Skip to content
2000
Volume 25, Issue 8
  • ISSN: 1389-5575
  • E-ISSN: 1875-5607

Abstract

Metabolic reprogramming is a hallmark of cancer. Distinct and unusual metabolic aberrations occur during tumor development that lead to the growth and development of tumors. Oncogenic signaling pathways eventually converge to regulate three major metabolic pathways in tumor cells glucose, lipid, and amino acid metabolism. Therefore, identifying and targeting the metabolic nodes of cancer cells can be a promising intervention and therapeutic strategy for patients with malignancies. The long road of new drug discovery for cancer therapy has necessitated relooking alternative strategies such as drug repurposing. Advanced genomic and proteomic technologies for the assessment of cancer-specific biological pathways have led to the discovery of new drug targets, which provide excellent opportunities for drug repurposing. The development of effective, safe, cheaper, and readily available anticancer agents is the need of the hour, and drug repurposing has the potential to break the current drug shortage bottleneck. This review will accordingly cover various metabolic pathways that are aberrant in cancer, and strategies for targeting metabolic reprogramming by using repurposed drugs.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/mrmc/10.2174/0113895575339660250106093738
2025-02-17
2025-11-01

  • From This Site

    /content/journals/mrmc/10.2174/0113895575339660250106093738
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. RanaA. AdhikaryM. SinghP.K. DasB.C. BhatnagarS. “Smart” drug delivery: A window to future of translational medicine.Front Chem.202310109559810.3389/fchem.2022.1095598 36688039
     [Google Scholar]
  2. MaoJ.J. PillaiG.G. AndradeC.J. LigibelJ.A. BasuP. CohenL. KhanI.A. MustianK.M. PuthiyedathR. DhimanK.S. LaoL. GhelmanR. Cáceres GuidoP. LopezG. Gallego-PerezD.F. SalicrupL.A. Integrative oncology: Addressing the global challenges of cancer prevention and treatment.CA Cancer J. Clin.202272214416410.3322/caac.21706 34751943
     [Google Scholar]
  3. SungH. FerlayJ. SiegelR.L. LaversanneM. SoerjomataramI. JemalA. BrayF. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J. Clin.202171320924910.3322/caac.21660 33538338
     [Google Scholar]
  4. SathishkumarK. ChaturvediM. DasP. StephenS. MathurP. Cancer incidence estimates for 2022 & projection for 2025: Result from National Cancer Registry Programme, India.Indian J. Med. Res.20221564&5598607 36510887
     [Google Scholar]
  5. ShajiA. KeechilatP. DkV. SauvagetC. Analysis of the mortality trends of 23 major cancers in the Indian population between 2000 and 2019: A joinpoint regression analysis.JCO Glob. Oncol.202399e220040510.1200/GO.22.00405 36947728
     [Google Scholar]
  6. Vander HeidenM.G. CantleyL.C. ThompsonC.B. Understanding the Warburg effect: The metabolic requirements of cell proliferation.Science2009324593010291033
     [Google Scholar]
  7. LuengoA. GuiD.Y. Vander HeidenM.G. Targeting metabolism for cancer therapy.Cell Chem. Biol.20172491161118010.1016/j.chembiol.2017.08.028 28938091
     [Google Scholar]
  8. VoraP. SomaniR. JainM. Drug repositioning: An approach for drug discovery.Mini Rev. Org. Chem.201613536337610.2174/1570193X13666160728121823
     [Google Scholar]
  9. LiC. HeW.Q. Global prediction of primary liver cancer incidences and mortality in 2040.J. Hepatol.2023784e144e14610.1016/j.jhep.2022.12.002 36513185
     [Google Scholar]
  10. XiaY. SunM. HuangH. JinW.L. Drug repurposing for cancer therapy.Signal Transduct. Target. Ther.2024919210.1038/s41392‑024‑01808‑1 38637540
     [Google Scholar]
  11. HijaziM.A. GessnerA. El-NajjarN. Repurposing of chronically used drugs in cancer therapy: A chance to grasp.Cancers 20231512319910.3390/cancers15123199 37370809
     [Google Scholar]
  12. GalluzziL. KeppO. HeidenM.G.V. KroemerG. Metabolic targets for cancer therapy.Nat. Rev. Drug Discov.2013121182984610.1038/nrd4145 24113830
     [Google Scholar]
  13. NavarroC. OrtegaÁ. SantelizR. GarridoB. ChacínM. GalbanN. VeraI. De SanctisJ.B. BermúdezV. Metabolic reprogramming in cancer cells: Emerging molecular mechanisms and novel therapeutic approaches.Pharmaceutics2022146130310.3390/pharmaceutics14061303 35745875
     [Google Scholar]
  14. KrishnamurthyN. GrimshawA.A. AxsonS.A. ChoeS.H. MillerJ.E. Drug repurposing: A systematic review on root causes, barriers and facilitators.BMC Health Serv. Res.202222197010.1186/s12913‑022‑08272‑z 35906687
     [Google Scholar]
  15. MallaR. ViswanathanS. MakenaS. KapoorS. VermaD. RajuA.A. DunnaM. MunirajN. Revitalizing cancer treatment: Exploring the role of drug repurposing.Cancers 2024168146310.3390/cancers16081463 38672545
     [Google Scholar]
  16. NosengoN. Can you teach old drugs new tricks?Nature2016534760731431610.1038/534314a 27306171
     [Google Scholar]
  17. SainiM. PariharN. SoniS.L. SharmaV. Drug repurposing: An overview.Asian J. Pharm. Res. Dev.202084194212
     [Google Scholar]
  18. PushpakomS. IorioF. EyersP.A. EscottK.J. HopperS. WellsA. DoigA. GuilliamsT. LatimerJ. McNameeC. NorrisA. SanseauP. CavallaD. PirmohamedM. Drug repurposing: Progress, challenges and recommendations.Nat. Rev. Drug Discov.2019181415810.1038/nrd.2018.168 30310233
     [Google Scholar]
