Skip to main content
Log in

Lipidome signatures of metastasis in a transgenic mouse model of sonic hedgehog medulloblastoma

  • Research Paper
  • Published:
Analytical and Bioanalytical Chemistry Aims and scope Submit manuscript

Abstract

Medulloblastoma (MB), the most common malignant pediatric brain tumor, has high propensity to metastasize. Currently, the standard treatment for MB patients includes radiation therapy administered to the entire brain and spine for the purpose of treating or preventing against metastasis. Due to this aggressive treatment, the majority of long-term survivors will be left with permanent and debilitating neurocognitive impairment, for the 30–40% patients that fail to respond to treatment, all will relapse with terminal metastatic disease. An understanding of the underlying biology that drives MB metastasis is lacking, and is critically needed in order to develop targeted therapeutics for its prevention. To examine the metastatic biology of sonic hedgehog (SHH) MB, the human MB subgroup with the worst clinical outcome in children, we first generated a robust SmoA1-Math-GFP mouse model that reliably reproduces human SHH MB whereby metastases can be visualized under fluorescence microscopy. Lipidome alterations associated with metastasis were then investigated by applying ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) under positive ionization mode to primary tumor samples collected from mice without (n = 18) and with (n = 7) metastasis. Thirty-four discriminant lipids associated with SHH MB metastasis were successfully annotated, including ceramides (Cers), sphingomyelins (SMs), triacylglycerols (TGs), diacylglycerols (DGs), phosphatidylcholines (PCs), and phosphatidic acids (PAs). This study provides deeper insights into dysregulations of lipid metabolism associated with SHH MB metastatic progression, and thus serves as a guide toward novel targeted therapies.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

Data generated in this work are available through the NIH Metabolomics Workbench (http://www.metabolomicsworkbench.org/) with project ID PR000872 (doi: https://doi.org/10.21228/M8ZT30, study ID ST001290).

References

  1. Coluccia D, Figuereido C, Isik S, Smith C, Rutka JT. Medulloblastoma: tumor biology and relevance to treatment and prognosis paradigm. Curr Neurol Neurosci Rep. 2016;16(5):43.

    PubMed  Google Scholar 

  2. Blomstrand M, Brodin NP, Munck AF, Rosenschold P, Vogelius IR, Sanchez Merino G, et al. Estimated clinical benefit of protecting neurogenesis in the developing brain during radiation therapy for pediatric medulloblastoma. Neuro-Oncology. 2012;14(7):882–9.

    PubMed  PubMed Central  Google Scholar 

  3. Crawford JR, MacDonald TJ, Packer RJ. Medulloblastoma in childhood: new biological advances. Lancet Neurol. 2007;6(12):1073–85.

    PubMed  CAS  Google Scholar 

  4. Johnston D, Keene D, Strother D, Taneva M, Lafay-Cousin L, Fryer C, et al. Survival following tumor recurrence in children with medulloblastoma. J Pediatr Hematol Oncol. 2018;40(3):E159–E63.

    PubMed  Google Scholar 

  5. Ostrom Q, Gittleman H, Truitt G, Boscia A, Kruchko C, Barnholtz-Sloan J. CBTRUS Statistical Report: primary brain and other central nervous system tumors diagnosed in the United States in 2011-2015. Neuro-Oncology. 2018;20:1–86.

    Google Scholar 

  6. Fossati P, Ricardi U, Orecchia R. Pediatric medulloblastoma: toxicity of current treatment and potential role of protontherapy. Cancer Treat Rev. 2009;35(1):79–96.

    PubMed  CAS  Google Scholar 

  7. Mulhern RK, Palmer SL, Merchant TE, Wallace D, Kocak M, Brouwers P, et al. Neurocognitive consequences of risk-adapted therapy for childhood medulloblastoma. J Clin Oncol. 2005;23(24):5511–9.

    PubMed  Google Scholar 

  8. Gajjar A, Chintagumpala M, Ashley D, Kellie S, Kun LE, Merchant TE, et al. Risk-adapted craniospinal radiotherapy followed by high-dose chemotherapy and stem-cell rescue in children with newly diagnosed medulloblastoma (St Jude Medulloblastoma-96): long-term results from a prospective, multicentre trial. Lancet Oncol. 2006;7(10):813–20.

    PubMed  Google Scholar 

  9. Sanders RP, Onar A, Boyett JM, Broniscer A, Morris EB, Qaddoumi I, et al. M1 Medulloblastoma: high risk at any age. J Neuro-Oncol. 2008;90(3):351–5.

