Metabolic ripple effects – deciphering how lipid metabolism in cancer interfaces with the tumor microenvironment

Altered regulation of cellular metabolism is considered a hallmark of cancer (Hanahan, 2022). Rapidly proliferating, transformed cancer cells require metabolic adaptations to support their enhanced energetic and biosynthetic demands (Hanahan, 2022; Vander Heiden and DeBerardinis, 2017). Because metabolic changes are necessary for tumor growth, ongoing efforts in cancer research seek to identify key nodes in these metabolic adaptations that might provide potential, novel targets for anti-cancer therapies (Stine et al., 2022).

However, these efforts have been hampered by various challenges (Fendt et al., 2020; Martínez-Reyes and Chandel, 2021; Stine et al., 2022). In particular, cell-extrinsic features in the tumor microenvironment (TME), such as limited oxygen, pathophysiological nutrient availability, acidity, the presence of stromal cells and physical stressors, influence the metabolism and targetable metabolic liabilities of cancer cells (Faubert et al., 2020; Lau and Vander Heiden, 2020; Lyssiotis and Kimmelman, 2017; Muir et al., 2018). As cancer cell metabolism is influenced by features outside of the cell, the metabolic properties and liabilities of cancer cells defined in one experimental model system might not be relevant in a clinical setting, in which cancer cells face different external stimuli (Elia and Haigis, 2021; Lau and Vander Heiden, 2020; Lim et al., 2020; Lyssiotis and Kimmelman, 2017; Muir and Vander Heiden, 2018). Thus, efforts to identify clinically relevant metabolic vulnerabilities of cancer cells must effectively model diverse components of the TME.

Lipid metabolism is required for cellular biomass and energy production. It is well established that oncogenic mutations and the signaling pathways downstream of these mutated oncogenes regulate lipid metabolic pathways in cancer cells to enable tumor growth and proliferation. For comprehensive reviews on how oncogenic mutations in cancer cells rewire cellular lipid metabolism, we refer readers to these excellent reviews: Dang and Semenza (1999); Iurlaro et al. (2014); Nagarajan et al. (2016); Snaebjornsson et al. (2020); and Vogel et al. (2024). However, recent research suggests that lipid metabolism in cancer cells also responds to factors in the TME. In the first part of this Review, we discuss this literature, detailing how the regulation of a select class of lipid metabolic reactions are entwined with influences from the TME.

Just as diverse TME features regulate cancer cell lipid metabolism, lipid availability in the TME alters numerous metabolic pathways, beyond lipid synthesis and catabolism. Still, relatively little is known about how lipid availability impacts tumor metabolism, even though lipids are one of the most abundant and dynamic classes of metabolites in circulation (Dallmann et al., 2012; Quehenberger and Dennis, 2011; Quehenberger et al., 2010). As such, in the second half of this Review, we explore recent studies demonstrating that lipid availability affects disparate cellular metabolic processes in cancers. By discussing this literature, we aim to highlight how lipid availability has ‘ripple’ effects on the entire metabolic network due to the dense and interconnected nature of cell metabolism. Given the strongly entwined interactions between the TME and cellular metabolism, we also discuss experimental tools and approaches that are needed to integrate disparate areas of TME research and metabolic biology, to enable researchers to better understand how the TME influences cancer cell metabolic phenotypes and targets.

Lipid metabolism is the set of cellular metabolic processes that facilitate the acquisition and utilization of sterols (see Glossary, Box 1), phospholipids (Box 1) – which are important in membrane synthesis, and neutral lipids (Box 1) – which are critical for storage (Chandel, 2021; Harayama and Riezman, 2018; Yoon et al., 2021). These lipid species are essential for many processes that maintain cellular homeostasis. Cells use fatty acids (Box 1), sterols and complex lipids (Box 1) as building blocks for cell membranes during cell proliferation (Fig. 1D). Cells can also catabolize fatty acids from the circulation or phospholipids to produce energy in the form of adenosine triphosphate (ATP) via mitochondrial β-oxidation (Fig. 1E). Finally, nearly all healthy and malignant cells store sterols and fatty acids in specialized organelles called lipid droplets that act as reservoirs for lipids (Olzmann and Carvalho, 2019; Tirinato et al., 2017; Walther and Farese, 2012; Zadoorian et al., 2023) (Fig. 1C). Although there are no quantitative studies on the partition of lipids in cancer cells into these different pathways, there is increasing evidence that how cancer cells acquire and utilize lipids is influenced by the TME. The metabolism of lipid species such as membrane phospholipids and sphingolipids (Box 1) is often altered in cancers (Cheng et al., 2016; Ogretmen, 2018). However, TME regulation of the metabolism of these lipids is largely unexplored. In this section, we discuss how the TME regulates the choice between different lipid acquisition and utilization pathways in cancer. We focus specifically on the metabolic pathways related to fatty acid and cholesterol species that are required for tumors to meet their metabolic requirements of growth, and for which TME regulation has been the most extensively studied (Fig. 1).

