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Glucose Metabolism and Glucose Transporters in Breast Cancer
Eunah Shin, Ja Seung Koo
Frontiers in Cell and Developmental Biology · 2021 · Review · CC BY
doi:10.3389/fcell.2021.728759 (opens in a new tab)
Abstract
Breast cancer is the most common malignancy in women worldwide and is associated with high mortality rates despite the continuously advancing treatment strategies. Glucose is essential for cancer cell metabolism owing to the Warburg effect. During the process of glucose metabolism, various glycolytic metabolites, such as serine and glycine metabolites, are produced and other metabolic pathways, such as the pentose phosphate pathway (PPP), are associated with the process. Glucose is transported into the cell by glucose transporters, such as GLUT. Breast cancer shows high expressions of glucose metabolism-related enzymes and GLUT, which are also related to breast cancer prognosis. Triple negative breast cancer (TNBC), which is a high-grade breast cancer, is especially dependent on glucose metabolism. Breast cancer also harbors various stromal cells such as cancer-associated fibroblasts and immune cells as tumor microenvironment, and there exists a metabolic interaction between these stromal cells and breast cancer cells as explained by the reverse Warburg effect. Breast cancer is heterogeneous, and, consequently, its metabolic status is also diverse, which is especially affected by the molecular subtype, progression stage, and metastatic site. In this review, we will focus on glucose metabolism and glucose transporters in breast cancer, and we will additionally discuss their potential applications as cancer imaging tracers and treatment targets.
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From PubMed Central, U.S. National Library of Medicine, as current on Oct 24, 2026. Paragraph numbers are ours, so an answer can point at one.
Introduction
Breast cancer is the most common malignancy in women worldwide, and ranks top in the cause of death in female cancers worldwide. A total of 2.1 million women were newly diagnosed with breast cancer in 2018, and 627,000 women died of breast cancer. Breast cancer is increasing in underdeveloped and developing countries, and it is decreasing in developed countries since the early 2000s. Breast cancer presents with diverse characteristics. To categorize such diverse features of breast cancer, molecular subtypes have been developed: luminal A, luminal B, HER-2, and basal-like type. Moreover, estrogen receptor (ER), progesterone receptor (PR), and HER-2 are the main targets for targeted therapy in breast cancer, and samples/cases that are negative for these three receptors are defined as triple negative breast cancer (TNBC), which comprises about 15% of breast cancer cases. Each of the molecular subtypes of breast cancer and TNBC shows distinct clinical and molecular features in treatment response. Generally, breast cancer is treated with surgery, chemo-radiotherapy, and targeted therapy for biomarkers. Breast cancer showing hormone receptor expressions is treated with hormonal therapy such as tamoxifen, and breast cancer showing HER-2 amplification is treated with targeted therapy such as trastuzumab. Those that do not have any treatment targets are treated with a non-specific chemotherapy.
One of the fundamental characteristics of cancer cells that differs from normal cells is metabolic reprogramming—producing energy through glycolysis rather than mitochondrial oxidative phosphorylation, which is known as the Warburg effect after the German scientist Otto Warburg who first described it in the 1950s. The Warburg effect was first described in the 1950s by Otto Warburg, a German scientist, who stated that cancer cells secrete high levels of lactate because of an increase in glycolysis. In the process of glycolysis, which is one of the main processes of glucose metabolism, glucose can enter cancer cells by glucose transporters. As a result, various glucose metabolites are produced that are related to diverse metabolic pathways, such as the serine/glycine metabolic pathway and pentose phosphate pathway (PPP). These glucose metabolic pathways and glucose transporters have pivotal roles in cancer metabolism as well as in cancer progression and metastasis, and such metabolic characteristics can be used in imaging diagnosis and targeted therapies. This review will focus on the glucose metabolic pathways, such as glycolysis, serine/glycine pathway, and PPP, in breast cancer and glucose transporters used in glycolysis and their potential implications in clinical practice.