    Google Scholar 

  10. Oyharcabal-Bourden V, Kalifa C, Gentet JC, Frappaz D, Edan C, Chastagner P, et al. Standard-risk medulloblastoma treated by adjuvant chemotherapy followed by reduced-dose craniospinal radiation therapy: a French Society of Pediatric Oncology Study. J Clin Oncol. 2005;23(21):4726–34.

    PubMed  CAS  Google Scholar 

  11. Northcott P, Dubuc A, Pfister S, Taylor M. Molecular subgroups of medulloblastoma. Expert Rev Neurother. 2012;12(7):871–84.

    PubMed  PubMed Central  CAS  Google Scholar 

  12. Taylor MD, Northcott PA, Korshunov A, Remke M, Cho YJ, Clifford SC, et al. Molecular subgroups of medulloblastoma: the current consensus. Acta Neuropathol. 2012;123(4):465–72.

    PubMed  CAS  Google Scholar 

  13. Northcott PA, Hielscher T, Dubuc A, Mack S, Shih D, Remke M, et al. Pediatric and adult sonic hedgehog medulloblastomas are clinically and molecularly distinct. Acta Neuropathol. 2011;122(2):231–40.

    PubMed  PubMed Central  Google Scholar 

  14. Gibson P, Tong Y, Robinson G, Thompson M, Currle D, Eden C, et al. Subtypes of medulloblastoma have distinct developmental origins. Nature. 2010;468(7327):1095–9.

    PubMed  PubMed Central  CAS  Google Scholar 

  15. Ramaswamy V, Remke M, Bouffet E, Bailey S, Clifford S, Doz F, et al. Risk stratification of childhood medulloblastoma in the molecular era: the current consensus. Acta Neuropathol. 2016;131(6):821–31.

    PubMed  PubMed Central  CAS  Google Scholar 

  16. Hallahan AR, Pritchard JI, Hansen S, Benson M, Stoeck J, Hatton BA, et al. The SmoA1 mouse model reveals that notch signaling is critical for the growth and survival of sonic hedgehog-induced medulloblastomas. Cancer Res. 2004;64(21):7794–800.

    PubMed  CAS  Google Scholar 

  17. Hatton BA, Villavicencio EH, Tsuchiya KD, Pritchard JI, Ditzler S, Pullar B, et al. The Smo/Smo model: hedgehog-induced medulloblastoma with 90% incidence and leptomeningeal spread. Cancer Res. 2008;68(6):1768–76.

    PubMed  CAS  Google Scholar 

  18. Lumpkin EA, Collisson T, Parab P, Omer-Abdalla A, Haeberle H, Chen P, et al. Math1-driven GFP expression in the developing nervous system of transgenic mice. Gene Expr Patterns. 2003;3(4):389–95.

    PubMed  CAS  Google Scholar 

  19. MacDonald TJ, Brown KM, LaFleur B, Peterson K, Lawlor C, Chen Y, et al. Expression profiling of medulloblastoma: PDGFRA and the RAS/MAPK pathway as therapeutic targets for metastatic disease. Nat Genet. 2001;29(2):143–52.

    PubMed  CAS  Google Scholar 

  20. Zhao X, Ponomaryov T, Ornell K, Zhou P, Dabral S, Pak E, et al. RAS/MAPK activation drives resistance to Smo inhibition, metastasis, and tumor evolution in Shh pathway-dependent tumors. Cancer Res. 2015;75(17):3623–35.

    PubMed  PubMed Central  CAS  Google Scholar 

  21. Jenkins N, Kalra R, Dubuc A, Sivakumar W, Pedone C, Wu X, et al. Genetic drivers of metastatic dissemination in sonic hedgehog medulloblastoma. Acta Neuropathol Commun. 2014;2:85.

    PubMed  PubMed Central  Google Scholar 

  22. Zhan M, Sun X, Liu J, Li Y, He X, Zhou Z, et al. Usp7 promotes medulloblastoma cell survival and metastasis by activating Shh pathway. Biochem Biophys Res Commun. 2017;484(2):429–34.

    PubMed  CAS  Google Scholar 

  23. Grausam K, Dooyema S, Bihannic L, Premathilake H, Morrissy A, Forget A, et al. ATOH1 promotes leptomeningeal dissemination and metastasis of sonic hedgehog subgroup medulloblastomas. Cancer Res. 2017;77(14):3766–77.

