Skip to main content
Log in

Novel workflow for combining Raman spectroscopy and MALDI-MSI for tissue based studies

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

Abstract

Molecular heterogeneity of cancer is a major obstacle in tumor diagnosis and treatment. To deal with this heterogeneity, a multidisciplinary combination of different analysis techniques is of urgent need because a combination enables the creation of a multimodal image of a tumor. Here, we develop a computational workflow in order to combine matrix-assisted laser desorption/ionization mass spectrometric (MALDI-MS) imaging and Raman microspectroscopic imaging for tissue based studies. The computational workflow can be used to confirm a spectral histopathology (SHP) based on one technique with another technique. In this contribution, we confirmed a Raman spectroscopic based SHP with MALDI-imaging. Owing to this combination, we could demonstrate, for a larynx carcinoma sample, that tissue types and different metabolic states could be extracted from the Raman spectra. Further investigations with the help of MALDI spectra yield a better characterization of variable epithelial differentiation and a better understanding of ongoing dysplastic alterations.

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

References

  1. World Health Organization (2014) Global battle against cancer won’t be won with treatment alone. Effective prevention measures urgently needed to prevent cancer crisis. On-line, Press Release No. 224

  2. Almendro V, Marusyk A, Polyak K (2013) Cellular heterogeneity and molecular evolution in cancer. Annu Rev Pathol Mech 8:277–302

    Article  CAS  Google Scholar 

  3. Cheng L, Alexander RE, MacLennan GT, Cummings OW, Lopez-Beltran A, Montironi R, Cramer HM, Davidson DD, Zhang S (2012) Molecular pathology of lung cancer: key to personalized medicine. Mod Pathol 25(3):347–369

    Article  CAS  Google Scholar 

  4. Lochhead P, Chan AT, Giovannucci E, Fuchs CS, Wu K, Nishihara R, O’Brien M, Ogino S (2014) Progress and opportunities in molecular pathological epidemiology of colorectal premalignant lesions. Am J Gastroenterol 109(8):1205–1214

    Article  CAS  Google Scholar 

  5. Netto GJ, Saad RD, Dysert PA (2003) Diagnostic molecular pathology: current techniques and clinical applications, part 1. Proc (Baylor Univ Med Cent) 16(4):379

    Google Scholar 

  6. Netto GJ, Saad R (2005) Diagnostic molecular pathology, part 2. Proteomics and clinical applications of molecular diagnostics in hematopathology. Proc (Baylor Univ Med Cent) 18(1):7

    Google Scholar 

  7. 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 72:645–654

    Article  CAS  Google Scholar 

  8. Eberlin LS, Tibshirani RJ, Zhang L, 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 111:2436–2441

    Article  CAS  Google Scholar 

  9. Takats Z, Wiseman JM, Gologan B, Cooks RG (2004) Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science (Washington, DC) 306:471–473

    Article  CAS  Google Scholar 

  10. 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 45:7188–7192

    Article  CAS  Google Scholar 

  11. Kim IC, Lee JH, Bang G, Kim YH, Choi SH, Kim KP, Kim HK, Ro L (2013) Lipid profiles for HER2-positive breast cancer. Anticancer Res 33:2467–2472

    CAS  Google Scholar 

  12. Kang HS, Lee SC, Park YS, Jeon YE, Lee JH, Jung SY, Park IH, Jang SH, Park HM, Yoo CW, Park SH, Han SY, Kim KP, Kim YH, Ro J, Kim HK (2011) Protein and lipid MALDI profiles classify breast cancers according to the intrinsic subtype. BMC Cancer 11:465

    Article  CAS  Google Scholar 

  13. Krasny L, Hoffmann F, Ernst G, Trede D, Alexandrov T, Havlicek V, Guntinas-Lichius O, von Eggeling F, Crecelius AC (2014) Spatial segmentation of MALDI FTICR MSI data: a powerful tool to explore the head and neck tumor in situ lipidome. J Am Soc Mass Spectrom 26:36–43

  14. Schmitt PM, Popp J (2003) Raman spectroscopy—a prospective tool in the life sciences. Chem Phys Chem 4:14–30

    Google Scholar 

  15. Bocklitz T, Schmitt M, Popp J (2014) Ex-vivo and in-vivo optical molecular pathology, chapter 7. Image processing – chemometric approaches to analyze optical molecular images. Wiley-VCH Verlag GmbH & Co: KGaA, pp 215–248

  16. Fagerer SR, Schmid T, Ibáñez AJ, Pabst M, Steinhoff R, Jefimovs K, Urban PL, Zenobi R (2013) Analysis of single algal cells by combining mass spectrometry with Raman and fluorescence mapping. Analyst 138(22):6732–6736

    Article  CAS  Google Scholar 

  17. Bocklitz TW, Crecelius AC, Matthäus C, Tarcea T, Eggeling F, Schmitt M, Schubert US, Popp J (2013) Deeper understanding of biological tissue: quantitative correlation of MALDI-TOF and Raman imaging. Anal Chem 85(22):10829–10834