General Aspects of Glucose Metabolism and Related Metabolic Pathways in Cancer
Glucose metabolism consists of glycolysis and PPP, and glycolysis-related metabolic pathways consist of serine and glycine metabolism (Figure 1). A major pathway in the glucose metabolism of cancer cells is aerobic glycolysis, in the process of which glucose is first transported into the cancer cells by glucose transporters and then metabolized to pyruvate by various enzymes. Many enzymes are involved in this process, of which, the key enzymes are hexokinase II (HKII), phosphofructokinase (PFK), and pyruvate kinase (PK). Pyruvates produced in glycolysis are then moved into the mitochondria by mitochondrial pyruvate carriers 1 and 2, where they are turned into acetyl-CoA and oxaloacetate by pyruvate dehydrogenase and pyruvate carboxylase, respectively, to enter the TCA cycle for oxidative phosphorylation (OXPHOS). With one of the intermediate metabolites produced during the process of glycolysis, 3-phosphoglycerate (3PG), starts the serine pathway, in which 3-phosphoglycerate (3PG) is oxidized to 3-phosphohydroxypyruvate (pPYR) by phosphoglycerate dehydrogenase (PHGDH) and pPYR is transaminated to phosphoserine (pSER) by phosphoserine aminotransferase (PSAT). pSER is dephosphorylated to serine by phosphoserine phosphatase. In glycine metabolism, glycine is metabolized to H-protein-S-aminomethyldihydrolipoyllysine by glycine decarboxylase (GLDC), an important component of the glycine cleavage system. This serine metabolism and glycine metabolism are linked by serine hydroxymethyltransferse (SHMT), which causes a reversible conversion of serine and glycine. Lastly, PPP is a metabolic pathway that occurs with glycolysis, playing a pivotal role in cell survival and growth by providing pentose phosphate for nucleic acid synthesis and also nicotinamide adenine dinucleotide phosphate (NADPH) for fatty acid synthesis and cell survival. PPP is comprised of two branches, the oxidative branch and non-oxidative branch. The oxidative branch converts glucose 6-phosphate (G6P) to ribulose-5-phosphate, CO2, and NADPH, and the non-oxidative branch produces glycolytic intermediates, such as fructose 6-phosphate (F6P), glyceraldehyde 3-phosphate (G3P), and sedoheptulose. These glycolytic intermediates are important for amino acid synthesis and produce ribose-5-phosphate (R5P) that is also important for nucleic acid synthesis. Enzymes that are involved in the oxidative branch are 6-phosphogluconate dehydrogenase (6PGD) and glucose 6-phosphate dehydrogenase (G6PD), and those that are involved in the non-oxidative branch are ribulose-5-phosphate epimerase (RPE), ribose 5-phosphate isomerase (RPI), transaldolase (TALDO), and transketolase (TKT).
Cancer cells produce a high level of reactive oxygen species (ROS) compared to normal cells due to the increased activation of various metabolic pathways. Cancer cell metabolism is closely related to ROS homeostasis; they cause ROS detoxifications by using various substrates and metabolic intermediates in metabolic pathways, the most representative of which are glycolysis by the Warburg effect and PPP. Glycolysis by the Warburg effect maintains redox homeostasis by being independent of mitochondrial OXPHOS that produces a large amount of ROS, and PPP by producing ROS-detoxifying molecule, NADPH, by G6PD and 6-Phosphogluconate dehydrogenase (6PGDH).
Molecules involved in the regulation of glucose metabolism in cancer in general are oncogenes such as Ras, Src, and MYC, transcription factors such as hypoxia-inducible factor-1 (HIF-1), signaling pathway such as phosphoinositide 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR), and tumor suppressor such as p53. Oncogenes such as Ras, Src, and MYC increase the expression of HIF-1 that increases the expression of various glycolytic enzymes, and HIF-1, MYC, and KRAS increase glucose uptake by inducing GLUT expression. In addition, the PI3K/Akt/mTOR pathway induces glycolytic enzymes and GLUT expression, and p53 regulates glycolysis and GLUT through mTOR and AMP-activated protein kinase (AMPK).
Glucose Transporters in Glycolysis
There are two families of glucose transporters: facilitative sugar transporters (GLUT, gene family name SLC2A) and Na+/glucose co-transporters (SGLT, gene family name solute carrier SLC5A). Additionally found families of glucose transporters are the Sugars Will Eventually be Exported Transporters (SWEET; SLC50) family and the Spinter protein (SLC63) family. SLC50 is a Na (+)/substrate co-transporter involved in the transport of glucose, myoinositol, and anions and located in the plasma membrane. SGLT1 (SLC5A1) and SGLT2 (SLC5A2) are important in glucose uptake with the former expressed mainly in the intestine and the latter in the kidney. GLUT has 14 isoforms that share structural features, such as 12 transmembrane domains, amino terminus, carboxy-terminus, and an N-glycosylation site. GLUTs can be subgrouped into three classes: class I (GLUT1–4 and GLUT14), class II (GLUT5, 7, 9, and 11), and class III (GLUT6, 8, 10, 12, and 13). Class I and class II GLUTs are called odd transporters, whereas class III GLUTs are called even transporters. Except for GLUT13, which is a proton-driven myoinositol transporter, all GLUTs are facilitative transporters. These GLUT isoforms differ in the tissue type in which they are present, their location within the cells, cohesiveness with substrates, and control mechanism. For instance, GLUT1 and GLUT3 are found in the brain, where they function mainly in glucose transport, whereas GLUT3–5 and GLUT10–11 are found in the muscle. Glucose is an important substrate for GLUT, but GLUT can also transport other substrates such as galactose, mannose, glucosamine, dehydroacetic acid, fructose, urate, and myo-inositol.