  19. WuK.C. LiaoK.S. YehL.R. WangY.K. Drug repurposing: The mechanisms and signaling pathways of anti-cancer effects of anesthetics.Biomedicines2022107158910.3390/biomedicines10071589 35884894
     [Google Scholar]
  20. SiddiquiS. DeshmukhA.J. MudaliarP. NalawadeA.J. IyerD. AichJ. Drug repurposing: re-inventing therapies for cancer without re-entering the development pipeline—a review.J. Egypt. Natl. Canc. Inst.20223413310.1186/s43046‑022‑00137‑0 35934727
     [Google Scholar]
  21. NongS. HanX. XiangY. QianY. WeiY. ZhangT. TianK. ShenK. YangJ. MaX. Metabolic reprogramming in cancer: Mechanisms and therapeutics.MedComm202342e21810.1002/mco2.218 36994237
     [Google Scholar]
  22. PantziarkaP. CapistranoI.R. De PotterA. VandeborneL. BoucheG. An open access database of licensed cancer drugs.Front. Pharmacol.20211262757410.3389/fphar.2021.627574 33776770
     [Google Scholar]
  23. BallingerA. Orlistat in the treatment of obesity.Expert Opin. Pharmacother.20001484184710.1517/14656566.1.4.841 11249520
     [Google Scholar]
  24. HazarikaM. WhiteR.M. JohnsonJ.R. PazdurR. FDA drug approval summaries: Pemetrexed (Alimta).Oncologist20049548248810.1634/theoncologist.9‑5‑482 15477632
     [Google Scholar]
  25. DaiJ. GaoJ. DongH. Prognostic relevance and validation of ARPC1A in the progression of low-grade glioma.Aging (Albany NY)20241614111621118410.18632/aging.205952 39012280
     [Google Scholar]
  26. LinJ. WangL. HuangM. XuG. YangM. Metabolic changes induced by heavy metal copper exposure in human ovarian granulosa cells.Ecotoxicol. Environ. Saf.202428511707810.1016/j.ecoenv.2024.117078 39305777
     [Google Scholar]
  27. JingR. JiangZ. TangX. Advances in millimeter-wave treatment and its biological effects development.Int. J. Mol. Sci.20242516863810.3390/ijms25168638 39201326
     [Google Scholar]
  28. SullivanM.R. DanaiL.V. LewisC.A. ChanS.H. GuiD.Y. KunchokT. DennstedtE.A. Vander HeidenM.G. MuirA. Quantification of microenvironmental metabolites in murine cancers reveals determinants of tumor nutrient availability.eLife20198e4423510.7554/eLife.44235 30990168
     [Google Scholar]
  29. TripathiV. JaiswalP. SahuK. MajumderS.K. KashyapD. Chandra JhaH. DixitA.K. ParmarH.S. Repurposing of metabolic drugs and mitochondrial modulators as an emerging class of cancer therapeutics with a special focus on breast cancer.Adv. Cancer Biol. Metastasis2022610006510.1016/j.adcanc.2022.100065
     [Google Scholar]
  30. HanahanD. WeinbergR.A. Hallmarks of cancer: The next generation.Cell20111445646674
     [Google Scholar]
  31. LiH. ZhouJ. SunH. QiuZ. GaoX. XuY. CaMeRe: A novel tool for inference of cancer metabolic reprogramming.Front. Oncol.20201020710.3389/fonc.2020.00207 32161720
     [Google Scholar]
  32. JacquetP. StéphanouA. Metabolic reprogramming, questioning, and implications for cancer.Biology 202110212910.3390/biology10020129 33562201
     [Google Scholar]
  33. YoshidaG.J. Metabolic reprogramming: The emerging concept and associated therapeutic strategies.J. Exp. Clin. Cancer Res.201534111110.1186/s13046‑015‑0221‑y 26445347
     [Google Scholar]
  34. PhanL.M. YeungS-C.J. LeeM-H. Cancer metabolic reprogramming: importance, main features, and potentials for precise targeted anti-cancer therapies.Cancer Biol. Med.2014111119 24738035
     [Google Scholar]
  35. SchiliroC. FiresteinB.L. Mechanisms of metabolic reprogramming in cancer cells supporting enhanced growth and proliferation.Cells2021105105610.3390/cells10051056 33946927
     [Google Scholar]
  36. GhanavatM. ShahrouzianM. Deris ZayeriZ. BanihashemiS. KazemiS.M. SakiN. Digging deeper through glucose metabolism and its regulators in cancer and metastasis.Life Sci.202126411860310.1016/j.lfs.2020.118603 33091446
     [Google Scholar]
  37. BarbaI. Carrillo-BoschL. SeoaneJ. Targeting the warburg effect in cancer: Where do we stand?Int. J. Mol. Sci.2024256314210.3390/ijms25063142 38542116
     [Google Scholar]
  38. Pérez-TomásR. Pérez-GuillénI. Lactate in the tumor microenvironment: An essential molecule in cancer progression and treatment.Cancers 20201211324410.3390/cancers12113244 33153193
     [Google Scholar]
  39. AbbaszadehZ. Çeşmeli, S.; Biray Avcı Ç. Crucial players in glycolysis: Cancer progress.Gene202072614415810.1016/j.gene.2019.144158 31629815
     [Google Scholar]
  40. LeeS.H. GolinskaM. GriffithsJ.R. HIF-1-independent mechanisms regulating metabolic adaptation in hypoxic cancer cells.Cells2021109237110.3390/cells10092371 34572020
     [Google Scholar]
  41. KieransS.J. TaylorC.T. Regulation of glycolysis by the hypoxia-inducible factor (HIF): Implications for cellular physiology.J. Physiol.20215991233710.1113/JP280572 33006160
     [Google Scholar]
  42. CruzatV. Macedo RogeroM. Noel KeaneK. CuriR. NewsholmeP. Glutamine: metabolism and immune function, supplementation and clinical translation.Nutrients20181011156410.3390/nu10111564 30360490
     [Google Scholar]
  43. MatésJ.M. Di PaolaF.J. Campos-SandovalJ.A. MazurekS. MárquezJ. Therapeutic targeting of glutaminolysis as an essential strategy to combat cancer. Seminars in cell & developmental biology.Elsevier2020Vol. 98344310.1016/j.semcdb.2019.05.012
     [Google Scholar]
  44. WangZ. LiuF. FanN. ZhouC. LiD. MacvicarT. DongQ. BrunsC.J. ZhaoY. Targeting glutaminolysis: new perspectives to understand cancer development and novel strategies for potential target therapies.Front. Oncol.20201058950810.3389/fonc.2020.589508 33194749
