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Proteomics : a promising approach for cancer research /

Proteomics: A Promising Approach for Cancer Research provides an updated overview of scientific knowledge, achievements and findings in the field of cancer proteomics.The book discusses topics such as the use of proteomics in cancer biology and drug discovery, its role in surgical oncology, applicat...

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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Ali, Shafat (Editor), Majid, Sabhiya (Editor), Rehman, Muneeb U. (Editor)
Format: eBook
Language:English
Published: London ; San Diego, CA : Academic Press, an imprint of Elsevier, [2023]
Subjects:
Cancer > Research > Methodology.
Proteomics.
Proteomics
Cancer > Recherche > Méthodologie.
Protéomique.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Intro
  • Proteomics: A Promising Approach for Cancer Research
  • Copyright
  • Contents
  • Contributors
  • Preface
  • Chapter 1 Cancer proteomics: An overview
  • 1 . Introduction
  • 2 . Definition and goals of proteomics
  • 2.1 Need for proteomics
  • 3 . Methods of protein measurement and biomarker identification
  • 3.1 2D PAGE
  • 3.2 Mass spectrometry
  • 3.3 Protein arrays
  • 3.4 Protein bioinformatics
  • 4 . Biomedical applications
  • 4.1 Proteomics and cancer
  • 4.2 Early diagnosis of cancer
  • 4.3 Determining tumor aggressiveness
  • 4.4 Individualized therapy
  • 5 . Mechanisms of proteomic changes in cancer
  • 6 . Cancer biomarker applications
  • 6.1 Cancer heterogeneity
  • 6.2 Initial early detection of cancer
  • 7 . Protocols for developing tumor biomarkers
  • 8 . General guidelines for a good study design for biomarker discovery
  • 9 . Applications of proteomics research in various cancers
  • 9.1 Types of cancers
  • 9.2 Biomarkers for lung cancer detection
  • 9.3 Breast cancer biomarkers
  • 9.4 Ovarian cancer biomarkers and implications from proteomics
  • 9.5 Ovarian cancer pathogenesis
  • 9.6 Etiology
  • 9.7 Ovarian cancer progression
  • 9.8 Targets for therapeutic means
  • 10 . Can proteomics research findings in cancer be translated into clinically oriented research?
  • 10.1 EGFR kinase inhibitors
  • 10.2 HSP90 inhibitors
  • 11 . Conclusion
  • References
  • Further reading
  • Chapter 2 Proteomics: A groundbreaking development in cancer biology
  • 1 . Introduction
  • 2 . Why proteomics?
  • 3 . Types of proteomics
  • 3.1 Structural proteomics
  • 3.2 Sequence proteomics
  • 3.3 Expression proteomics
  • 3.4 Functional and interaction proteomics
  • 4 . Proteomics: Analytical approaches
  • 5 . Conventional techniques
  • 5.1 Chromatography-based techniques
  • 5.2 Size exclusion chromatography.
  • 5.3 Ion-exchange chromatography
  • 5.4 Affinity chromatography
  • 5.5 ELISA (enzyme linked immunosorbent assay)
  • 5.6 Western blotting
  • 6 . Advanced techniques
  • 6.1 Protein microarray
  • 6.2 Analytical protein microarray
  • 6.3 Functional protein microarray
  • 6.4 Reverse-phase protein microarray
  • 6.5 Edman sequencing
  • 7 . Gel-based approaches
  • 7.1 Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE)
  • 7.2 Two-dimensional gel electrophoresis
  • 7.3 Mass spectrometry
  • 8 . Quantitative techniques
  • 8.1 Stable isotopic labeling with amino acids in cell culture (SILAC)
  • 8.2 Isotope-coded affinity tag (ICAT)
  • 8.3 Isobaric tag for relative and absolute quantitation (iTRAQ)
  • 9 . High-throughput techniques
  • 9.1 X-ray crystallography
  • 9.2 NMR spectroscopy
  • 10 . Proteomics: A breakthrough in cancer
  • 11 . Oncoproteomics
  • 12 . Proteomic variations in cancer
  • 13 . Necessity of proteomics in cancer
  • 13.1 Early detection and diagnosis of cancer
  • 14 . Heterogeneity in cancer
  • 15 . Detecting tumor aggressiveness
  • 16 . Personalized cancer treatment
  • References
  • Chapter 3 Proteomics: Application of next-generation proteomics in cancer research
  • 1 . Introduction
  • 2 . What is proteomics?