Glucose Metabolism and Glycolysis-Related Metabolic Pathways in Breast Cancer
Cancer cells harbor a metabolic shift to aerobic glycolysis that plays an important role in tumor growth, progression, and metastasis; therefore, glucose metabolism and glycolysis-related metabolic pathways can have a diverse impact on cancer cells in breast cancer.
Expression of Glycolysis-Related Enzymes and GLUTs in Breast Cancer
Breast cancer shows an increased expression of glycolysis-related enzymes, namely, HKII, 6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase 3 (PFKFB3), and pyruvate kinase M2 (PKM2). In primary breast cancer, HKII is overexpressed in about 79% of tumors, which has been correlated with an increased histologic grade and proliferative activity. The expression of 6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase 3 activates PFK-1, a key enzyme in glycolysis, and is correlated with HER-2 expression and poor prognosis. Additionally, 6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase 3 expression is related to the expression of vascular endothelial growth factor (VEGF)-α in breast cancer, which contributes to angiogenesis and distant metastasis. PFK-2 is a muscle isoform M2 of PK, a key enzyme in glycolysis, and its expression is correlated with a poor prognosis in breast cancer. Lactates produced by glycolysis are transported in and out of cells by monocarboxylate transporter (MCT). MCT1 overexpression in breast cancer is correlated with ER negativity, PR negativity, high Ki-67 labeling index, basal-like type, high grade, high stage, increased recurrence, and poor prognosis. As for MCT4, tumoral MCT4 expression and stromal MCT4 expression are associated with poor prognosis.
Breast cancer has been reported to have an increased expression of GLUT1–6 and 12 (Table 1; ), and the most important glucose transporter for glucose uptake in breast cancer is GLUT1. Glucose uptake by GLUT1 is important in the carcinomatous transformation and carcinogenesis of breast cancer, and it plays an important role in the early phase of breast cancer development. GLUT1 overexpression in breast cancer is correlated with high histologic grade, high proliferative activity, poor differentiation, and poor prognosis. GLUT4 is an insulin-stimulated glucose transporter, and glucose uptake is dependent on insulin stimulation in cancer cell lines. It has also been reported that hyperinsulinemia increases the risk of breast cancer irrespective of the body mass index (BMI), and so it can be postulated that insulin is associated with breast cancer. Cross-talks between signaling pathways regulated by 17 beta-estradiol (E2) and insulin-like growth factor (IGF), strong mitogen for cancer cells, and actions through ER-signaling are some possible mechanisms associated with the insulin effect on breast cancer.
Overexpression of glycolysis-related enzymes and GLUTs in breast cancer is due to the activation of the signaling pathways controlling the enzyme expression in breast cancer (Figure 2). The main molecular pathways involved in the control of aerobic glycolysis are the PI3K/AKT, AMP-activated protein kinase (AMPK), mitogen-activated protein kinase, Wnt, and mTOR pathways. Among these, the PI3K/AKT, AMPK, and mTOR pathways are activated in breast cancer. PI3K/AKT activates phosphofructokinase-2 (PFK-2) by phosphorylation. PI3K/AKT pathway activation leads to GLUT1 overexpression, which is then translocated from the cytoplasm to the plasma membrane. AKT is activated by E2, thus increasing the glucose uptake in MCF-7 breast cancer cell line through translocation of GLUT4 to the plasma membrane. PIK3CA and AKT1 gene mutations are common in breast cancer, and PIK3CA mutation is usually found in ER-positive and HER-2 positive breast cancer. AMPK translocates GLUT4 to the cytoplasmic membrane by activating PFK-2 and increases GLUT1 expression. AMPK is highly expressed in TNBC and known to be associated with poor prognosis. mTOR is a downstream effector of AKT, comprising mTOR complex 1 (mTORC1) and mTOR complex 2 (mTORC2). mTORC1 promotes the transition from OXPHOS to glycolysis and increases the expression of HIF-1α, which in turn increases the expression of glycolysis-related enzymes such as PFK. mTORC2 promotes glycolysis by activating AKT and GLUT1-related glucose uptake. mTOR is activated in breast cancer through HER-2 overexpression, PI3K pathway alteration, and mTOR mutation. Second, the increased expression of glycolysis-related enzymes in breast cancer is because of the activation of transcription factors (Figure 2). The transcription factors associated with glycolysis are c-myc, p53, and HIF-1. c-myc is responsible for