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Applications of Mass Spectrometry Imaging to Cancer.

Applications of Mass Spectrometry Imaging to Cancer, the latest volume in the Advances in Cancer Research provides invaluable information on the exciting and fast-moving field of cancer research. This volume presents original reviews on applications of mass spectrometry imaging to cancer.- Provides...

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Bibliographic Details
Main Author: Drake, Richard R.
Corporate Author: ScienceDirect (Online service)
Other Authors: Mcdonnell, Liam
Format: eBook
Language:English
Published: San Diego : Elsevier Science & Technology, 2017.
Series:Advances in Cancer Research.
Subjects:
Cancer > Spectroscopic imaging.
Cancer > Imagerie spectroscopique.
Cancer > Spectroscopic imaging
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Front Cover
  • Applications of Mass Spectrometry Imaging to Cancer
  • Copyright
  • Contents
  • Contributors
  • Preface
  • References
  • Chapter One: The Importance of Histology and Pathology in Mass Spectrometry Imaging
  • 1. Importance of Pathology
  • 2. Possible Errors Caused by Tissue Inherent Factors-Why Histology Is Important for Supervised Analysis
  • 3. Possible Errors Caused by Sample Inherent Factors-Small Pretherapeutic Biopsies
  • 4. Possible Errors Caused by Sample Preparations-Artifacts Are Not Your Friend
  • 5. Possible Errors Caused by Ill-Defined Sample Groups in the Training Set-Keep It Black and White/Shades of Gray Are Not ...
  • 6. Conclusion
  • References
  • Chapter Two: Applications of Mass Spectrometry Imaging to Cancer
  • 1. Introduction
  • 1.1. The Advantages of MSI
  • 1.2. The Basic Principles of MSI
  • 1.2.1. MALDI-TOF
  • 1.2.2. MALDI-FT-ICR
  • 1.2.3. SIMS-TOF
  • 1.2.4. DESI
  • 2. Protein MSI in Cancer Research
  • 2.1. Distinguishing Tissue Types by Peptide MSI
  • 2.2. Determining Tumor Margins by Peptide MSI
  • 2.3. Prediction of Metastasis by Peptide MSI
  • 2.4. Analysing Chemoresponse by Peptide MSI
  • 2.5. Identification of Diagnostic and Prognostic Markers by Peptide MSI
  • 2.6. Characterisation of Intra- and Intertumor Variability by Peptide MSI
  • 2.7. Practical Considerations for Proteolytic Peptide MSI: Sample Preparation
  • 2.8. Practical Considerations for Peptide MSI: Spatial Resolution
  • 2.9. Practical Considerations for Peptide MSI: Mass Analysers
  • 2.10. Practical Considerations for Peptide MSI: Identification
  • 3. Lipid MSI in Cancer Research
  • 3.1. Profiling Lipids in Cancer by DESI-MSI
  • 3.2. Profiling Lipids in Cancer by SIMS-MSI
  • 4. Glycan MSI in Cancer Research
  • 5. Drug Imaging in Cancer Research
  • 5.1. MALDI-MSI on Tissue Sections
  • 5.2. MALDI-MSI on Whole Body Sections.
  • 5.3. MALDI-MSI on 3D Tissue Cultures
  • 6. Data Analysis
  • 6.1. Spatial Information
  • 6.2. Preprocessing: Peak Detection
  • 6.3. Classification of FFPE-TMAs and the Importance of Dimension Reduction
  • 7. Concluding Remarks
  • 7.1. The Future of MSI: Molecular Pathology
  • References
  • Chapter Three: Assessing the Potential of Metal-Assisted Imaging Mass Spectrometry in Cancer Research
  • 1. Introduction
  • 2. Material
  • 3. Silver-Assisted IMS
  • 3.1. Preparation of Silver-Coated Glass Slides
  • 3.2. Tissue Deposition on Silver- or ITO-Coated Slides
  • 3.3. Silver Deposition on Tissue Section
  • 3.4. LDI Data Acquisition of a Silver-Coated Tissue Section
  • 3.5. Fast Optimization of New Tissue Sections
  • 4. Gold-Assisted IMS
  • 4.1. Preparation of Gold-Coated Glass Slides
  • 4.2. Tissue Deposition on ITO- or Gold-Coated Slides
  • 4.3. Sodium Salt Deposition
  • 4.4. Gold Deposition on Tissue Section
  • 4.5. LDI Data Acquisition of a CBS-Au-Coated Tissue Section
  • 5. Applications to Cancer Research
  • 6. Concluding Remarks
  • References
  • Chapter Four: MALDI Mass Spectrometry Imaging of N-Linked Glycans in Cancer Tissues
  • 1. Introduction
  • 2. Glycosylation and Cancer
  • 2.1. Function and Types of Glycosylation
  • 2.2. N-Linked Glycan Biosynthesis
  • 2.3. N-Linked Glycans and Cancer
  • 3. Methodology for N-Linked Glycan Detection by MALDI Imaging
  • 3.1. Tissue Sources
  • 3.2. Glycan Visualization in Tissues: Lectins and Anticarbohydrate Antibodies
  • 3.3. Histochemistry Stains
  • 3.4. Peptide N-Glycosidase F
  • 3.5. Matrix and Instrumentation Choices for N-Glycans
  • 3.6. Structural Confirmation
  • 4. N-Glycan Distribution Linked With Histopathology
  • 4.1. Major Structural Classes
  • 4.2. High-Mannose N-Glycans
  • 4.3. Nontumor Stroma and Normal Tissue Glycans
  • 4.4. N-Glycan Branching and Sialylation.