We want to highlight two key features of lipid metabolism. First, tumors broadly have two lipid acquisition pathways. Tumors can acquire the sterols, fatty acids and complex lipids needed for growth via de novo synthesis (Fig. 1B) from the precursor acetyl coenzyme A (CoA) or via uptake from the environment through fatty acid and sterol uptake systems (Fig. 1A). Although de novo lipid synthesis is restricted to select healthy tissues (Hollands and Cawthorne, 1981), many tumor cells express lipid synthesis enzymes and produce lipids de novo, at least in cell culture models (Menendez and Lupu, 2007; Röhrig and Schulze, 2016). How cells acquire lipids, whether by synthesis or uptake, is tightly regulated and linked to the interactions between the cell and its environment. Thus, the mode of lipid acquisition in cancer cells is tightly coupled to the TME. Second, lipid homeostasis requires lipid classes to be balanced in the cell. For example, having a balance of saturated and unsaturated fatty acids is essential for processes that involve membrane function, such as cellular signaling. A failure to maintain a healthy ratio of saturated and unsaturated fatty acids results in cell death (Liang et al., 2022; Sunshine and Iruela-Arispe, 2017; Volmer et al., 2013). Thus, cancers must tightly control and maintain the balance of lipid stoichiometry, despite challenges from TME stressors. Here, we highlight how lipid acquisition and utilization changes in cancer cells in response to TME to enable tumors to maintain lipid homeostasis despite the metabolic challenges of the TME.

Many tumors have limited perfusion due to pathological angiogenesis and structural stresses on blood vessels, driven by uncontrolled growth and desmoplasia (Box 1) (DuFort et al., 2016; Fukumura et al., 2010; Jain, 2013; Jain et al., 2014; Olive et al., 2009). Limited perfusion results in reduced oxygen delivery, making hypoxia a key feature of many tumors (Challapalli et al., 2017; Wilson and Hay, 2011). Below, we discuss studies that demonstrate how hypoxia in the TME influences cellular lipid metabolism (Fig. 2).

Several enzymes that metabolize lipids require oxygen as a cofactor. For example, fatty acid desaturases, such as the enzyme stearoyl-CoA desaturase (SCD), utilize oxygen to catalyze the conversion of saturated fatty acids to unsaturated fatty acids and maintain a homeostatic balance between these fatty acids (Flowers and Ntambi, 2008; Paton and Ntambi, 2009; Sen et al., 2023). Thus, TME hypoxia reduces SCD activity (Agarwala et al., 2023; Kamphorst et al., 2013; Paton and Ntambi, 2009; Young et al., 2013) and constrains the ability of cancer cells to maintain a balance between unsaturated and saturated fatty acids.

Hypoxic cancer cells use two lipid metabolic adaptations to cope with limited desaturase activity. First, hypoxia enhances the uptake of exogenous unsaturated fatty acids and lysolipids (Box 1) in both normal and cancer cells (Bensaad et al., 2014; Kamphorst et al., 2013; Krishnan et al., 2009). This enables hypoxic cancer cells to acquire the unsaturated fatty acids that are needed to maintain a balance between saturated and unsaturated fatty acid levels, thus maintaining lipid homeostasis. Additionally, hypoxia triggers the release of monounsaturated fatty acids (MUFAs) from lipid droplets to compensate for loss of SCD activity in cancer cells. The catabolism of lipid droplets allows hypoxic cancer cells to maintain balanced fatty acid saturation when SCD activity is limited, facilitating cancer cell growth in the TME (Ackerman et al., 2018). Thus, hypoxia, by limiting a single cofactor required for lipid metabolic enzymes, can substantially alter how cancers acquire the unsaturated fatty acids that are required for lipid homeostasis.

In addition to directly regulating metabolic enzyme activity, hypoxia also indirectly impacts lipid metabolism in tumors. Oxygen serves as the terminal electron acceptor in the electron transport chain (ETC). In hypoxic conditions, the regeneration of nicotinamide adenine dinucleotide (NAD⁺) is limited due to reduced electron transport and concomitant loss of NADH oxidation (Birsoy et al., 2015; Sullivan et al., 2015). The reduction in NAD⁺ availability perturbs lipid metabolic reactions that require NAD⁺ as a cofactor. One such reaction is the oxidative production of citrate, a critical precursor of acetyl-CoA needed for fatty acid synthesis. Thus, citrate production and lipid synthesis are limited in hypoxic cells (Fan et al., 2013; Li et al., 2022; Wise et al., 2011).

Hypoxic cancer cells therefore require adaptations to overcome this restricted oxidative production of citrate. For example, they can produce citrate reductively by using glutamine as a carbon source (Fendt et al., 2013; Metallo et al., 2011; Mullen et al., 2011; Wise et al., 2011). However, reductive citrate production is unlikely to be sufficient to support de novo fatty acid synthesis (Li et al., 2022). Hypoxic cancer cells also adapt to reduced synthetic capacity by acquiring exogenous fatty acids (Li et al., 2022) or by synthesizing acetyl-CoA from other carbon sources taken up from outside of the cell. These sources include acetate (Gao et al., 2016), a metabolite that is increased in the TME of some tumors (Murthy et al., 2024), or citrate (Kumar et al., 2021). Thus, hypoxia indirectly constrains cancer cell fatty acid synthesis by limiting the ETC, which forces tumors to rely on alternative means of acquiring fatty acids.

In addition to regulating lipogenic substrate availability, hypoxia also regulates lipid metabolism by activating oxygen-sensing pathways, which regulate lipid metabolic reactions. For instance, hypoxia-sensing pathways regulate both fatty acid and sterol synthesis. Recent work has shown that sterol regulatory element-binding protein 2 (SREBP2, encoded by SREBF2), a key transcriptional regulator of sterol synthesis enzymes (Brown and Goldstein, 1997), is ubiquitinated and degraded by the hypoxia-responsive, endoplasmic reticulum-resident ubiquitin ligase named membrane-associated ring-CH-type finger 6 (MARCHF6) (Dickson et al., 2023) (Fig. 2). Interestingly, SREBP1 (encoded by SREBF1), a closely related protein that regulates fatty acid metabolism (Shimano and Sato, 2017), is not regulated by MARCHF6, suggesting that sterol and fatty acid metabolism are differentially regulated by hypoxia. Notably, the MARCHF6-mediated degradation of SREBP2 does not occur in tumor-infiltrating myeloid cells, in which hypoxia instead promotes SREBP2 processing by promoting Golgi–endoplasmic reticulum fusion (Nakahara et al., 2023). This suggests that different cell types experiencing hypoxia have different lipid metabolic responses.

