Targeting GLUTs in Cancer: Mechanisms, Combination Strategies, and Translational Challenges

Mei-na Shi , Dong-fan Yang , Tong Chu , Da-yuan Zheng , Wen-zhe Ma

Current Medical Science ›› : 1 -20.

PDF
Current Medical Science ›› :1 -20. DOI: 10.1007/s11596-026-00245-1
Review
review-article
Targeting GLUTs in Cancer: Mechanisms, Combination Strategies, and Translational Challenges
Author information +
History +
PDF

Abstract

Cancer cells exhibit metabolic reprogramming, most notably the Warburg effect, which underscores their heightened dependency on glucose uptake facilitated by glucose transporters (GLUTs). While targeting GLUTs holds promise for disrupting tumor metabolism, monotherapeutic inhibition often leads to compensatory resistance mechanisms, metabolic plasticity, and dose-limiting toxicity. This review comprehensively examines the rationale and mechanisms underlying combined strategies that integrate GLUT inhibitors with conventional chemotherapy, targeted therapy, immunotherapy, and radiotherapy. Such combinations exploit synthetic lethality, reverse immunosuppression, enhance DNA damage, and overcome adaptive resistance. We also discuss emerging approaches such as isoform-specific inhibitors, nanocarrier-based delivery, and artificial intelligence-guided combination design to improve selectivity and efficacy. Finally, we highlight key translational challenges and discuss how cross-disease insights into GLUT biology may inform the safety, selectivity, and therapeutic design of cancer-directed GLUT-targeted combination strategies.

Keywords

Glucose transporters / Warburg effect / Cancer metabolism / Combination therapy / Metabolic reprogramming / Immunotherapy / Synthetic lethality / Drug repurposing / Tumor microenvironment

Cite this article

Download citation ▾
Mei-na Shi, Dong-fan Yang, Tong Chu, Da-yuan Zheng, Wen-zhe Ma. Targeting GLUTs in Cancer: Mechanisms, Combination Strategies, and Translational Challenges. Current Medical Science 1-20 DOI:10.1007/s11596-026-00245-1

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Warburg O. On the origin of cancer cells. Science., 1956, 123(3191): 309-314

[2]

Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science., 2009, 324(5930): 1029-1033

[3]

Liberti MV, Locasale JW. The Warburg effect: how does it benefit cancer cells Trends Biochem Sci., 2016, 41(3): 211-218

[4]

Pavlova NN, Thompson CB. The emerging hallmarks of cancer metabolism. Cell Metab., 2016, 23(1): 27-47

[5]

DeBerardinis RJ, Chandel NS. Fundamentals of cancer metabolism. Sci Adv., 2016, 2(5e1600200

[6]

Kawatani M, Osada H. Small-molecule inhibitors of glucose transporters. Glucose Transporters. Amsterdam: Elsevier; 2025:213–242.

[7]

Kim JW, Dang CV. Cancer’s molecular sweet tooth and the Warburg effect. Cancer Res., 2006, 66(18): 8927-8930

[8]

Hay N. Reprogramming glucose metabolism in cancer: can it be exploited for cancer therapy Nat Rev Cancer., 2016, 16(10): 635-649

[9]

Luengo A, Gui DY, Vander Heiden MG. Targeting metabolism for cancer therapy. Cell Chem Biol., 2017, 24(9): 1161-1180

[10]

Temre MK, Kumar A, Singh SM. An appraisal of the current status of inhibition of glucose transporters as an emerging antineoplastic approach: Promising potential of new pan-GLUT inhibitors. Front Pharmacol., 2022, 13: 1035510

[11]

Grover-McKay M, Walsh SA, Seftor EA, et al.. Role for glucose transporter 1 protein in human breast cancer. Pathol Oncol Res., 1998, 4(2): 115-120

[12]

Amann T, Hellerbrand C. GLUT1 as a therapeutic target in hepatocellular carcinoma. Expert Opin Ther Targets., 2009, 13(12): 1411-1427

[13]

Chen C, Pore N, Behrooz A, et al. Regulation of glut1 mRNA by hypoxia-inducible factor-1. Interaction between H-ras and hypoxia. J Biol Chem. 2001;276(12):9519–9525.