increasing the gene expression of glycolysis-related genes and, consequently, glycolysis-related enzymes, such as GLUT, HK, and PFK. Moreover, estrogen is responsible for the increased expression of c-myc, and about 80% of breast cancers are ER-positive. p53 is a well-known tumor suppressor, gene mutations of which are found in most cancers including breast cancer. p53 mutation is found in about 20%–30% of breast cancers and more often in ER-negative breast cancer. p53 suppresses phosphoglycerate mutase (PGM), GLUT1, GLUT3, and GLUT4 expression; hence, p53 mutation leads to an increased glycolysis in breast cancer. Lastly, the transcription factor HIF-1α, which is activated by hypoxia, is an important regulator in glycolysis and increases the expression of glycolysis-related molecules, such as HKII, PFK-1, lactate dehydrogenase (LDH) A, GLUT-1, and GLUT-3. HIF-1α promotes the metabolic shift to glycolysis by suppressing the mitochondrial function through the activation of pyruvate dehydrogenase kinase 1 (PKD1) and MAX interactor 1 (MXI1). HIF-1α overexpression has been reported in breast cancer, and it is attributed to the increased expression of glycolysis-related proteins in breast cancer because HIF-1α overexpression is related to HER-2 positivity and TNBC.
Breast cancer is susceptible to sex hormones such as estrogen, which may have an effect on the regulation of glucose metabolism. E2 and ERα stimulation activates the MAPK pathway, regulates expression of GLUT4, and increases glucose uptake. Furthermore, E2 activates the PI3K pathway that is involved in glucose metabolism in breast cancer cells, and suppresses phosphatase and tensin homolog (PTEN), a phosphatidylinositol-3 kinase inhibitory protein.
Expression of Glycolysis-Related Enzymes and GLUTs in TNBC
Triple negative breast cancer is defined as breast cancer that is negative for ER, PR, and HER-2 and accounts for about 15% of breast cancer cases. Basal-like breast cancer (BLBC) is defined as those that have high expressions of basal genes in gene expression studies such as DNA microarray. Therefore, TNBC and BLBC are not the same in the strict sense of definitions, although they can overlap in many instances. TNBC is a heterogeneous group, and many researches have focused on the subgrouping of TNBC. have grouped TNBC further into basal-like1, basal-like2, mesenchymal, and luminal androgen receptor, and have grouped TNBC further into basal-like immune-activated, basal-like immune suppressed, mesenchymal, and luminal androgen receptor. The general characteristics of TNBC include the histological characteristics of high grade, high proposition index, and tumor necrosis, and clinical characteristics of higher rate of metastasis and poor prognosis. With these histological and clinical features, TNBC can be postulated to be of high metabolic status. One of the important metabolic features of TNBC is high glucose uptake, and GLUT1 overexpression is seen in TNBC. High expression of glycolysis-related enzymes, such as HK2, PKM2, and LDH, and that of lactate transporters MCT1 and MCT4 have also been reported in TNBC. The high expression of glycolysis-related proteins in TNBC is owing to the fact that the glycolysis regulatory factors, such as HIF-1, c-myc, and EGF signaling, are promoted in TNBC. Therefore, TNBC cells are much more dependent on glucose metabolism than non-TNBC cells (MCF-7), and GLUT1 inhibition shows a more anti-proliferative effect for TNBC cells than non-TNBC cells (MCF-7).
Non-glycolysis Glucose Metabolism Pathway in Breast Cancer
In glucose metabolism, non-glycolysis metabolic pathways, such as the serine/glycine metabolic pathway and PPP, play important roles in breast cancer. The expression of serine/glycine metabolic pathway-related proteins in breast cancer differs depending on the breast cancer molecular subtype. Serine metabolic pathway-related proteins were highly expressed in TNBC, and glycine metabolic pathway-related proteins were highly expressed in HER-2 type breast cancer. The basal-like type also showed a higher expression of serine/glycine metabolic pathway-related proteins among the TNBC subtypes. Analysis using the cBioPortal TCGA Pan-Cancer Atlas shows PHGDH amplification in approximately 2.2% of breast cancers. PHGDH expression is observed frequently in ER-negative breast cancer, and increased PHGDH expression in breast cancer is associated with poor prognosis. Similarly, phosphoserine aminotransferase 1 (PSAT1) is more frequently expressed in ER-negative breast cancer and is associated with poor prognosis. Serine hydroxymethyltransferase 2 expression level is associated with the histologic grade of breast cancer.
