, offer promising strategies for cancer therapy through enhanced regulation of glucose metabolism, ATP production, and apoptosis induction [252]. The therapeutic potential of these inhibitors is underlined by their ability to selectively target cancer cells while sparing normal cells, thereby minimizing systemic toxicity. Several glucose transporter inhibitors have shown promising results in preclinical studies, including STF-31, Glutor, BAY-876, and WZB117. These compounds have demonstrated efficacy in inhibiting glucose uptake and suppressing tumor growth in various cancer models [216, 248]. However, challenges remain in translating these findings to clinical applications. Many glucose transport inhibitors have faced limitations such as low selectivity, high toxicity, and side effects. To address these issues, researchers are exploring combination therapies and developing more advanced and effective glucose metabolism enzyme-targeted anticancer drugs. Ongoing research and clinical trials are crucial to optimize their efficacy, dosing regimens, and to overcome potential resistance mechanisms, making glucose transport inhibitors a pivotal addition to the arsenal against cancer.

Table 6 Overview of the glucose transport inhibitors

Monocarboxylate Transporter (MCT) inhibitors

Monocarboxylate Transporter (MCT) inhibitors are emerging as promising agents in the realm of cancer metabolism therapeutics [253, 254] (Table 7). MCTs, particularly MCT1 [255, 256] and MCT4 [257, 258], play crucial roles in the transport of lactate and other monocarboxylates across cell membranes, which is vital for maintaining the metabolic flexibility and survival of cancer cells in the hypoxic tumor microenvironment. Cancer cells often rely on aerobic glycolysis leading to excessive lactate production, and MCTs facilitate the efflux of this lactate to prevent intracellular acidification and sustain glycolytic flux. Inhibiting MCTs can disrupt this metabolic adaptation, leading to intracellular lactate accumulation, reduced glycolysis, and subsequent metabolic stress in cancer cells. This metabolic disruption can potentiate cell death, reduce tumor growth, and enhance the efficacy of other treatments, such as radiotherapy and chemotherapy [216, 259]. Additionally, MCT inhibitors can target the metabolic symbiosis between glycolytic cancer cells and oxidative tumor cells, further hampering tumor progression. Given their selective action on the altered metabolic pathways in cancer cells, MCT inhibitors offer a targeted therapeutic approach with potentially reduced systemic toxicity. Clinical trials are ongoing to evaluate the efficacy and safety of these inhibitors, making them a significant focus in the development of novel anticancer strategies. Moreover, combination therapy using MCT inhibitors shows promise. Recent research reveals potential therapeutic strategies for both non-small cell lung cancer (NSCLC) and multiple myeloma (MM) by repurposing syrosingopine in combination with other metabolic inhibitors—UK-5099 for NSCLC and metformin for MM. In NSCLC, the syrosingopine-UK-5099 combination synergistically induces cell cycle arrest, apoptosis, and mitochondrial damage through lactate accumulation and oxidative stress, mediated by the activation of the integrated stress response (ISR) via heme-regulated inhibitor kinase (HRI) [260]. In MM, the syrosingopine-metformin combination targets metabolic vulnerabilities by inhibiting both glycolysis and oxidative phosphorylation, activating p-AMPKα, reducing protein synthesis, and significantly decreasing tumor burden [261].

Table 7 Overview of the Monocarboxylate Transporter (MCT) inhibitors

Amino acid transport inhibitors

Amino acid transport inhibitors represent a promising approach in cancer metabolism therapy by targeting the critical nutrient supply that cancer cells rely on for growth and survival [262, 263] (Table 8). Cancer cells often exhibit increased uptake of amino acids to support their rapid proliferation and metabolic demands. By inhibiting the transporters responsible for amino acid uptake, such as the LAT1 (L-type amino acid transporter 1) and ASCT2 (alanine-serine-cysteine transporter 2), these therapies can effectively starve cancer cells of essential nutrients. This disruption in amino acid supply can lead to impaired protein synthesis, altered cellular metabolism, and the induction of stress responses that may culminate in cell death [262, 263]. Additionally, inhibiting amino acid transport can sensitize cancer cells to other treatments by enhancing metabolic vulnerabilities. As a result, amino acid transport inhibitors are being explored in combination with other therapeutic strategies to achieve more effective cancer control [263, 264]. Such as, a recent study has shown that JPH203 can sensitize cancer cells to radiation therapy by inhibiting radiation-induced amino acid uptake and downregulating mTOR activity, which enhances cellular senescence. This combination of JPH203 and radiation therapy presents a promising approach to cancer treatment, potentially improving the efficacy of radiotherapy while maintaining cellular ATP and GSH levels, indicating minimal toxicity [265]. Ongoing research is focused on identifying specific inhibitors, understanding their mechanisms of action, and optimizing their clinical application to improve patient outcomes in various cancer types. For example, drugs targeting amino acid transporters and related enzymes have transitioned from preclinical research to clinical trials and have demonstrated efficacy in some cases. Clinically, Tamoxifen and Raloxifene block glutamine uptake by inhibiting ASCT2 expression in breast cancer to suppress tumor growth [266]. However, challenges remain in developing selective inhibitors and addressing the metabolic plasticity of cancer cells. Some drugs targeting amino acid metabolism have shown promising effects in animal experiments, but realizing their potential clinically is still difficult. Nevertheless, compared to other therapies, amino acid depletion therapy is generally safer for normal cells, making it an attractive avenue for further research and development in cancer treatment.