The same hypoxia-responsive signaling pathways that constrain lipid synthesis also facilitate metabolic adaptations to decreased lipid synthesis. As discussed above, hypoxic cancer cells adapt to inhibited lipid synthesis in three main ways: (1) through the reductive generation of citrate for lipid synthesis; (2) through the uptake of exogenous acetate or citrate for lipid synthesis; and (3) through the uptake of exogenous lipids, circumventing lipid synthesis entirely. Hypoxia-sensing pathways contribute to all three of these adaptive mechanisms. For example, the hypoxia-stabilized transcription factor hypoxia-inducible factor 1-α (HIF1α, encoded by HIF1A) promotes the ubiquitination and degradation of the α-ketoglutarate dehydrogenase (αKGDH) complex by the E3 ubiquitin ligase SIAH2 (Sun and Denko, 2014) (Fig. 2). This degradation inhibits glutamine oxidation and promotes the reductive generation of citrate and lipid synthesis under hypoxic conditions (Sun and Denko, 2014). Additionally, HIF1α promotes the expression of acyl-CoA synthetase short-chain family member 2 (ACSS2), which converts acetate to cytosolic acetyl-CoA. Thus, HIF1α activation of ACSS2 allows cancer cells to use acetate lipid synthesis in hypoxic conditions when oxidative production of acetyl-CoA may be limited (Comerford et al., 2014; Schug et al., 2015) (Fig. 2). Hypoxia-responsive signaling also regulates lipid uptake in cancer cells. HIF1α increases cellular lipid uptake by inducing the expression of fatty acid-binding proteins (FABPs) 3 and 7 (FABP3 and FABP7) in glioblastoma, which are both required for cancer cell survival in hypoxic conditions (Bensaad et al., 2014). HIF1α signaling also promotes lipid uptake by increasing the expression of lipoprotein receptors in cancer cells (Shen et al., 2012). In addition to HIF1α, hypoxia activates other pathways that promote lipid accumulation. Hypoxia increases lipid uptake and FABP4 levels in ovarian cancer cells by downregulating the FABP4 inhibitory microRNA miR-409-3p (Gharpure et al., 2018). Thus, hypoxia-sensing pathways enable cells to switch from oxidative de novo lipid synthesis to alternative pathways of lipid acquisition that are not limited by oxygen availability.

Lastly, in addition to regulating lipid synthesis and uptake in cancer cells, hypoxia also regulates the metabolic utilization of lipids in cancer cells. HIF1α activity downregulates the expression of carnitine palmitoyltransferase 1A (CPT1A) and medium- and long-chain acyl-CoA dehydrogenases, key enzymes for the import of mitochondrial fatty acids and for the β-oxidation of lipids, thus limiting fatty acid catabolism in cancer cells (Du et al., 2017; Huang et al., 2014; Miess et al., 2018). HIF signaling instead promotes increased storage of fatty acids in lipid droplets, both by increasing the transcription of lipid droplet proteins (Qiu et al., 2015) and by inhibiting enzymes that hydrolyze lipids from droplets (Zhang et al., 2017b). Importantly, redirecting fatty acids from catabolism towards storage in lipid droplets is critical for tumor growth (Du et al., 2017; Qiu et al., 2015; Zhang et al., 2017b). Therefore, oxygen-sensing pathways allow tumors to adapt to hypoxia by regulating the metabolic fates of lipids in cancer cells.

When considered together, a key theme emerges from these studies: TME hypoxia constrains de novo lipogenesis in cancers. In response, hypoxia-sensing pathways enable tumors to cope with this constraint by activating alternative pathways, such as lipid uptake, to allow tumors to acquire the lipids they need for their homeostasis and growth.

Limited vascular perfusion and altered metabolic activity of both malignant and stromal cells can lead to pathophysiological concentrations of amino acids in the TME (Apiz Saab et al., 2023; Fukumura et al., 2010; Menjivar et al., 2023). Variability in amino acid abundance influences lipid metabolism in two ways: directly, as amino acids can be substrates for lipid metabolic reactions, and indirectly, through cellular programs that alter cell signaling in response to amino acid abundance. Below (and in Fig. 3), we discuss how amino acid availability in the TME regulates lipid metabolism in tumors.

Glutamine (Fendt et al., 2013; Metallo et al., 2011; Mullen et al., 2011; Wise et al., 2011), as discussed previously, can be used as a carbon source to produce lipogenic acetyl-CoA when glucose-derived citrate is depleted. In pancreatic cancer, alanine, which is abundant in the pancreatic TME due to its excretion by pancreatic stromal stellate cells (Box 1), can also be a source of acetyl-CoA for lipogenesis (Sousa et al., 2016). Pancreatic cancers can also catabolize branched-chain amino acids (Zhu et al., 2020) to support lipogenesis (Lee et al., 2019), a pathway similarly used by adipocytes to fuel lipogenesis (Green et al., 2016). Beyond fatty acid synthesis, cancer cells can also use amino acids for complex lipid synthesis. The amino acid serine, for example, is necessary for sphingolipid synthesis. In colorectal cancer, a reduction of serine in the TME leads to the decreased production of canonical sphingolipids (Gao et al., 2018; Muthusamy et al., 2020). Importantly, the enzyme that uses serine as a substrate, serine palmitoyltransferase (SPT), is promiscuous and can use alanine as a substrate to produce 1-deoxysphingolipid when serine levels are low (Lone et al., 2019). Under conditions of serine deprivation, colorectal tumors produce toxic levels of 1-deoxysphingolipid that slow tumor growth (Muthusamy et al., 2020). Thus, by virtue of serving as substrates in multiple lipid metabolic pathways, amino acids in the TME directly impact tumor lipid metabolism.

