Analytical and Bioanalytical Chemistry

, Volume 398, Issue 7–8, pp 2969–2978 | Cite as

Multivariate statistical differentiation of renal cell carcinomas based on lipidomic analysis by ambient ionization imaging mass spectrometry

  • Allison L. Dill
  • Livia S. Eberlin
  • Cheng Zheng
  • Anthony B. Costa
  • Demian R. Ifa
  • Liang Cheng
  • Timothy A. Masterson
  • Michael O. Koch
  • Olga Vitek
  • R. Graham CooksEmail author
Original Paper


Desorption electrospray ionization (DESI) mass spectrometry (MS) was used in an imaging mode to interrogate the lipid profiles of thin tissue sections of 11 sample pairs of human papillary renal cell carcinoma (RCC) and adjacent normal tissue and nine sample pairs of clear cell RCC and adjacent normal tissue. DESI-MS images showing the spatial distributions of particular glycerophospholipids (GPs) and free fatty acids in the negative ion mode were compared to serial tissue sections stained with hematoxylin and eosin (H&E). Increased absolute intensities as well as changes in relative abundance were seen for particular compounds in the tumor regions of the samples. Multivariate statistical analysis using orthogonal projection to latent structures treated partial least square discriminate analysis (PLS-DA) was used for visualization and classification of the tissue pairs using the full mass spectra as predictors. PLS-DA successfully distinguished tumor from normal tissue for both papillary and clear cell RCC with misclassification rates obtained from the validation set of 14.3% and 7.8%, respectively. It was also used to distinguish papillary and clear cell RCC from each other and from the combined normal tissues with a reasonable misclassification rate of 23%, as determined from the validation set. Overall DESI-MS imaging combined with multivariate statistical analysis shows promise as a molecular pathology technique for diagnosing cancerous and normal tissue on the basis of GP profiles.


Molecular disease diagnostics by DESI without sample preparation. a Good information is obtained by mapping the distribution of individual compounds in the tissue (e.g., PI(18:0/20:4). b Even better discrimination between tumor and healthy tissue is achieved using PLS-DA to consider all the data after having established through a training set of samples the features that correlate with disease as recognized by standard H&E stain pathological examination


Ambient ionization Kidney cancer Lipidomics Mass spectrometry Molecular imaging Phospholipids Tissue analysis 



We thank the Purdue University Center for Cancer Research and its director, Timothy Ratliff, for assistance in obtaining the human kidney cancer samples. This work was supported by the National Institutes of Health (Grant 1 R21 EB00 9459-01).

Supplementary material

216_2010_4259_MOESM1_ESM.pdf (870 kb)
ESM 1 (PDF 869 kb)


