Tissue Profiling by MALDI-Tof MS: Basic Principles From Small Molecules to Proteins

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1 Tissue Profiling by MALDI-Tof MS: Basic Principles From Small Molecules to Proteins James Mobley, Ph.D. Proteomics Facility Vanderbilt University Imaging Mass Spectrometry of Thin Tissue Sections To obtain information on the local protein composition at any coordinate on the section To reconstruct -dimensional density maps (or images) for all of the signals detected To obtain molecular profiles and images indicative of health status Discovery tool to answer fundamental questions relevant to protein expression in normal and diseased tissues

2 Slice frozen tissue on cryostat (~ μm thick) Profiling Thaw slice onto MALDI plate, allow to dry Imaging Droplets Apply matrix Spray coating Laser Acquire mass spectra Laser Protein profiles Protein images m/z 8 88 MALDI Time-of-Flight Mass Spectrometry Matrix Sample +/- U Ionizing Probe (start) M M M Ion detector (MCP) Ion signals % Intensity ~ ~

3 Protein expression profiling by MALDI-MS Human breast tumor needle biopsy mm % Intensity x α+ 79 β ~ α + β Intensity Intensity

4 Human glioma biopsy mm C X 5 Tumor A B D Non-Tumor Tumor (A) Tumor (A) Tumor (B) Tumor (B) Non Tumor (C) Non Tumor (C) Non Tumor (D) Non Tumor (D) 8 Schwartz et Al. Clin. Cancer Res.,, (). m/z 5 mm Brain glioma section stained with Methylene blue 5 % Intensity x % Intensity

5 Principle of MALDI MS Imaging Frozen section MS Images Matrix application Raster of section 6 8 m/z MALDI Mass Spectrum Spray deposition of matrix on tissue sections Spray nebulizer for TLC plates Matrix solution Tissue section Nitrogen 5

6 Comparing matrix coatings: Applied Biosystems DE-STR Spotted % Intensity um Laser spot μm Sprayed % Intensity Mouse Brain , c) 759, d) Imaging resolution: 5 μm mm % m/z 67 % Intensity , e) 8, f) x ~99 m/z 759 m/z , g) m/z 8 m/z 8 Chaurand et Al. Anal Chem, 76, 86A-9A (). 6

7 Glioma mouse model - intracranial injection of GL6 cancer cells 965 Tumor mm Tumor Non tumor Relative intensities NT) T) , α , β , α + 568, β x NT) 6 7 T) Glioma mouse model. Imaging resolution: μm mm m/z 69 m/z 759 m/z 99 Acyl CoAbinding protein m/z 7 and 8 Histone H m/z Cytochrome C m/z 8 and ~5 5 Histones HB and H m/z 9 m/z 98 and 5 67 α and β hemoglobins m/z 8 Chaurand et Al. Anal Chem, 76, 86A-9A (). m/z 7 m/z 87 % 7

8 Acoustic Drop Ejection technology provides a nozzle-free means of generating microdroplets on-demand x y Sample plate Ejection of microdroplets Matrix reservoir Coupling membrane Coupling reservoir Transducer RF generator Waveform generator Current performances: - Spot size: ~8- µm - Drop ejection rate: Hz - Drops per pixel: 6-8 Manual spotting vs The RapidSpotter A) Mouse brain, Analysis of the corpus callosum B) 8

9 RapidSpotter Imaging of a Mouse Brain Section m/z 7885 m/z 89 m/z 688 μm Matrix printing % % m/z 79 m/z 6759 m/z 78 Create custom plate file Intensity

10 Schematic Representation of Protein Marker Identification Homogenate Lung Tumor * m/z RP HPLC Fractions Tryptic Digestion MS/MS MALDI MS * 5 5 m/z Mw Matches Mw Matches Add Post- Translational Modification Database Search Protein ID m/z mucosa submucosa Normal human colon biopsy µm muscle m/z 55 Combined Image m/z 79 m/z 8958 Combined Image

11 cortex medula Rat kidney sagittal section m/z 9979 m/z,95.5 mm Intensity m/z 99 m/z 7, Overlay Overlay Molecular Determination of Tumor Margins Histological tumor margin Non-tumor cm 5 x spots 5 µm resolution Tumor Vessel Fibrous stroma Skeletal muscle Robert Caldwell,

12 B A B A C D E E C D Soft Tissue Sarcoma Myosin light chain Histone H isoform (m/z, 7) Histone H isoform (m/z,85) Rob Caldwell

13

14 Histological vs. molecular assessment of the tumor margin: Brain Cancer protein expression profiling by MALDI-MS Laser ; Matrix droplets are regionally deposited on the sample. Each spot area is analyzed using MALDI-MS ; Computer algorithms are used to smooth and correct baseline of each spectrum N N N N T T T T T T T ; Hierarchical cluster analysis of human brain cancer and normal brain spectra Schwartz SA et Al, Cancer Research, 65(7), (5)

15 Weighted Flexible Compound Covariate Method Pairwise comparisons are performed between groups Fisher s exact test Individual protein signals differentially expressed are selected using 6 independent statistical analysis Significance Analysis of Microarrays Kruskal- Wallis test Proteins found in at least analysis were included in the final marker list A pathology prediction model is generated using the top significant protein classifiers Jason Moore, Yu Shyr Vanderbilt University t-test Weighted Gene Analysis Information- Score Method Human glioma protein expression profiling by MALDI-MS Non-Tumor Absolute Intensity Grade Tumor Grade Tumor Grade Tumor 8 5