Table 8 Overview of the amino acid transport inhibitors

Isocitrate dehydrogenase (IDH) inhibitors

Isocitrate Dehydrogenase (IDH) inhibitors represent a promising class of targeted therapies in the realm of cancer metabolism (Table 9). IDH enzymes, specifically IDH1 and IDH2, play crucial roles in the citric acid cycle, catalyzing the conversion of isocitrate to alpha-ketoglutarate (α-KG). Mutations in IDH1 and IDH2 genes, often found in various cancers such as gliomas, AML, and cholangiocarcinoma, result in the production of the oncometabolite 2-hydroxyglutarate (2-HG) [43, 267]. This aberrant metabolite disrupts cellular differentiation and promotes tumorigenesis by inhibiting α-KG-dependent dioxygenases, including those involved in DNA and histone demethylation. IDH inhibitors, such as ivosidenib (AG-120) and enasidenib (AG-221), specifically target these mutant enzymes, reducing 2-HG levels and thereby restoring normal cellular differentiation processes [267, 268]. Clinical trials have demonstrated the efficacy of IDH inhibitors, leading to their approval for treating IDH-mutant cancers. The precision of these inhibitors in targeting metabolic pathways unique to cancer cells underscores their potential to offer a more effective and less toxic alternative to traditional chemotherapies, heralding a new era in cancer treatment focused on metabolic vulnerabilities. Moreover, combining IDH inhibitors with other agents can enhance treatment outcomes. For instance, the FDA recently approved ivosidenib in combination with azacitidine for newly diagnosed IDH1-mutated AML in older adults or those with comorbidities. This approval followed a phase 3 study demonstrating improved event-free survival, overall survival, and complete remission rates with the combination therapy [269].

Table 9 Overview of the Isocitrate dehydrogenase (IDH) inhibitors

Oxidative phosphorylation (OXPHOS) inhibitors

Oxidative phosphorylation (OXPHOS) inhibitors represent a promising approach in cancer metabolism therapy (Table 10), targeting the unique metabolic dependencies of cancer cells [270, 271]. OXPHOS is a critical process occurring in the mitochondria, where cells produce ATP, the primary energy currency, through the electron transport chain and ATP synthase. Cancer cells often exhibit altered metabolic states, including increased reliance on glycolysis even in the presence of oxygen, but many tumors retain or adapt to a dependence on OXPHOS for survival and proliferation, particularly under nutrient-limited or low-oxygen conditions [50, 272]. Inhibiting OXPHOS disrupts ATP production, generating oxidative stress and triggering cell death in OXPHOS-dependent cancer cells [273]. Various agents, such as metformin, phenformin, and IACS-010759, target different components of the mitochondrial electron transport chain, highlighting the heterogeneity of tumor metabolic dependencies and the need for personalized treatment strategies [63, 274]. Additionally, OXPHOS inhibitors can enhance the efficacy of existing therapies, such as chemotherapy and radiotherapy, by sensitizing cancer cells to these treatments [273, 275]. Despite their potential, challenges remain, including the identification of biomarkers to predict responsiveness and managing off-target effects on normal cells, which also rely on OXPHOS for energy production. Combining oxidative phosphorylation inhibitors with other therapeutic agents can enhance their effectiveness in cancer treatment. Recent research has shown that OXPHOS inhibitors can be particularly effective when used in conjunction with other treatments such as chemotherapy, targeted therapies, or immunotherapies. This combinatorial approach can help overcome resistance mechanisms, and improve tumor response [275]. Therefore, ongoing research is crucial to optimize the therapeutic window and enhance the specificity of OXPHOS inhibitors in cancer treatment.