  1. 1.
    Athar M (2002) Oxidative stress and experimental carcinogenesis. Indian J Exp Biol 40(6):656–667Google Scholar
  2. 2.
    Sakai K, Okuyama H, Yura J, Takeyama H, Shinagawa N, Tsuruga N, Kato K, Miura K, Kawase K, Tsujimura T, Naruse T, Koike A (1992) Composition and turnover of phospholipids and neutral lipids in human breast-cancer and reference tissues. Carcinogenesis 13(4):579–584CrossRefGoogle Scholar
  3. 3.
    Shimma S, Sugiura Y, Hayasaka T, Hoshikawa Y, Noda T, Setou M (2007) MALDI-based imaging mass spectrometry revealed abnormal distribution of phospholipids in colon cancer liver metastasis. J Chromatogr B: AnalTechnol Biomed Life Sci 855(1):98–103CrossRefGoogle Scholar
  4. 4.
    Aboagye EO, Bhujwalla ZM (1999) Malignant transformation alters membrane choline phospholipid metabolism of human mammary epithelial cells. Cancer Res 59(1):80–84Google Scholar
  5. 5.
    Glunde K, Jie C, Bhujwalla ZM (2004) Molecular causes of the aberrant choline phospholipid metabolism in breast cancer. Cancer Res 64(12):4270–4276CrossRefGoogle Scholar
  6. 6.
    Alonso T, Morgan RO, Marvizon JC, Zarbl H, Santos E (1988) Malignant transformation by ras and other oncogenes produces common alterations in inositol phospholipid signaling pathways. Proc Natl Acad Sci USA 85(12):4271–4275CrossRefGoogle Scholar
  7. 7.
    Alonso T, Santos E (1990) Increased intracellular glycerophosphoinositol is a biochemical marker for transformation by membrane-associated and cytoplasmic oncogenes. Biochem Biophys Res Commun 171(1):14–19CrossRefGoogle Scholar
  8. 8.
    Valitutti S, Cucchi P, Colletta G, Di Filippo C, Corda D (1991) Transformation by the k-ras oncogene correlates with increases in phospholipase a2 activity, glycerophosphoinositol production and phosphoinositide synthesis in thyroid cells. Cell Signal 3(4):321–332CrossRefGoogle Scholar
  9. 9.
    Yamaji-Hasegawa A, Tsujimoto M (2006) Asymmetric distribution of phospholipids in biomembranes. Biol Pharm Bull 29(8):1547–1553CrossRefGoogle Scholar
  10. 10.
    Utsugi T, Schroit AJ, Connor J, Bucana CD, Fidler IJ (1991) Elevated expression of phosphatidylserine in the outer-membrane leaflet of human tumor-cells and recognition by activated human blood monocytes. Cancer Res 51(11):3062–3066Google Scholar
  11. 11.
    Zwaal RFA, Comfurius P, Bevers EM (2005) Surface exposure of phosphatidylserine in pathological cells. Cell Mol Life Sci 62(9):971–988CrossRefGoogle Scholar
  12. 12.
    Chaurio RA, Janko C, Munoz LE, Frey B, Herrmann M, Gaipl US (2009) Phospholipids: key players in apoptosis and immune regulation. Molecules 14(12):4892–4914CrossRefGoogle Scholar
  13. 13.
    Kim R, Emi M, Tanabe K, Arihiro K (2006) Tumor-driven evolution of immunosuppressive networks during malignant progression. Cancer Res 66(11):5527–5536CrossRefGoogle Scholar
  14. 14.
    Sandra F, Esposti MD, Ndebele K, Gona P, Knight D, Rosenquist M, Khosravi-Far R (2005) Tumor necrosis factor-related apoptosis-inducing ligand alters mitochondrial membrane lipids. Cancer Res 65(18):8286–8297CrossRefGoogle Scholar
  15. 15.
    Mollinedo F, Gajate C, Martin-Santamaria S, Gago F (2004) Et-18-och3 (edelfosine): a selective antitumour lipid targeting apoptosis through intracellular activation of fas/cd95 death receptor. Curr Med Chem 11(24):3163–3184Google Scholar
  16. 16.
    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
  17. 17.
    Chaurand P, Cornett DS, Caprioli RM (2006) Molecular imaging of thin mammalian tissue sections by mass spectrometry. Curr Opin Biotechnol 17(4):431–436CrossRefGoogle Scholar
  18. 18.
    Cornett DS, Reyzer ML, Chaurand P, Caprioli RM (2007) MALDI imaging mass spectrometry: molecular snapshots of biochemical systems. Nat Meth 4(10):828–833CrossRefGoogle Scholar
  19. 19.
    Xu BJ, Gonzalez AL, Kikuchi T, Yanagisawa K, Massion PP, Wu H, Mason SE, Olson SJ, Shyr Y, Carbone DP, Caprioli RM (2008) MALDI-MS derived prognostic protein markers for resected non-small cell lung cancer. Proteomics Clin Appl 2(10–11):1508–1517CrossRefGoogle Scholar
  20. 20.