    PubMed  PubMed Central  CAS  Google Scholar 

  24. Cairns R, Harris I, Mak T. Regulation of cancer cell metabolism. Nat Rev Cancer. 2011;11(2):85–95.

    PubMed  CAS  Google Scholar 

  25. Spratlin JL, Serkova NJ, Eckhardt SG. Clinical applications of metabolomics in oncology: a review. Clin Cancer Res. 2009;15(2):431–40.

    PubMed  PubMed Central  CAS  Google Scholar 

  26. Griffin JL, Shockcor JP. Metabolic profiles of cancer cells. Nat Rev Cancer. 2004;4(7):551–61.

    PubMed  CAS  Google Scholar 

  27. Paine M, Liu J, Huang D, Ellis S, Trede D, Kobarg J, et al. Three-dimensional mass spectrometry imaging identifies lipid markers of medulloblastoma metastasis. Sci Rep. 2019;9(1):2205.

    PubMed  PubMed Central  Google Scholar 

  28. Adibhatla R, Hatcher J, Dempsey R. Lipids and lipidomics in brain injury and diseases. AAPS J. 2006;8(2):E314–E21.

    PubMed  PubMed Central  Google Scholar 

  29. Theodoridis GA, Gika HG, Want EJ, Wilson ID. Liquid chromatography-mass spectrometry based global metabolite profiling: a review. Anal Chim Acta. 2012;711:7–16.

    PubMed  CAS  Google Scholar 

  30. Wilson ID, Nicholson JK, Castro-Perez J, Granger JH, Johnson KA, Smith BW, et al. High resolution “ultra performance” liquid chromatography coupled to oa-TOF mass spectrometry as a tool for differential metabolic pathway profiling in functional genomic studies. J Proteome Res. 2005;4(2):591–8.

    PubMed  CAS  Google Scholar 

  31. Huang D, Gaul D, Nan H, Kim J, Fernandez F. Deep metabolomics of a high-grade serous ovarian cancer triple-knockout mouse model. J Proteome Res. 2019;18(8):3184–94.

    PubMed  PubMed Central  CAS  Google Scholar 

  32. Rao Y, Lee Y, Jarjoura D, Ruppert A, Liu C, Hsu J, et al. A comparison of normalization techniques for microRNA microarray data. Stat Appl Genet Mol Biol. 2008;7(1):22.

    Google Scholar 

  33. Quackenbush J. Microarray data normalization and transformation. Nat Genet. 2002;32:496–501.

    PubMed  CAS  Google Scholar 

  34. Mehmood T, Liland K, Snipen L, Saebo S. A review of variable selection methods in partial least squares regression. Chemom Intell Lab Syst. 2012;118:62–9.

    CAS  Google Scholar 

  35. Worley B, Powers R. Multivariate analysis in metabolomics. Curr Metabolomics. 2013;1(1):92–107.

    PubMed  PubMed Central  CAS  Google Scholar 

  36. Wishart D, Feunang Y, Marcu A, Guo A, Liang K, Vazquez-Fresno R, et al. HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018;46(D1):D608–D17.

    PubMed  CAS  Google Scholar 

  37. Fahy E, Sud M, Cotter D, Subramaniam S. LIPID MAPS online tools for lipid research. Nucleic Acids Res. 2007;35:W606–W12.

    PubMed  PubMed Central  Google Scholar 

  38. Guijas C, Montenegro-Burke J, Domingo-Almenara X, Palermo A, Warth B, Hermann G, et al. METLIN: a technology platform for identifying knowns and unknowns. Anal Chem. 2018;90(5):3156–64.

    PubMed  PubMed Central  CAS  Google Scholar 

  39. Coleman R, Lee D. Enzymes of triacylglycerol synthesis and their regulation. Prog Lipid Res. 2004;43(2):134–76.

    PubMed  CAS  Google Scholar 

  40. Zhang P, Reue K. Lipin proteins and glycerolipid metabolism: roles at the ER membrane and beyond. Biochim Biophys Acta Biomembr. 2017;1859(9):1583–95.

    PubMed  CAS  Google Scholar 

  41. Gimeno R, Cao J. Thematic review series: glycerolipids - mammalian glycerol-3-phosphate acyltransferases: new genes for an old activity. J Lipid Res. 2008;49(10):2079–88.

    PubMed  CAS  Google Scholar 

  42. Gonzalez-Baro M, Lewin T, Coleman R. Regulation of triglyceride metabolism II. Function of mitochondrial GPAT1 in the regulation of triacylglycerol biosynthesis and insulin action. Am J Physiol Gastrointest Liver Physiol. 2007;292(5):G1195–G9.