[14]

Krzeslak A, Wojcik-Krowiranda K, Forma E, et al.. Expression of GLUT1 and GLUT3 glucose transporters in endometrial and breast cancers. Pathol Oncol Res., 2012, 18(3): 721-728

[15]

Szablewski L. Expression of glucose transporters in cancers. Biochim Biophys Acta BBA Rev Cancer., 2013, 1835(2): 164-169

[16]

Garrido P, Osorio FG, Morán J, et al.. Loss of GLUT4 induces metabolic reprogramming and impairs viability of breast cancer cells. J Cell Physiol., 2015, 230(1): 191-198

[17]

Rogers S, Docherty SE, Slavin JL, et al.. Differential expression of GLUT12 in breast cancer and normal breast tissue. Cancer Lett., 2003, 193(2): 225-233

[18]

Macheda ML, Rogers S, Best JD. Molecular and cellular regulation of glucose transporter (GLUT) proteins in cancer. J Cell Physiol., 2005, 202(3): 654-662

[19]

Barron CC, Bilan PJ, Tsakiridis T, et al.. Facilitative glucose transporters: Implications for cancer detection, prognosis and treatment. Metabolism., 2016, 65(2): 124-139

[20]

Olszewski K, Barsotti A, Feng XJ, et al.. Inhibition of glucose transport synergizes with chemical or genetic disruption of mitochondrial metabolism and suppresses TCA cycle-deficient tumors. Cell Chem Biol., 2022, 29(3): 423-435.e10

[21]

Tilekar K, Upadhyay N, Iancu CV, et al.. Power of two: combination of therapeutic approaches involving glucose transporter (GLUT) inhibitors to combat cancer. Biochim Biophys Acta Rev Cancer., 2020, 1874(2 188457

[22]

Peng X, Zheng J, Liu T, et al.. Tumor microenvironment heterogeneity, potential therapeutic avenues, and emerging therapies. CCDT., 2024, 24(3): 288-307

[23]

Wang D, Pascual JM, Yang H, et al.. Glut-1 deficiency syndrome: Clinical, genetic, and therapeutic aspects. Ann Neurol., 2005, 57(1): 111-118

[24]

Reckzeh ES, Waldmann H. Development of glucose transporter (GLUT) inhibitors. Eur J Org Chem., 2020, 2020(16): 2321-2329

[25]

Gottesman MM, Fojo T, Bates SE. Multidrug resistance in cancer: role of ATP-dependent transporters. Nat Rev Cancer., 2002, 2(1): 48-58

[26]

Bristow RG, Hill RP. Hypoxia, DNA repair and genetic instability. Nat Rev Cancer., 2008, 8(3): 180-192

[27]

Chang CH, Qiu J, O’Sullivan D, et al.. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell., 2015, 162(6): 1229-1241

[28]

Siebeneicher H, Cleve A, Rehwinkel H, et al.. Identification and optimization of the first highly selective GLUT1 inhibitor BAY-876. ChemMedChem., 2016, 11(20): 2261-2271

[29]

Jones RG, Plas DR, Kubek S, et al.. AMP-activated protein kinase induces a p53-dependent metabolic checkpoint. Mol Cell., 2005, 18(3): 283-293

[30]

Jiang P, Du W, Wu M. Regulation of the pentose phosphate pathway in cancer. Protein Cell., 2014, 5(8): 592-602

[31]

Wang T, Zhang M, Gong X, et al. Inhibition of Nogo-B reduces the progression of pancreatic cancer by regulation NF-κB/GLUT1 and SREBP1 pathways. iScience. 2024;27(5):109741.

