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Assessment of Metabolic Signature for Cancer Diagnosis Using Desorption Electrospray Ionization Mass Spectrometric Imaging

  • Shibdas BanerjeeEmail author
  • Soumen Kanti Manna
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1928)

Abstract

Metabolic reprogramming is a hallmark of tumor development. A technique that can map this complex biochemical shift by taking a snapshot of various metabolites in a tissue specimen (biopsy) is of high utility in the context of cancer diagnosis. Desorption electrospray ionization mass spectrometric imaging (DESI-MSI) is such a powerful and emerging analytical technique to simultaneously visualize the distributions of hundreds of metabolites, lipids, and other small molecules in the biological tissue. In DESI-MSI, a fine spray of high-velocity charged microdroplets rapidly extracts molecular species from the tissue surface and subsequently transfers them to the mass spectrometer, while the sample is continuously moved in two dimensions under the impinging spray of microdroplets. This allows a detailed multiplex molecular mapping of the tissue. DESI-MSI enables simultaneous examination of hundreds of putative metabolic biomarkers, an approach that lends much more predictive power than simply evaluating one or a few candidate biomarkers. The speed, versatility, lack of complicated sample preparation, and operation at ambient conditions make DESI-MSI extremely promising as a rapid diagnostic and prognostic tool.

Key words

DESI-MSI Tissue imaging Cancer margin Metabolites and lipids Histopathology 

Notes

Acknowledgments

Authors are thankful to Prof. Richard N. Zare for his encouragement and advice. S.B. gratefully acknowledges the help from Dr. Livia S. Eberlin, Prof. Robert J. Tibshirani, Prof. James D. Brooks, Dr. Christian A. Kunder, Dr. Rosalie Nolley, Dr. Richard Fan, and Dr. Geoffrey A. Sonn. This work was supported by the Indian Institute of Science Education and Research, Tirupati, and Saha Institute of Nuclear Physics, Kolkata. S.B. is also thankful to Science and Engineering Research Board, Department of Science and Technology, Government of India, for providing Ramanujan Fellowship Research Grant (SB/S2/RJN-130/2017).

