Skip to main content

Advertisement

Log in

Recent advances in understanding brain cancer metabolomics: a review

  • Review Article
  • Published:
Medical Oncology Aims and scope Submit manuscript

Abstract

Regardless of the significant progress made in surgical techniques and adjuvant therapies, brain tumors are a major contributor to cancer-related morbidity and mortality in both pediatric and adult populations. Gliomas represent a significant proportion of cerebral neoplasms, exhibiting diverse levels of malignancy. The etiology and mechanisms of resistance of this malignancy are inadequately comprehended, and the optimization of patient diagnosis and prognosis is a challenge due to the diversity of the disease and the restricted availability of therapeutic options. Metabolomics refers to the comprehensive analysis of endogenous and exogenous small molecules, both in a targeted and untargeted manner, that enables the characterization of an individual’s phenotype and offers valuable insights into cellular activity, particularly in the context of cancer biology, including brain tumor biology. Metabolomics has garnered attention in current years due to its potential to facilitate comprehension of the dynamic spatiotemporal regulatory network of enzymes and metabolites that enables cancer cells to adapt to their environment and foster the development of tumors. Metabolic changes are widely acknowledged as a significant characteristic for tracking the advancement of diseases, treatment efficacy, and identifying novel molecular targets for successful medical management. Metabolomics has emerged as an exciting area for personalized medicine and drug discovery, utilizing advanced analytical techniques such as nuclear magnetic resonance spectroscopy (MRS) and mass spectrometry (MS) to achieve high-throughput analysis. This review examines and highlights the latest developments in MRS, MS, and other technologies in studying human brain tumor metabolomics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data Availability

The articles analyzed during the current study are available in the literature and listed in the references.

Code Availability

Not applicable.

References

  1. Gavrilovic IT, Posner JB. “Brain metastases: epidemiology and pathophysiology,“ (in eng), J Neurooncol, vol. 75, no. 1, pp. 5–14, Oct 2005.

  2. Ferlay J, Parkin DM, Steliarova-Foucher E. “Estimates of cancer incidence and mortality in Europe in 2008,“ (in eng), Eur J Cancer, vol. 46, no. 4, pp. 765 – 81, Mar 2010.

  3. Ostrom QT, Cioffi G, Waite K, Kruchko C, Barnholtz-Sloan JS. “CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2014–2018,“ (in eng), Neuro Oncol, vol. 23, no. 12 Suppl 2, pp. iii1-iii105, Oct 5 2021.

  4. Weller M, et al. Glioma. Nat reviews Disease primers. 2015;1(1):1–18.

    Google Scholar 

  5. Björkblom B et al. “Distinct metabolic hallmarks of WHO classified adult glioma subtypes,“ (in eng), Neuro Oncol, vol. 24, no. 9, pp. 1454–68, Sep 1 2022.

  6. Wang H, Xu T, Huang Q, Jin W, Chen J. Immunotherapy for Malignant Glioma: Current Status and Future Directions,“ (in eng). Trends Pharmacol Sci. Feb 2020;41(2):123–38.

  7. Escamilla-Ramírez A et al. “Autophagy as a Potential Therapy for Malignant Glioma,“ (in eng), Pharmaceuticals (Basel), vol. 13, no. 7, Jul 19 2020.

  8. Dunn GP et al. “Emerging insights into the molecular and cellular basis of glioblastoma,“ (in eng), Genes Dev, vol. 26, no. 8, pp. 756 – 84, Apr 15 2012.

  9. Randall EC et al. “Localized Metabolomic Gradients in Patient-Derived Xenograft Models of Glioblastoma,“ (in eng), Cancer Res, vol. 80, no. 6, pp. 1258–67, Mar 15 2020.

  10. Garcia JH, Jain S, Aghi MK. Metabolic drivers of Invasion in Glioblastoma,“ (in eng). Front Cell Dev Biol. 2021;9:683276.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Baxter ME, Miller HA, Chen J, Williams BJ, Frieboes HB. “Metabolomic differentiation of tumor core versus edge in glioma,“ (in eng), Neurosurg Focus, vol. 54, no. 6, p. E4, Jun 2023.

  12. Griffin JL, Kauppinen RA. A metabolomics perspective of human brain tumours. (in eng) Febs j. Mar 2007;274(5):1132–9.