[32]

Pacold ME, Brimacombe KR, Chan SH, et al.. Corrigendum: a PHGDH inhibitor reveals coordination of serine synthesis and one-carbon unit fate. Nat Chem Biol., 2016, 12(8): 656

[33]

Kim J, Kim J, Bae JS. ROS homeostasis and metabolism: a critical liaison for cancer therapy. Exp Mol Med., 2016, 48(11 e269

[34]

Altman BJ, Stine ZE, Dang CV. From Krebs to clinic: glutamine metabolism to cancer therapy. Nat Rev Cancer., 2016, 16(10): 619-634

[35]

Levy JMM, Towers CG, Thorburn A. Targeting autophagy in cancer. Nat Rev Cancer., 2017, 17(9): 528-542

[36]

Alizadeh J, Kavoosi M, Singh N, et al.. Regulation of autophagy via carbohydrate and lipid metabolism in cancer. Cancers., 2023, 15(8): 2195

[37]

Ancey PB, Contat C, Meylan E. Glucose transporters in cancer–from tumor cells to the tumor microenvironment. FEBS J., 2018, 285(16): 2926-2943

[38]

Flavahan WA, Wu Q, Hitomi M, et al.. Brain tumor initiating cells adapt to restricted nutrition through preferential glucose uptake. Nat Neurosci., 2013, 16(10): 1373-1382

[39]

Koppula P, Olszewski K, Zhang Y, et al.. KEAP1 deficiency drives glucose dependency and sensitizes lung cancer cells and tumors to GLUT inhibition. IScience., 2021, 24(6 102649

[40]

Yun J, Rago C, Cheong I, et al.. Glucose deprivation contributes to the development of KRAS pathway mutations in tumor cells. Science., 2009, 325(5947): 1555-1559

[41]

Chen Q, Meng YQ, Xu XF, et al.. Blockade of GLUT1 by WZB117 resensitizes breast cancer cells to adriamycin. Anticancer Drugs., 2017, 28(8): 880-887

[42]

Miller ZA, Muthuswami S, Mueller A, et al.. GLUT1 inhibitor BAY-876 induces apoptosis and enhances anti-cancer effects of bitter receptor agonists in head and neck squamous carcinoma cells. Cell Death Discovery., 2024, 10(1): 339

[43]

Shibuya K, Okada M, Suzuki S, et al.. Targeting the facilitative glucose transporter GLUT1 inhibits the self-renewal and tumor-initiating capacity of cancer stem cells. Oncotarget., 2015, 6(2): 651-661

[44]

Mori Y, Yamawaki K, Ishiguro T, et al.. ALDH-dependent glycolytic activation mediates stemness and paclitaxel resistance in patient-derived spheroid models of uterine endometrial cancer. Stem Cell Reports., 2019, 13(4): 730-746

[45]

Wu Q, Ba-Alawi W, Deblois G, et al.. GLUT1 inhibition blocks growth of RB1-positive triple negative breast cancer. Nat Commun., 2020, 11(1): 4205

[46]

Liu W, Fang Y, Wang XT, et al.. Overcoming 5-Fu resistance of colon cells through inhibition of Glut1 by the specific inhibitor WZB117. Asian Pac J Cancer Prev., 2014, 15(17): 7037-7041

[47]

Malm SW, Hanke NT, Gill A, et al.. The anti-tumor efficacy of 2-deoxyglucose and D-allose are enhanced with p38 inhibition in pancreatic and ovarian cell lines. J Exp Clin Cancer Res., 2015, 34(1): 31

[48]

Suzuki S, Okada M, Takeda H, et al.. Involvement of GLUT1-mediated glucose transport and metabolism in gefitinib resistance of non-small-cell lung cancer cells. Oncotarget., 2018, 9(66): 32667-32679

[49]

Chen Z, Tian D, Liao X, et al.. Apigenin combined with gefitinib blocks autophagy flux and induces apoptotic cell death through inhibition of HIF-1α, c-myc, p-EGFR, and glucose metabolism in EGFR L858R+T790M-mutated H1975 cells. Front Pharmacol., 2019, 10: 260

[50]