Amino acid abundance also indirectly affects cellular lipid metabolism through amino acid-sensing signaling pathways that regulate lipid metabolism (Efeyan et al., 2015; Palm and Thompson, 2017; Torrence and Manning, 2018). In particular, mammalian target of rapamycin (mTOR), general control nonderepressible protein 2 (GCN2, encoded by EIF2AK4) and SREBP can all sense cellular amino acid abundance and alter lipid metabolism.

mTOR is an amino acid-sensing protein complex that regulates lipid metabolism (Caron et al., 2015; Lamming and Sabatini, 2013; Ricoult and Manning, 2013). In amino acid-replete conditions, mTOR complex 1 (mTORC1) is active and drives lipid biogenesis by activating SREBP transcription, processing and trafficking (Caron et al., 2015; Lamming and Sabatini, 2013; Ricoult and Manning, 2013). However, in solid tumors that have decreased amino acid availability, mTORC1 can be inactivated (Bielska et al., 2022; Palm et al., 2015). Thus, amino acid stress in the TME likely dampens lipogenesis in tumors by suppressing mTOR activity, although this remains to be assessed. Interestingly, mTOR inactivation appears to be adaptive for tumors and is required for cell survival under nutrient stress (Bielska et al., 2022; Palm et al., 2015).

Decreased mTOR activity also aids cells that are coping with nutrient stress by changing the way cells utilize lipids. For example, amino acid starvation leads to increased fat storage in lipid droplets in an mTOR-dependent manner (Nguyen et al., 2017). Increased fat storage is contingent on the lipid droplet regulators diacylglycerol O-acyltransferase 1 (DGAT1) (Nguyen et al., 2017) and hypoxia-inducible lipid droplet-associated protein (HILPDA) (VandeKopple et al., 2019) and prevents excessive fatty acid β-oxidation. When cells are unable to store lipids in droplets under nutrient starvation, acylcarnitines (Box 1) accumulate, triggering mitochondrial dysfunction and cell death (Nguyen et al., 2017). This is reflected in xenograft tumors of human colorectal cancer cells in mice, in which the ablation of HILPDA decreased tumor growth and lipid droplet accumulation (VandeKopple et al., 2019). Thus, colorectal tumors must store lipids in lipid droplets rather than oxidize them to survive amino acid deprivation in the TME (VandeKopple et al., 2019). This implies that mTOR suppression enables tumors to survive in the amino acid-deprived TME by altering lipid utilization.

GCN2 is an integrated stress response kinase that senses amino acid deprivation via uncharged tRNAs and stalled ribosomes. During amino acid starvation in tissues, GCN2 suppresses lipid synthesis by inhibiting the expression of SREBP and of SREBP target genes (Dudek and Semenkovich, 1995; Guo and Cavener, 2007). Interventions that lower TME amino acid availability suppress SREBP activity and lipid synthesis in tumors in a GCN2-dependent manner (Xiao et al., 2016). Thus, GCN2 signaling might be a critical pathway by which amino acid abundance in the TME regulates tumor lipid synthesis.

Lastly, SREBP transcription factors themselves sense the availability of specific amino acids. For example, glutamine activates lipogenesis in tumors by activating SREBP cleavage-activating protein (SCAP) (Cheng et al., 2022). Interestingly, the catabolism of glutamine to ammonia is required for SREBP activation, indicating that SREBP responds to ammonia availability as well, which is elevated in the TME of solid tumors (Spinelli et al., 2017).

Altogether, these studies demonstrate that amino acid deprivation perturbs lipogenesis in cancer cells. Amino acid-sensing programs also change the way cancer cells utilize lipids to continue meeting the metabolic needs of tumors, facilitating continued growth.

Some cancers have limited glucose in their TME (Gullino et al., 1965; Helmlinger et al., 2002; Ho et al., 2015; Nwosu et al., 2023). Below (and in Fig. 4), we discuss how limited glucose in the TME impacts tumor lipid metabolism.

In cancer cells, glucose limitation triggers many nutrient-sensing pathways that interface with lipid metabolism. One such pathway is SREBP transcriptional activity. Glucose mediates SCAP glycosylation and activation, facilitating the activation of SREBP and downstream signaling (Cheng et al., 2015). Thus, glucose availability dictates the transcription of lipogenic genes through the SREBP–SCAP axis. Glucose deprivation also influences lipid metabolism by lowering cellular ATP levels and activating AMP-activated protein kinase (AMPK) (Hardie et al., 2016; Herzig and Shaw, 2018; Lin and Hardie, 2018). AMPK inhibits cellular fatty acid synthesis by phosphorylating and inhibiting acetyl-CoA carboxylase 1 (ACC1, encoded by ACACA), limiting the conversion of the lipogenic substrate acetyl-CoA to malonyl-CoA (Hardie et al., 2016; Herzig and Shaw, 2018; Lin and Hardie, 2018). Notably, xenograft tumors of both human lung and breast cancer cells in mice rely on AMPK signaling and downregulated lipid synthesis to survive glucose deprivation (Jeon et al., 2012). If AMPK is perturbed, continued fatty acid synthesis exhausts cellular NADPH pools, resulting in impaired regeneration of reduced glutathione and making cells sensitive to redox stress. Thus, glucose deprivation in tumors, similar to amino acid deprivation and hypoxia, suppresses lipid synthesis in cancer cells. This suppression preserves cellular NADPH pools, which are essential for proliferating tumors.