     [Google Scholar]
  45. MaG. ZhangZ. LiP. ZhangZ. ZengM. LiangZ. LiD. WangL. ChenY. LiangY. NiuH. Reprogramming of glutamine metabolism and its impact on immune response in the tumor microenvironment.Cell Commun. Signal.202220111410.1186/s12964‑022‑00909‑0 35897036
     [Google Scholar]
  46. GrindeM.T. HilmarsdottirB. TunsetH.M. HenriksenI.M. KimJ. HaugenM.H. RyeM.B. MaelandsmoG.M. MoestueS.A. Glutamine to proline conversion is associated with response to glutaminase inhibition in breast cancer.Breast Cancer Res.20192116110.1186/s13058‑019‑1141‑0 31088535
     [Google Scholar]
  47. XiangL. MouJ. ShaoB. WeiY. LiangH. TakanoN. SemenzaG.L. XieG. Glutaminase 1 expression in colorectal cancer cells is induced by hypoxia and required for tumor growth, invasion, and metastatic colonization.Cell Death Dis.20191024010.1038/s41419‑018‑1291‑5 30674873
     [Google Scholar]
  48. SahaS. IslamS.M. Abdullah-AL-WadudM. IslamS. AliF. ParkK. Multiomics analysis reveals that GLS and GLS2 differentially modulate the clinical outcomes of cancer.J. Clin. Med.20198335510.3390/jcm8030355 30871151
     [Google Scholar]
  49. DiasM.M. AdamoskiD. Dos ReisL.M. AscençãoC.F.R. de OliveiraK.R.S. MafraA.C.P. da Silva BastosA.C. QuinteroM. de G Cassago, C.; Ferreira, I.M.; Fidelis, C.H.V.; Rocco, S.A.; Bajgelman, M.C.; Stine, Z.; Berindan-Neagoe, I.; Calin, G.A.; Ambrosio, A.L.B.; Dias, S.M.G. GLS2 is protumorigenic in breast cancers.Oncogene202039369070210.1038/s41388‑019‑1007‑z 31541193
     [Google Scholar]
  50. XiangL. XieG. LiuC. ZhouJ. ChenJ. YuS. LiJ. PangX. ShiH. LiangH. Knock-down of glutaminase 2 expression decreases glutathione, NADH, and sensitizes cervical cancer to ionizing radiation.Biochim. Biophys. Acta Mol. Cell Res.20131833122996300510.1016/j.bbamcr.2013.08.003 23954443
     [Google Scholar]
  51. López de la OlivaA.R. Campos-SandovalJ.A. Gómez-GarcíaM.C. CardonaC. Martín-RufiánM. SialanaF.J. CastillaL. BaeN. LoboC. PeñalverA. García-FrutosM. CarroD. EnriqueV. PazJ.C. MirmiraR.G. GutiérrezA. AlonsoF.J. SeguraJ.A. MatésJ.M. LubecG. MárquezJ. Nuclear translocation of glutaminase GLS2 in human cancer cells associates with proliferation arrest and differentiation.Sci. Rep.2020101225910.1038/s41598‑020‑58264‑4 32042057
     [Google Scholar]
  52. CardaciS. CirioloM.R. TCA cycle defects and cancer: when metabolism tunes redox state.Int. J. Cell Biol.2012201211910.1155/2012/161837 22888353
     [Google Scholar]
  53. ChoiY.K. ParkK.G. Targeting glutamine metabolism for cancer treatment.Biomol. Ther. 2018261192810.4062/biomolther.2017.178 29212303
     [Google Scholar]
  54. YeY. YuB. WangH. YiF. Glutamine metabolic reprogramming in hepatocellular carcinoma.Front. Mol. Biosci.202310124205910.3389/fmolb.2023.1242059 37635935
     [Google Scholar]
  55. JinJ. ByunJ.K. ChoiY.K. ParkK.G. Targeting glutamine metabolism as a therapeutic strategy for cancer.Exp. Mol. Med.202355470671510.1038/s12276‑023‑00971‑9 37009798
     [Google Scholar]
  56. DayeD. WellenK.E. Metabolic reprogramming in cancer: unraveling the role of glutamine in tumorigenesis. Seminars in cell & developmental biology.Elsevier2012Vol. 2336236910.1016/j.semcdb.2012.02.002
     [Google Scholar]
  57. LiC. ZhangG. ZhaoL. MaZ. ChenH. Metabolic reprogramming in cancer cells: glycolysis, glutaminolysis, and Bcl-2 proteins as novel therapeutic targets for cancer.World J. Surg. Oncol.20151411510.1186/s12957‑016‑0769‑9 26791262
     [Google Scholar]
  58. Pérez-EscuredoJ. DadhichR.K. DhupS. CacaceA. Van HéeV.F. De SaedeleerC.J. SboarinaM. RodriguezF. FontenilleM.J. BrissonL. PorporatoP.E. SonveauxP. Lactate promotes glutamine uptake and metabolism in oxidative cancer cells.Cell Cycle2016151728310.1080/15384101.2015.1120930 26636483
     [Google Scholar]
  59. FanY. XueH. LiZ. HuoM. GaoH. GuanX. Exploiting the Achilles’ heel of cancer: disrupting glutamine metabolism for effective cancer treatment.Front. Pharmacol.202415134552210.3389/fphar.2024.1345522 38510646
     [Google Scholar]
  60. MaanM. PetersJ.M. DuttaM. PattersonA.D. Lipid metabolism and lipophagy in cancer.Biochem. Biophys. Res. Commun.2018504358258910.1016/j.bbrc.2018.02.097 29438712
     [Google Scholar]
  61. WangM. WangK. LiaoX. HuH. ChenL. MengL. GaoW. LiQ. Carnitine palmitoyltransferase system: A new target for anti-inflammatory and anticancer therapy?Front. Pharmacol.20211276058110.3389/fphar.2021.760581 34764874
     [Google Scholar]
  62. MaY. TemkinS.M. HawkridgeA.M. GuoC. WangW. WangX.Y. FangX. Fatty acid oxidation: An emerging facet of metabolic transformation in cancer.Cancer Lett.20184359210010.1016/j.canlet.2018.08.006 30102953
     [Google Scholar]
  63. ShaoH. MohamedE.M. XuG.G. WatersM. JingK. MaY. ZhangY. SpiegelS. IdowuM.O. FangX. Carnitine palmitoyltransferase 1A functions to repress FoxO transcription factors to allow cell cycle progression in ovarian cancer.Oncotarget2016743832384610.18632/oncotarget.6757 26716645
     [Google Scholar]
  64. JinY. TanY. WuJ. RenZ. Lipid droplets: A cellular organelle vital in cancer cells.Cell Death Discov.20239125410.1038/s41420‑023‑01493‑z 37474495
     [Google Scholar]
  65. CruzA.L.S. BarretoE.A. FazoliniN.P.B. ViolaJ.P.B. BozzaP.T. Lipid droplets: platforms with multiple functions in cancer hallmarks.Cell Death Dis.202011210510.1038/s41419‑020‑2297‑3 32029741
     [Google Scholar]