Cretella D, Fumarola C, Bonelli M, et al.. Pre-treatment with the CDK4/6 inhibitor palbociclib improves the efficacy of paclitaxel in TNBC cells. Sci Rep., 2019, 9(1): 13014

[51]

Reckzeh ES, Karageorgis G, Schwalfenberg M, et al.. Inhibition of glucose transporters and glutaminase synergistically impairs tumor cell growth. Cell Chem Biol., 2019, 26(9): 1214-28.e25

[52]

Gross MI, Demo SD, Dennison JB, et al.. Antitumor activity of the glutaminase inhibitor CB-839 in triple-negative breast cancer. Mol Cancer Ther., 2014, 13(4): 890-901

[53]

Xie T, Dickson KA, Yee C, et al.. Targeting homologous recombination deficiency in ovarian cancer with PARP inhibitors: synthetic lethal strategies that impact overall survival. Cancers., 2022, 14(19): 4621

[54]

Li YL, Weng HC, Hsu JL, et al.. The combination of MK-2206 and WZB117 exerts a synergistic cytotoxic effect against breast cancer cells. Front Pharmacol., 2019, 10: 1311

[55]

Wang ZH, Peng WB, Zhang P, et al.. Lactate in the tumour microenvironment: From immune modulation to therapy. EBioMedicine., 2021, 73 103627

[56]

Zeng W, Li F, Jin S, et al.. Functional polarization of tumor-associated macrophages dictated by metabolic reprogramming. J Exp Clin Cancer Res., 2023, 42(1): 245

[57]

Angelin A, Gil-de-Gómez L, Dahiya S, et al.. Foxp3 reprograms T cell metabolism to function in low-glucose, high-lactate environments. Cell Metab., 2017, 25(6): 1282-1293.e7

[58]

Ma G, Zhang Z, Li P, et al.. Reprogramming of glutamine metabolism and its impact on immune response in the tumor microenvironment. Cell Commun Signal., 2022, 20(1): 114

[59]

Ho PC, Bihuniak JD, MacIntyre AN, et al.. Phosphoenolpyruvate is a metabolic checkpoint of anti-tumor T cell responses. Cell., 2015, 162(6): 1217-1228

[60]

Tang X, Mao X, Ling P, et al.. Glycolysis inhibition induces anti-tumor central memory CD8+T cell differentiation upon combination with microwave ablation therapy. Nat Commun., 2024, 15(1): 4665

[61]

Wang J, Jia W, Zhou X, et al.. CBX4 suppresses CD8+ T cell antitumor immunity by reprogramming glycolytic metabolism. Theranostics., 2024, 14(10): 3793-3809

[62]

Davoodzadeh Gholami M, Kardar GA, Saeedi Y, et al.. Exhaustion of T lymphocytes in the tumor microenvironment: Significance and effective mechanisms. Cell Immunol., 2017, 322: 1-14

[63]

Ahmed SA, Parama D, Daimari E, et al.. Rationalizing the therapeutic potential of apigenin against cancer. Life Sci., 2021, 267 118814

[64]

MacIntyre AN, Gerriets VA, Nichols AG, et al.. The glucose transporter Glut1 is selectively essential for CD4 T cell activation and effector function. Cell Metab., 2014, 20(1): 61-72

[65]

Weng HC, Sung CJ, Hsu JL, et al.. The combination of a novel GLUT1 inhibitor and cisplatin synergistically inhibits breast cancer cell growth by enhancing the DNA damaging effect and modulating the Akt/mTOR and MAPK signaling pathways. Front Pharmacol., 2022, 13 879748

[66]

Wu MX, Yang YW. Metal-organic framework (MOF)-based drug/cargo delivery and cancer therapy. Adv Mater., 2017, 29(23): 1606134

[67]

Chelakkot C, Chelakkot VS, Shin Y, et al.. Modulating glycolysis to improve cancer therapy. Int J Mol Sci., 2023, 24(3): 2606

[68]