High expression of PPP-related enzymes, such as 6PGD and TKT, is reported in breast cancer. G6PD, one of the PPP-related enzymes, is associated with the molecular subtype of breast cancer, and G6PD overexpression is associated with poor prognosis of breast cancer. 6PGDH expression is high in TNBC, and the expression of G6PDH and 6PGL are high in HER-2 type. The expression of G6PDH is also the highest in brain metastasis among metastatic breast cancers. The expression of TKT is associated with tumor size and high TKT expression is associated with poor prognosis in a mouse model of breast cancer. Increased PPP flux by G6PD and HK2 enhancement induces tamoxifen resistance in breast cancer. An increase in HK2 transcription by the yes-associated protein (YAP) axis also promotes the migration of breast cancer cells.
Glucose Metabolism in the Tumor Microenvironment of Breast Cancer
Breast cancer is one of those tumors that harbors tumor stroma, the main cell components of which include cancer-associated fibroblasts (CAFs), cancer-associated adipocytes (CAAs), and immune cells. These stromal cells affect the development, progression, and metastasis of breast cancer through various interactions with breast cancer cells. Thus, metabolic interactions are present between breast cancer cells and stromal cells (Figure 3), and glucose metabolism in tumor stromal cells is suggested in the reverse Warburg effect. According to the reverse Warburg effect, aerobic glycolysis occurs in CAFs that are present in the breast cancer stroma. In brief, the reverse Warburg theory describes the glycolysis that occurs in CAFs by ROS, HIF1A, and nuclear factor-κB (NF-κB), resulting in lactate being released from CAFs by MCT4, which is then transported into the tumor cells by MCT1 in breast cancer, creating energy by mitochondrial OXPHOS. Lactate produced by CAFs is transported into the tumor cells as potent nutrients for the TCA cycle, and this lactate can be an important source of energy for cancer cells because lactate is the primary source of carbon for the TCA cycle among circulating metabolites. In co-cultural studies of breast cancer cell lines and fibroblasts and studies of human breast cancer tissue, MCT4 was expressed in CAFs, whereas MCT1 was expressed in tumor cells. In a co-cultural study of MCF7 breast cancer cells and normal fibroblasts, culture of MCF7 breast cancer cells alone or fibroblasts alone did not exhibit MCT4 expression, whereas co-culture of MCF7 breast cancer cells and fibroblasts showed MCT4 expression in CAFs. The co-culture with fibroblasts showed MCT1 upregulation in MCF7 breast cancer cells. Breast CAFs showed higher expressions of GLUT1 and PDK1 than normal fibroblasts, and the co-cultural study of breast cancer cells and fibroblasts showed an increase in glycolysis and glucose transporter-related genes in CAFs. The reverse Warburg effect is not only observed between cancer cells and CAFs but also between hypoxic and oxygenated cancer cells.
One type of immune cells in the tumor stroma is tumor-associated macrophages (TAMs) that inhibit antitumor immunity in breast cancer, resulting in tumor progression. In general, TAMs exhibit properties of M2 macrophages, and TAMs in hypoxic tumor regions express HIF-1, which controls the expression of glycolysis-related genes, including GLUT1, HK2, PFFB3, and PGK1. Therefore, TAMs in hypoxic tumor environments may utilize glycolysis. In addition, lactate generated in the glycolysis process is an important metabolite, which activates M2 macrophages. In a co-culture study of breast cancer cells and macrophages, G protein-coupled receptor 132 (Gpr132) senses lactate in the tumor environment to transform macrophages into M2-like phenotypes to promote cancer cell adherence, migration, and invasion. In addition, HIF-1α-stabilizing long non-coding RNA (HISLA) is transferred from TAMs to breast cancer cells via extracurricular vessel transmission, which increases glycolysis in breast cancer cells.