  66. HalldorssonS. RohatgiN. MagnusdottirM. ChoudharyK.S. GudjonssonT. KnutsenE. BarkovskayaA. HilmarsdottirB. PeranderM. MælandsmoG.M. GudmundssonS. RolfssonÓ. Metabolic re-wiring of isogenic breast epithelial cell lines following epithelial to mesenchymal transition.Cancer Lett.201739611712910.1016/j.canlet.2017.03.019 28323032
     [Google Scholar]
  67. WenY.A. XingX. HarrisJ.W. ZaytsevaY.Y. MitovM.I. NapierD.L. WeissH.L. Mark EversB. GaoT. Adipocytes activate mitochondrial fatty acid oxidation and autophagy to promote tumor growth in colon cancer.Cell Death Dis.201782e2593e259310.1038/cddis.2017.21 28151470
     [Google Scholar]
  68. TanZ. ZouY. ZhuM. LuoZ. WuT. ZhengC. XieA. WangH. FangS. LiuS. LiY. LuZ. Carnitine palmitoyl transferase 1A is a novel diagnostic and predictive biomarker for breast cancer.BMC Cancer202121140910.1186/s12885‑021‑08134‑7 33858374
     [Google Scholar]
  69. CazzanigaM. BonanniB. Relationship between metabolic reprogramming and mitochondrial activity in cancer cells. Understanding the anticancer effect of metformin and its clinical implications.Anticancer Res.2015351157895796 26503999
     [Google Scholar]
  70. TorresanoL. Nuevo-TapiolesC. SantacatterinaF. CuezvaJ.M. Metabolic reprogramming and disease progression in cancer patients.Biochim. Biophys. Acta Mol. Basis Dis.20201866516572110.1016/j.bbadis.2020.165721 32057942
     [Google Scholar]
  71. HuY. LouX. WangR. SunC. LiuX. LiuS. WangZ. NiC. Aspirin, a potential GLUT1 inhibitor in a vascular endothelial cell line.Open Med.201914155256010.1515/med‑2019‑0062 31565672
     [Google Scholar]
  72. HoskinA.J. HoltA.K. LeggeD.N. CollardT.J. WilliamsA.C. VincentE.E. Aspirin and the metabolic hallmark of cancer: novel therapeutic opportunities for colorectal cancer.Explor. Target. Antitumor Ther.20234460061510.37349/etat.2023.00155 37720350
     [Google Scholar]
  73. LiuY. FengJ. SunM. LiuB. YangG. BuY. ZhaoM. WangT. ZhangW. YuanH. ZhangX. Aspirin inhibits the proliferation of hepatoma cells through controlling GLUT1-mediated glucose metabolism.Acta Pharmacol. Sin.201940112213210.1038/s41401‑018‑0014‑x 29925918
     [Google Scholar]
  74. TataranniT. PiccoliC. Dichloroacetate (DCA) and cancer: An overview towards clinical applications.Oxid. Med. Cell. Longev.20198201079
     [Google Scholar]
  75. KankotiaS. StacpooleP.W. Dichloroacetate and cancer: new home for an orphan drug? Biochimica et Biophysica Acta (BBA)-.Rev. Can.201418462617629
     [Google Scholar]
  76. CookK.M. ShenH. McKelveyK.J. GeeH.E. HauE. Targeting glucose metabolism of cancer cells with dichloroacetate to radiosensitize high-grade gliomas.Int. J. Mol. Sci.20212214726510.3390/ijms22147265 34298883
     [Google Scholar]
  77. MadhokB.M. YeluriS. PerryS.L. HughesT.A. JayneD.G. Dichloroacetate induces apoptosis and cell-cycle arrest in colorectal cancer cells.Br. J. Cancer2010102121746175210.1038/sj.bjc.6605701 20485289
     [Google Scholar]
  78. GrayL.R. TompkinsS.C. TaylorE.B. Regulation of pyruvate metabolism and human disease.Cell. Mol. Life Sci.201471142577260410.1007/s00018‑013‑1539‑2 24363178
     [Google Scholar]
  79. YehC.S. WangJ.Y. ChungF.Y. LeeS.C. HuangM.Y. KuoC.W. YangM.J. LinS.R. Significance of the glycolytic pathway and glycolysis related-genes in tumorigenesis of human colorectal cancers.Oncol. Rep.2008191819110.3892/or.19.1.81 18097579
     [Google Scholar]
  80. LinG. HillD.K. AndrejevaG. BoultJ.K.R. TroyH. FongA-C.L F W.T. OrtonM.R. PanekR. ParkesH.G. JafarM. KohD-M. RobinsonS.P. JudsonI.R. GriffithsJ.R. LeachM.O. EykynT.R. ChungY-L. Dichloroacetate induces autophagy in colorectal cancer cells and tumours.Br. J. Cancer2014111237538510.1038/bjc.2014.281 24892448
     [Google Scholar]
  81. KoltaiT. FliegelL. Dichloroacetate for cancer treatment: Some facts and many doubts.Pharmaceuticals202417674410.3390/ph17060744 38931411
     [Google Scholar]
  82. GoelR. 2-deoxy-d-glucose: From diagnostics to therapeutics.Int. J. Basic Clin. Pharmacol.202110673210.18203/2319‑2003.ijbcp20212086
     [Google Scholar]
  83. ZhangX.D. DeslandesE. VilledieuM. PoulainL. DuvalM. GauduchonP. SchwartzL. IcardP. Effect of 2-deoxy-d-glucose on various malignant cell lines in vitro.Anticancer Res.2006265A35613566 17094483
     [Google Scholar]
  84. ZhangD. LiJ. WangF. HuJ. WangS. SunY. 2-deoxy-d-glucose targeting of glucose metabolism in cancer cells as a potential therapy.Cancer Lett.2014355217618310.1016/j.canlet.2014.09.003 25218591
     [Google Scholar]
  85. BertheA. ZaffinoM. MullerC. FoulquierF. HoudouM. SchulzC. BostF. De FayE. MazerbourgS. FlamentS. Protein N-glycosylation alteration and glycolysis inhibition both contribute to the antiproliferative action of 2-deoxyglucose in breast cancer cells.Breast Cancer Res. Treat.2018171358159110.1007/s10549‑018‑4874‑z 29971627
     [Google Scholar]
  86. ZhangZ. ZhouL. XieN. NiceE.C. ZhangT. CuiY. HuangC. Overcoming cancer therapeutic bottleneck by drug repurposing.Signal Transduct. Target. Ther.20205111310.1038/s41392‑020‑00213‑8 32616710
     [Google Scholar]
  87. RenaG. HardieD.G. PearsonE.R. The mechanisms of action of metformin.Diabetologia20176091577158510.1007/s00125‑017‑4342‑z 28776086
     [Google Scholar]
  88. SalaniB. RioA.D. MariniC. SambucetiG. CorderaR. MaggiD. Metformin, cancer and glucose metabolism.Endocr. Relat. Cancer2014216R461R47110.1530/ERC‑14‑0284 25273809