  13. Seshacharyulu P, Ponnusamy MP, Haridas D, Jain M, Ganti AK, Batra SK. Targeting the EGFR signaling pathway in cancer therapy,“ (in eng). Expert Opin Ther Targets. Jan 2012;16(1):15–31.

  14. Chakravarti A, et al. RTOG 0211: a phase 1/2 study of radiation therapy with concurrent gefitinib for newly diagnosed glioblastoma patients,“ (in eng). Int J Radiat Oncol Biol Phys. Apr 1 2013;85(5):1206–11.

  15. Marin-Valencia I et al. “Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse human glioblastomas in the mouse brain in vivo,“ (in eng), Cell Metab, vol. 15, no. 6, pp. 827 – 37, Jun 6 2012.

  16. Martini M, Ciraolo E, Gulluni F, Hirsch E. Targeting PI3K in Cancer: any Good News?,“ (in eng). Front Oncol. 2013;3:108.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Ferrara N. “VEGF as a therapeutic target in cancer,“ (in eng), Oncology, vol. 69 Suppl 3, pp. 11 – 6, 2005.

  18. Jun HJ et al. “Acquired MET expression confers resistance to EGFR inhibition in a mouse model of glioblastoma multiforme,“ (in eng), Oncogene, vol. 31, no. 25, pp. 3039-50, Jun 21 2012.

  19. Huang TT, Sarkaria SM, Cloughesy TF, Mischel PS. “Targeted therapy for malignant glioma patients: lessons learned and the road ahead,“ (in eng), Neurotherapeutics, vol. 6, no. 3, pp. 500 – 12, Jul 2009.

  20. DeBerardinis RJ, Lum JJ, Hatzivassiliou G, Thompson CB. “The biology of cancer: metabolic reprogramming fuels cell growth and proliferation,“ (in eng), Cell Metab, vol. 7, no. 1, pp. 11–20, Jan 2008.

  21. DeBerardinis RJ, Thompson CB. “Cellular metabolism and disease: what do metabolic outliers teach us?,“ (in eng), Cell, vol. 148, no. 6, pp. 1132-44, Mar 16 2012.

  22. Schulze A, Harris AL. “How cancer metabolism is tuned for proliferation and vulnerable to disruption,“ (in eng) Nature, vol. 491, no. 7424, pp. 364 – 73, Nov 15 2012.

  23. Wolf A, Agnihotri S, Guha A. “Targeting metabolic remodeling in glioblastoma multiforme,“ (in eng), Oncotarget, vol. 1, no. 7, pp. 552 – 62, Nov 2010.

  24. Marin-Valencia I, et al. Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse human glioblastomas in the mouse brain in vivo. Cell Metabol. 2012;15(6):827–37.

    Article  CAS  Google Scholar 

  25. Guo D, Bell EH, Chakravarti A. “Lipid metabolism emerges as a promising target for malignant glioma therapy,“ (in eng), CNS Oncol, vol. 2, no. 3, pp. 289 – 99, May 2013.

  26. Guo D, Cloughesy TF, Radu CG, Mischel PS. “AMPK: A metabolic checkpoint that regulates the growth of EGFR activated glioblastomas,“ (in eng), Cell Cycle, vol. 9, no. 2, pp. 211–2, Jan 15 2010.

  27. Guo D et al. “The AMPK agonist AICAR inhibits the growth of EGFRvIII-expressing glioblastomas by inhibiting lipogenesis,“ (in eng), Proc Natl Acad Sci U S A, vol. 106, no. 31, pp. 12932-7, Aug 4 2009.

  28. Kefas B, Comeau L, Erdle N, Montgomery E, Amos S, Purow B. Pyruvate kinase M2 is a target of the tumor-suppressive microRNA-326 and regulates the survival of glioma cells,“ (in eng). Neuro Oncol. Nov 2010;12(11):1102–12.

  29. Yang W et al. “EGFR-induced and PKCε monoubiquitylation-dependent NF-κB activation upregulates PKM2 expression and promotes tumorigenesis,“ (in eng), Mol Cell, vol. 48, no. 5, pp. 771 – 84, Dec 14 2012.

  30. Dang L, Jin S, Su SM. “IDH mutations in glioma and acute myeloid leukemia,“ (in eng), Trends Mol Med, vol. 16, no. 9, pp. 387 – 97, Sep 2010.

  31. Guo D et al. “EGFR signaling through an Akt-SREBP-1-dependent, rapamycin-resistant pathway sensitizes glioblastomas to antilipogenic therapy,“ (in eng), Sci Signal, vol. 2, no. 101, p. ra82, Dec 15 2009.