16 6 % % proteins Grade, and Non-Tumor Clustering analysis of proteomic patterns in human glioma Non-Tumor vs. All Tumor - Training cohort Non-tumor Grade Clustering analysis of proteomic patterns in human glioma Non-Tumor vs. Grade - Training cohort proteins

17 Kaplan-Meier survival curves for groups with poor and good prognostic. Classification according to the expression pattern of 9 distinct MS peaks Long-term survival group (n = 6) % Surviving Patient Population 8 6 P-value <. 9 proteins were significant N = 6 Grade Glioma N = 5 5 Short-term survival group (n = 5) P-value <.5 8 proteins where significant 5 6 Month post surgery Schwartz SA et Al, Cancer Research, 65(7), (5) Human brain glioma Low grade vs. high grade m/z 86, S Beta Relative Intensities HG LG 68 % m/z 86 HG LG Immunohistochemistry HG LG µm 7

18 Analysis of drugs in tissue by mass spectrometry Cut frozen slice ( μm) Dose animal orally i.v. Remove tissue Apply matrix Reyzer ML et al, J Mass Spectrom, 8, 8-9 () Reyzer ML et al, Cancer Res 6, 99-9 () Laser Analyze by: MALDI MS and MALDI MS/MS MMTV/HER transgenic mouse mammary tumors MMTV/HER cells transplanted in FVB female mice. Tumor grown to a size of ~ mm. OSI 77 is an intracellular tyrosine kinase EGF receptor inhibitor. Administered orally for week Tumor Volume (mm ) 8 6 Captisol µl (vector) OSI 77 mg/kg Days post-treatment Contributed by M. Sliwkowski (Genentech, Inc.) 8

19 MS/MS analysis of OSI-77 in tumor tissue Tumors removed after a single mg/kg dose of OSI-77 O O m/z 6. +H O N N O NH +H m/z 78. +H + MW = 9. Intensity 78. [OSI77 + H] + 6. hr HC C 5 Monitored CAD transition m/z Intensity 5 m/z 78 Spot # 6 8 m/z Dose dependence of protein alteration ( hr after dose) 9 control mice, Av of 5 spectra thymosin β x dosed mice, Av of 9 spectra per dose Relative intensity Control mg/kg mg/kg mg/kg

20 Using Protein Fingerprints to Evaluate Drug Therapy drug treatment surgical/ MRI assessment of tumor volume 5 days MS profiling of proteome changes Whole Rat Imaging Sheerin Khatib-Shahid Average Ion Spectrum for Whole Rat Sagittal Section Muscle Thymus Kidney Brain Caudal Liver Cecum Heart m/z wall region Cortex m/z m/z m/z cm

21 Whole Rat Sagittal Section Imaging Rat Head Subsection % 5% cm % signal intensity Optical image Brain White matter Corpus Callosum Eye socket m/z 76 m/z 7 m/z 5978 m/z 6858 Drug Imaging Olanzapine (MW ) N N N CH 8 56 Intensity N H S CH Spleen Kidney Stomach Lung Liver Cecum Heart cm Optical image of orally dosed (8 mg/ml) rat abdomen MALDI MS/MS Image of OLZ (m/z 56) in stomach hours post-dose MS/MS Image of OLZ, x signal intensity with stomach signals masked

22 h Optical Image fur kidney liver lung spinal cord brain testis bladder? thoracic cavity Olanzapine m/z 56 thymus N-desmethyl metabolite m/z hydroxymethyl metabolite m/z 9 7 Areas of Further Development - Increase number of proteins analyzed to >> - Develop sample protocols to investigate peptides - Achieve high sensitivity above 5 kda - Integrate detergents into tissue protocol for membrane associated proteins - Pixel-to-pixel cycle time of about ms needed - Integrate bioinformatic tools, image processing - Develop sample protocols targeted at specific tissues/diseases - Improve protein identification protocols

23 Tissue Profiling/Imaging MS Conclusions - Excellent discovery tool - MW annotated patterns keyed to tissue location - Augments (not replaces) current molecular technologies - Significant clinical potential (disease diagnosis, state and progression, prognosis, risk assessment (?) - Provides temporal proteomic profile that, with genomic profile, will be vital to personalized medicine MSRC Richard Caprioli (Director) Shannon Cornett James Mobley Michelle Reyzer Jeremy Norris Robert Caldwell Erin Seeley Stacey Oppenheimer Sheerin Khatib-Shahid Kristin Burnum Kristen Herring Saturday Puolitaival Hans Reudi Aerni Annette Erskine Ken Shriver Others Per Andren, Uppsala University Robert Weil, NIH Walter Korfmacher, Schering-Plough Markus Stoeckli, Novartis Acknowledgments Vanderbilt Collaborators Carlos Arteaga David Carbone Robert Coffey Jr. Marie-Claire Orgebin-Crist Ariel Deutch Dennis Hallahan Pat Levitt Robert Matusik Jason Moore Hal Moses Jennifer Pietenpol Ned Porter Yu Shyr Robert Whitehead Ken Schriver Funding NIH (NCI, GMS, NIDA) Vanderbilt University

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