دانلود کتاب Proteomic and Metabolomic Approaches to Biomarker Discovery

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Front Matter Copyright Contributors Preface to the second edition Biomarker discovery: Study design and execution Introduction Definitions Biomarker Sensitivity Specificity Positive predictive value (PPV) Negative predictive value (NPV) Proteomics Metabolomics Profiling The current state of biomarker discovery Study design and execution Study design Study execution Personnel and instrumentation Errors in study design The sample Cancer type and stage Sample type Selection of patients and controls Number of samples Ethnicity, sex, and age Sample collection, handling, and storage Method of sample analysis Type of sample Errors in study execution Sample preparation Methods of analysis Number of replicates Effect of mass spectrometer type on the results Effect of separation instrumentation on the results Errors in measurements Personnel and experimental validation Specificity of proteins as biomarkers Published results comparison Statistical data analysis Recommendations Concluding remarks and recommendations Acknowledgments References Proteomic and mass spectrometry technologies for biomarker discovery Introduction Protein biomarker discovery and development pipeline Proteomic samples Protein identification using mass spectrometry Protein digestion Protein and peptide separation techniques Protein and peptide ionization techniques Mass spectrometry instrumentation Deconvolution and database search of tandem mass spectra Posttranslational modifications as disease biomarkers Protein quantification using mass spectrometry Label-free quantification Metabolic and enzymatic labeling Chemical labeling Selected reaction monitoring assays Separation and enrichment strategies for quantification of low-abundance proteins Biomarker verification Biomarker validation Limitations of mass spectrometry for protein biomarker discovery Conclusions and future outlook: Integrated biomarker discovery platform References Tissue sample preparation for proteomic analysis Introduction Types of tissues available for MS-based proteomics Fresh-frozen tissue Formalin-fixed paraffin-embedded tissue Tissue processing for LC-MS analysis Manual tools for tissue homogenization Glass homogenizers/grinders Glass-teflon homogenizers/grinders Stainless-steel homogenizers/pulverizers Apparatuses for tissue cutting, disruption, and homogenization Histology microtomes Mechanical rotor/stator type homogenizers/grinders Cryogenic homogenizers/grinders Bead-beating-based homogenizers/disruptors Pressure cycling homogenizers Ultrasonic homogenizers Extraction/solubilization buffers Buffers used in gel-based tissue proteomics Buffers used in gel-free tissue proteomics Detergent and chaotrope-based buffers used in gel-free tissue proteomics Aqueous/organic buffers Immunodepletion of abundant serum proteins from tissue homogenates Concluding remarks Acknowledgments References Sample preparation in global metabolomics of biological fluids and tissues Introduction An ideal sample preparation method for global metabolomics? Sample preparation methods for biofluids Dilute-and-shoot: Preferred method for urine metabolomics Solvent precipitation: Preferred method for plasma, serum, and other biofluids Plasma versus serum in global metabolomics Choice of anticoagulant in global metabolomics Protein removal efficiency and selection of plasma-precipitant ratio Selection of extraction solvent: Metabolite coverage, recovery, and method reproducibility Incorporating derivatization step for GC-MS compatibility Liquid-liquid extraction approaches Ultrafiltration Solid-phase extraction Evaporation and reconstitution step Sample preparation methods for tissues New trends in sample preparation for global metabolomics In vivo sampling: microdialysis and solid-phase microextraction Turbulent flow chromatography (TFC) Dried blood (or biofluid) spot analysis Overview of sample preparation approaches for lipidomics Sample preparation methods for lipidomics of biofluids Sample preparation methods for lipidomics of tissues Quality control of sample preparation in global metabolomics Conclusions and future perspective Acknowledgment References Serum and plasma collection: Preanalytical variables and standard operating procedures in biomarker research Introduction Importance of preanalytical variables Standard operating procedures (SOPs) Sample selection considerations Human blood and its components Serum Plasma Hemolyzed samples Other biosamples Blood-borne pathogens, universal precautions, and safety Human subject research protections Conclusions Update References Sample depletion, fractionation, and enrichment for biomarker discovery Introduction Depletion Fractionation procedures for proteins and metabolites Affinity chromatography Isoelectric focusing Size exclusion chromatography Conclusions References Current NMR strategies for biomarker discovery Introduction: Why NMR? Advancements in NMR hardware Sample preparation for NMR analysis Biological fluids without macromolecules Biological fluids with macromolecules Cells and tissue extracts Intact tissue for HR-MAS Internal and external chemical shift standards Internal standards External standard One-dimensional NMR methods: 1H, 13C, 31P 1H 13C 31P 2D methods Homonuclear 2D J-resolved