  32. Guo D et al. “An LXR agonist promotes glioblastoma cell death through inhibition of an EGFR/AKT/SREBP-1/LDLR-dependent pathway,“ (in eng), Cancer Discov, vol. 1, no. 5, pp. 442 – 56, Oct 2011.

  33. Williams KJ, et al. An essential requirement for the SCAP/SREBP signaling axis to protect cancer cells from lipotoxicity,“ (in eng). Cancer Res. May 1 2013;73(9):2850–62.

  34. Ru P, Williams TM, Chakravarti A, Guo D. “Tumor metabolism of malignant gliomas,“ (in eng), Cancers (Basel), vol. 5, no. 4, pp. 1469-84, Nov 8 2013.

  35. Marziali G et al. “Metabolic/Proteomic Signature Defines Two Glioblastoma Subtypes With Different Clinical Outcome,“ (in eng), Sci Rep, vol. 6, p. 21557, Feb 9 2016.

  36. Goryńska PZ et al. “Metabolomic Phenotyping of Gliomas: What Can We Get with Simplified Protocol for Intact Tissue Analysis?,“ (in eng), Cancers (Basel), vol. 14, no. 2, Jan 9 2022.

  37. Nakamizo S, et al. GC/MS-based metabolomic analysis of cerebrospinal fluid (CSF) from glioma patients,“ (in eng). J Neurooncol. May 2013;113(1):65–74.

  38. Miller HA, et al. Evaluation of disease staging and chemotherapeutic response in non-small cell lung cancer from patient tumor-derived metabolomic data,“ (in eng). Lung Cancer. Jun 2021;156:20–30.

  39. Wang LB et al. “Proteogenomic and metabolomic characterization of human glioblastoma,“ (in eng), Cancer Cell, vol. 39, no. 4, pp. 509–528.e20, Apr 12 2021.

  40. Oliver SG, Winson MK, Kell DB, Baganz F. Systematic functional analysis of the yeast genome,“ (in eng). Trends Biotechnol. Sep 1998;16(9):373–8.

  41. Nicholson JK, Lindon JC, Holmes E. “’Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data,“ (in eng), Xenobiotica, vol. 29, no. 11, pp. 1181-9, Nov 1999.

  42. Griffin JL, Shockcor JP. “Metabolic profiles of cancer cells,“ (in eng), Nat Rev Cancer, vol. 4, no. 7, pp. 551 – 61, Jul 2004.

  43. Semreen AM et al. “Metabolomics Analysis Revealed Significant Metabolic Changes in Brain Cancer Cells Treated with Paclitaxel and/or Etoposide,“ (in eng), Int J Mol Sci, vol. 23, no. 22, Nov 11 2022.

  44. Masui K, Cavenee WK, Mischel PS, Shibata N. The metabolomic landscape plays a critical role in glioma oncogenesis,“ (in eng). Cancer Sci. May 2022;113(5):1555–63.

  45. Hanahan D, Weinberg RA. “Hallmarks of cancer: the next generation,“ (in eng), Cell, vol. 144, no. 5, pp. 646 – 74, Mar 4 2011.

  46. Masui K, Cavenee WK, Mischel PS. “Cancer metabolism as a central driving force of glioma pathogenesis,“ (in eng), Brain Tumor Pathol, vol. 33, no. 3, pp. 161-8, Jul 2016.

  47. Masui K, Onizuka H, Cavenee WK, Mischel PS, Shibata N. “Metabolic reprogramming in the pathogenesis of glioma: Update,“ (in eng), Neuropathology, vol. 39, no. 1, pp. 3–13, Feb 2019.

  48. Pavlova NN, Thompson CB. “The Emerging Hallmarks of Cancer Metabolism,“ (in eng), Cell Metab, vol. 23, no. 1, pp. 27–47, Jan 12 2016.

  49. Gonçalves V, Pereira JFS, Jordan P. “Signaling Pathways Driving Aberrant Splicing in Cancer Cells,“ (in eng), Genes (Basel), vol. 9, no. 1, Dec 29 2017.

  50. Haglund K, Rusten TE, Stenmark H. Aberrant receptor signaling and trafficking as mechanisms in oncogenesis,“ (in eng). Crit Rev Oncog. Aug 2007;13(1):39–74.

