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Chapter 134 : The Future of Cancer Diagnostics: Proteomics, Immunoproteomics, and Beyond

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Abstract:

A new paradigm for cancer diagnostics is that the concept of a biomarker for cancer detection and monitoring is not limited to a single protein but can comprise a proteomic pattern of many individual proteins and the changes this pattern undergoes when tissues transform from a normal to a malignant state. This chapter addresses the issues related to technology development, validation, and quality assurance, and discusses trends in future diagnostic strategies. The importance of mass spectrometry (MS) to the fields of proteomics and cancer diagnostics is undeniable. Although the mass spectrometer can be found in many designs and is used for various functions, nearly all mass spectrometers can be described as the combination of three basic components: the ion source, the mass analyzer, and a detector. The chapter describes the importance of the three most popular ionization techniques for MS: matrix-assisted laser desorption ionization (MALDI), surface-enhanced laser-desorption ionization (SELDI), and electrospray ionization (ESI). ESI MS requires more extensive sample preparation and theoretical expertise than MALDI or SELDI-MS; however, it is the most powerful MS technique available. Diagnostic strategies based on immunoproteomics exploit the natural response of the human immune system by identifying antigens associated with major histocompatibility complex (MHC) class I and class II molecules that are uniquely associated with cancer cells.

Citation: Winters M, Lowenthal M, Feldman A, Liotta L. 2006. The Future of Cancer Diagnostics: Proteomics, Immunoproteomics, and Beyond, p 1183-1192. In Detrick B, Hamilton R, Folds J (ed), Manual of Molecular and Clinical Laboratory Immunology, 7th Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815905.ch134

Key Concept Ranking

High-Performance Liquid Chromatography
0.43724063
Major Histocompatibility Complex
0.4140989
Humoral Immune Response
0.40066558
0.43724063
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Image of FIGURE 1
FIGURE 1

Schematic representation of three typical ionization and sample introduction techniques for MS analysis. Following ionization, analyte molecules are accelerated into a mass analyzer and detector of an appropriate instrumental configuration. (A) SELDI utilizes energy-absorbing molecule solution to absorb laser energy and induce ionization of immobilized analyte molecules. The analyte is covalently bound to a chip surface by one of many surface-capture chemistries (e.g., cation-anion exchange or reverse phase). (B) In MALDI, microliter volumes of the analyte and excess matrix can be dissolved in organic solvents and spotted by one of many techniques onto a plate. The matrix (e.g., alpha-cyano-4-hydroxycinnamic acid or sinapic acid) contains a chromophore that absorbs energy from the laser pulse and produces a plasma, resulting in vaporization and ionization of the analyte. Only molecular ions of the analyte molecules are produced, and almost no fragmentation occurs. (C) ESI utilizes a high positive or negative potential at an atmospheric, liquid junction to ionize a sample into the gas phase. This production of ions, called pneumatic nebulization, disperses the emerging solution into a very fine spray of charged droplets. As the solvent evaporates, droplet size decreases while the surface charge increases until, at the Rayleigh limit, Coulomb repulsion overcomes the droplet’s surface tension and the droplet explodes. The process continues until each analyte ion is individually charged, often producing multiply charged ions. EAM, energy-absorbing molecule.

Citation: Winters M, Lowenthal M, Feldman A, Liotta L. 2006. The Future of Cancer Diagnostics: Proteomics, Immunoproteomics, and Beyond, p 1183-1192. In Detrick B, Hamilton R, Folds J (ed), Manual of Molecular and Clinical Laboratory Immunology, 7th Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815905.ch134
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Image of FIGURE 2
FIGURE 2

ICAT MS-based protein profiling. This method relies on the labeling of protein samples from two different sources with two chemically identical reagents that differ only in masses as a result of isotope composition. Protein extract from two different samples is reacted with one of two forms of the ICAT reagent, an isotopically light form in which the linker contains eight hydrogens or a heavy form in which the linker contains eight deuterium atoms. The ICAT reagent reacts with cys-teine residues in proteins via a thiol-reactive group and contains a biotin moiety to facilitate purification. Peptides are recovered on the basis of the biotin tag by avidin affinity chromatography and are then analyzed by MS. Example of a labeled peptide.

Citation: Winters M, Lowenthal M, Feldman A, Liotta L. 2006. The Future of Cancer Diagnostics: Proteomics, Immunoproteomics, and Beyond, p 1183-1192. In Detrick B, Hamilton R, Folds J (ed), Manual of Molecular and Clinical Laboratory Immunology, 7th Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815905.ch134
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Image of FIGURE 3
FIGURE 3

Reverse-phase protein microarrays. Nanoliter amounts of tissue lysate are arrayed in dilution curves onto multiple nitrocellulose-coated slides. An analyte-specific ligand (e.g., antibody) is applied in solution phase; bound antibodies are detected by secondary tagging. Signal amplification is a prerequisite for achieving the sensitivity required for analysis of low-abundance proteins. A reliable method capitalizes on the catalyzed reporter deposition technology developed for clinical immunoassays. This technology is based on the enzyme-mediated deposition of biotin-tyramide conjugates at the site of a biotinylated antibody-ligand complex (CSA kit; DakoCytomation). Upon image analysis, the relative proportion of the analyte protein molecules in the total protein can be determined. Each array is scanned, spot intensities are analyzed, data are normalized to the total protein level, and a standardized, single value is generated for each sample on the array. This single datum point may then be used for comparison to those of every other spot on the array. This data set may be used for generation of network profiles across patient samples.

Citation: Winters M, Lowenthal M, Feldman A, Liotta L. 2006. The Future of Cancer Diagnostics: Proteomics, Immunoproteomics, and Beyond, p 1183-1192. In Detrick B, Hamilton R, Folds J (ed), Manual of Molecular and Clinical Laboratory Immunology, 7th Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815905.ch134
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