  • 4.5. Fucosylation and the Glycan Isomer Problem
  • 5. Emerging Applications
  • 5.1. Combined Glycan and Peptide MS Imaging
  • 5.2. Custom Multitumor TMA and Other Enzymes
  • 5.3. Linkage to Genomic Studies
  • 5.4. Potential Clinical Diagnostic Applications of N-Glycan MSI Data
  • 6. Summary
  • References
  • Chapter Five: In Situ Metabolomics in Cancer by Mass Spectrometry Imaging
  • 1. Metabolomics in Cancer
  • 2. In Situ Metabolomics by MALDI Imaging
  • 3. Fresh-Frozen- vs Formalin-Fixed Paraffin-Embedded Tissue Samples
  • 4. Tissue-Based Disease Classification-Diagnostic Markers and Metabolic Signatures
  • 5. Therapy Response Prediction and Prognosis
  • 6. Intra- and Intertumoral Heterogeneity
  • 7. Conclusion
  • References
  • Chapter Six: Mass Spectrometry Imaging in Oncology Drug Discovery
  • 1. Introduction
  • 2. How MSI Can Inform Our Understanding of Pharmacokinetic-Pharmacodynamic Relationships
  • 3. Biodistribution
  • 4. Tumor Metabolism: MSI Analysis for More Than Just Drug Distribution
  • 5. Sample Preparation
  • 6. Quantitation
  • 7. Toxicity and Safety Assessment
  • 8. Biomarkers for Efficacy
  • 9. Drug Delivery
  • 10. Tumor Microenvironment
  • 11. Assessing Hypoxia
  • 12. BBB Penetration
  • 13. Beyond Small Molecules
  • 14. Clinical Translation
  • 15. Emerging Applications: Spheroids
  • 16. Increased Spatial Resolution
  • 17. Metrology for MS Imaging
  • 18. Conclusion
  • References
  • Chapter Seven: MALDI IMS and Cancer Tissue Microarrays
  • 1. Introduction
  • 2. TMA Technology
  • 2.1. Preparation of the Donor Block
  • 2.2. FFPE TMA Construction
  • 3. MALDI IMS Analysis of TMAs
  • 3.1. Sample Preparation
  • 3.1.1. Cutting, Deparaffinization, and AR
  • 3.1.2. In Situ Enzymatic Digestion
  • 3.1.3. Matrix Deposition
  • 3.2. MALDI IMS Analysis
  • 3.3. Data Analysis
  • 4. Identification of Peptides
  • 5. Application of MALDI IMS on FFPE TMAs.
  • 6. Perspectives and Concluding Remarks
  • Acknowledgments
  • References
  • Chapter Eight: Mass Spectrometry Imaging for the Investigation of Intratumor Heterogeneity
  • 1. Tumor Heterogeneity
  • 1.1. Intratumor Heterogeneity
  • 1.2. The Study of ITH
  • 1.3. Clinical Relevance of ITH
  • 1.4. Techniques to Study Spatial Organization of ITH
  • 2. MSI to Study Tumor Heterogeneity
  • 3. Multivariate Data Analysis Strategies in MSI
  • 3.1. Unsupervised Analysis
  • 3.2. Supervised Classification
  • 3.3. Projection Methods
  • 4. MSI Applications for the Investigation of ITH
  • 4.1. Revealing ITH by Clustering
  • 4.2. Supervised Classification of ITH
  • 4.3. Investigating the Degree of ITH
  • 4.4. Investigation of ITH on Different Molecular Levels
  • 5. Future Applications of MSI in ITH Research
  • 6. Perspective
  • References
  • Chapter Nine: Ambient Mass Spectrometry in Cancer Research
  • 1. Desorption Electrospray Ionization
  • 2. Intraoperative Mass Spectrometry
  • 3. REIMS Instrumentation
  • 4. DESI-MSI for Drug Imaging in Cancer Research
  • References
  • Chapter Ten: Rapid Mass Spectrometry Imaging to Assess the Biochemical Profile of Pituitary Tissue for Potential Intraope ...
  • 1. Introduction
  • 2. Current Imaging and Visualization Techniques
  • 3. Mass Spectrometry in Clinical Usage
  • 3.1. Atmospheric Pressure Ionization Mass Spectrometry
  • 3.2. Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry
  • 4. Future Directions
  • References
  • Chapter Eleven: Mass Spectrometry Imaging in Cancer Research: Future Perspectives
  • 1. MSI-Based Diagnostics
  • 2. Biological Insights
  • 3. Multimodal MSI
  • 4. Targeted MSI
  • 5. Summary
  • References
  • Index
  • Back Cover.