The TME is often acidic due to the high levels of metabolic activity in the tumor and limited perfusion, which is needed to remove acidic waste (Corbet and Feron, 2017; Swietach et al., 2023; Webb et al., 2011). In numerous studies, TME acidity has been shown to induce the accumulation of lipid droplets in cancer cells, driven by both increased lipid synthesis and increased lipid uptake, depending on the cell type (Corbet et al., 2020; Dierge et al., 2021; Ding et al., 2022; Menard et al., 2016; Nardi et al., 2019). In human colorectal and squamous cell carcinoma cells (Corbet et al., 2020; Dierge et al., 2021), lipid uptake via cluster determinant 36 (CD36) is required for acid-induced lipid droplet formation (Corbet et al., 2020; Dierge et al., 2021). In human glioblastoma cell lines (Menard et al., 2016), lipid droplet fatty acids come from lipoprotein uptake (Menard et al., 2016). In contrast, in liver cancer cells, acid-induced lipid droplets form via increased fatty acid synthesis (Ding et al., 2022) and, in pancreatic cancer, acidity increases SREBP activity and sterol synthesis (Kondo et al., 2017).

Acid-driven lipid accumulation is functionally important to tumors. Acidity increases fatty acid β-oxidation by downregulating acetyl-CoA carboxylase 2 (ACC2), a negative regulator of β-oxidation (Corbet et al., 2016). The enhanced β-oxidation of lipids stored in lipid droplets is an important source of ATP, which is necessary for metastatic progression (Corbet et al., 2020). Inhibiting β-oxidation reverses the enhanced metastatic potential of cancer cells (Corbet et al., 2020). Thus, acidity in the TME regulates both lipid abundance and utilization in cancer cells (Fig. 4).

Notably, cancer cells in different contexts require lipid droplets for distinct purposes. As discussed previously, nutrient-deprived tumors require lipid droplets to sequester a toxic buildup of acylcarnitines (Nguyen et al., 2017; VandeKopple et al., 2019), whereas lipid droplet hydrolysis is required in cancer cells in acidic environments to produce energy via β-oxidation (Corbet et al., 2020). How lipid metabolism in cancer cells responds to environments that are both hypoxic and acidic remains to be determined.

Tumors can be thought of as complex ecosystems that contain both malignant and stromal cells that interact in intricate ways (de Visser and Joyce, 2023). In the following section, we discuss how stromal cells in the TME influence tumor lipid metabolism (Fig. 5).

Adipocytes in the TME provide lipids to cancer cells. These lipids are consumed via β-oxidation in cancer cells in multiple cancer models, including mouse models of ovarian and breast tumors, and zebrafish models of melanoma (Mukherjee et al., 2020, 2023; Nieman et al., 2011; Wang et al., 2017; Zhang et al., 2018). In ovarian cancer, adipocytes produce fatty acids, which are taken up by FABP4-expressing cancer cells and oxidized into ATP (Mukherjee et al., 2020). Because ovarian tumor cells use fatty acids to produce ATP, ovarian cancer metastases preferentially home to adipocyte-rich sites such as the omentum (Box 1) (Mukherjee et al., 2020, 2023; Nieman et al., 2011). Interestingly, FABP4 expression also promotes carboplatin resistance in human ovarian cancer cells in culture and when xenografted in mice, indicating that adipocyte-induced FABP4 expression is critical to both growth and survival in the presence of chemotherapy in ovarian tumors (Mukherjee et al., 2020). Similarly, human breast cancer cells, both in culture and in murine xenograft tumors, take up adipocyte-derived free fatty acids, which can be stored in lipid droplets or oxidized for energy production (Wang et al., 2017). Disrupting this process by genetically perturbing the hydrolysis of fatty acids from lipid droplets or by pharmacologically inhibiting lipid oxidation inhibited breast cancer invasion in human cell lines and syngeneic mouse models of breast cancer (Wang et al., 2017). Lastly, melanoma invasion requires fatty acid transport protein (FATP)-mediated uptake of adipocyte-derived fatty acids in zebrafish models of breast cancer (Zhang et al., 2018). Altogether, these studies indicate that adipocyte-derived fatty acids are crucial for growth and metastatic progression in multiple models of diverse cancers.

Aside from providing fatty acids to tumor cells, adipocytes regulate cancer lipid metabolism by releasing adipokines (Box 1). A common adipokine to influence cancer growth is leptin, which is secreted by adipocytes and regulates systemic energy homeostasis. The leptin receptor (LEPR) is expressed in many tumors, making cancers primed to respond to adipocyte-derived leptin (de Candia et al., 2021). In both human breast cancer cell lines and genetically engineered mouse models of breast cancer, leptin exposure promotes fatty acid β-oxidation (Blanquer-Rosselló et al., 2016; Liu et al., 2019; Pham et al., 2021; Wang et al., 2018). Notably, human breast cancer cells exposed to leptin grew more aggressively than unexposed cells, indicating that adipocyte-derived leptin plays a role in driving tumor progression (Wang et al., 2018). Other adipokines, such as adiponectin, perturb breast tumor proliferation by inhibiting cholesterol uptake in genetically engineered mouse models of breast cancer (Liu et al., 2013). These findings show that the way in which adipokines influence tumor growth is complex. Future studies are therefore needed to determine how tumor and lipid metabolism respond to different adipocyte signals with diverging outcomes.

