Proteomic and Metabolomic Approaches to Biomarker Discovery

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
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