Zhao F, Ming J, Zhou Y, et al.. Inhibition of Glut1 by WZB117 sensitizes radioresistant breast cancer cells to irradiation. Cancer Chemother Pharmacol., 2016, 77(5): 963-972

[69]

Bao YY, Zhou SH, Lu ZJ, et al.. Inhibiting GLUT-1 expression and PI3K/Akt signaling using apigenin improves the radiosensitivity of laryngeal carcinoma in vivo. Oncol Rep., 2015, 34(4): 1805-1814

[70]

Dai LB, Yu Q, Zhou SH, et al.. Effect of combination of curcumin and GLUT-1 AS-ODN on radiosensitivity of laryngeal carcinoma through regulating autophagy. Head Neck., 2020, 42(9): 2287-2297

[71]

Ren Z, Zhao J, Li S, et al.. Targeting glucose transporter 1 (GLUT1) in cancer: molecular mechanisms and nanomedicine applications. Int J Nanomedicine., 2025, 20: 11859-11879

[72]

Semenza GL. Targeting HIF-1 for cancer therapy. Nat Rev Cancer., 2003, 3(10): 721-732

[73]

Chang CK, Chiu PF, Yang HY, et al.. Targeting colorectal cancer with conjugates of a glucose transporter inhibitor and 5-fluorouracil. J Med Chem., 2021, 64(8): 4450-4461

[74]

Wang J, Yu J, Zhang Y, et al.. Glucose transporter inhibitor-conjugated insulin mitigates hypoglycemia. Proc Natl Acad Sci U S A., 2019, 116(22): 10744-10748

[75]

Hu Z, Crews CM. Recent developments in PROTAC-mediated protein degradation: from bench to clinic. ChemBioChem., 2022, 23(2 e202100270

[76]

Mueckler M, Caruso C, Baldwin SA, et al.. Sequence and structure of a human glucose transporter. Science., 1985, 229(4717): 941-945

[77]

McBrayer SK, Cheng JC, Singhal S, et al.. Multiple myeloma exhibits novel dependence on GLUT4, GLUT8, and GLUT11: implications for glucose transporter-directed therapy. Blood., 2012, 119(20): 4686-4697

[78]

Liu Y, Cao Y, Zhang W, et al.. A small-molecule inhibitor of glucose transporter 1 downregulates glycolysis, induces cell-cycle arrest, and inhibits cancer cell growth in vitro and in vivo. Mol Cancer Ther., 2012, 11(8): 1672-1682

[79]

Bernhard C, Reita D, Martin S, et al.. Glioblastoma metabolism: insights and therapeutic strategies. IJMS., 2023, 24(11): 9137

[80]

Fan K, Liu Z, Gao M, et al.. Targeting nutrient dependency in cancer treatment. Front Oncol., 2022, 12 820173

[81]

Iancu CV, Bocci G, Ishtikhar M, et al.. GLUT3 inhibitor discovery through in silico ligand screening and in vivo validation in eukaryotic expression systems. Sci Rep., 2022, 12(1): 1429

[82]

Wei C, Bajpai R, Sharma H, et al.. Development of GLUT4-selective antagonists for multiple myeloma therapy. Eur J Med Chem., 2017, 139: 573-586

[83]

Peng X, Gandhi V. ROS-activated anticancer prodrugs: a new strategy for tumor-specific damage. Ther Deliv., 2012, 3(7): 823-833

[84]

Cheng Q, Shi XL, Li QL, et al.. Current advances on nanomaterials interfering with lactate metabolism for tumor therapy. Adv Sci (Weinh)., 2024, 11(3 e2305662

[85]

Gralewska P, Gajek A, Marczak A, et al.. Targeted nanocarrier-based drug delivery strategies for improving the therapeutic efficacy of PARP inhibitors against ovarian cancer. Int J Mol Sci., 2024, 25(15): 8304

[86]

Xiao F, Li J, Huang K, et al.. Macropinocytosis: mechanism and targeted therapy in cancers. Am J Cancer Res., 2021, 11(1): 14-30

[87]

Porporato PE, Payen VL, Pérez-Escuredo J, et al.. A mitochondrial switch promotes tumor metastasis. Cell Rep., 2014, 8(3): 754-766

[88]

Spinelli JB, Yoon H, Ringel AE, et al.. Metabolic recycling of ammonia via glutamate dehydrogenase supports breast cancer biomass. Science., 2017, 358(6365): 941-946

[89]

Faubert B, Solmonson A, DeBerardinis RJ. Metabolic reprogramming and cancer progression. Science. 2020;368(6487):eaaw5473.

