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

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.

[1]  P. Bohn,et al.  Correlated mass spectrometry imaging and confocal Raman microscopy for studies of three-dimensional cell culture sections. , 2014, The Analyst.

[2]  Christoph Krafft,et al.  Raman and FTIR imaging of lung tissue: Bronchopulmonary sequestration , 2009 .

[3]  M. Setou,et al.  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) , 2014, Analytical and Bioanalytical Chemistry.

[4]  E. Giovannucci,et al.  Progress and Opportunities in Molecular Pathological Epidemiology of Colorectal Premalignant Lesions , 2014, The American Journal of Gastroenterology.

[5]  S. Choi,et al.  Lipid profiles for HER2-positive breast cancer. , 2013, Anticancer research.

[6]  S. Park,et al.  Protein and lipid MALDI profiles classify breast cancers according to the intrinsic subtype , 2011, BMC Cancer.

[7]  G. Netto,et al.  Diagnostic Molecular Pathology: Current Techniques and Clinical Applications, Part I , 2003, Proceedings.

[8]  Antonella I. Mazur,et al.  Molecular pathology via IR and Raman spectral imaging , 2013, Journal of biophotonics.

[9]  Christina Gloeckner,et al.  Modern Applied Statistics With S , 2003 .

[10]  S. Choi,et al.  Lipid MALDI MS Profiling Accurately Distinguishes Papillary ThyroidCarcinoma from Normal Tissue , 2013 .

[11]  Kornelia Polyak,et al.  Cellular heterogeneity and molecular evolution in cancer. , 2013, Annual review of pathology.

[12]  Liang Cheng,et al.  Molecular pathology of lung cancer: key to personalized medicine , 2012, Modern Pathology.

[13]  Walter Krämer,et al.  Review of Modern applied statistics with S, 4th ed. by W.N. Venables and B.D. Ripley. Springer-Verlag 2002 , 2003 .

[14]  Jürgen Popp,et al.  Raman spectroscopy--a prospective tool in the life sciences. , 2003, Chemphyschem : a European journal of chemical physics and physical chemistry.

[15]  D. Trede,et al.  Spatial Segmentation of MALDI FT-ICR MSI Data: A Powerful Tool to Explore the Head and Neck Tumor In Situ Lipidome , 2014, Journal of The American Society for Mass Spectrometry.

[16]  Christoph Krafft,et al.  Identification of organelles and vesicles in single cells by Raman microspectroscopic mapping , 2005 .

[17]  Adrian Baddeley,et al.  spatstat: An R Package for Analyzing Spatial Point Patterns , 2005 .

[18]  M. Schmitt,et al.  Deeper understanding of biological tissue: quantitative correlation of MALDI-TOF and Raman imaging. , 2013, Analytical chemistry.

[19]  Christoph Krafft,et al.  Near infrared Raman spectra of human brain lipids. , 2005, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[20]  L. Qiu,et al.  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 , 2014, Analytical and Bioanalytical Chemistry.

[21]  R. Cooks,et al.  Tissue imaging at atmospheric pressure using desorption electrospray ionization (DESI) mass spectrometry. , 2006, Angewandte Chemie.

[22]  R. Tibshirani,et al.  Molecular assessment of surgical-resection margins of gastric cancer by mass-spectrometric imaging , 2014, Proceedings of the National Academy of Sciences.

[23]  Jürgen Popp,et al.  Image Processing—Chemometric Approaches to Analyze Optical Molecular Images , 2014 .

[24]  K. Jefimovs,et al.  Analysis of single algal cells by combining mass spectrometry with Raman and fluorescence mapping. , 2013, The Analyst.

[25]  Christoph Krafft,et al.  Raman and FTIR microscopic imaging of colon tissue: a comparative study , 2008, Journal of biophotonics.

[26]  Christoph Krafft,et al.  Mapping of single cells by near infrared Raman microspectroscopy , 2003 .

[27]  M. Schmitt,et al.  Classification of inflammatory bowel diseases by means of Raman spectroscopic imaging of epithelium cells. , 2012, Journal of biomedical optics.

[28]  G. Netto,et al.  Diagnostic Molecular Pathology, Part 2: Proteomics and Clinical Applications of Molecular Diagnostics in Hematopathology , 2005, Proceedings.

[29]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[30]  William N. Venables,et al.  Modern Applied Statistics with S , 2010 .

[31]  K. Ligon,et al.  Classifying human brain tumors by lipid imaging with mass spectrometry. , 2012, Cancer research.

[32]  Jürgen Popp,et al.  How to pre-process Raman spectra for reliable and stable models? , 2011, Analytica chimica acta.

[33]  R. Cooks,et al.  Mass Spectrometry Sampling Under Ambient Conditions with Desorption Electrospray Ionization , 2004, Science.