Table 10 Overview of the oxidative phosphorylation (OXPHOS) inhibitors

Fatty acid synthesis inhibitors

Fatty acid synthesis inhibitors represent a promising avenue in cancer metabolism therapy, targeting the metabolic reprogramming characteristic of many cancers [118, 276] (Table 11). Cancer cells often exhibit increased de novo lipogenesis, crucial for rapid cell proliferation and survival [118, 277]. This enhanced fatty acid synthesis is driven by upregulated expression of key enzymes, such as fatty acid synthase (FASN), which catalyzes the formation of palmitate from acetyl-CoA and malonyl-CoA. Inhibiting FASN disrupts the production of fatty acids necessary for membrane biosynthesis, energy storage, and signaling molecule generation, thereby impeding tumor growth and inducing apoptosis [118]. Various FASN inhibitors, including natural products like orlistat and synthetic molecules such as TVB-2640, have demonstrated efficacy in preclinical studies by selectively targeting cancer cells while sparing normal cells, which rely more on dietary fatty acids [118, 278]. By exploiting the metabolic vulnerabilities of cancer cells, fatty acid synthesis inhibitors offer a targeted therapeutic approach that can potentially enhance the efficacy of existing treatments and overcome resistance mechanisms in various malignancies.

Table 11 Overview of the fatty acid synthesis inhibitors

Challenges and future directions

There are several challenges associated with cancer metabolism, but various strategies can be implemented to address these issues effectively (Fig. 6). One of the significant challenges in targeting cancer metabolism is overcoming the metabolic plasticity of cancer cells. These cells can dynamically adapt to various microenvironmental stresses such as nutrient deprivation and hypoxia, making it difficult to target a single metabolic pathway effectively [70]. This adaptability is achieved through metabolic flexibility (the ability to use different nutrients) and plasticity (the ability to process metabolic substrates in different ways). Furthermore, metabolic heterogeneity within and between tumors adds another layer of complexity. Different cancer cells within the same tumor may rely on distinct metabolic pathways, complicating the development of universal metabolic inhibitors [70, 279]. This heterogeneity is influenced by factors such as the tissue of origin, driving mutations, and the tumor microenvironment. Redundancy and compensation in metabolic pathways also pose a challenge, as cancer cells can bypass metabolic blockades by upregulating alternative pathways or utilizing neighboring stromal cells to supply essential nutrients, undermining the efficacy of targeted therapies [280, 281]. This ability to switch between different metabolic modes allows cancer cells to maintain growth even during glucose or amino acid deprivation. Additionally, the tumor microenvironment significantly influences cancer metabolism. Interactions between cancer cells and stromal cells, immune cells, and extracellular matrix components can modify metabolic pathways, making it challenging to predict therapeutic outcomes [279, 281]. The architectural and mechanical properties of the tumor environment play a crucial role in controlling metabolic plasticity.

Fig. 6
figure 6

The flow chart illustrates the multifaceted challenges and future directions in overcoming metabolic plasticity in cancer cells. The left section highlights the primary challenges, including metabolic plasticity, metabolic heterogeneity within and between tumors, redundancy and compensation in metabolic pathways, influence of the tumor microenvironment and the difficulty in effectively targeting single metabolic pathways. The right section outlines future directions, such as comprehensive profiling of cancer metabolism at single-cell resolution using advanced omics technologies, targeting multiple pathways with combination therapies, modulating the tumor microenvironment to reduce metabolic adaptability, and understanding the temporal dynamics of metabolic changes to develop phase-specific therapies

To address these challenges, future directions include comprehensive profiling of cancer metabolism at single-cell resolution using advanced omics technologies (genomics, proteomics, metabolomics). This approach can help identify key metabolic vulnerabilities. Targeting multiple pathways simultaneously with combination therapies could overcome the redundancy and compensation seen in cancer metabolism. Modulating the tumor microenvironment, such as normalizing blood supply or altering the extracellular matrix, may reduce the metabolic adaptability of cancer cells and enhance the efficacy of metabolic inhibitors. Understanding the temporal dynamics of metabolic changes in cancer cells could lead to therapies that target specific metabolic states or phases of the cell cycle, reducing the likelihood of adaptation.

Combination therapies present another set of challenges in targeting cancer metabolism [154]. One major challenge is the increased risk of toxicity and adverse side effects, which can limit the doses that can be safely administered [282]. Unanticipated interactions between drugs can also affect their efficacy and safety profiles, complicating the design of combination regimens [283]. Optimizing the dosing and scheduling for combination therapies is complex and requires extensive preclinical and clinical testing [284]. Despite these efforts, cancer cells may still develop resistance to combination therapies through various mechanisms, including genetic mutations and epigenetic alterations [285].

To enhance the efficacy of combination therapies, future directions include the rational design of combinations based on mechanistic insights into cancer metabolism and signaling pathways, which can improve efficacy and reduce toxicity. Identifying synergistic drug combinations through high-throughput screening and computational modeling can enhance therapeutic outcomes while minimizing side effects. Adaptive therapy strategies that dynamically adjust treatment based on tumor response and resistance patterns may prolong the efficacy of combination treatments and delay resistance. Personalizing combination therapies to individual patients based on their unique genetic and metabolic profiles can optimize efficacy and reduce adverse effects, leading to more effective and tailored treatment approaches.