In multiple tumor types, stromal fibroblasts influence lipid metabolism by providing lipids and lipogenic precursors to cancer cells. In human melanoma and breast cancer cell lines, exposure to cancer-associated fibroblasts (CAFs) increases the lipid content of cancer cells. This requires both the secretion of lipids by fibroblasts and the transport of these lipids by FATPs in the cancer cells (Alicea et al., 2020; Lopes-Coelho et al., 2018). Interestingly, in both cancer types, CAF exposure increases FATP expression in the cancer cells, suggesting that CAFs not only provide lipids, but also secrete paracrine signaling factors to facilitate the uptake of these lipids (Alicea et al., 2020; Lopes-Coelho et al., 2018). Pharmacologically blocking FATP-mediated lipid uptake with FATP inhibitors in melanoma slows tumor progression and prevents resistance to targeted therapies (Alicea et al., 2020). This suggests that this metabolic interaction between CAFs and melanoma cells is crucial for disease progression. In co-culture with human pancreatic cancer cell lines, CAFs alter cancer lipid metabolism by secreting lysophosphatidylcholine (LPC) (Auciello et al., 2019). Pancreatic cancer cells use CAF-derived LPC to synthesize phosphatidylcholine (Auciello et al., 2019). CAF-secreted LPC also alters cellular signaling when hydrolyzed to lysophosphatidic acid in pancreatic tumors, which promotes oncogenic signaling and tumor progression through AKT serine/threonine kinase (AKT) activation (Auciello et al., 2019).

In addition to providing lipids directly to cancer cells, CAFs regulate tumor lipid metabolism by altering substrate availability for lipid synthesis in tumors. In prostate and pancreatic cancer cells, CAF-derived exosomes supply tumors with glutamine, glucose and other metabolites that can be used as carbon sources for lipid biosynthesis. In particular, cultured prostate and pancreatic cancer cells use glutamine from CAF-derived exosomes to synthesize lipids via reductive carboxylation (Zhao et al., 2016). Additionally, as discussed above, pancreatic tumor stellate cells provide cancer cells with alanine that can similarly be used for lipogenic reactions through its conversion to acetyl-CoA (Sousa et al., 2016).

There is increasing evidence that immune cells in the TME also regulate lipid metabolism in cancer cells. For example, immune signaling in the TME has recently been shown to constrain tumor progression by regulating lipid metabolism. In mouse models of ovarian cancer and melanoma, CD8⁺ T cells alter lipid metabolism in tumors by releasing interferon γ (IFNγ, encoded by IFNG) (Wang et al., 2019). In response to IFNγ, cancer cells downregulate SLC7A11 and SLC3A2 expression, which together mediate cysteine import in mammalian cells (Lewerenz et al., 2013). With cysteine import limited, cancer cells are unable to synthesize sufficient glutathione to reduce lipid peroxides (Wang et al., 2019). These lipid peroxides accumulate in IFNγ-exposed cancer cells and trigger ferroptosis (Box 1), a mode of cell death due to accumulation of oxidized lipids (Dixon and Olzmann, 2024; Jiang et al., 2021). Thus, immune signaling in the TME can potently affect cancer cell lipid metabolism. Further studies are necessary to fully understand how the complex cytokine signaling networks present in the TME affect tumor lipid metabolism.

In addition to regulating tumor lipid metabolism via cytokine signaling, it is possible that immune cells dictate lipid metabolism in cancer cells by directly altering lipid availability in the TME. Many TME-infiltrating immune cells rapidly import extracellular lipids (Herber et al., 2010; Ma et al., 2021; Masetti et al., 2022; Miska et al., 2022; Su et al., 2020; Wang et al., 2020; Xu et al., 2021). Furthermore, some immune cells release lipids in the TME. For example, tumor-infiltrating macrophages were found to release cholesterol in mouse models of ovarian and prostate cancer (El-Kenawi et al., 2021; Kaymak et al., 2022). Thus, immune cells may restrict TME levels of certain lipids, while increasing the availability of others. Further studies are necessary to understand how immune cells affect TME lipid availability and how such regulation impacts cancer cell lipid metabolism.

The studies discussed above investigate how lipid metabolism in cancer cells responds to isolated features of the TME. It is clear in these studies that different elements of the TME divergently regulate lipid metabolism in cancer cells. As cancers face multiple TME stresses simultaneously, future work is needed to examine how tumor lipid metabolism changes in response to multiple TME features. Nevertheless, a key finding that emerges from these studies is that most TME features suppress de novo lipid synthesis in cancer. Tumors instead utilize alternative lipid acquisition strategies, such as increasing lipid uptake from the environment or stromal cells. Thus, lipid uptake may be an underappreciated metabolic requirement of cancers.

Lastly, although we have focused this Review on how the TME impacts lipid metabolism in cancer cells, the TME also affects lipid metabolism in other cell types present in the TME. Notably, the TME affects lipid metabolism in immune cells, which affects immune control of tumors (Broadfield et al., 2021; Lou et al., 2022; Marelli et al., 2022; Vitale et al., 2019; Zhang et al., 2024). We refer readers to the following references for comprehensive reviews on how the TME affects immune cell lipid metabolism and function: Broadfield et al. (2021); Lou et al. (2022); Marelli et al. (2022); Vitale et al. (2019); and Zhang et al. (2024).