     [Google Scholar]
  89. ZhaoB. LuoJ. YuT. ZhouL. LvH. ShangP. Anticancer mechanisms of metformin: A review of the current evidence.Life Sci.202025411771710.1016/j.lfs.2020.117717 32339541
     [Google Scholar]
  90. PantziarkaP. SukhatmeV. BoucheG. MeheusL. SukhatmeV.P. Repurposing drugs in oncology (ReDO)—diclofenac as an anti-cancer agent.Ecancermedicalscience201610610
     [Google Scholar]
  91. GottfriedE. LangS.A. RennerK. BosserhoffA. GronwaldW. RehliM. EinhellS. GedigI. SingerK. SeilbeckA. MackensenA. GrauerO. HauP. DettmerK. AndreesenR. OefnerP.J. KreutzM. New aspects of an old drug-diclofenac targets MYC and glucose metabolism in tumor cells.PLoS One201387e6698710.1371/journal.pone.0066987 23874405
     [Google Scholar]
  92. YangL. LiJ. LiY. ZhouY. WangZ. ZhangD. LiuJ. ZhangX. Diclofenac impairs the proliferation and glucose metabolism of triple negative breast cancer cells by targeting the c Myc pathway.Exp. Ther. Med.202121658410.3892/etm.2021.10016 33850556
     [Google Scholar]
  93. AbdalbariF.H. TelleriaC.M. The gold complex auranofin: new perspectives for cancer therapy.Discov. Oncol.20211214210.1007/s12672‑021‑00439‑0 35201489
     [Google Scholar]
  94. GamberiT. ChiappettaG. FiaschiT. ModestiA. SorbiF. MagheriniF. Upgrade of an old drug: Auranofin in innovative cancer therapies to overcome drug resistance and to increase drug effectiveness.Med. Res. Rev.20224231111114610.1002/med.21872 34850406
     [Google Scholar]
  95. KouL. WeiS. KouP. Current progress and perspectives on using gold compounds for the modulation of tumor cell metabolism.Front Chem.2021973346310.3389/fchem.2021.733463 34434922
     [Google Scholar]
  96. HoltA.K. NajumudeenA.K. CollardT.J. LiH. MillettL.M. HoskinA.J. LeggeD.N. MortenssonE.M.H. FlanaganD.J. JonesN. KollareddyM. TimmsP. HitchingsM.D. CroninJ. SansomO.J. WilliamsA.C. VincentE.E. Aspirin reprogrammes colorectal cancer cell metabolism and sensitises to glutaminase inhibition.Cancer Metab.20231111810.1186/s40170‑023‑00318‑y 37858256
     [Google Scholar]
  97. BokuS. WatanabeM. SukenoM. YaoiT. HirotaK. Iizuka-OhashiM. ItohK. SakaiT. Deactivation of glutaminolysis sensitizes PIK3CA-mutated colorectal cancer cells to aspirin-induced growth inhibition.Cancers (Basel) 2020125109710.3390/cancers12051097 32365457
     [Google Scholar]
  98. SaladiniS. AventaggiatoM. BarrecaF. MorganteE. SansoneL. RussoM.A. TafaniM. Metformin impairs glutamine metabolism and autophagy in tumour cells.Cells2019814910.3390/cells8010049 30646605
     [Google Scholar]
  99. Gómez-CebriánN. Domingo-OrtíI. PovedaJ.L. VicentM.J. Puchades-CarrascoL. Pineda-LucenaA. Multi-omic approaches to breast cancer metabolic phenotyping: Applications in diagnosis, prognosis, and the development of novel treatments.Cancers 20211318454410.3390/cancers13184544 34572770
     [Google Scholar]
  100. BaoJ. ZhuL. ZhuQ. SuJ. LiuM. HuangW. SREBP-1 is an independent prognostic marker and promotes invasion and migration in breast cancer.Oncol. Lett.20161242409241610.3892/ol.2016.4988 27703522
     [Google Scholar]
  101. ZhuY. LinX. ZhouX. ProchownikE.V. WangF. LiY. Posttranslational control of lipogenesis in the tumor microenvironment.J. Hematol. Oncol.202215112010.1186/s13045‑022‑01340‑1 36038892
     [Google Scholar]
  102. Savukaitytė A.; Bartnykaitė A.; Bekampytė J.; Ugenskienė R.; Juozaitytė E. DDIT4 downregulation by siRNA approach increases the activity of proteins regulating fatty acid metabolism upon aspirin treatment in human breast cancer cells.Curr. Issues Mol. Biol.20234564665467410.3390/cimb45060296 37367045
     [Google Scholar]
  103. SchlaepferI.R. JoshiM. CPT1A-mediated fat oxidation, mechanisms, and therapeutic potential.Endocrinology20201612bqz04610.1210/endocr/bqz046 31900483
     [Google Scholar]
  104. YangG. WangY. FengJ. LiuY. WangT. ZhaoM. YeL. ZhangX. Aspirin suppresses the abnormal lipid metabolism in liver cancer cells via disrupting an NFκB-ACSL1 signaling.Biochem. Biophys. Res. Commun.2017486382783210.1016/j.bbrc.2017.03.139 28359761
     [Google Scholar]
  105. ForetzM. GuigasB. BertrandL. PollakM. ViolletB. Metformin: from mechanisms of action to therapies.Cell Metab.201420695396610.1016/j.cmet.2014.09.018 25456737
     [Google Scholar]
  106. BarbatoD.L. VeglianteR. DesideriE. CirioloM.R. Managing lipid metabolism in proliferating cells: new perspective for metformin usage in cancer therapy. Biochimica et Biophysica Acta (BBA)-.Rev. Can.201418452317324
     [Google Scholar]
  107. BhallaK. HwangB.J. DewiR.E. TwaddelW. GoloubevaO.G. WongK.K. SaxenaN.K. BiswalS. GirnunG.D. Metformin prevents liver tumorigenesis by inhibiting pathways driving hepatic lipogenesis.Cancer Prev. Res. 20125454455210.1158/1940‑6207.CAPR‑11‑0228 22467080
     [Google Scholar]
  108. JiangW. HuJ.W. HeX.R. JinW.L. HeX.Y. Statins: A repurposed drug to fight cancer.J. Exp. Clin. Cancer Res.202140124110.1186/s13046‑021‑02041‑2 34303383
     [Google Scholar]
  109. ZhangQ. DongJ. YuZ. Pleiotropic use of statins as non-lipid-lowering drugs.Int. J. Biol. Sci.202016142704271110.7150/ijbs.42965 33110390
     [Google Scholar]
  110. GöbelA. ZinnaV.M. Dell’EndiceS. JaschkeN. KuhlmannJ.D. WimbergerP. RachnerT.D. Anti-tumor effects of mevalonate pathway inhibition in ovarian cancer.BMC Cancer202020170310.1186/s12885‑020‑07164‑x 32727400