Identifying reliable biomarkers for metabolic targeting poses several challenges. One of the primary challenges is the identification and validation of biomarkers that accurately reflect metabolic changes in cancer cells. This requires extensive clinical testing to ensure sensitivity, specificity, and reproducibility [286]. This process is complex and time-consuming, as it involves rigorous evaluation of potential biomarkers across diverse patient populations. Tumor heterogeneity can lead to variability in biomarker expression, complicating their use in predicting therapeutic responses [216]. Additionally, metabolic biomarkers may change dynamically in response to therapy and disease progression, necessitating the development of robust methods for real-time monitoring [287]. Some metabolic biomarkers may also be difficult to measure non-invasively, limiting their clinical utility.

Future directions in this area include developing liquid biopsy techniques to measure circulating metabolites, exosomes, or other biomarkers, providing minimally invasive methods for monitoring cancer metabolism and treatment response. Integrating multi-omics data (e.g., genomics, proteomics, metabolomics) can help identify comprehensive biomarker signatures that reflect the metabolic state of cancer cells. Advances in imaging technologies and biosensors can enable real-time monitoring of metabolic changes in tumors, aiding in the timely adjustment of therapeutic strategies. Developing predictive biomarkers that can identify patients most likely to benefit from specific metabolic therapies can enhance personalized treatment approaches and improve outcomes. By addressing these challenges and pursuing these future directions, researchers can make significant strides in the effective targeting of cancer metabolism.

Conclusion

The study of altered metabolism in cancer has unveiled crucial energy pathways driving tumor growth and survival, highlighting therapeutic opportunities. Key metabolic mechanisms include the Warburg effect, where cancer cells prefer glycolysis even in oxygen-rich conditions, alongside oxidative phosphorylation, glutaminolysis, and lipid metabolism. These processes, regulated by oncogenes, tumor suppressors, epigenetic changes, and the tumor microenvironment, offer targets for therapy. Potential interventions include glycolysis inhibitors like 2-deoxy-D-glucose, oxidative phosphorylation inhibitors, glutamine metabolism inhibitors such as CB-839, and fatty acid synthase inhibitors. Additionally, modulating key regulators like the mTOR and PI3K/AKT pathways expands therapeutic options. However, cancer cells’ metabolic plasticity challenges single-agent therapies, suggesting that combination therapies may enhance efficacy. Identifying biomarkers for metabolic targeting will aid in patient selection and treatment monitoring. Future research should explore the interplay between metabolic pathways and their regulation by the tumor microenvironment to develop effective treatments. Integrating metabolic inhibitors with conventional therapies promises to transform cancer treatment, offering hope for improved patient outcomes. Overall, studying altered cancer metabolism provides critical insights and paves the way for innovative and precise therapeutic strategies.

Availability of data and materials

No datasets were generated or analysed during the current study.

Abbreviations

TME:

Tumor microenvironment

HIFs:

Hypoxia-inducible factors

AMPK:

AMP-activated protein kinase

LUAD:

Lung adenocarcinoma

LDHA:

Lactate dehydrogenase A

OXPHOS:

Oxidative phosphorylation

ETC:

Electron transport chain

AML:

Acute myeloid leukemia

LSCs:

Leukemic stem cells

ROS:

Reactive oxygen species

MMPs:

Matrix metalloproteinases

EMT:

Epithelial-mesenchymal transition

CSCs:

Cancer stem cells

TCA:

Tricarboxylic acid

GDH:

Glutamate dehydrogenase

FAO:

Fatty acid oxidation

PI3K:

Phosphatidylinositol 3-kinase

PIP3:

Phosphatidylinositol (3,4,5)-trisphosphate

CAFs:

Cancer-associated fibroblasts

TAMs:

Tumor-associated macrophages

VEGF:

Vascular endothelial growth factor

HATs:

Histone acetyltransferases

HDACs:

Histone deacetylases

miRNAs:

microRNAs

lncRNAs:

Long non-coding RNAs

ECM:

Extracellular matrix

PKM2:

Pyruvate kinase M2

LDH:

Lactate dehydrogenase

IDH:

Isocitrate dehydrogenase

CPT1:

Carnitine Palmitoyltransferase 1

ACAD:

Acyl-CoA Dehydrogenase

MCT:

Monocarboxylate Transporter

HK2:

Hexokinase 2

PFK:

Phosphofructokinase

GLUT:

Glucose Transporters

TIGAR:

TP53-Induced Glycolysis and Apoptosis Regulator

SCO2:

Synthesis of Cytochrome c Oxidase 2

PTEN:

Phosphatase and Tensin Homolog

LKB1:

Liver Kinase B1

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