References

  1. 1.
    Zhang J, Rector J, Lin JQ, Young JH, Sans M, Katta N, Giese N, Yu W, Nagi C, Suliburk J, Liu J, Bensussan A, DeHoog RJ, Garza KY, Ludolph B, Sorace AG, Syed A, Zahedivash A, Milner TE, Eberlin LS (2017) Nondestructive tissue analysis for ex vivo and in vivo cancer diagnosis using a handheld mass spectrometry system. Sci Transl Med 9(406):eaan3968PubMedPubMedCentralCrossRefGoogle Scholar
  2. 2.
    Balog J, Sasi-Szabó L, Kinross J, Lewis MR, Muirhead LJ, Veselkov K, Mirnezami R, Dezső B, Damjanovich L, Darzi A, Nicholson JK, Takáts Z (2013) Intraoperative tissue identification using rapid evaporative ionization mass spectrometry. Sci Transl Med 5(194):194ra193–194ra193CrossRefGoogle Scholar
  3. 3.
    Pirro V, Alfaro CM, Jarmusch AK, Hattab EM, Cohen-Gadol AA, Cooks RG (2017) Intraoperative assessment of tumor margins during glioma resection by desorption electrospray ionization-mass spectrometry. Proc Natl Acad Sci U S A 114(26):6700–6705PubMedPubMedCentralGoogle Scholar
  4. 4.
    Hao J-J, Lin D-C, Dinh HQ, Mayakonda A, Jiang Y-Y, Chang C, Jiang Y, Lu C-C, Shi Z-Z, Xu X, Zhang Y, Cai Y, Wang J-W, Zhan Q-M, Wei W-Q, Berman BP, Wang M-R, Koeffler HP (2016) Spatial intratumoral heterogeneity and temporal clonal evolution in esophageal squamous cell carcinoma. Nat Genet 48:1500PubMedPubMedCentralCrossRefGoogle Scholar
  5. 5.
    Axelson H, Fredlund E, Ovenberger M, Landberg G, Påhlman S (2005) Hypoxia-induced dedifferentiation of tumor cells—a mechanism behind heterogeneity and aggressiveness of solid tumors. Semin Cell Dev Biol 16(4):554–563PubMedCrossRefGoogle Scholar
  6. 6.
    Mazor T, Pankov A, Song JS, Costello JF (2016) Intratumoral heterogeneity of the epigenome. Cancer Cell 29(4):440–451PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Levine AJ, Puzio-Kuter AM (2010) The control of the metabolic switch in cancers by oncogenes and tumor suppressor genes. Science 330(6009):1340–1344PubMedCrossRefGoogle Scholar
  8. 8.
    Vander Heiden MG, Cantley LC, Thompson CB (2009) Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324(5930):1029–1033PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Iurlaro R, León-Annicchiarico CL, Muñoz-Pinedo C (2014) Chapter three - regulation of cancer metabolism by oncogenes and tumor suppressors. In: Galluzzi L, Kroemer G (eds) Methods in enzymology, vol 542. Academic Press, New York, pp 59–80.  https://doi.org/10.1016/B978-0-12-416618-9.00003-0CrossRefGoogle Scholar
  10. 10.
    Vermeersch KA, Styczynski MP (2013) Applications of metabolomics in cancer research. J Carcinog 12:9PubMedPubMedCentralCrossRefGoogle Scholar
  11. 11.
    DeBerardinis RJ, Chandel NS (2016) Fundamentals of cancer metabolism. Sci Adv 2(5):e1600200PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Baenke F, Peck B, Miess H, Schulze A (2013) Hooked on fat: the role of lipid synthesis in cancer metabolism and tumour development. Dis Model Mech 6(6):1353–1363PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    van Meer G, Voelker DR, Feigenson GW (2008) Membrane lipids: where they are and how they behave. Nat Rev Mol Cell Biol 9(2):112–124PubMedPubMedCentralCrossRefGoogle Scholar
  14. 14.
    Andronesi OC, Rapalino O, Gerstner E, Chi A, Batchelor TT, Cahill DP, Sorensen AG, Rosen BR (2013) Detection of oncogenic IDH1 mutations using magnetic resonance spectroscopy of 2-hydroxyglutarate. J Clin Invest 123(9):3659–3663PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Leather T, Jenkinson MD, Das K, Poptani H (2017) Magnetic resonance spectroscopy for detection of 2-hydroxyglutarate as a biomarker for IDH mutation in gliomas. Metabolism 7(2):29CrossRefGoogle Scholar
  16. 16.
    Kurhanewicz J, Vigneron DB (2008) Advances in MR spectroscopy of the prostate. Magn Reson Imaging Clin N Am 16(4):697–69xPubMedPubMedCentralCrossRefGoogle Scholar
  17. 17.
    Spratlin JL, Serkova NJ, Gail Eckhardt S (2009) Clinical applications of metabolomics in oncology: a review. Clin Cancer Res 15(2):431–440PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Armitage EG, Southam AD (2016) Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics. Metabolomics 12(9):146PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Ifa DR, Eberlin LS (2016) Ambient ionization mass spectrometry for cancer diagnosis and surgical margin evaluation. Clin Chem 62(1):111–123PubMedCrossRefGoogle Scholar
  20. 20.
    Takáts Z, Wiseman JM, Gologan B, Cooks RG (2004) Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science 306(5695):471–473PubMedCrossRefGoogle Scholar
  21. 21.
    Wiseman JM, Ifa DR, Song Q, Cooks RG (2006) Tissue imaging at atmospheric pressure using desorption electrospray ionization (DESI) mass spectrometry. Angew Chem Int Ed 45(43):7188–7192CrossRefGoogle Scholar