     [Google Scholar]
  111. DuarteJ.A. de BarrosA.L.B. LeiteE.A. The potential use of simvastatin for cancer treatment: A review.Biomed. Pharmacother.202114111185810.1016/j.biopha.2021.111858 34323700
     [Google Scholar]
  112. GuptaS.C. SungB. PrasadS. WebbL.J. AggarwalB.B. Cancer drug discovery by repurposing: Teaching new tricks to old dogs.Trends Pharmacol. Sci.201334950851710.1016/j.tips.2013.06.005 23928289
     [Google Scholar]
  113. LianX. WangG. ZhouH. ZhengZ. FuY. CaiL. Anticancer properties of fenofibrate: A repurposing use.J. Cancer2018991527153710.7150/jca.24488 29760790
     [Google Scholar]
  114. KoltaiT. Fenofibrate in cancer: mechanisms involved in anticancer activity.F1000 Res.201545510.12688/f1000research.6153.2
     [Google Scholar]
  115. ChenL. PengJ. WangY. JiangH. WangW. DaiJ. TangM. WeiY. KuangH. XuG. XuH. ZhouF. Fenofibrate-induced mitochondrial dysfunction and metabolic reprogramming reversal: The anti-tumor effects in gastric carcinoma cells mediated by the PPAR pathway.Am. J. Transl. Res.2020122428446 32194894
     [Google Scholar]
  116. JanC.I. TsaiM.H. ChiuC.F. HuangY.P. LiuC.J. ChangN.W. Fenofibrate suppresses oral tumorigenesis via reprogramming metabolic processes: potential drug repurposing for oral cancer.Int. J. Biol. Sci.201612778679810.7150/ijbs.13851 27313493
     [Google Scholar]
  117. MichelakisE.D. WebsterL. MackeyJ.R. Dichloroacetate (DCA) as a potential metabolic-targeting therapy for cancer.Br. J. Cancer200899798999410.1038/sj.bjc.6604554 18766181
     [Google Scholar]
  118. BrownK. RufiniA. New concepts and challenges in the clinical translation of cancer preventive therapies: The role of pharmacodynamic biomarkers.Ecancermedicalscience2015960110.3332/ecancer.2015.601 26635905
     [Google Scholar]
  119. AlfonsoL. AiG. SpitaleR.C. BhatG.J. Molecular targets of aspirin and cancer prevention.Br. J. Cancer20141111616710.1038/bjc.2014.271 24874482
     [Google Scholar]
  120. DovizioM. TacconelliS. SostresC. RicciottiE. PatrignaniP. Mechanistic and pharmacological issues of aspirin as an anticancer agent.Pharmaceuticals (Basel) 20125121346137110.3390/ph5121346 24281340
     [Google Scholar]
  121. ZhaoH. LiY. Cancer metabolism and intervention therapy.Mol. Biomed.202121510.1186/s43556‑020‑00012‑1 35006438
     [Google Scholar]
  122. TwarockS. ReichertC. BachK. ReinersO. KretschmerI. GorskiD.J. GorgesK. GrandochM. FischerJ.W. Inhibition of the hyaluronan matrix enhances metabolic anticancer therapy by dichloroacetate in vitro and in vivo.Br. J. Pharmacol.2019176234474449010.1111/bph.14808 31351004
     [Google Scholar]
  123. LaiH.W. KasaiM. YamamotoS. FukuharaH. KarashimaT. KurabayashiA. FurihataM. HanazakiK. InoueK. OguraS. Metabolic shift towards oxidative phosphorylation reduces cell-density-induced cancer-stem-cell-like characteristics in prostate cancer in vitro.Biol. Open2023124bio05961510.1242/bio.059615 36919762
     [Google Scholar]
  124. WethF.R. HoggarthG.B. WethA.F. PatersonE. WhiteM.P.J. TanS.T. PengL. GrayC. Unlocking hidden potential: Advancements, approaches, and obstacles in repurposing drugs for cancer therapy.Br. J. Cancer2024130570371510.1038/s41416‑023‑02502‑9 38012383
     [Google Scholar]
  125. AfzaalH. WaseemT. SaeedA. NooriF.A. Obaidullah; Babar, M.M. Regulatory considerations and intellectual property rights of repurposed drugs.Prog. Mol. Biol. Transl. Sci.202420535737510.1016/bs.pmbts.2024.03.019 38789186
     [Google Scholar]
  126. LiddicoatJ. LiddellK. DarrowJ. AboyM. JordanM. CrespoC. MinssenT. Repositioning generic drugs: Empirical findings and policy implications.IIC Int. Rev. Ind. Prop. Copyr. Law20225391287132210.1007/s40319‑022‑01241‑3
     [Google Scholar]
  127. MarusinaK. WelschD.J. RoseL. BrockD. BahrN. The CTSA Pharmaceutical Assets Portal – a public–private partnership model for drug repositioning.Drug Discov. Today Ther. Strateg.201183-4778310.1016/j.ddstr.2011.06.006 22768020
     [Google Scholar]
  128. KaushikI. RamachandranS. PrasadS. SrivastavaS.K. Drug rechanneling: A novel paradigm for cancer treatment. Seminars in cancer biology.Elsevier2021Vol. 6827929010.1016/j.semcancer.2020.03.011
     [Google Scholar]
  129. EntonuM.E. IkaM.D. EmmanuelE. BarnabasC.L. GaiyaD.D. UduS.K. Drug repurposing: Recent advancements, challenges, and future therapeutics for cancer treatment.JBMOA2022102263010.15406/jbmoa.2022.10.00322
     [Google Scholar]
  130. VerbaanderdC. RoomanI. HuysI. Exploring new uses for existing drugs: innovative mechanisms to fund independent clinical research.Trials202122132210.1186/s13063‑021‑05273‑x 33947441
     [Google Scholar]
  131. van der PolK.H. AljofanM. BlinO. CornelJ.H. RongenG.A. WoestelandtA.G. SpeddingM. Drug repurposing of generic drugs: challenges and the potential role for government.Appl. Health Econ. Health Policy202321683184010.1007/s40258‑023‑00816‑6 37398987
     [Google Scholar]
  132. Global pharma companies’ return on R&D investment increases after record low2023Available from: https://www.deloitte.com/uk/en/about/press-room/global-pharma-companies-return-on-rd-investment-increases-after-record-low.html
  133. Research and development in the pharmaceutical industry. 2021Available from: https://www.cbo.gov/publication/57126#:~:text=Developing%20new%20drugs%20is%20a,than%20$2%20billion%20per%20drug (accessed 31-10-2024).