  51. Xu D, Shao F, Bian X, Meng Y, Liang T, Lu Z. “The Evolving Landscape of Noncanonical Functions of Metabolic Enzymes in Cancer and Other Pathologies,“ (in eng), Cell Metab, vol. 33, no. 1, pp. 33–50, Jan 5 2021.

  52. Joyce DD et al. “Examining the association of health literacy and numeracy with prostate-related knowledge and prostate cancer treatment regret,“ (in eng), Urol Oncol, vol. 38, no. 8, pp. 682.e11-682.e19, Aug 2020.

  53. Labuschagne CF, Zani F, Vousden KH. Control of metabolism by p53 - Cancer and beyond,“ (in eng). Biochim Biophys Acta Rev Cancer. Aug 2018;1870(1):32–42.

  54. Stine ZE, Walton ZE, Altman BJ, Hsieh AL, Dang CV. MYC, Metabolism, and Cancer,“ (in eng). Cancer Discov. Oct 2015;5(10):1024–39.

  55. Tajan M, Vousden KH. “Dietary Approaches to Cancer Therapy,“ (in eng), Cancer Cell, vol. 37, no. 6, pp. 767–85, Jun 8 2020.

  56. Pan C, Li B, Simon MC. “Moonlighting functions of metabolic enzymes and metabolites in cancer,“ (in eng), Mol Cell, vol. 81, no. 18, pp. 3760–74, Sep 16 2021.

  57. Lv L, Lei Q. “Proteins moonlighting in tumor metabolism and epigenetics,“ (in eng), Front Med, vol. 15, no. 3, pp. 383–403, Jun 2021.

  58. Warburg O. “On respiratory impairment in cancer cells,“ (eng) Sci, vol. 124, no. 3215, pp. 269 – 70, Aug 10 1956.

  59. Dando I, et al. Oncometabolites in cancer aggressiveness and tumour repopulation,“ (in eng). Biol Rev Camb Philos Soc. Aug 2019;94(4):1530–46.

  60. Hensley CT et al. “Metabolic Heterogeneity in Human Lung Tumors,“ (in eng), Cell, vol. 164, no. 4, pp. 681 – 94, Feb 11 2016.

  61. Vlashi E et al. “Metabolic state of glioma stem cells and nontumorigenic cells,“ (in eng), Proc Natl Acad Sci U S A, vol. 108, no. 38, pp. 16062-7, Sep 20 2011.

  62. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. (in eng) Science. May 22 2009;324(5930):1029–33.

  63. Strickland M, Stoll EA. Metabolic reprogramming in Glioma,“ (in eng). Front Cell Dev Biol. 2017;5:43.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Krell D, Assoku M, Galloway M, Mulholland P, Tomlinson I, Bardella C. Screen for IDH1, IDH2, IDH3, D2HGDH and L2HGDH mutations in glioblastoma,“ (in eng). PLoS ONE. 2011;6(5):e19868.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Mashimo T et al. “Acetate is a bioenergetic substrate for human glioblastoma and brain metastases,“ (in eng), Cell, vol. 159, no. 7, pp. 1603-14, Dec 18 2014.

  66. Lin H et al. “Fatty acid oxidation is required for the respiration and proliferation of malignant glioma cells,“ (in eng), Neuro Oncol, vol. 19, no. 1, pp. 43–54, Jan 2017.

  67. Dimitrov L, Hong CS, Yang C, Zhuang Z, Heiss JD. New developments in the pathogenesis and therapeutic targeting of the IDH1 mutation in glioma,“ (in eng). Int J Med Sci. 2015;12(3):201–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Ceccarelli M et al. “Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma,“ (in eng), Cell, vol. 164, no. 3, pp. 550 – 63, Jan 28 2016.

  69. Keum YS, Choi BY. “Isocitrate dehydrogenase mutations: new opportunities for translational research,“ (in eng), BMB Rep, vol. 48, no. 5, pp. 266 – 70, May 2015.

  70. DeBerardinis RJ, Chandel NS. Fundamentals of cancer metabolism,“ (in eng). Sci Adv. May 2016;2(5):e1600200.

  71. Agnihotri S, Zadeh G. “Metabolic reprogramming in glioblastoma: the influence of cancer metabolism on epigenetics and unanswered questions,“ (in eng), Neuro Oncol, vol. 18, no. 2, pp. 160 – 72, Feb 2016.