    PubMed  CAS  Google Scholar 

  43. Takeuchi K, Reue K. Biochemistry, physiology, and genetics of GPAT, AGPAT, and lipin enzymes in triglyceride synthesis. Am J Physiol Endocrinol Metab. 2009;296(6):E1195–E209.

    PubMed  PubMed Central  CAS  Google Scholar 

  44. Reue K, Brindley D. Multiple roles for lipins/phosphatidate phosphatase enzymes in lipid metabolism. J Lipid Res. 2008;49(12):2493–503.

    PubMed  PubMed Central  CAS  Google Scholar 

  45. Yen C, Stone S, Koliwad S, Harris C, Farese R. DGAT enzymes and triacylglycerol biosynthesis. J Lipid Res. 2008;49(11):2283–301.

    PubMed  PubMed Central  CAS  Google Scholar 

  46. Iqbal J, Hussain M. Intestinal lipid absorption. Am J Physiol Endocrinol Metab. 2009;296(6):E1183–E94.

    PubMed  PubMed Central  CAS  Google Scholar 

  47. Yen C, Nelson D, Yen M. Thematic review series: intestinal lipid metabolism: new developments and current insights intestinal triacylglycerol synthesis in fat absorption and systemic energy metabolism. J Lipid Res. 2015;56(3):489–501.

    PubMed  PubMed Central  CAS  Google Scholar 

  48. Santos C, Schulze A. Lipid metabolism in cancer. FEBS J. 2012;279(15):2610–23.

    PubMed  CAS  Google Scholar 

  49. Zou Y, Watters A, Cheng N, Perry C, Xu K, Alicea G, et al. Polyunsaturated fatty acids from astrocytes activate PPAR gamma signaling in cancer cells to promote brain metastasis. Cancer Discov. 2019;9(12):1720–35.

    PubMed  PubMed Central  CAS  Google Scholar 

  50. GonÄi FM, Alonso A. Structure and functional properties of diacylglycerols in membranes. Prog Lipid Res. 1999;38(1):1–48.

    Google Scholar 

  51. Martin D, Robbins M, Spector A, Wen B, Hussey D. The fatty acid composition of human gliomas differs from that found in nonmalignant brain tissue. Lipids. 1996;31(12):1283–8.

    PubMed  CAS  Google Scholar 

  52. Hammond L, Gallagher P, Wang S, Hiller S, Kluckman K, Posey-Marcos E, et al. Mitochondrial glycerol-3-phosphate acyltransferase-deficient mice have reduced weight and liver triacylglycerol content and altered glycerolipid fatty acid composition. Mol Cell Biol. 2002;22(23):8204–14.

    PubMed  PubMed Central  CAS  Google Scholar 

  53. Wenk M. The emerging field of lipidomics. Nat Rev Drug Discov. 2005;4(7):594–610.

    PubMed  CAS  Google Scholar 

  54. Bandu R, Mok HJ, Kim KP. Phospholipids as cancer biomarkers: mass spectrometry-based analysis. Mass Spectrom Rev. 2018;37(2):107–38.

    PubMed  CAS  Google Scholar 

  55. Podo F. Tumour phospholipid metabolism. NMR Biomed. 1999;12(7):413–39.

    PubMed  CAS  Google Scholar 

  56. Glunde K, Serkova N. Therapeutic targets and biomarkers identified in cancer choline phospholipid metabolism. Pharmacogenomics. 2006;7(7):1109–23.

    PubMed  CAS  Google Scholar 

  57. Bishop W, Bell R. Assembly of phospholipids into cellular membranes - biosynthesis, transmembrane movement and intracellular translocation. Annu Rev Cell Biol. 1988;4:579–610.

    PubMed  CAS  Google Scholar 

  58. Ackerstaff E, Glunde K, Bhujwalla ZM. Choline phospholipid metabolism: a target in cancer cells? J Cell Biochem. 2003;90(3):525–33.

    PubMed  CAS  Google Scholar 

  59. Peet AC, Davies NP, Ridley L, Brundler MA, Kombogiorgas D, Lateef S, et al. Magnetic resonance spectroscopy suggests key differences in the metastatic behaviour of medulloblastoma. Eur J Cancer. 2007;43(6):1037–44.

    PubMed  Google Scholar 

  60. Herminghaus S, Pilatus U, Moller-Hartmann W, Raab P, Lanfermann H, Schlote W, et al. Increased choline levels coincide with enhanced proliferative activity of human neuroepithelial brain tumors. NMR Biomed. 2002;15(6):385–92.