  • 3 . Techniques in proteomics
  • 4 . Proteomics in cancer research
  • 5 . What is next-generation proteomics?
  • 6 . Edman sequencing
  • 7 . Protein microarray
  • 8 . Functional protein microarray
  • 9 . Analytical protein microarray
  • 10 . Reverse-phase protein microarray
  • 11 . Mass spectrometry-based proteomics
  • 11.1 Methodology
  • 11.2 Label-based quantitation
  • 11.3 Label-free quantitation
  • 12 . Advancements of MS technique in cancer research
  • 13 . Applications of MS in cancer research
  • 13.1 Investigation of posttranslational modifications of proteins.
  • 13.2 Phosphoproteomics
  • 13.3 Glycoproteomics
  • 13.4 Histoproteomics
  • 13.5 Discovery of tumor biomarkers
  • 13.6 Liquid biopsy
  • 13.7 Tissue biopsy and protein network biology
  • 13.8 Monitoring drug effects
  • References
  • Chapter 4 Proteomics approaches in the identification of cancer biomarkers and drug discovery
  • 1 . Introduction
  • 2 . Proteomics and cancer biomarkers
  • 2.1 Lung cancer
  • 2.2 Breast cancer
  • 2.3 Ovarian cancer
  • 2.4 Bladder cancer
  • 2.5 Colorectal cancer
  • 2.6 Esophageal cancer
  • 3 . Proteomics and drug discovery
  • 3.1 Chemical proteomics
  • 3.1.1 Activity-based probe profiling (ABPP)
  • 3.1.2 Compound-centric approach (CCCP)
  • 3.2 Functional proteomics
  • 3.3 Clinical proteomics
  • 4 . Current techniques and advancements in proteomics
  • 4.1 Separation techniques in proteomics
  • 4.1.1 Bottom-up proteomics
  • 4.1.2 Top-down proteomics
  • 4.1.3 Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE)
  • 4.1.4 Mass spectrometry for protein characterization
  • 4.1.5 Ionization sources for mass spectrometry
  • 4.1.5.1 Mass analyzers for separation
  • 4.1.5.2 Emerging technologies
  • 4.1.5.3 Protein chips
  • 4.1.5.4 Molecular scanner
  • 5 . Challenges in proteomics
  • 6 . Conclusion
  • References
  • Chapter 5 Proteomic profiling and its applications in cancer research
  • 1 . Introduction
  • 2 . Proteomic alterations in cancer
  • 3 . Analytical approaches of proteomics
  • 4 . Applications of proteomics in cancer
  • 5 . Applications of cancer biomarkers
  • 6 . Tumor aggressiveness detection
  • 7 . Lung cancer
  • 8 . Breast cancer
  • 9 . Ovarian cancer
  • 10 . Established biomarker panels: Their usefulness, challenges, and emerging potential
  • 11 . Prostate cancer
  • 12 . Conclusion
  • References
  • Further reading
  • Chapter 6 Role of proteomics in surgical oncology.