  72. Nguyen TL, Durán RV. “Prolyl hydroxylase domain enzymes and their role in cell signaling and cancer metabolism,“ (in eng), Int J Biochem Cell Biol, vol. 80, pp. 71–80, Nov 2016.

  73. Kinnaird A, Zhao S, Wellen KE, Michelakis ED. “Metabolic control of epigenetics in cancer,“ (in eng), Nat Rev Cancer, vol. 16, no. 11, pp. 694–707, Nov 2016.

  74. Nakazawa MS, Keith B, Simon MC. “Oxygen availability and metabolic adaptations,“ (in eng), Nat Rev Cancer, vol. 16, no. 10, pp. 663 – 73, Sep 23 2016.

  75. Urenjak J, Williams SR, Gadian DG, Noble M. Proton nuclear magnetic resonance spectroscopy unambiguously identifies different neural cell types,“ (in eng). J Neurosci. Mar 1993;13(3):981–9.

  76. Florian CL, Preece NE, Bhakoo KK, Williams SR, Noble M. “Characteristic metabolic profiles revealed by 1H NMR spectroscopy for three types of human brain and nervous system tumours,“ (in eng), NMR Biomed, vol. 8, no. 6, pp. 253 – 64, Sep 1995.

  77. Gill SS, et al. Brain metabolites as 1H NMR markers of neuronal and glial disorders,“ (in eng). NMR Biomed. Dec 1989;2:5–6.

  78. Peeling J, Sutherland G. “High-resolution 1H NMR spectroscopy studies of extracts of human cerebral neoplasms,“ (in eng), Magn Reson Med, vol. 24, no. 1, pp. 123 – 36, Mar 1992.

  79. Raja G, Jang Y-K, Suh J-S, Kim H-S, Ahn SH, Kim T-J. “Microcellular Environmental Regulation of Silver Nanoparticles in Cancer Therapy: A Critical Review,“ Cancers, vol. 12, no. 3, p. 664, 2020.

  80. Raja G, Jung Y, Jung SH, Kim T-J. 1H-NMR-based metabolomics for cancer targeting and metabolic engineering –A review. Process Biochem. 2020;99:112–22. 2020/12/01/.

    Article  CAS  Google Scholar 

  81. Raja G, Selvaraj V, Suk M, Suk KT, Kim T-J. Metabolic phenotyping analysis of graphene oxide nanosheets exposures in breast cancer cells: Metabolomics profiling techniques. Process Biochem. 2021;104:39–45. 2021/05/01/.

    Article  CAS  Google Scholar 

  82. Ganesan R, Yoon SJ, Suk KT. Microbiome and Metabolomics in Liver Cancer: Scientific Technology. Int J Mol Sci. 2023;24(1):537.

    Article  CAS  Google Scholar 

  83. Jellum E, Bjørnson I, Nesbakken R, Johansson E, Wold S. “Classification of human cancer cells by means of capillary gas chromatography and pattern recognition analysis,“ (in eng), J Chromatogr, vol. 217, pp. 231-7, Nov 6 1981.

  84. Olsen P, Rasmussen M, Zhu W, Tonnesen E, Stefano GB. “Human gliomas contain morphine,“ (in eng), Med Sci Monit, vol. 11, no. 5, pp. Ms18-21, May 2005.

  85. Sugita Y, Yamada S, Sugita S, Sakata K, Morimatsu M, Shigemori M. The biochemical analysis of neurotransmitters in central neurocytomas,“ (in eng). Int J Mol Med. May 2001;7(5):521–5.

  86. Bieberich E, Freischütz B, Suzuki M, Yu RK. Differential effects of glycolipid biosynthesis inhibitors on ceramide-induced cell death in neuroblastoma cells,“ (in eng). J Neurochem. Mar 1999;72(3):1040–9.

  87. Miller BL, et al. In vivo 1H MRS choline: correlation with in vitro chemistry/histology,“ (in eng). Life Sci. 1996;58(22):1929–35.

    Article  CAS  PubMed  Google Scholar 

  88. Fuss TL, Cheng LL. “Evaluation of Cancer Metabolomics Using ex vivo High Resolution Magic Angle Spinning (HRMAS) Magnetic Resonance Spectroscopy (MRS),“ (in eng), Metabolites, vol. 6, no. 1, Mar 22 2016.