    Doroshenko VM, Laiko VV, Taranenko NI, Berkout VD, Lee HS (2002) Recent developments in atmospheric pressure MALDI mass spectrometry. Int J Mass Spectrom 221(1):39–58CrossRefGoogle Scholar
  21. 21.
    Fletcher JS, Lockyer NP, Vaidyanathan S, Vickerman JC (2007) TOF-SIMS 3D biomolecular imaging of Xenopus laevis oocytes using buckminsterfullerene (c-60) primary ions. Anal Chem 79(6):2199–2206CrossRefGoogle Scholar
  22. 22.
    Winograd N (2003) Prospects for imaging TOF-SIMS: from fundamentals to biotechnology. Appl Surf Sci 203:13–19CrossRefGoogle Scholar
  23. 23.
    Nemes P, Barton AA, Vertes A (2009) Three-dimensional imaging of metabolites in tissues under ambient conditions by laser ablation electrospray ionization mass spectrometry. Anal Chem 81(16):6668–6675CrossRefGoogle Scholar
  24. 24.
    Nemes P, Barton AA, Li Y, Vertes A (2008) Ambient molecular imaging and depth profiling of live tissue by infrared laser ablation electrospray ionization mass spectrometry. Anal Chem 80(12):4575–4582CrossRefGoogle Scholar
  25. 25.
    Nemes P, Vertes A (2007) Laser ablation electrospray ionization for atmospheric pressure, in vivo, and imaging mass spectrometry. Anal Chem 79(21):8098–8106CrossRefGoogle Scholar
  26. 26.
    Kertesz V, Ford MJ, Van Berkel GJ (2005) Automation of a surface sampling probe/electrospray mass spectrometry system. Anal Chem 77(22):7183–7189CrossRefGoogle Scholar
  27. 27.
    Shelley JT, Ray SJ, Hieftje GM (2008) Laser ablation coupled to a flowing atmospheric pressure afterglow for ambient mass spectral imaging. Anal Chem 80(21):8308–8313CrossRefGoogle Scholar
  28. 28.
    Schafer KC, Denes J, Albrecht K, Szaniszlo T, Balog J, Skoumal R, Katona M, Toth M, Balogh L, Takats Z (2009) In vivo, in situ tissue analysis using rapid evaporative ionization mass spectrometry. Angew Chem Int Ed 48(44):8240–8242CrossRefGoogle Scholar
  29. 29.
    Takats Z, Wiseman JM, Gologan B, Cooks RG (2004) Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science 306(5695):471–473CrossRefGoogle Scholar
  30. 30.
    Dill AL, Ifa DR, Manicke NE, Zheng OY, Cooks RG (2009) Mass spectrometric imaging of lipids using desorption electrospray ionization. J Chromatogr B Anal Technol Biomed Life Sci 877(26):2883–2889CrossRefGoogle Scholar
  31. 31.
    Kertesz V, Van Berkel GJ (2008) Improved imaging resolution in desorption electrospray ionization mass spectrometry. Rapid Commun Mass Spectrom 22(17):2639–2644CrossRefGoogle Scholar
  32. 32.
    Wiseman JM, Puolitaival SM, Takats Z, Cooks RG, Caprioli R (2005) Mass spectrometric profiling of intact biological tissue by using desorption electrospray ionization. Angew Chem Int Ed 44(43):7094–7097CrossRefGoogle Scholar
  33. 33.
    Dill AL, Ifa DR, Manicke NE, Costa AB, Ramos-Vara JA, Knapp DW, Cooks RG (2009) Lipid profiles of canine invasive transitional cell carcinoma of the urinary bladder and adjacent normal tissue by desorption electrospray ionization imaging mass spectrometry. Anal Chem 81(21):8758–8764CrossRefGoogle Scholar
  34. 34.
    Eberlin LS, Dill AL, Costa AB, Ifa DR, Cheng L, Masterson T, Koch M, Ratliff TL, Cooks RG (2010) Cholesterol sulfate imaging in human prostate cancer tissue by desorption electrospray ionization mass spectrometry. Anal Chem 82(9):3430–3434CrossRefGoogle Scholar
  35. 35.
    Eberlin LS, Dill AL, Golby AJ, Ligon KL, Wiseman JM, Cooks RG, Agar NYR (2010) Discrimination of human astrocytoma subtypes by lipid analysis using desorption electrospray ionization imaging mass spectrometry. Angew Chem Int Ed 49(34):5953–5956Google Scholar
  36. 36.
    Cheng LA, Williamson SR, Zhang SB, MacLennan GT, Montironi R, Lopez-Beltran A (2010) Understanding the molecular genetics of renal cell neoplasia: implications for diagnosis, prognosis and therapy. Expert Rev Anticancer Ther 10(6):843–864CrossRefGoogle Scholar
  37. 37.
    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):321–325CrossRefGoogle Scholar
  38. 38.
    Eberlin LS, Ifa DR, Wu C, Cooks RG (2010) Three-dimensional visualization of mouse brain by lipid analysis using ambient ionization mass spectrometry. Angew Chem Int Ed 49(5):873–876.Google Scholar