  22. 22.
    Eberlin LS, Norton I, Orringer D, Dunn IF, Liu X, Ide JL, Jarmusch AK, Ligon KL, Jolesz FA, Golby AJ, Santagata S, Agar NYR, Cooks RG (2013) Ambient mass spectrometry for the intraoperative molecular diagnosis of human brain tumors. Proc Natl Acad Sci U S A 110(5):1611–1616PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Eberlin LS, Tibshirani RJ, Zhang J, Longacre TA, Berry GJ, Bingham DB, Norton JA, Zare RN, Poultsides GA (2014) Molecular assessment of surgical-resection margins of gastric cancer by mass-spectrometric imaging. Proc Natl Acad Sci U S A 111(7):2436–2441PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Eberlin LS, Gabay M, Fan AC, Gouw AM, Tibshirani RJ, Felsher DW, Zare RN (2014) Alteration of the lipid profile in lymphomas induced by MYC overexpression. Proc Natl Acad Sci U S A 111(29):10450–10455PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Eberlin LS (2014) DESI-MS imaging of lipids and metabolites from biological samples. In: Raftery D (ed) Mass spectrometry in metabolomics: methods and protocols. Springer New York, New York, NY, pp 299–311.  https://doi.org/10.1007/978-1-4939-1258-2_20CrossRefGoogle Scholar
  26. 26.
    Banerjee S, Mazumdar S (2012) Electrospray ionization mass spectrometry: a technique to access the information beyond the molecular weight of the analyte. Int J Analyt Chem 2012:282574Google Scholar
  27. 27.
    Fenn J, Mann M, Meng C, Wong S, Whitehouse C (1989) Electrospray ionization for mass spectrometry of large biomolecules. Science 246(4926):64–71PubMedCrossRefGoogle Scholar
  28. 28.
    Kebarle P, Verkerk UH (2010) On the mechanism of electrospray ionization mass spectrometry (ESIMS). In: Electrospray and MALDI mass spectrometry. John Wiley & Sons, Inc., New York, pp 1–48.  https://doi.org/10.1002/9780470588901.ch1CrossRefGoogle Scholar
  29. 29.
    Perry RH, Bellovin DI, Shroff EH, Ismail AI, Zabuawala T, Felsher DW, Zare RN (2013) Characterization of MYC-induced tumorigenesis by in situ lipid profiling. Anal Chem 85(9):4259–4262PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Eberlin LS, Margulis K, Planell-Mendez I, Zare RN, Tibshirani R, Longacre TA, Jalali M, Norton JA, Poultsides GA (2016) Pancreatic cancer surgical resection margins: molecular assessment by mass spectrometry imaging. PLoS Med 13(8):e1002108PubMedPubMedCentralCrossRefGoogle Scholar
  31. 31.
    Gouw AM, Eberlin LS, Margulis K, Sullivan DK, Toal GG, Tong L, Zare RN, Felsher DW (2017) Oncogene KRAS activates fatty acid synthase, resulting in specific ERK and lipid signatures associated with lung adenocarcinoma. Proc Natl Acad Sci U S A 114(17):4300–4305PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Banerjee S, Zare RN, Tibshirani RJ, Kunder CA, Nolley R, Fan R, Brooks JD, Sonn GA (2017) Diagnosis of prostate cancer by desorption electrospray ionization mass spectrometric imaging of small metabolites and lipids. Proc Natl Acad Sci U S A 114(13):3334–3339PubMedPubMedCentralCrossRefGoogle Scholar
  33. 33.
    Eberlin LS, Norton I, Dill AL, Golby AJ, Ligon KL, Santagata S, Cooks RG, Agar NYR (2012) Classifying human brain tumors by lipid imaging with mass spectrometry. Cancer Res 72(3):645–654PubMedCrossRefGoogle Scholar
  34. 34.
    Eberlin LS, Ferreira CR, Dill AL, Ifa DR, Cooks RG (2011) Desorption electrospray ionization mass spectrometry for lipid characterization and biological tissue imaging. Biochim Biophys Acta 1811(11):946–960PubMedPubMedCentralCrossRefGoogle Scholar
  35. 35.
    Zhang J, Feider CL, Nagi C, Yu W, Carter SA, Suliburk J, Cao HST, Eberlin LS (2017) Detection of metastatic breast and thyroid cancer in lymph nodes by desorption electrospray ionization mass spectrometry imaging. J Am Soc Mass Spectrom 28(6):1166–1174PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Dória ML, McKenzie JS, Mroz A, Phelps DL, Speller A, Rosini F, Strittmatter N, Golf O, Veselkov K, Brown R, Ghaem-Maghami S, Takats Z (2016) Epithelial ovarian carcinoma diagnosis by desorption electrospray ionization mass spectrometry imaging. Sci Rep 6:39219PubMedPubMedCentralCrossRefGoogle Scholar
  37. 37.
    Abbassi-Ghadi N, Golf O, Kumar S, Antonowicz S, McKenzie JS, Huang J, Strittmatter N, Kudo H, Jones EA, Veselkov K, Goldin R, Takats Z, Hanna GB (2016) Imaging of esophageal lymph node metastases by desorption electrospray ionization mass spectrometry. Cancer Res 76(19):5647–5656PubMedCrossRefGoogle Scholar
  38. 38.