  89. Ganesan R, Prabhakaran V-S, Valsala Gopalakrishnan A. “Metabolomic Signatures in Doxorubicin-Induced Metabolites Characterization, Metabolic Inhibition, and Signaling Pathway Mechanisms in Colon Cancer HCT116 Cells,“ Metabolites, vol. 12, no. 11, p. 1047, 2022.

  90. Lindon JC, Nicholson JK, Holmes E, Everett JR. Metabonomics: metabolic processes studied by NMR spectroscopy of biofluids. Concepts in Magnetic Resonance: An Educational Journal. 2000;12(5):289–320.

    Article  CAS  Google Scholar 

  91. Pudakalakatti S et al. “NMR Spectroscopy-Based Metabolomics of Platelets to Analyze Brain Tumors,“ (in eng), Reports (MDPI), vol. 4, no. 4, Dec 2021.

  92. Evilia RF, “Quantitative NMR. spectroscopy,“ Analytical Letters, vol. 34, no. 13, pp. 2227–2236, 2001.

  93. Wishart DS. Quantitative metabolomics using NMR. TRAC Trends Anal Chem. 2008;27(3):228–37.

    Article  CAS  Google Scholar 

  94. Pan Z, Raftery D. Comparing and combining NMR spectroscopy and mass spectrometry in metabolomics,“ (in eng). Anal Bioanal Chem. Jan 2007;387(2):525–7.

  95. Bharti SK, Roy R. Quantitative 1H NMR spectroscopy. TRAC Trends Anal Chem. 2012;35:5–26.

    Article  CAS  Google Scholar 

  96. Beckonert O, et al. Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat Protoc. 2007;2(11):2692.

    Article  CAS  PubMed  Google Scholar 

  97. Podo F. “Tumour phospholipid metabolism,“ (in eng), NMR Biomed, vol. 12, no. 7, pp. 413 – 39, Nov 1999.

  98. Albers MJ et al. “Proton-decoupled 31P MRS in untreated pediatric brain tumors,“ (in eng), Magn Reson Med, vol. 53, no. 1, pp. 22 – 9, Jan 2005.

  99. Segebarth CM et al. “1H image-guided localized 31P MR spectroscopy of human brain: quantitative analysis of 31P MR spectra measured on volunteers and on intracranial tumor patients,“ (in eng), Magn Reson Med, vol. 11, no. 3, pp. 349 – 66, Sep 1989.

  100. Segebarth CM, Balériaux DF, Arnold DL, Luyten PR, den Hollander JA. “MR image-guided P-31 MR spectroscopy in the evaluation of brain tumor treatment,“ (in eng), Radiology, vol. 165, no. 1, pp. 215–9, Oct 1987.

  101. Heindel W, Bunke J, Glathe S, Steinbrich W, Mollevanger L. “Combined 1H-MR imaging and localized 31P-spectroscopy of intracranial tumors in 43 patients,“ (in eng), J Comput Assist Tomogr, vol. 12, no. 6, pp. 907 – 16, Nov-Dec 1988.

  102. Hubesch B, Sappey-Marinier D, Roth K, Meyerhoff DJ, Matson GB, Weiner MW. “P-31 MR spectroscopy of normal human brain and brain tumors,“ (in eng), Radiology, vol. 174, no. 2, pp. 401-9, Feb 1990.

  103. Tate AR et al. “Towards a method for automated classification of 1H MRS spectra from brain tumours,“ (in eng), NMR Biomed, vol. 11, no. 4–5, pp. 177 – 91, Jun-Aug 1998.

  104. Preul MC, et al. Accurate, noninvasive diagnosis of human brain tumors by using proton magnetic resonance spectroscopy,“ (in eng). Nat Med. Mar 1996;2(3):323–5.

  105. Bezabeh T, Ijare OB, Nikulin AE, Somorjai RL, Smith IC. MRS-based Metabolomics in Cancer Research,“ (in eng). Magn Reson Insights. 2014;7:1–14.

    PubMed  PubMed Central  Google Scholar 

  106. Bouzier AK, Quesson B, Valeins H, Canioni P, Merle M. [1-13 C] glucose metabolism in the tumoral and nontumoral cerebral tissue of a glioma‐bearing rat. J Neurochem. 1999;72(6):2445–55.

    Article  CAS  PubMed  Google Scholar 

  107. Mashimo T et al. “Acetate is a bioenergetic substrate for human glioblastoma and brain metastases,“ Cell, vol. 159, no. 7, pp. 1603–1614, 2014.