[90]

Qu Y, Dou B, Tan H, et al.. Tumor microenvironment-driven non-cell-autonomous resistance to antineoplastic treatment. Mol Cancer., 2019, 18(1): 69

[91]

Yu L, Zhang J, Li Y. Effects of microenvironment in osteosarcoma on chemoresistance and the promise of immunotherapy as an osteosarcoma therapeutic modality. Front Immunol., 2022, 13 871076

[92]

Castells M, Thibault B, Delord JP, et al.. Implication of tumor microenvironment in chemoresistance: tumor-associated stromal cells protect tumor cells from cell death. Int J Mol Sci., 2012, 13(8): 9545-9571

[93]

Öhlund D, Elyada E, Tuveson D. Fibroblast heterogeneity in the cancer wound. J Exp Med., 2014, 211(8): 1503-1523

[94]

Meng L, Zheng Y, Liu H, et al.. The tumor microenvironment: a key player in multidrug resistance in cancer. Oncologie., 2024, 26(1): 41-58

[95]

Osthus RC, Shim H, Kim S, et al.. Deregulation of glucose transporter 1 and glycolytic gene expression by c-Myc. J Biol Chem., 2000, 275(29): 21797-21800

[96]

Gaglio D, Metallo CM, Gameiro PA, et al.. Oncogenic K-Ras decouples glucose and glutamine metabolism to support cancer cell growth. Mol Syst Biol., 2011, 7: 523

[97]

Tsai YS, Chareddy YS, Price BA, et al.. An integrated model for predicting KRAS dependency. PLoS Comput Biol., 2023, 19(5 e1011095

[98]

Zhou Y, Tao L, Qiu J, et al.. Tumor biomarkers for diagnosis, prognosis and targeted therapy. Sig Transduct Target Ther., 2024, 9(1): 132

[99]

Gwinn DM, Shackelford DB, Egan DF, et al.. AMPK phosphorylation of raptor mediates a metabolic checkpoint. Mol Cell., 2008, 30(2): 214-226

[100]

Krasny L, Huang PH. Data-independent acquisition mass spectrometry (DIA-MS) for proteomic applications in oncology. Mol Omics., 2020, 17(1): 29-42

[101]

Frejno M, Meng C, Ruprecht B, et al.. Proteome activity landscapes of tumor cell lines determine drug responses. Nat Commun., 2020, 11(1): 3639

[102]

Rosenberger G, Li W, Turunen M, et al.. Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis. Nat Commun., 2024, 15: 3909

[103]

Crowl S, Jordan BT, Ahmed H, et al.. KSTAR: an algorithm to predict patient-specific kinase activities from phosphoproteomic data. Nat Commun., 2022, 13: 4283

[104]

Mund A, Coscia F, Kriston A, et al.. Deep Visual Proteomics defines single-cell identity and heterogeneity. Nat Biotechnol., 2022, 40(8): 1231-1240

[105]

Duncan KD, Pětrošová H, Lum JJ, et al.. Mass spectrometry imaging methods for visualizing tumor heterogeneity. Curr Opin Biotechnol., 2024, 86 103068

[106]

Yang H, Zhang MZ, Sun HW, et al.. A novel microcrystalline BAY-876 formulation achieves long-acting antitumor activity against aerobic glycolysis and proliferation of hepatocellular carcinoma. Front Oncol., 2021, 11 783194

[107]