spectroscopy COSY/TOCSY Heteronuclear 2D: 1H-13C HSQC Targeted metabolic profiling Targeted analysis: Stable isotope tagging Targeted analysis: Metabolite specific Flux analysis using 13C labeling High-resolution magic angle spinning (HR-MAS) NMR spectroscopy Magnetic resonance spectroscopy (MRS) NMR data processing and preparation for statistical analysis Data postprocessing Spectral alignment Data preparation for statistical analysis Binning Targeted/quantitative spectral fitting Data normalization and scaling Multivariate statistical analysis NMR metabolite identification Future directions and conclusion References Gas chromatography/mass spectrometry-based metabonomics Introduction GC/MS in metabonomics Overview of GC/MS-based metabonomics Experimental design Sample preparation GC/MS data acquisition Data analysis Biomarker discovery Strengths and limitations of GC/MS Applications Strategies to address large-scale metabonomic investigations Methodological considerations in sample preparation and analysis Quality control Retention index markers Managing missing values and normalization Conclusion and future outlook Update References Liquid chromatographic methods combined with mass spectrometry in metabolomics Introduction Chromatographic methods for metabolite profiling Reversed-phase LC separations Hydrophilic interaction liquid chromatography (HILIC) Other approaches to the profiling of polar and ionic metabolites Miniaturized LC systems Multicolumn and multidimensional separations Ion mobility spectrometry combined with LC-MS Detection Quality control, data analysis, and biomarker detection Metabolite identification and biomarker validation Conclusions References Further reading Capillary electrophoresis-mass spectrometry for proteomic and metabolic analysis Analysis of metabolite profiles using capillary electrophoresis-mass spectrometry Capillary zone electrophoresis-electrospray ionization-mass spectrometry Sheath-liquid versus sheathless electrospray interfaces Analysis of protein expression levels using capillary electrophoresis-mass spectrometry Single-dimension capillary electrophoretic separation Capillary electrophoresis-based multidimensional separations Capillary isoelectric focusing Transient capillary isotachophoresis/capillary zone electrophoresis Conclusion Update Acknowledgments References Associating 2-DE and CPLLs for low-abundance protein discovery: A winning strategy Historical recalls Progressive evolution of 2-DE toward proteomics applications Low-abundance proteins as a major target in proteomics Enriching low-abundance proteins by the treatment of the initial sample Proteome fractionation: A complex procedure with protein losses Depletion: A biospecific method with limited enrichment Group-specific protein enrichment LAP enrichment by the reduction of dynamic protein concentration range with CPLLs The discovery of low-abundance protein with 2-DE and its association with CPLLs enrichment Toward the discovery of undetectable low-abundance proteins Discovery of novel allergens of low abundance Biomarker discovery targets Conclusion References Two-dimensional difference in gel electrophoresis for biomarker discovery Introduction Gel electrophoresis: Historical perspective Two-dimensional differential in-gel electrophoresis Strengths and weaknesses of 2D-PAGE and 2D-DIGE Application of 2D-DIGE to biomarker discovery Update Conclusions Acknowledgment References Affinity-targeting schemes for protein biomarkers Introduction The unique value of affinity selection Conclusion References Protein and metabolite identification Protein identification Introduction Peptide mapping Tandem mass spectrometry Protein databases Top-down mass spectrometry Metabolite identification in global metabolomics MS metabolite identification NMR metabolite identification Conclusion References Quantitative proteomics in development of disease protein biomarkers Introduction Quantitative proteomic profiling for protein biomarker discovery Modes of mass spectrometric data collection in proteomic profiling Data-dependent acquisition (DDA) Data-independent acquisition (DIA) Quantitation technologies Label-free quantitative proteomics Metabolic labeling Chemical tagging with stable isotope labels Enzymatic 18O-labeling Protein biomarker discovery Differentially expressed proteins Disease-specific protein isomers Abnormal protein activities as emerging biomarkers Targeted proteomic validation of biomarker candidates Multiple reaction monitoring or selected reaction monitoring MS Parallel reaction monitoring MS Quantitation of signature peptides Sample throughput in biomarker validation Standardization Public data repositories for assay development ProteomeXchange UniProt ProteomicsDB and ProteomeTools CPTAC Conclusion References Mass spectrometry and NMR spectroscopy based quantitative metabolomics Metabolomics Comparative chemometric analysis versus quantitative metabolomics Mass spectrometry Liquid chromatography-resolved MS methods (LC-MS) Metabolite quantitation using LC-MS Gas chromatography-resolved MS methods (GC-MS) Ion mobility MS NMR spectroscopy Solvent suppression Suppression of macromolecular signals Quantitative referencing Spectral simplification methods Metabolite quantitation using 1D NMR Expanding the quantifiable metabolite pool in blood plasma and serum Analysis of coenzymes and