    PubMed  CAS  Google Scholar 

  61. Astrakas LG, Zurakowski D, Tzika A, Zarifi MK, Anthony DC, Girolami UD, et al. Noninvasive magnetic resonance spectroscopic imaging biomarkers to predict the clinical grade of pediatric brain tumors. Clin Cancer Res. 2004;10(24):8220–8.

    PubMed  CAS  Google Scholar 

  62. Pascual F, Carman G. Phosphatidate phosphatase, a key regulator of lipid homeostasis. Biochim Biophys Acta. 2013;1831(3):514–22.

    PubMed  CAS  Google Scholar 

  63. Shaughnessy R, Retamal C, Oyanadel C, Norambuena A, Lopez A, Bravo-Zehnder M, et al. Epidermal growth factor receptor endocytic traffic perturbation by phosphatidate phosphohydrolase inhibition: new strategy against cancer. FEBS J. 2014;281(9):2172–89.

    PubMed  CAS  Google Scholar 

  64. Ohanian J, Ohanian V. Sphingolipids in mammalian cell signalling. Cell Mol Life Sci. 2001;58(14):2053–68.

    PubMed  CAS  Google Scholar 

  65. Ogretmen B, Hannun Y. Biologically active sphingolipids in cancer pathogenesis and treatment. Nat Rev Cancer. 2004;4(8):604–16.

    PubMed  CAS  Google Scholar 

  66. Chen J, Zhang X, Cao R, Lu X, Zhao S, Fekete A, et al. Serum 27-nor-5beta-cholestane-3,7,12,24,25 pentol glucuronide discovered by metabolomics as potential diagnostic biomarker for epithelium ovarian cancer. J Proteome Res. 2011;10(5):2625–32.

    PubMed  CAS  Google Scholar 

  67. Li F, Zhang N. Ceramide: therapeutic potential in combination therapy for cancer treatment. Curr Drug Metab. 2016;17(1):37–51.

    CAS  Google Scholar 

  68. Senkal C, Ponnusamy S, Bielawski J, Hannun Y, Ogretmen B. Antiapoptotic roles of ceramide-synthase-6-generated C-16-ceramide via selective regulation of the ATF6/CHOP arm of ER-stress-response pathways. FASEB J. 2010;24(1):296–308.

    PubMed  PubMed Central  Google Scholar 

  69. Grosch S, Schiffmann S, Geisslinger G. Chain length-specific properties of ceramides. Prog Lipid Res. 2012;51(1):50–62.

    PubMed  Google Scholar 

  70. Schiffmann S, Sandner J, Birod K, Wobst I, Angioni C, Ruckhäberle E, et al. Ceramide synthases and ceramide levels are increased in breast cancer tissue. Carcinogenesis. 2009;30(5):745–52.

    PubMed  CAS  Google Scholar 

  71. Tech K, Gershon TR. Energy metabolism in neurodevelopment and medulloblastoma. Transl Pediatr. 2015;4(1):12–9.

    PubMed  PubMed Central  Google Scholar 

  72. Anderson D. Role of lipids in the MAPK signaling pathway. Prog Lipid Res. 2006;45(2):102–19.

    PubMed  CAS  Google Scholar 

Download references

Acknowledgments

The authors acknowledge the American Society for Mass Spectrometry for a post-doctoral Research Award to MRLP that made this collaboration possible. Math1-GFP reporter mice were kindly provided by Dr. Tracy-Ann Read (Emory Winship Cancer Institute). The authors thank support from the Emory/Georgia Tech Children’s Healthcare of Atlanta Center for Pediatric Nanomedicine.

Funding

FMF received financial support from endowed Vasser-Wooley funds. RCE received funding support from Georgia CTSA (UL1TR002378) and (KL2TR002381).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Tobey J. MacDonald or Facundo M. Fernández.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This research involved animals and was performed under protocols approved by Emory University, and was in compliance with state and federal Animal Welfare Acts.

Consent for publication

All authors give the consent for the article to be published in Analytical and Bioanalytical Chemistry.

Additional information

Publisher’s note

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

Electronic supplementary material

ESM 1

(PDF 618 kb).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, D., Liu, J., Eldridge, R.C. et al. Lipidome signatures of metastasis in a transgenic mouse model of sonic hedgehog medulloblastoma. Anal Bioanal Chem 412, 7017–7027 (2020). https://doi.org/10.1007/s00216-020-02837-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-020-02837-9

Keywords

Navigation