Wahl RL, Jacene H, Kasamon Y, et al.. From RECIST to PERCIST: Evolving Considerations for PET response criteria in solid tumors. J Nucl Med., 2009, 50(Suppl 1): 122S-150S

[108]

Casasnovas RO, Meignan M, Berriolo-Riedinger A, et al.. SUVmax reduction improves early prognosis value of interim positron emission tomography scans in diffuse large B-cell lymphoma. Blood., 2011, 118(1): 37-43

[109]

Mohanti BK, Rath GK, Anantha N, et al.. Improving cancer radiotherapy with 2-deoxy-d-glucose: phase I/II clinical trials on human cerebral gliomas. Int J Radiat Oncol., 1996, 35(1): 103-111

[110]

Singh D, Banerji AK, Dwarakanath BS, et al.. Optimizing cancer radiotherapy with 2-deoxy-d-glucose dose escalation studies in patients with glioblastoma multiforme. Strahlenther Onkol., 2005, 181(8): 507-514

[111]

Raez LE, Papadopoulos K, Ricart AD, et al.. A phase I dose-escalation trial of 2-deoxy-D-glucose alone or combined with docetaxel in patients with advanced solid tumors. Cancer Chemother Pharmacol., 2013, 71(2): 523-530

[112]

Dwarakanath BS, Singh D, Banerji AK, et al.. Clinical studies for improving radiotherapy with 2-deoxy-D-glucose: present status and future prospects. J Cancer Res Ther., 2009, 5(Suppl 1): S21-S26

[113]

Shriwas P, Roberts D, Li Y, et al.. A small-molecule pan-class I glucose transporter inhibitor reduces cancer cell proliferation in vitro and tumor growth in vivo by targeting glucose-based metabolism. Cancer Metab., 2021, 9(1): 14

[114]

Sakamoto KM, Kim KB, Kumagai A, et al.. Protacs: Chimeric molecules that target proteins to the Skp1–Cullin–F box complex for ubiquitination and degradation. Proc Natl Acad Sci U S A., 2001, 98(15): 8554-8559

[115]

Zengerle M, Chan KH, Ciulli A. Selective small molecule induced degradation of the BET bromodomain protein BRD4. ACS Chem Biol., 2015, 10(8): 1770-1777

[116]

Burslem GM, Crews CM. Proteolysis-targeting chimeras as therapeutics and tools for biological discovery. Cell., 2020, 181(1): 102-114

[117]

Christopoulos A. Allosteric binding sites on cell-surface receptors: novel targets for drug discovery. Nat Rev Drug Discov., 2002, 1(3): 198-210

[118]

Changeux JP, Christopoulos A. Allosteric modulation as a unifying mechanism for receptor function and regulation. Diabetes Obesity Metabolism., 2017, 19(S1): 4-21

[119]

Drew D, North RA, Nagarathinam K, et al.. Structures and general transport mechanisms by the major facilitator superfamily (MFS). Chem Rev., 2021, 121(9): 5289-5335

[120]

Preuer K, Lewis RPI, Hochreiter S, et al.. DeepSynergy: predicting anti-cancer drug synergy with Deep Learning. Bioinformatics., 2018, 34(9): 1538-1546

[121]

Wang L, Song Y, Wang H, et al.. Advances of artificial intelligence in anti-cancer drug design: a review of the past decade. Pharmaceuticals (Basel)., 2023, 16(2): 253

[122]

Lao C, Zheng P, Chen H, et al.. DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies. BMC Bioinformatics., 2024, 25(1): 105

[123]

Jiang L, Jiang C, Yu X, et al. DeepTTA: a transformer-based model for predicting cancer drug response. Brief Bioinform. 2022;23(3):bbac100.