  134. KaitinK.I. The landscape for pharmaceutical innovation: Drivers of cost-effective clinical research.Pharm. Outsourcing201020103605
     [Google Scholar]
  135. ChaY. ErezT. ReynoldsI.J. KumarD. RossJ. KoytigerG. KuskoR. ZeskindB. RissoS. KaganE. PapapetropoulosS. GrossmanI. LaifenfeldD. Drug repurposing from the perspective of pharmaceutical companies.Br. J. Pharmacol.2018175216818010.1111/bph.13798 28369768
     [Google Scholar]
  136. VolberdingP.A. LagakosS.W. KochM.A. PettinelliC. MyersM.W. BoothD.K. BalfourH.H.Jr ReichmanR.C. BartlettJ.A. HirschM.S. MurphyR.L. HardyW.D. SoeiroR. FischlM.A. BartlettJ.G. MeriganT.C. HyslopN.E. RichmanD.D. ValentineF.T. CoreyL. Zidovudine in asymptomatic human immunodeficiency virus infection. A controlled trial in persons with fewer than 500 CD4-positive cells per cubic millimeter.N. Engl. J. Med.19903221494194910.1056/NEJM199004053221401 1969115
     [Google Scholar]
  137. YongP.F. D’CruzD.P. Mycophenolate mofetil in the treatment of lupus nephritis.Biologics200822297310 19707362
     [Google Scholar]
  138. Pharmacists day 2024: Celebrating pharmacists’ crucial role in global health. 2024Available from: https://pib.gov.in/PressNoteDetails.aspx?NoteId=153211&ModuleId=3&reg=3&lang=1 (accessed 31-10-2024)
  139. TanoliZ. Vähä-KoskelaM. AittokallioT. Artificial intelligence, machine learning, and drug repurposing in cancer.Expert Opin. Drug Discov.202116997798910.1080/17460441.2021.1883585 33543671
     [Google Scholar]
  140. IssaN.T. StathiasV. SchürerS. DakshanamurthyS. Machine and deep learning approaches for cancer drug repurposing. In: Seminars in cancer biology.Elsevier2021Vol. 6813214210.1016/j.semcancer.2019.12.011
     [Google Scholar]
  141. BaptistaD. FerreiraP.G. RochaM. Deep learning for drug response prediction in cancer.Brief. Bioinform.202122136037910.1093/bib/bbz171 31950132
     [Google Scholar]
  142. LeCunY. BengioY. HintonG. Deep learning for drug response prediction in cancer.Brief. Bioinformatics.2015221360379
     [Google Scholar]
  143. ChangY. ParkH. YangH.J. LeeS. LeeK.Y. KimT.S. JungJ. ShinJ.M. Cancer drug response profile scan (CDRscan): A deep learning model that predicts drug effectiveness from cancer genomic signature.Sci. Rep.201881885710.1038/s41598‑018‑27214‑6 29891981
     [Google Scholar]
  144. HuZ. TangJ. WangZ. ZhangK. ZhangL. SunQ. Deep learning for image-based cancer detection and diagnosis - A survey.Pattern Recognit.20188313414910.1016/j.patcog.2018.05.014
     [Google Scholar]
  145. DanaeeP. GhaeiniR. HendrixD.A. A deep learning approach for cancer detection and relevant gene identification. Pacific symposium on biocomputing 2017; World Scientific201721922910.1142/9789813207813_0022
     [Google Scholar]
  146. KumarV.T.R.P. ArulselviM. SastryK.B.S. Comparative assessment of colon cancer classification using diverse deep learning approaches.JDSIS20231212813510.47852/bonviewJDSIS32021193
     [Google Scholar]
  147. VezakisI.A. LambrouG.I. MatsopoulosG.K. Deep learning approaches to osteosarcoma diagnosis and classification: A comparative methodological approach.Cancers 2023158229010.3390/cancers15082290 37190217
     [Google Scholar]
  148. WangL. SongY. WangH. ZhangX. WangM. HeJ. LiS. ZhangL. LiK. CaoL. Advances of artificial intelligence in anti-cancer drug design: A review of the past decade.Pharmaceuticals202316225310.3390/ph16020253 37259400
     [Google Scholar]
  149. KadurinA. AliperA. KazennovA. MamoshinaP. VanhaelenQ. KhrabrovK. ZhavoronkovA. The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology.Oncotarget201787108831089010.18632/oncotarget.14073 28029644
     [Google Scholar]
  150. LeiY. YangB. JiangX. JiaF. LiN. NandiA.K. Applications of machine learning to machine fault diagnosis: A review and roadmap.Mech. Syst. Signal Process.202013810658710.1016/j.ymssp.2019.106587
     [Google Scholar]
  151. WangS. ZhangJ. An intelligent process fault diagnosis system based on Andrews plot and convolutional neural network.JDMD20221312713810.37965/jdmd.2022.67
     [Google Scholar]
  152. SunJ. GuX. HeJ. YangS. TuY. WuC. A robust approach of multi-sensor fusion for fault diagnosis using convolution neural network.JDMD2022103110
     [Google Scholar]
  153. CorselloS.M. BittkerJ.A. LiuZ. GouldJ. McCarrenP. HirschmanJ.E. JohnstonS.E. VrcicA. WongB. KhanM. AsieduJ. NarayanR. MaderC.C. SubramanianA. GolubT.R. The drug repurposing hub: A next-generation drug library and information resource.Nat. Med.201723440540810.1038/nm.4306 28388612
     [Google Scholar]
  154. SunW. SandersonP.E. ZhengW. Drug combination therapy increases successful drug repositioning.Drug Discov. Today20162171189119510.1016/j.drudis.2016.05.015 27240777
     [Google Scholar]
  155. MokhtariR.B. HomayouniT.S. BaluchN. MorgatskayaE. KumarS. DasB. YegerH. Combination therapy in combating cancer.Oncotarget2017823380223804310.18632/oncotarget.16723 28410237
     [Google Scholar]
  156. YuZ. ZhaoG. XieG. ZhaoL. ChenY. YuH. ZhangZ. LiC. LiY. Metformin and temozolomide act synergistically to inhibit growth of glioma cells and glioma stem cells in vitro and in vivo.Oncotarget2015632329303294310.18632/oncotarget.5405 26431379