Impact of Glucose Metabolism and Glucose Transporters on Breast Cancer Biology and the Response to Treatment
First, the proliferation of tumor cells requires a lot of energy and a variety of materials are needed to create new tumor cells, which is also true for breast cancer cells. Therefore, glucose metabolism and glucose transporters, which provide energy sources for breast cancer, and PPP, which provides the materials needed for the synthesis of nucleotides, lipids, and non-essential amino acids, play important roles in breast cancer proliferation. Second, glucose metabolism affects the maintenance of epithelial-mesenchymal transition (EMT) and cancer stem cell (CSC) phenotype in breast cancer. Increased glycolysis and PPP by epigenetic silencing of fructose-1,6-biphosphatase can increase NADPH and reduce ROS levels, which enhance EMT and CSC phenotype in basal-like breast cancer. In a breast cancer cell line study, high glucose levels increased glycolytic enzyme, motor protein, and NF-κB levels and glucose uptake, and reduced actin, resulting in EMT phenotype activation. In addition, HIF-1 activation by hypoxia maintains ROS homeostasis through the glycolytic pathway and serine synthesis pathway, which is important for breast CSC induction. Moreover, glucose metabolism is associated with treatment resistance in breast cancer, where induced glycolysis is observed by AKT/mTOR/HIF-1α axis activation in tamoxifen resistant breast cancer cells, and when HKII is inhibited, tamoxifen sensitivity is recovered. Increased glycolysis is observed in trastuzumab resistant breast cancer cells, and glycolytic inhibition reduces trastuzumab resistance. The expression of PFK-2 is linked to the responsiveness of anticancer drugs such as epirubicin and 5-fluorouacil in breast cancer cells. Chemoresistant TNBC cells exhibit increased glycolysis and lactate permutation, and PHGDH expression correlates with the responsiveness of chemotherapy in TNBC cells. GLUT is associated with breast cancer metastasis; a proteomic analysis of MDA-MB-231 (metastatic breast cancer cell line) and MCF-10A (normal breast epithelial cell line) showed that one of the three strongest breast cancer-related proteins was GLUT1. The GLUT expression showed a difference according to the metastatic sites, and the expression of GLUT1 was the highest in brain metastasis. Additionally, GLUT12 plays an important role in tumor growth and metastasis through aerobic glycolysis in TNBC.
Clinical Application of Glucose Transporters and Glucose Metabolism in Breast Cancer
As we have seen earlier, glucose transporter expression is high in breast cancer, and glucose metabolism is carried through the glycolytic, serine/glycine, and PPPs that play important roles in tumor growth and progression. Therefore, they may have a variety of clinical applications, especially in imaging diagnosis and targeted therapy.
Imaging Diagnosis
Positron emission tomography (PET) using 18F-fluorodeoxy glucose (FDG), a radioactive analog of glucose, is the representative functional imaging technique based on the principle that tumor cells uptake large amounts of glucose by GLUT via the Warburg effect. These PETs are used for tumor staging and treatment response monitoring. These FDG-PET/CTs are also useful for diagnosis, staging, and treatment evaluation in breast cancer. In addition to FDG-PET/CT, functional imaging based on glucose metabolism can be performed using magnetic resistance spectroscopy (MRS). Multiple metabolites can be simultaneously identified in tumor tissues using MRS, which can analyze labeling patterns using stable isotopic traces, and glucose metabolites can be analyzed using 13C-MRS and [13C]-labeled glucose to image the glycolysis status. MRS can perform effective metabolic monitoring in breast cancer. Breast cancer with different 13C-MRS expression patterns show a different glucose metabolism. A high-resolution magic angle spinning MRS analysis of metabolites in breast cancer, such as β-glucose, lactate, and glycine, shows good prognosis with reduced concentrations of glycine. The concentration of β-glucose shows a negative correlation with proliferation index (MIB-1), indicating that MR metabolite analysis is valuable in breast cancer prognostication.
Therapeutic Target of Glucose Metabolism and Glucose Transporters
The expression of glucose transporters and glucose metabolic enzymes in breast cancer is high; thus, their inhibition can serve as an effective treatment strategy against breast cancer (Figure 4). Various preclinical and clinical studies have been conducted to investigate this implication.