antioxidants in whole blood, tissue and cells Metabolite quantitation using 2D NMR Isotope-labeled NMR Ex vivo isotope labeling Combining NMR and MS for metabolite quantitation Combining NMR and MS with chemical derivatization for metabolite quantitation Conclusions References Top-down mass spectrometry for protein molecular diagnostics, structure analysis, and biomarker discovery Introduction Mass spectrometry hardware for top-down Ionization Mass analyzers Tandem mass spectrometry Sample preparation and separations Sample preparation High-performance liquid chromatography Orthogonal and multidimensional separations Informatics Current status Concluding remarks Acknowledgments References Using data-independent mass spectrometry to extend detectable dynamic range without prior fractionation Introduction Advancement in mass spectrometry Principle of the precursor acquisition independent from ion count (PAcIFIC) Recent improvements to PAcIFIC PAcIFIC and quantification Quantitative PAcIFIC (qPAcIFIC) PAcIFIC with high-resolution high mass accuracy precursor ion scans Proteome profiling with PAcIFIC Human plasma Breast cancer Abdominal aortic aneurysm (AAA) Conclusions References Imaging mass spectrometry of intact biomolecules in tissue sections Introduction Matrix application Protein analysis Peptides and protein digests Lipid analysis Drug analysis Three-dimensional imaging High-speed imaging Conclusions and perspectives Acknowledgments References Mass spectrometry-based approach for protein biomarker verification Introduction MRM-MS assay generation for protein quantitation MRM-MS assay performance characteristics for biomarker verification Sample enrichment strategies for improving biomarker verification Mass spectrometry-based strategies to improve biomarker verification Stable isotope-labeled internal standards used Bioinformatics software for MRM-MS assays and biomarker verification Selected biomarker verification applications based on MRM-MS Conclusions and perspectives References Mass spectrometry metabolomic data handling for biomarker discovery Metabolomics for biomarker discovery Mass spectrometry-based metabolomics Direct MS methods Hyphenated MS methods Targeted vs. untargeted strategies Data handling Signal processing Resolution tuning, noise reduction, and mass features detection Spectral features alignment Comparing sample data and reference data Data pretreatment-Normalization, scaling, and feature filtering Data modeling Exploratory analysis with unsupervised methods Principal component analysis Cluster analysis Regression and classification with supervised methods Partial least squares regression Decision trees Other supervised methods Model validation Conventional statistical analysis and ROC curves Conclusion References Analytical methods and biomarker validation Introduction Discussion Analytical method validation Experimental design and execution Biomarker identification and confirmation Biomarker validation Phase 1: Preclinical exploratory studies to identify potentially useful markers Phase 2: Clinical assay development for clinical disease Phase 3: Retrospective longitudinal repository studies Phase 4: Prospective screening studies Phase 5: Cancer control studies Conclusions Update References Multivariate analysis for metabolomics and proteomics data Study 1: Cancer detection by proteomics Study 2: Detection of heart disease by metabolomics Conclusions References Cell surface protein enrichment for biomarker and drug target discovery using mass spectrometry-based proteomics Introduction Cell surface proteomics in the context of biomarker discovery Enrichment of cell surface proteins for bottom-up MS-based proteomics General nonselective cell surface protein enrichment techniques Centrifugation-based enrichment of cell surface proteins Biotinylation-based enrichment of cell surface proteins Cell surface proteins enrichment using selective/targeted isolation techniques Lectin-specific enrichment of cell surface glycoproteins Hydrazide capturing for enrichment of cell surface glycoproteins Combined approaches for enrichment of cell surface protein Concluding remarks Acknowledgments References Advances in lipidomics for cancer biomarker discovery Introduction Lipidomics Lipid biomarkers in cancer Lipid extraction techniques Mass spectrometry Shotgun lipidomics Liquid chromatography-mass spectrometry (LC-MS) Mass spectral imaging lipidomics Alternative detection methods Challenges of antibody production against amphiphiles Conclusion References Mass spectrometry for the identification of protein biomarkers in urinary extracellular vesicles Acknowledgments References Designing clinical studies for biomarker discovery: The Design criteria Introduction Methodological aspects of biomarker identification studies: The Design criteria Items related to the trial design Prospective versus retrospective design Single-agent versus combination therapy Disease setting Clinical efficacy endpoints Patient selection Sample size Type of biological samples Timing of acquisition of sequential samples Validation of biomarkers Items related to the molecular aspects of the biomarkers Molecular nature of the biomarker Preclinical evidence Conventional versus high-throughput techniques Regulatory and ethical aspects Conclusions References Index A B C D E F G H I J K L M N O P Q R S T U V W X