  39. 39.
    Ifa DR, Wiseman JM, Song QY, Cooks RG (2007) Development of capabilities for imaging mass spectrometry under ambient conditions with desorption electrospray ionization (DESI). Int J Mass Spectrom 259:8–15CrossRefGoogle Scholar
  40. 40.
    Trygg J, Wold S (2002) Orthogonal projections to latent structures (O-PLS). J Chemom 16(3):119–128.CrossRefGoogle Scholar
  41. 41.
    Team RDC (2009) R: a language and environment for statistical computing (trans: Book citations: Books without editor: E. Wingender GRiE, VCH, Weinheim, 1993, p. 215. Books with editor: T. D. In: Atwood JL, Davies JED, MacNicol DD, Vögtle F, Suslick KS (eds) Tullius in Comprehensive supramolecular chemistry, vol. 5, Pergamon, Oxford, 1996, pp 317–343.). Vienna, AustriaGoogle Scholar
  42. 42.
    Wehrens RM, Mevik BH (2007) PLS: partial least squares regression (PLSR) and principal component regression (PCR) R package versiion 21-0 http://meviknet/work/software/plshtml
  43. 43.
    De Meyer T, Sinnaeve D, Van Gasse B, Tsiporkova E, Rietzschel ER, De Buyzere ML, Gillebert TC, Bekaert S, Martins JC, Van Criekinge W (2008) NMR-based characterization of metabolic alterations in hypertension using an adaptive, intelligent binning algorithm. Anal Chem 80(10):3783–3790CrossRefGoogle Scholar
  44. 44.
    Pulfer M, Murphy RC (2003) Electrospray mass spectrometry of phospholipids. Mass Spectrom Rev 22(5):332–364CrossRefGoogle Scholar
  45. 45.
    Manicke NE, Wiseman JM, Ifa DR, Cooks RG (2008) Desorption electrospray ionization (DESI) mass spectrometry and tandem mass spectrometry (MS/MS) of phospholipids and sphingolipids: ionization, adduct formation, and fragmentation. J Am Soc Mass Spectrom 19(4):531–543CrossRefGoogle Scholar
  46. 46.
    Hsu FF, Turk J (2000) Characterization of phosphatidylinositol, phosphatidylinositol-4-phosphate, and phosphatidylinositol-4, 5-bisphosphate by electrospray ionization tandem mass spectrometry: a mechanistic study. J Am Soc Mass Spectrom 11(11):986–999CrossRefGoogle Scholar
  47. 47.
    Hsu FF, Turk J (2008) Structural characterization of unsaturated glycerophospholipids by multiple-stage linear ion-trap mass spectrometry with electrospray ionization. J Am Soc Mass Spectrom 19(11):1681–1691CrossRefGoogle Scholar
  48. 48.
    Hsu FF, Turk J (2005) Studies on phosphatidylserine by tandem quadrupole and multiple stage quadrupole ion-trap mass spectrometry with electrospray ionization: structural characterization and the fragmentation processes. J Am Soc Mass Spectrom 16(9):1510–1522CrossRefGoogle Scholar
  49. 49.
    Murphy RC (1993) Mass spectrometry of lipids. Plenum, New YorkGoogle Scholar
  50. 50.
    Nefliu M, Smith JN, Venter A, Cooks RG (2008) Internal energy distributions in desorption electrospray ionization (DESI). J Am Soc Mass Spectrom 19(3):420–427CrossRefGoogle Scholar
  51. 51.
    Clarke R, Ressom HW, Wang AT, Xuan JH, Liu MC, Gehan EA, Wang Y (2008) The properties of high-dimensional data spaces: implications for exploring gene and protein expression data. Nat Rev Cancer 8(1):37–49CrossRefGoogle Scholar
  52. 52.
    Lechevallier E (2007) Core biopsy of solid renal masses under ct guidance. Eur Urol Suppl 6(8):540–543CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Allison L. Dill
    • 1
  • Livia S. Eberlin
    • 1
  • Cheng Zheng
    • 2
  • Anthony B. Costa
    • 1
  • Demian R. Ifa
    • 1
  • Liang Cheng
    • 3
  • Timothy A. Masterson
    • 4
  • Michael O. Koch
    • 4
  • Olga Vitek
    • 2
  • R. Graham Cooks
    • 1
    • 5
    Email author
  1. 1.Department of Chemistry and Center for Analytical Instrumentation DevelopmentPurdue UniversityWest LafayetteUSA
  2. 2.Department of StatisticsPurdue UniversityWest LafayetteUSA
  3. 3.Department of Pathology and Laboratory MedicineIndiana University School of MedicineIndianapolisUSA
  4. 4.Department of UrologyIndiana University School of MedicineIndianapolisUSA
  5. 5.Department of ChemistryPurdue UniversityWest LafayetteUSA

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