GLUT1 Inhibitors
GLUT1 inhibitors—WZB117 and SFT-31—inhibit cell proliferation and promote apoptosis in breast cancer cell lines. WZB117 increases the effectiveness of radiation and anticancer drugs in breast cancer cell lines. BAY-876, a selective GLUT1 inhibitor, decreases glucose uptake in TNBC cell lines and 2-deoxy-D-glucose (2-DG), a synthetic non-metabolizable glucose analog, competes with glucose for binding GLUT, which reduces glucose uptake in the MDA-MB-231 TNBC cell line. As for 2-DG, there are two different phenomena resulting from the suppression of glycolysis: first, glucose can be deviated to PPP because 2-DG is not metabolized any further after phosphorylation into 2-deoxy-D-glucose-6-phosphate (2-DG-6-P) by HKII; and second, 2-DG induces autophagy due to endoplasmic reticulum (ER) stress. Suppression of glycolysis leads to a decreased ATP, by which N-linked glycosylation is suppressed and AMPK is activated. AMPK activation and N-linked glycosylation lead to ER stress. Autophagy promotes tumor growth in the early stage of cancer, maintains tumor survival, and increases metastasis in the advanced stage. Anti-GLUT1 monoclonal antibody decreases glucose uptake in the MDA-MB-231 TNBC cell line, and decreases cancer cell proliferation and promotes apoptosis in MCF-1 and T47D breast cancer cell lines. Polyphenols, a huge family of natural compounds found in plants or food, is one category of the GLUT1 inhibitors that shows an anti-tumoral effect against various cancers including breast cancer. The anti-tumoral mechanism of polyphenols against breast cancer includes increased apoptosis, cell cycle arrest, enhanced autophagy, decreased angiogenesis, anti-inflammatory effect, blockade for estrogen, aromatase modulation, altered redox balance, and inhibition of the HER-2 pathway. Polyphenols inhibiting GLUT1 in breast cancer are as follows: Resveratol suppresses glucose uptake in T-47D cell line by reducing GLUT1 protein level, and hesperetin suppresses glucose uptake by decreasing GLUT 1 mRNA and protein levels. Quercetin decreases the glucose uptake in MCF-7 and MDA-MB-231 by reducing GLUT1 protein level, as does glabridin in MDA-MB-231. Epigallocatechin-3-gallate (EGCG) decreases the glucose and lactate levels in cancer cells by reducing GLUT1 mRNA levels in 4T1 cell line, and cantharidin suppresses metastasis by inhibiting glucose uptake and lactate production through decreasing GLUT1 protein level in MCF-7 and MDA-MB-231. Kudingcha, one of the Ligustrum robustum species, inhibit cancer proliferation through decreasing GLUT1 protein level in MDA-MB-231 and HCC1806. Vitamin D3 decreases glucose uptake by decreasing GLUT1 mRNA and protein levels in MCF-7 and MDA-MB-231.
Glucose Metabolic Enzyme Inhibitors
First, 3-bromopyruvate (3-BrPA), an inhibitor of hexokinase, causes apoptosis in MDA-MB-231 breast cancer cell line and increases the response to daunorubicin and tamoxifen in breast cancer. Methyl jasmonate, another hexokinase inhibitor, caused a decrease in tumor volume in mice bearing 4T1 breast cancer cell line. Resveratrol, an inhibitor of PFK, decreases the cell viability and glucose consumption in MCF-7 breast cancer cell line. Cyclosporin A, an immunosuppressive agent, inhibits the expression and activity of PKM2 in breast cancer cell lines (MCF-7, MDA-MB-435, and MDA-MB-231) and causes tumor cell death by reducing cell viability. Cyclosporin A also maintains mitochondrial function by suppressing mitochondrial permeability transition pore. When oxamate, an LDH inhibitor, is administered in conjunction with doxorubicin and metformin, it causes a rapid tumor growth inhibition in the xenograft model using human MDA-MB-231 TNBC cell line. When paclitaxel and oxamate are administered together, they induce an effective killing of paclitaxel-resident TNBC cells. Gossypol, a lipid soluble polyphenolic compound, exhibits antitumor effects by inhibiting glycolysis through LDH isoenzyme type 5 inhibition. Gossypol causes anti-proliferative activity and apoptosis in breast cancer cells, and when R--gossypol (AT-101) is administered in conjunction with trastuzumab in HER-2 positive breast cancer cell line, it causes synergistic cytotoxicity and apoptosis. Galloflavin, an LDHA inhibitor, induces cell death in MDA-MB-231 cell lines and acquired tamoxifen resistance MCF-7 breast cancer cell lines.
Serine and glycine pathway inhibitors can be used for the management of tumors that use serine and glycine metabolism and for treatment of tumors showing recurrence and treatment resistance. PHGDH inhibitors—NCT-503 and CBR-5884—are both allosteric PHGDH inhibitors; NCT-503 binds to the near substrate-binding pockets; and CBR-5884 hinders PHGD holigomerization. NCT-503 inhibits tumor growth in PHGDH-amplified breast cancer xenografts, and CBR-5884 inhibits tumor cell proliferation in high PHGDH-expressing breast cancer cell lines (MDA-MB-468, MDA-MB-436, HCC70, and Hs578T). PKUMDL-WQ-2101 and PKUMDL-WQ-2201, which are allosteric PHGDH inhibitors, show an antitumor activity in PHGDH-amplified breast cancer cell lines (MDA-MB-468 and HCC70). An NAD-competitive PHGDH inhibitor, 15 fragments, reduces cell proliferation in PHGDH-amplified breast cancer cell line (MDA-MB-468). Sertraline, an antidepressant, is a selective serotonin reuptake inhibitor (SSRI) class, but it also works as a competitive dual SHMT1/2 inhibitor, reducing the cell growth in serine/glycine synthesis-addicted breast cancer cell line (MDA-MB-468) and decreasing the tumor growth in a mouse xenograft study.