The studies discussed above show that constraints in the TME promote the reliance of tumors on exogenous lipids. As such, to understand tumor metabolism, we need to better understand lipid availability in the TME. Although we know less about lipid availability relative to other features of the TME, a small but growing body of work suggests that TME lipids are important regulators of cancer metabolism. Lipids influence not only tumor lipid metabolism, but also how cancers metabolize other substrates such as glucose. In this section, we review studies that show that lipids are important microenvironmental drivers of cancer metabolism and biology.

Extracellular lipids are transported into the TME from the systemic circulation by carrier proteins, such as albumin and lipoproteins (Van der Horst et al., 2009). After entering the TME, cancer cells take up these lipids using lipid transporters (e.g. CD36 or FATPs) (Glatz et al., 2010) or lipoprotein receptors (Deng et al., 2022), or by macropinocytosis (Box 1) (Salloum et al., 2023) (Fig. 1A). Here, we discuss how lipid availability alters tumor lipid metabolism (Fig. 6A).

Lipid availability in the TME is dynamic. Several studies have found that modifying dietary fat intake changes lipid metabolism in tumors (Altea-Manzano et al., 2023; Goswami et al., 2023; Lien and Vander Heiden, 2019; Lien et al., 2021; Ringel et al., 2020). In mouse models of multiple cancers (Altea-Manzano et al., 2023; Mana et al., 2021; Pascual et al., 2017; Ringel et al., 2020), high-fat diets increase fatty acid concentrations in the TME (Altea-Manzano et al., 2023; Lien et al., 2021), thus enhancing fatty acid uptake and oxidation (Altea-Manzano et al., 2023; Mana et al., 2021; Pascual et al., 2017; Ringel et al., 2020). These diet-driven changes in lipid metabolism are required for tumor progression. Inhibiting lipid uptake and oxidation slows tumor progression in genetically engineered mouse models of breast and colorectal cancer, and metastasis in xenograft models of squamous cell carcinoma (Altea-Manzano et al., 2023; Mana et al., 2021; Pascual et al., 2017). Dietary interventions can also lower lipid availability in the TME. For example, caloric restriction lowers fatty acid levels in mouse models of pancreatic cancer. This forces pancreatic tumors to rely heavily on the de novo synthesis of fatty acids, particularly of MUFAs, for growth (Lien et al., 2021).

Lipid availability also changes as tumors metastasize. For example, in early metastatic spread, human melanoma cells injected into mice that invade the lymph are exposed to an environment enriched in MUFAs (Fig. 6A) (Ubellacker et al., 2020). MUFAs prevent lipid peroxidation and cell death by ferroptosis (Magtanong et al., 2019). As metastasizing melanoma cells incorporate these MUFAs into phospholipids in cellular membranes, they acquire resistance to ferroptosis, facilitating metastatic spread (Ubellacker et al., 2020). Lipid availability in metastatic sites can also influence disease progression. As discussed above, ovarian and melanoma mouse models of cancer that invade adipose-rich tissues adapt by taking up and using fatty acids from the lipid-rich metastatic TME (Mukherjee et al., 2020, 2023; Nieman et al., 2011; Wang et al., 2017; Zhang et al., 2018). Liver steatosis, in which lipids accumulate in hepatocytes, makes the liver more susceptible to metastatic colonization by breast cancer cells (Li et al., 2020).

Not every metastatic site is lipid rich. Notably, the brain microenvironment has very few exogenous lipids (Ferraro et al., 2021). Thus, brain metastases arising from murine xenograft breast tumor substantially upregulate de novo lipid synthesis (Ferraro et al., 2021; Jin et al., 2020). As a result, genetic perturbation of de novo lipid synthesis inhibits the growth of brain metastases in these mouse models of breast cancer, while the primary tumor remains unaffected.

These studies show that lipid availability in the TME is a key regulator of lipid metabolism in cancer cells. There is also emerging evidence that TME lipids are key regulators of lipid biology and function in immune cells. We refer readers interested in this topic to recent reviews on this topic (Corn et al., 2020; Goswami et al., 2023; Prendeville and Lynch, 2022). The following section highlights how lipid availability alters features of cancer cell metabolism beyond lipid metabolism, exhibiting metabolic ripple effects across the cancer cell metabolome.

As metabolic pathways are highly interconnected, changes in lipid availability have ripple effects that alter many metabolic pathways. As a result, lipid availability in cancer cells affects metabolic nodes beyond lipid metabolism, as we discuss below (Fig. 6B).

As mentioned above, oxidative metabolism in mitochondria is linked to lipid synthesis through the NAD⁺/NADH redox cofactor. Lipid synthesis, by consuming large amounts of acetyl-CoA, consumes a substantial portion of the cellular NAD⁺ pool (Li et al., 2022), whereas oxidative metabolism regenerates NAD⁺ from NADH in the complex I reaction (Birsoy et al., 2015; Sullivan et al., 2015). When cancer cells are starved of lipids, they must rely on de novo lipid synthesis to maintain cellular homeostasis. These cells compensate for this increased demand for lipid synthesis, and thus increased NAD⁺ requirement, by elevating ETC activity and their oxygen consumption to regenerate NAD⁺ (Li et al., 2022). Due to this demand for NAD⁺, lipid-starved cancer cells require oxygen and ETC activity to enable lipid synthesis and growth (Li et al., 2022). Thus, fluctuations in lipid availability indirectly alter ETC activity by modulating cellular NAD⁺ requirements, indicating that TME lipid availability affects mitochondrial oxidative metabolism in tumors.