  108. Dowling C, et al. Preoperative proton MR spectroscopic imaging of brain tumors: correlation with histopathologic analysis of resection specimens. Am J Neuroradiol. 2001;22(4):604–12.

    CAS  PubMed  PubMed Central  Google Scholar 

  109. Salzillo TC et al. “Interrogating Metabolism in Brain Cancer,“ (in eng), Magn Reson Imaging Clin N Am, vol. 24, no. 4, pp. 687–703, Nov 2016.

  110. Lindon J, Holmes E, Nicholson J. Pattern recognition methods and applications in biomedical magnetic resonance. Progress Nucl Magn Reson Spectrosc. 2001;1(39):1–40.

    Article  Google Scholar 

  111. Ganesan R, Mukherjee AG, Gopalakrishnan AV, Prabhakaran V-S. “Solid-State NMR-Based Metabolomics Imprinting Elucidation in Tissue Metabolites, Metabolites Inhibition, and Metabolic Hub in Zebrafish by Chitosan,“ Metabolites, vol. 12, no. 12, p. 1263, 2022.

  112. Larkin JR et al. “Early Diagnosis of Brain Metastases Using a Biofluids-Metabolomics Approach in Mice,“ (in eng), Theranostics, vol. 6, no. 12, pp. 2161–2169, 2016.

  113. Oresković D, Klarica M. “The formation of cerebrospinal fluid: nearly a hundred years of interpretations and misinterpretations,“ (in eng), Brain Res Rev, vol. 64, no. 2, pp. 241 – 62, Sep 24 2010.

  114. Crews B et al. “Variability analysis of human plasma and cerebral spinal fluid reveals statistical significance of changes in mass spectrometry-based metabolomics data,“ (in eng), Anal Chem, vol. 81, no. 20, pp. 8538-44, Oct 15 2009.

  115. Locasale JW et al. “Metabolomics of human cerebrospinal fluid identifies signatures of malignant glioma,“ (in eng), Mol Cell Proteomics, vol. 11, no. 6, p. M111.014688, Jun 2012.

  116. Wang FX, et al. Cerebrospinal fluid-based metabolomics to characterize different types of brain tumors. (in eng) J Neurol. Apr 2020;267(4):984–93.

  117. Ahmed KA, Chinnaiyan P. “Applying metabolomics to understand the aggressive phenotype and identify novel therapeutic targets in glioblastoma,“ (in eng), Metabolites, vol. 4, no. 3, pp. 740 – 50, Aug 27 2014.

  118. Pan X et al. “In vitro metabonomic study detects increases in UDP-GlcNAc and UDP-GalNAc, as early phase markers of cisplatin treatment response in brain tumor cells,“ (in eng), J Proteome Res, vol. 10, no. 8, pp. 3493 – 500, Aug 5 2011.

  119. Rosi A et al. “(1) H NMR spectroscopy of glioblastoma stem-like cells identifies alpha-aminoadipate as a marker of tumor aggressiveness,“ (in eng), NMR Biomed, vol. 28, no. 3, pp. 317 – 26, Mar 2015.

  120. Yan H et al. “IDH1 and IDH2 mutations in gliomas,“ (in eng), N Engl J Med, vol. 360, no. 8, pp. 765 – 73, Feb 19 2009.

  121. Dang L et al. “Cancer-associated IDH1 mutations produce 2-hydroxyglutarate,“ (in eng), Nature, vol. 462, no. 7274, pp. 739 – 44, Dec 10 2009.

  122. Chinnaiyan P et al. “The metabolomic signature of malignant glioma reflects accelerated anabolic metabolism,“ (in eng), Cancer Res, vol. 72, no. 22, pp. 5878–88, Nov 15 2012.

  123. Kalinina J, et al. Detection of “oncometabolite” 2-hydroxyglutarate by magnetic resonance analysis as a biomarker of IDH1/2 mutations in glioma,“ (in eng). J Mol Med (Berl). Oct 2012;90(10):1161–71.

  124. Chaumeil MM, et al. Non-invasive in vivo assessment of IDH1 mutational status in glioma,“ (in eng). Nat Commun. 2013;4:2429.

    Article  PubMed  Google Scholar 

  125. Kallenberg K et al. “Untreated glioblastoma multiforme: increased myo-inositol and glutamine levels in the contralateral cerebral hemisphere at proton MR spectroscopy,“ (in eng), Radiology, vol. 253, no. 3, pp. 805 – 12, Dec 2009.