  • 1 . Introduction
  • 2 . Surgical oncology
  • 3 . Proteomic techniques in surgical oncology
  • 4 . Mass spectrometry
  • 5 . MALDI MSI (matrix aided laser desorption ionization mass spectrometry imaging)
  • 6 . SELDI-TOF MS
  • 7 . Laser capture microdissection (LCM)
  • 8 . Proteomics techniques used cancer biomarkers with special reference to surgical oncology
  • 9 . Gastrointestinal cancer biomarker and proteomics
  • 10 . Lung cancer biomarker and proteomics
  • 11 . Bladder cancer and renal cancer
  • 12 . Prostate cancer biomarker and proteomics
  • 12.1 Breast cancer biomarker and proteomics
  • 13 . Brain cancer and proteomics
  • 13.1 Ovarian cancer biomarkers and proteomics
  • 14 . Leukemia and proteomics
  • 15 . Conclusion
  • Acknowledgment
  • Consent for publication
  • Conflict of interest
  • Author contributions
  • References
  • Further reading
  • Chapter 7 Applications of mass spectroscopy in understanding cancer proteomics
  • 1 . Introduction
  • 1.1 Ionization source
  • 1.2 Mass analyzers
  • 1.3 Protein identification
  • 1.3.1 Peptide mass fingerprinting
  • 1.3.2 Peptide sequencing by tandem mass spectrometry
  • 1.3.3 Quantitative analysis
  • 2 . Mass spectrometry-based diagnostics
  • 2.1 Mass spectrometry as a biomarker discovery tool
  • 2.2 Mass spectrometry as a cancer diagnostic tool
  • 3 . Mass spectroscopy imaging
  • 4 . Protein MSI in cancer research
  • 4.1 Distinguishing tissue types by peptide MSI
  • 4.2 Determining tumor margins by peptide MSI
  • 4.3 Prediction of metastasis by peptide MSI
  • 4.4 Analyzing chemoresponse by peptide MSI
  • 4.5 Identification of diagnostic and prognostic markers by peptide MSI
  • 4.6 Characterization of intra- and intertumor variability by peptide MSI
  • 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 . Application of MS in cancer biomarker discovery
  • 6.1 Gastric cancer
  • 6.2 Pancreatic cancer
  • 6.3 Liver cancer
  • 6.4 Colorectal cancer (CRC)
  • 6.5 Lung cancer
  • 6.6 Melanoma
  • 6.7 Breast cancer
  • 6.8 Ovarian and uterine cervical cancers
  • 6.9 Urinary cancers
  • 7 . Conclusion and future perspectives
  • References
  • Chapter 8 Proteomic approaches in the study of cancers
  • 1 . Introduction
  • 2 . Proteomic approaches in cancer therapy
  • 2.1 Proteomic approaches against cancer growth
  • 2.2 Proteomic approaches against cancer metastasis
  • 2.3 Proteomic approaches against drug resistance
  • 3 . Proteomic approach in brain cancers
  • 4 . Proteomic approach in ovarian cancers
  • 5 . Proteomics approach in gastrointestinal cancer
  • 6 . Proteomics approach in lung cancer
  • 7 . Conclusion
  • References
  • Chapter 9 Cancer proteomics: Application of case studies in diverse cancers
  • 1 . Introduction
  • 2 . Proteome study of gastric cancer
  • 3 . Proteome study of esophageal cancer
  • 4 . Proteome study of lung cancer
  • 5 . Proteome study of genitourinary cancer
  • 6 . Proteome study of breast cancer
  • 7 . Proteome study of ovarian cancer
  • 8 . Conclusion
  • Acknowledgment
  • Consent for publication
  • Conflict of interest
  • Author contributions
  • References
  • Chapter 10 The enduring interdependence of shotgun and targeted proteomics in cancer research
  • 1 . Introduction
  • 2 . Epidemiology of cancer
  • 3 . Hallmarks of cancer
  • 4 . Alterations in metabolism in cancer cells
  • 5 . Genomic studies maybe insufficient to study cancer cell behaviors
  • 6 . Traditional vs proteomic technologies
  • 7 . Shotgun proteomics approach
  • 8 . Targeted proteomics
  • 9 . Relevance of targeted proteomics in cancer
  • 10 . Advanced targeted methods.