In addition to affecting cellular metabolism by modulating substrates and cofactors available in cancer cells, lipid availability also affects cancer cell metabolism through nutrient-sensing pathways that detect lipid abundance in cells. For example, lipid availability regulates the HIF1α pathway and, thus, the cellular response to hypoxia. HIF1α target genes are upregulated when certain FABPs bind exogenous fatty acids (Seo et al., 2020). For instance, oleic acid stimulates the activity of FABP5, enhancing the translation of HIF1α. As HIF1α is critical for cancer cell adaptation to hypoxia, oleic acid might indirectly help cancer cells survive hypoxia by increasing HIF1α translation (Seo et al., 2020). Lipid availability in the TME also alters the way cancer cells metabolize glucose. Glucose transporter 1 (GLUT1, encoded by SLC2A1), which is responsible for glucose uptake at the cell membrane in cancer cells, requires S-palmitoylation to maintain membrane localization and glucose import (Zhang et al., 2021). S-palmitoylation is sensitive to levels of exogenous palmitate (Spinelli et al., 2018). Thus, glucose utilization by cancer cells might be regulated by palmitate availability in the TME. Interestingly, many nutrient transporters are S-palmitoylated (Villanueva and Hagenbuch, 2023), suggesting that the uptake of many nutrients in cancer cells is regulated by the availability of palmitate in the TME.

Lastly, various studies have shown that exogenous lipids significantly alter cellular metabolism via changes in histone modification (Eduardo et al., 2024 preprint; McDonnell et al., 2016; Yadav et al., 2022). In cells exposed to fatty acids, lipid oxidation leads to increased cellular levels of acetyl-CoA (McDonnell et al., 2016), which in turn leads to the increased acetylation of histones. As a result, exposure of a cell to fatty acids leads to significant changes in its chromatin packaging (McDonnell et al., 2016; Yadav et al., 2022). Thus, histone modifications driven by fatty acid exposure lead to altered gene expression, resulting in differential activity of many metabolic pathways. In particular, one-carbon metabolism (Box 1) and serine synthesis are both elevated in human breast cancer cell lines exposed to high levels of fatty acids in vitro (Eduardo et al., 2024 preprint; Yadav et al., 2022). Thus, lipids influence metabolism by acting as a source of acetyl-CoA for cancer cells.

These findings highlight intriguing links between lipid availability and diverse areas of tumor metabolism. Future studies are necessary to determine the tumor metabolic pathways affected by TME lipid availability and the mechanisms by which these lipids impact cancer cell metabolism.

A consensus emerging from these studies is that the TME severely constrains the ability of cancer cells to synthesize lipids from canonical lipogenic pathways. Thus, tumors must rely on alternative lipid acquisition strategies. Another key conclusion is that lipid availability in the TME regulates other aspects of tumor metabolism. Lipid metabolism is highly interconnected with other metabolic pathways through shared cofactors, substrates and signaling pathways. Given this interconnection, TME lipid availability influences many metabolic properties of cancer cells, just as many non-lipid TME components influence lipid metabolism in cancer cells. To better understand the metabolic requirements of tumors, it is vitally important for future studies to: (1) accurately characterize the lipid composition of the TME, and (2) identify which TME lipids affect tumor biology and by what mechanisms.

Numerous emerging technologies will allow researchers to more accurately characterize lipids in the TME. Recent studies have isolated interstitial fluid from breast, colorectal, lung, melanoma, pancreatic and renal tumors to probe nutrient availability in the local microenvironment of these solid tumors (Apiz Saab and Muir, 2023). Lipidomic analysis can be applied to these interstitial fluid isolates to measure lipid availability in the TME (Altea-Manzano et al., 2023; Lien et al., 2021; Ringel et al., 2020; Xu et al., 2021; Zhang et al., 2017a). Rapidly maturing imaging mass spectrometry technologies will facilitate identification of the lipid species present in tumors and in specific regions and cell types (Alexandrov, 2023). Already, these imaging technologies are being applied to identify potential metabolic exchange between malignant and stromal cells in human lung cancer samples (Hu et al., 2023). Applying these techniques to investigate how lipid availability changes across tumor types, with disease progression and with therapeutic interventions will further enhance our understanding of which lipids are present in the TME.

Although emerging technologies are rapidly enabling the cataloging of lipids in the TME, the second goal – understanding the functional implications of TME lipid composition – remains challenging. New experimental tools are needed to answer these questions. Recently, novel systems, such as the fatty acid library for comprehensive ontologies (FALCON) system, have been developed to allow researchers to rapidly assess the functional effects of individual lipids on cellular phenotypes ex vivo (Wieder et al., 2023). Combined with information on the lipid composition of the TME, tools such as FALCON could identify TME lipids that functionally affect cancer cell biology. Additionally, the development of cell culture media with physiological levels of non-lipid nutrients has helped to identify previously unknown metabolic features of cancer (Ackermann and Tardito, 2019; Apiz Saab et al., 2023; Cantor, 2019; Cantor et al., 2017; Schug et al., 2015; Vande Voorde et al., 2019). The development of media with physiological levels of lipids could enable researchers to identify how lipids in the TME impact tumor metabolism, as well as the lipid species that contribute to these effects. This information will be crucial for identifying and targeting the metabolic requirements of cancers.

We thank all members of the Muir Laboratory for helpful discussion and thoughtful feedback. We thank Grace Croley for assistance with editing the manuscript.