    Article  CAS  Google Scholar 

  18. Ahlf DR, Masyuko RN, Hummon AB, Bohn PW (2014) Correlated mass spectrometry imaging and confocal Raman microscopy for studies of three-dimensional cell culture sections. Analyst 139:4578–4585

    Article  CAS  Google Scholar 

  19. R Development Core Team (2007) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  20. Baddeley A, Turner R (2005) SPATSTAT: an R package for analyzing spatial point patterns. J Stat Softw 12(6):1–42

    Article  Google Scholar 

  21. Gibb S (2013) readBrukerFlexData: reads mass spectrometry data in Bruker *flex format, R package version 1.7

  22. Venables WN, Ripley BD (2002) Modern applied statistics with S, 4th edn. Springer, New York

    Book  Google Scholar 

  23. Peaks MM (2008) Peaks R package version 0.2

  24. Bocklitz T, Walter A, Hartmann K, Rösch P, Popp J (2011) How to pre-process Raman spectra for reliable and stable models? Anal Chim Acta 704:47–56

    Article  CAS  Google Scholar 

  25. Diem D, Mazur A, Lenau K, Schubert J, Bird B, Miljkovíc M, Krafft C, Popp J (2013) Molecular pathology via IR and Raman spectral imaging. J Biophoton 6(11/12):855–886

    Article  CAS  Google Scholar 

  26. Bielecki C, Bocklitz TW, Schmitt J, Krafft C, Marquardt C, Gharbi A, Knösel T, Stallmach A, Popp J (2012) Classification of inflammatory bowel diseases by means of Raman spectroscopic imaging of epithelium cells. J Biomed Opt 17(7):076030

    Article  Google Scholar 

  27. Guo S, Qiu L, Wang Y, Qin X, Liu H, He M, Zhang Y, Li Z, Chen X (2014) Tissue imaging and serum lipidomic profiling for screening potential biomarkers of thyroid tumors by matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry. Anal Bioanal Chem 406:4357–4370

    Article  CAS  Google Scholar 

  28. Ryu J, Bang G, Lee JH, Choi SH, Jung YS, Kim KP, Kim YH, Kim HK (2013) Lipid MALDI MS profiling accurately distinguishes papillary thyroid carcinoma from normal tissue. J Proteom Bioinf 6:65–71

    Article  CAS  Google Scholar 

  29. Uchiyama Y, Hayasaka T, Masaki N, Watanabe Y, Masumoto K, Nagata T, Katou F, Seto M (2014) Imaging mass spectrometry distinguished the cancer and stromal regions of oral squamous cell carcinoma by visualizing phosphatidylcholine (16:0/16:1) and phosphatidylcholine (18:1/20:4). Anal Bioanal Chem 406:1307–1316

    Article  CAS  Google Scholar 

  30. Krafft C, Knetschke T, Siegner A, Funk RHW, Salzer S (2003) Mapping of single cells by near infrared Raman microspectroscopy. Vib Spectrosc 32(1):75–83

    Article  CAS  Google Scholar 

  31. Krafft C, Codrich D, Pelizzo G, Sergo V (2009) Raman and FTIR imaging of lung tissue: bronchopulmonary sequestration. J Raman Spectrosc 40(6):595–603

    Article  CAS  Google Scholar 

  32. Krafft C, Codrich D, Pelizzo G, Serg V (2008) Raman and FTIR microscopic imaging of colon tissue: a comparative study. J Biophotonics 1:154–169

    Article  CAS  Google Scholar 

  33. Krafft C, Neudert L, Simat T, Salzer R (2005) Near infrared Raman spectra of human brain lipids. Spectrochim Acta A 61A:1529–1535

    Article  CAS  Google Scholar 

  34. Krafft C, Knetschke T, Funk RHW, Salzer R (2005) Identification of organelles and vesicles in single cells by Raman microspectroscopic mapping. Vib Spectrosc 38:85–93

    Article  CAS  Google Scholar 

Download references

Acknowledgments

Financial support of the Carl-Zeiss Stiftung and the German Research Foundation (DFG) for the research projects PO 563/13-1, PO 563/16-1, EG 102/5-1, and SCHU 1229/15-1 is gratefully acknowledged. F.v.E., U.S., and O.G.-L. thank the German Research Foundation (DFG) for the grant EG 102/4-1 (UltrafleXtreme) and Bruker Daltonics for the cooperation.

Conflict of interest

The authors declare that no conflict of interest exists.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Thomas Bocklitz or Jürgen Popp.

Additional information

Thomas Bocklitz and Katharina Bräutigam contributed equally to this work and share main authorship.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(PDF 7.56 mb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bocklitz, T., Bräutigam, K., Urbanek, A. et al. Novel workflow for combining Raman spectroscopy and MALDI-MSI for tissue based studies. Anal Bioanal Chem 407, 7865–7873 (2015). https://doi.org/10.1007/s00216-015-8987-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-015-8987-5

Keywords

Navigation