    Alfaro CM, Jarmusch AK, Pirro V, Kerian KS, Masterson TA, Cheng L, Cooks RG (2016) Ambient ionization mass spectrometric analysis of human surgical specimens to distinguish renal cell carcinoma from healthy renal tissue. Anal Bioanal Chem 408(20):5407–5414PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Calligaris D, Feldman DR, Norton I, Brastianos PK, Dunn IF, Santagata S, Agar NYR (2015) Molecular typing of Meningiomas by desorption electrospray ionization mass spectrometry imaging for surgical decision-making. Int J Mass Spectrom 377:690–698PubMedPubMedCentralCrossRefGoogle Scholar
  40. 40.
    Guenther S, Muirhead LJ, Speller AVM, Golf O, Strittmatter N, Ramakrishnan R, Goldin RD, Jones E, Veselkov K, Nicholson J, Darzi A, Takats Z (2015) Spatially resolved metabolic phenotyping of breast cancer by desorption electrospray ionization mass spectrometry. Cancer Res 75(9):1828–1837PubMedCrossRefGoogle Scholar
  41. 41.
    Calligaris D, Caragacianu D, Liu X, Norton I, Thompson CJ, Richardson AL, Golshan M, Easterling ML, Santagata S, Dillon DA, Jolesz FA, Agar NYR (2014) Application of desorption electrospray ionization mass spectrometry imaging in breast cancer margin analysis. Proc Natl Acad Sci U S A 111(42):15184–15189PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Abbassi-Ghadi N, Veselkov K, Kumar S, Huang J, Jones E, Strittmatter N, Kudo H, Goldin R, Takats Z, Hanna GB (2014) Discrimination of lymph node metastases using desorption electrospray ionisation-mass spectrometry imaging. Chem Commun 50(28):3661–3664CrossRefGoogle Scholar
  43. 43.
    Calligaris D, Norton I, Feldman DR, Ide JL, Dunn IF, Eberlin LS, Cooks RG, Jolesz FA, Golby AJ, Santagata S, Agar NY (2013) Mass spectrometry imaging as a tool for surgical decision-making. J Mass Spectrom 48(11):1178–1187PubMedPubMedCentralCrossRefGoogle Scholar
  44. 44.
    Ifa DR, Wiseman JM, Song Q, Cooks RG (2007) Development of capabilities for imaging mass spectrometry under ambient conditions with desorption electrospray ionization (DESI). Int J Mass Spectrom 259(1):8–15CrossRefGoogle Scholar
  45. 45.
    Manicke NE, Kistler T, Ifa DR, Cooks RG, Ouyang Z (2009) High-throughput quantitative analysis by desorption electrospray ionization mass spectrometry. J Am Soc Mass Spectrom 20(2):321–325PubMedCrossRefGoogle Scholar
  46. 46.
    Kiernan J (2015) Histological and Histochemical methods: theory and practice. Scion Publishing Limited, BanburyGoogle Scholar
  47. 47.
    Xiong X, Xu W, Eberlin LS, Wiseman JM, Fang X, Jiang Y, Huang Z, Zhang Y, Cooks RG, Ouyang Z (2012) Data processing for 3D mass spectrometry imaging. J Am Soc Mass Spectrom 23(6):1147–1156PubMedCrossRefGoogle Scholar
  48. 48.
    Kishton RJ, Rathmell JC (2015) Novel therapeutic targets of tumor metabolism. Cancer J 21(2):62–69PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    Eberlin LS, Ferreira CR, Dill AL, Ifa DR, Cheng L, Cooks RG (2011) Non-destructive, histologically compatible tissue imaging by desorption electrospray ionization mass spectrometry. Chembiochem 12(14):2129–2132PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Hsu C-C, Chou P-T, Zare RN (2015) Imaging of proteins in tissue samples using nanospray desorption electrospray ionization mass spectrometry. Anal Chem 87(22):11171–11175PubMedCrossRefGoogle Scholar
  51. 51.
    Dakubo GD (2010) The Warburg phenomenon and other metabolic alterations of cancer cells. In: Mitochondrial genetics and cancer. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 39–66. https://doi.org/10.1007/978-3-642-11416-8_2CrossRefGoogle Scholar
  52. 52.
    Chambers MC, Maclean B, Burke R, Amodei D, Ruderman DL, Neumann S, Gatto L, Fischer B, Pratt B, Egertson J, Hoff K, Kessner D, Tasman N, Shulman N, Frewen B, Baker TA, Brusniak M-Y, Paulse C, Creasy D, Flashner L, Kani K, Moulding C, Seymour SL, Nuwaysir LM, Lefebvre B, Kuhlmann F, Roark J, Rainer P, Detlev S, Hemenway T, Huhmer A, Langridge J, Connolly B, Chadick T, Holly K, Eckels J, Deutsch EW, Moritz RL, Katz JE, Agus DB, MacCoss M, Tabb DL, Mallick P (2012) A cross-platform toolkit for mass spectrometry and proteomics. Nat Biotechnol 30:918PubMedPubMedCentralCrossRefGoogle Scholar
  53. 53.
    Race AM, Styles IB, Bunch J (2012) Inclusive sharing of mass spectrometry imaging data requires a converter for all. J Proteomics 75(16):5111–5112PubMedCrossRefGoogle Scholar
  54. 54.
    Robichaud G, Garrard KP, Barry JA, Muddiman DC (2013) MSiReader: an open-source interface to view and analyze high resolving power MS imaging files on Matlab platform. J Am Soc Mass Spectrom 24(5):718–721PubMedPubMedCentralCrossRefGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Indian Institute of Science Education and Research TirupatiTirupatiIndia
  2. 2.Biophysics and Structural Genomics DivisionSaha Institute of Nuclear Physics (HBNI)KolkataIndia

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