[124]

Frangieh CJ, Melms JC, Thakore PI, et al.. Multimodal pooled Perturb-CITE-seq screens in patient models define mechanisms of cancer immune evasion. Nat Genet., 2021, 53(3): 332-341

[125]

Hajim WI, Zainudin S, Mohd Daud K, et al.. Optimized models and deep learning methods for drug response prediction in cancer treatments: a review. PeerJ Comput Sci., 2024, 10 e1903

[126]

Kaizer AM, Belli HM, Ma Z, et al.. Recent innovations in adaptive trial designs: a review of design opportunities in translational research. J Clin Transl Sci., 2023, 7(1 e125

[127]

Renfro LA, Sargent DJ. Statistical controversies in clinical research: basket trials, umbrella trials, and other master protocols: a review and examples. Ann Oncol., 2017, 28(1): 34-43

[128]

Woodcock J, LaVange LM. Master protocols to study multiple therapies, multiple diseases, or both. N Engl J Med., 2017, 377(1): 62-70

[129]

Ferrara D, Shiyam Sundar LK, Chalampalakis Z, et al.. Low-dose and standard-dose whole-body [18F] FDG-PET/CT imaging: implications for healthy controls and lung cancer patients. Front Phys., 2024, 12: 1378521

[130]

Lopez de Rodas M, Villalba-Esparza M, Sanmamed MF, et al. Biological and clinical significance of tumour-infiltrating lymphocytes in the era of immunotherapy: a multidimensional approach. Nat Rev Clin Oncol. 2025;22(3):163–181.

[131]

Tie J, Wang Y, Tomasetti C, et al. Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage II colon cancer. Sci Transl Med. 2016;8(346):346ra92.

[132]

Moding EJ, Liu Y, Nabet BY, et al.. Circulating tumor DNA dynamics predict benefit from consolidation immunotherapy in locally advanced non-small cell lung cancer. Nat Cancer., 2020, 1(2): 176-183

[133]

Xie N, Tan Z, Banerjee S, et al.. Glycolytic reprogramming in myofibroblast differentiation and lung fibrosis. Am J Respir Crit Care Med., 2015, 192(12): 1462-1474

[134]

Cho SJ, Moon JS, Nikahira K, et al.. GLUT1-dependent glycolysis regulates exacerbation of fibrosis via AIM2 inflammasome activation. Thorax., 2020, 75(3): 227-236

[135]

Henderson NC, Rieder F, Wynn TA. Fibrosis: from mechanisms to medicines. Nature., 2020, 587(7835): 555-566

[136]

Jacobs SR, Herman CE, MacIver NJ, et al.. Glucose uptake is limiting in T cell activation and requires CD28-mediated Akt-dependent and independent pathways. J Immunol., 2008, 180(7): 4476-4486

[137]

Michalek RD, Gerriets VA, Jacobs SR, et al.. Cutting edge: distinct glycolytic and lipid oxidative metabolic programs are essential for effector and regulatory CD4+ T cell subsets. J Immunol., 2011, 186(6): 3299-3303

[138]

Freemerman AJ, Johnson AR, Sacks GN, et al.. Metabolic reprogramming of macrophages: glucose transporter 1 (GLUT1)-mediated glucose metabolism drives a proinflammatory phenotype. J Biol Chem., 2014, 289(11): 7884-7896

[139]

Hresko RC, Hruz PW. HIV protease inhibitors act as competitive inhibitors of the cytoplasmic glucose binding site of GLUTs with differing affinities for GLUT1 and GLUT4. PLoS One., 2011, 6(9 e25237

[140]

Gualdoni GA, Mayer KA, Kapsch AM, et al.. Rhinovirus induces an anabolic reprogramming in host cell metabolism essential for viral replication. Proc Natl Acad Sci U S A., 2018, 115(30): E7158-E7165

[141]

Winkler EA, Nishida Y, Sagare AP, et al.. GLUT1 reductions exacerbate Alzheimer’s disease vasculo-neuronal dysfunction and degeneration. Nat Neurosci., 2015, 18(4): 521-530

Funding

the Science and Technology Development Fund, Macau SAR(0075/2024/RIB2)

Rights & permissions

The Author(s), under exclusive licence to the Huazhong University of Science and Technology

PDF

1

Accesses

0

Citation

Detail

Sections
Recommended

/