     [Google Scholar]
  157. CrystalA.S. ShawA.T. SequistL.V. FribouletL. NiederstM.J. LockermanE.L. FriasR.L. GainorJ.F. AmzallagA. GreningerP. LeeD. KalsyA. Gomez-CaraballoM. ElamineL. HoweE. HurW. LifshitsE. RobinsonH.E. KatayamaR. FaberA.C. AwadM.M. RamaswamyS. Mino-KenudsonM. IafrateA.J. BenesC.H. EngelmanJ.A. Patient-derived models of acquired resistance can identify effective drug combinations for cancer.Science201434662161480148610.1126/science.1254721 25394791
     [Google Scholar]
  158. AshleyE.A. DhordaM. FairhurstR.M. AmaratungaC. LimP. SuonS. SrengS. AndersonJ.M. MaoS. SamB. SophaC. ChuorC.M. NguonC. SovannarothS. PukrittayakameeS. JittamalaP. ChotivanichK. ChutasmitK. SuchatsoonthornC. RuncharoenR. HienT.T. Thuy-NhienN.T. ThanhN.V. PhuN.H. HtutY. HanK.T. AyeK.H. MokuoluO.A. OlaosebikanR.R. FolaranmiO.O. MayxayM. KhanthavongM. HongvanthongB. NewtonP.N. OnyambokoM.A. FanelloC.I. TshefuA.K. MishraN. ValechaN. PhyoA.P. NostenF. YiP. TripuraR. BorrmannS. BashraheilM. PeshuJ. FaizM.A. GhoseA. HossainM.A. SamadR. RahmanM.R. HasanM.M. IslamA. MiottoO. AmatoR. MacInnisB. StalkerJ. KwiatkowskiD.P. BozdechZ. JeeyapantA. CheahP.Y. SakulthaewT. ChalkJ. IntharabutB. SilamutK. LeeS.J. VihokhernB. KunasolC. ImwongM. TarningJ. TaylorW.J. YeungS. WoodrowC.J. FleggJ.A. DasD. SmithJ. VenkatesanM. PloweC.V. StepniewskaK. GuerinP.J. DondorpA.M. DayN.P. WhiteN.J. Spread of artemisinin resistance in Plasmodium falciparum malaria.N. Engl. J. Med.2014371541142310.1056/NEJMoa1314981 25075834
     [Google Scholar]
  159. PolatZ.A. WalochnikJ. ObwallerA. VuralA. DursunA. AriciM.K. Miltefosine and polyhexamethylene biguanide: A new drug combination for the treatment of A canthamoeba keratitis.Clin. Exp. Ophthalmol.201442215115810.1111/ceo.12120 23601234
     [Google Scholar]
  160. ZilberbergM.D. ShorrA.F. MicekS.T. Vazquez-GuillametC. KollefM.H. Multi-drug resistance, inappropriate initial antibiotic therapy and mortality in Gram-negative severe sepsis and septic shock: A retrospective cohort study.Crit. Care201418659610.1186/s13054‑014‑0596‑8 25412897
     [Google Scholar]
  161. CorreiaA.S. GärtnerF. ValeN. Drug combination and repurposing for cancer therapy: The example of breast cancer.Heliyon202171e0594810.1016/j.heliyon.2021.e05948 33490692
     [Google Scholar]
  162. RodriguesR. DuarteD. ValeN. Drug repurposing in cancer therapy: influence of patient’s genetic background in breast cancer treatment.Int. J. Mol. Sci.2022238428010.3390/ijms23084280 35457144
     [Google Scholar]
  163. ZhouY. PengS. WangH. CaiX. WangQ. Review of personalized medicine and pharmacogenomics of anti-cancer compounds and natural products.Genes 202415446810.3390/genes15040468 38674402
     [Google Scholar]
  164. SubasriM. BarrettD. SibalijaJ. BitacolaL. KimR.B. Pharmacogenomic-based personalized medicine: Multistakeholder perspectives on implementational drivers and barriers in the Canadian healthcare system.Clin. Transl. Sci.20211462231224110.1111/cts.13083 34080317
     [Google Scholar]
  165. KoutsilieriS. TzioufaF. SismanoglouD.C. PatrinosG.P. Unveiling the guidance heterogeneity for genome-informed drug treatment interventions among regulatory bodies and research consortia.Pharmacol. Res.202015310459010.1016/j.phrs.2019.104590 31830522
     [Google Scholar]
  166. SadeeW. WangD. HartmannK. TolandA.E. Pharmacogen-omics: driving personalized medicine.Pharmacol. Rev.202375478981410.1124/pharmrev.122.000810 36927888
     [Google Scholar]
  167. RanaA. BhatnagarS. Advancements in folate receptor targeting for anti-cancer therapy: A small molecule-drug conjugate approach.Bioorg. Chem.202111210494610.1016/j.bioorg.2021.104946 33989916
     [Google Scholar]
  168. LiJ. WangQ. XiaG. AdilijiangN. LiY. HouZ. FanZ. LiJ. Recent advances in targeted drug delivery strategy for enhancing oncotherapy.Pharmaceutics2023159223310.3390/pharmaceutics15092233 37765202
     [Google Scholar]
  169. KalaydinaR.V. BajwaK. QorriB. DeCarloA. SzewczukM.R. Recent advances in “smart” delivery systems for extended drug release in cancer therapy.Int. J. Nanomedicine2018134727474510.2147/IJN.S168053 30154657
     [Google Scholar]
  170. ManzariM.T. ShamayY. KiguchiH. RosenN. ScaltritiM. HellerD.A. Targeted drug delivery strategies for precision medicines.Nat. Rev. Mater.20216435137010.1038/s41578‑020‑00269‑6 34950512
     [Google Scholar]
/content/journals/mrmc/10.2174/0113895575339660250106093738
Loading
Drug Repurposing: A Conduit to Unravelling Metabolic Reprogramming for Cancer Treatment
Mini Rev Med Chem 25, 601 (2025); https://doi.org/10.2174/0113895575339660250106093738
/content/journals/mrmc/10.2174/0113895575339660250106093738
/content/journals/mrmc/10.2174/0113895575339660250106093738
Loading

Data & Media loading...


  • Article Type:     Review Article
Keyword(s): cancer; cancer metabolism; cancer treatment; cell death; Drug repurposing; metabolic reprogramming

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test