G6PD, one of the important enzymes in PPP, has a potent non-competitive inhibitor, dehydroepiandrosterone (DHEA), which is an adrenal cortical steroid. DHEA inhibits the growth and migration of breast cancer cell lines (MCF-7, MDA-MB-231, and Hs578T). DHEA can bind estrogen or androgen receptors because it is metabolized to estrogen or androgen, however, the suppression of MCT-7 cell line growth by DHEA is reported to be independent of estrogen or androgen receptors. 6-aminonicotinamide, a G6PD inhibitor, can decrease mammosphere formation and aldehyde dehydrogenase (ALDH) activity when given with DHEA in breast cancer stem-like cells that show high PPP activity. CB83, another G6PD inhibitor, can inhibit growth of MCF10-AT1 breast cancer cell line. Oxythiamine, an inhibitor of TKT, also increases the response of breast cancer cells to doxorubicin or docetaxel.
Conclusion
Because of the high expressions of GLUT-1 and the enzymes involved in glucose metabolism, tumor cells in breast cancer, as in other tumors, are provided with energy through glucose metabolism. There are several characteristic factors to consider in the glucose metabolism of breast cancer. Because breast cancer is heterogeneous, inter- and intratumoral heterogeneity is also seen in glucose metabolism. First, glucose metabolic activity is different among the molecular subtypes, especially in TNBC, which shows an increased glycolytic phenotype. According to the traditional Warburg theory, tumors showing aerobic glycolysis are suggested to exhibit a decreased mitochondrial OXPHOS; however, TNBC with a high metabolic activity shows both enhanced glycolysis and sustained mitochondrial OXPHOS. Luminal type breast cancer rely more on OXPHOS than glycolysis compared to TNBC. It also presents metabolic switches between glycolysis and OXPHOS during cancer progression. Therefore, metabolic intratumoral heterogeneity is exhibited in breast cancer, showing different glycolytic activities depending on the tumor cell type. Second, there is a metabolic interaction between tumor cells and the surrounding stromal cells in breast cancer. Breast cancer is a typical tumor that contains various stromal cells, the main components of which are CAFs, CAAs, and immune cells. Metabolic interactions exist between breast cancer cells and stromal cells; especially according to the reverse Warburg theory, lactates produced by glycolysis in CAFs enter tumor cells and produce energy through OXPHOS. Among the immune cells, B-cells and NK cells use glycolysis, and tumor-associated neutrophils use glycolysis and PPP, allowing a metabolic competition with the tumor cells. Third, unlike in other tumors, CAAs are stromal cells that are specifically present in breast cancer, and previous studies suggest that β-oxidation in tumor cells is primarily studied through the lipid transfer between CAAs and tumor cells. As the glucose metabolic interaction between CAAs and tumor cells is rarely studied in breast cancer, it requires further study. Metabolic interactions between tumor cells and stromal cells in these breast cancer cases are also reported to be affected by cancer phenotypes, which may require further research on the metabolic cross-talk between the cancer cells and stromal cells according to the molecular subtype of breast cancer. Fourth, breast cancer shows differential metabolic features depending on the stage and metastatic site. In order for the tumor to progress into distant metastasis, multiple and complex processes, such as intravasation, survival in blood stream, and extravasation, must be accomplished during this process, and the hurdles, such as anchorage independent survival and tumor cell proliferation in foreign microenvironment, should be overcome. One way to overcome this challenge is metabolic reprogramming. Breast cancer shows metabolic differences between the primary and metastatic tumors, and breast cancer does not rely on a single metabolic pathway, but uses multiple metabolic pathways. Highly metastatic 4T1 cells show increased glycolysis and OXPHOS compared to non-metastatic 67NR breast cancer cells. The most common metastatic sites are the brain, bone, lung, and liver, which exhibit differential metabolic features owing to different microenvironments. Liver metastatic breast cancer demonstrates increased glycolytic pathways compared to bone and lung metastatic breast cancer, whereas brain metastatic breast cancer shows increased glycolysis and PPP compared to bone metastatic breast cancer. As a result of the above characteristics of glucose metabolism in breast cancer, further studies are needed to consider tumor imaging using glucose metabolism and glucose metabolic markers as treatment targets. In addition, because glucose metabolism is associated with resistance to anticancer drugs or targeted treatments in breast cancer, glucose metabolic inhibitors can also be considered for a combined therapy with conventional treatments.
Author Contributions
ES and JK: writing—original draft, investigation, and writing—review and editing. Both authors contributed to the article and approved the submitted version.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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