  126. Pandey R, Caflisch L, Lodi A, Brenner AJ, Tiziani S. Metabolomic signature of brain cancer,“ (in eng). Mol Carcinog. Nov 2017;56(11):2355–71.

  127. Hourani R, et al. Proton magnetic resonance spectroscopic imaging to differentiate between nonneoplastic lesions and brain tumors in children,“ (in eng). J Magn Reson Imaging. Feb 2006;23(2):99–107.

  128. Marcus KJ, et al. Predicting survival of children with CNS tumors using proton magnetic resonance spectroscopic imaging biomarkers,“ (in eng). Int J Oncol. Mar 2007;30(3):651–7.

  129. Wilson M, Davies NP, Brundler MA, McConville C, Grundy RG, Peet AC. “High resolution magic angle spinning 1H NMR of childhood brain and nervous system tumours,“ (in eng), Mol Cancer, vol. 8, p. 6, Feb 10 2009.

  130. Wilson M et al. “Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours,“ (in eng), Eur J Cancer, vol. 49, no. 2, pp. 457 – 64, Jan 2013.

  131. Wilson M, Gill SK, MacPherson L, English M, Arvanitis TN, Peet AC. “Noninvasive detection of glutamate predicts survival in pediatric medulloblastoma,“ (in eng), Clin Cancer Res, vol. 20, no. 17, pp. 4532-9, Sep 1 2014.

  132. Cuellar-Baena S, et al. Comparative metabolic profiling of paediatric ependymoma, medulloblastoma and pilocytic astrocytoma,“ (in eng). Int J Mol Med. Dec 2010;26(6):941–8.

  133. Tzika AA et al. “Proton magnetic spectroscopic imaging of the child’s brain: the response of tumors to treatment,“ (in eng), Neuroradiology, vol. 43, no. 2, pp. 169 – 77, Feb 2001.

  134. Tzika AA et al. “Spectroscopic and perfusion magnetic resonance imaging predictors of progression in pediatric brain tumors,“ (in eng), Cancer, vol. 100, no. 6, pp. 1246-56, Mar 15 2004.

  135. Warren KE, et al. Proton magnetic resonance spectroscopic imaging in children with recurrent primary brain tumors,“ (in eng). J Clin Oncol. Mar 2000;18(5):1020–6.

  136. Laprie A et al. “Longitudinal multivoxel MR spectroscopy study of pediatric diffuse brainstem gliomas treated with radiotherapy,“ (in eng), Int J Radiat Oncol Biol Phys, vol. 62, no. 1, pp. 20–31, May 1 2005.

  137. Astrakas LG et al. “Noninvasive magnetic resonance spectroscopic imaging biomarkers to predict the clinical grade of pediatric brain tumors,“ (in eng), Clin Cancer Res, vol. 10, no. 24, pp. 8220–8, Dec 15 2004.

  138. DeBerardinis RJ et al. “Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis,“ (in eng), Proc Natl Acad Sci U S A, vol. 104, no. 49, pp. 19345-50, Dec 4 2007.

  139. Colquhoun A. Cell biology-metabolic crosstalk in glioma,“ (in eng). Int J Biochem Cell Biol. Aug 2017;89:171–81.

Download references

Acknowledgements

The authors thank the VIT, Vellore, Tamilnadu, India, for supporting this work.

Funding

No funding is available.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, A.V.G., R.J., B.V., R.G., K.R; resources and data curation, A.G.M.; writing— original draft preparation, A.G.M.; writing—review and editing, A.V.G., A.G.M., B.V., R.G., K.R.; visualization, A.V.G., R.J., M.P.; supervision, A.V.G., K.R., A.D., M.P.; project administration, A.V.G., R.G. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Abilash Valsala Gopalakrishnan.

Ethics declarations

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

We assure you this manuscript has not been published in part or whole and is not under consideration for publication elsewhere in any language. All the authors have thoroughly studied the manuscript and approved its consent and submission to the “Medical Oncology” journal.

Conflict of Interest

The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mukherjee, A., Gopalakrishnan, A.V., Jayaraj, R. et al. Recent advances in understanding brain cancer metabolomics: a review. Med Oncol 40, 220 (2023). https://doi.org/10.1007/s12032-023-02109-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12032-023-02109-3

Keywords

Navigation