Cancer Biomarkers in Diagnosis and Therapeutics

Preface
Contents
Editor and Contributors
1: Introduction to Cancer Biomarkers
	1.1 Introduction
		1.1.1 Clinical Pathology of Cancer and Biomarkers
	1.2 Serum, Biological Fluid, and Tissue Cancer Biomarkers
	1.3 Clinical Applications and Performance Indications of Cancer Biomarkers
		1.3.1 Sensitivity and Specificity for the Evaluation of the Accuracy of CB
		1.3.2 Receiver Operating Characteristic (ROC) Curve Examination
		1.3.3 Ideal Biomarkers
	1.4 Clinical Uses and Limitations of Cancer Biomarkers
		1.4.1 Screening/Early Identification
		1.4.2 Identifying/Differential Determination
		1.4.3 Prognosis/Estimation
		1.4.4 Therapeutic Monitoring/Follow-Up/Evidence of Metastasis or Recurrence
	1.5 Uses of CB in Malignant Cancers
		1.5.1 Breast Malignant Growth
		1.5.2 Prostate Cancer
		1.5.3 Ovarian Malignancy
		1.5.4 Colorectal Malignant Growth
	1.6 New Biomarkers/Approval/Advancements
		1.6.1 Challenges for the Investigation of Novel Biomarkers
		1.6.2 Genomic Advancements
		1.6.3 Epigenomics
		1.6.4 Proteomics
		1.6.5 Metabolomics
	1.7 Conclusion
	References
2: Technologies for Identification and Validation of Cancer Biomarkers
	2.1 Cancer Biomarkers
	2.2 Types of Cancer Biomarkers
		2.2.1 Screening Biomarkers
		2.2.2 Predictive Biomarkers
		2.2.3 Prognostic Biomarkers
		2.2.4 Diagnostic Biomarkers
		2.2.5 Monitoring Biomarkers
	2.3 Discovery of CBMs
		2.3.1 Preclinical Studies
			2.3.1.1 In-Silico Studies
			2.3.1.2 In Vitro
			2.3.1.3 Microfluidics Chip Technology
			2.3.1.4 In Vivo
		2.3.2 Clinical Studies
			2.3.2.1 CBMs Already in Clinics?
			2.3.2.2 CBMs Clinical Trials
	2.4 Technologies That Lead to CBMs Discovery
		2.4.1 Genomics (Nuclear and Mitochondrial CBMs)
			2.4.1.1 Next-Generation Sequencing (DNA and RNA seq)
			2.4.1.2 Microarrays: Gene Expression Profiling
			2.4.1.3 Genome-Wide Association Studies
		2.4.2 Proteomics (Cytoplasmic and Membrane CBMs)
			2.4.2.1 Western Blotting
			2.4.2.2 FACS
			2.4.2.3 MALDI-TOF
		2.4.3 Bioinformatics (Predictive/Deduced CBMs)
			2.4.3.1 Molecular Docking
			2.4.3.2 Simulations
			2.4.3.3 Molecules-Interaction Network Analysis
			2.4.3.4 Support Vector Machine Learning
			2.4.3.5 Integrated Databases
		2.4.4 Metabolomics
		2.4.5 Epigenetics Biomarkers
			2.4.5.1 DNA Methylation: Aberrations
			2.4.5.2 Histone Posttranslational Modifications
			2.4.5.3 Chromatin Spatial Modifications
			2.4.5.4 MicroRNAs
		2.4.6 Microbiomics Biomarkers
		2.4.7 Cancer Imaging Technologies
	2.5 Emerging Technologies
		2.5.1 Circulatory Cancer Biomarkers
			2.5.1.1 Circulating Tumor Cells
			2.5.1.2 Circulatory DNA/RNA
			2.5.1.3 miRNA
			2.5.1.4 Exosomes
		2.5.2 Drug Repurposing
	References
3: Biomarkers for Cancer Drug Development
	3.1 Introduction
	3.2 Cancer Therapy
	3.3 Biomarkers
		3.3.1 Biomarkers Discovery
		3.3.2 Cancer Biomarkers Classification
	3.4 Biomarkers in Drug Development
	3.5 Biomarkers in Cancer Treatment
	3.6 Cancer Biomarkers Currently Available in Clinic
		3.6.1 FZR1 as a Probable Biomarker for NACT in Breast Cancer
	3.7 Biomarkers for Preclinical Modelling
		3.7.1 Screening Apoptosis
		3.7.2 CD20, CD22, CD30, and CD79b as Lymphoid Malignancy Targets
		3.7.3 CD33, CD123 and CLL-1 as Focuses for Myeloid Malignancies
		3.7.4 Biomarkers for Strong Tumor Immunotherapy
		3.7.5 Tyrosine Kinase Biomarkers as Targets of Small Molecule Inhibitors
		3.7.6 Designing Biomarkers Through Systems Biology for Cancer Treatment
	3.8 Challenges of Biomarkers in Medical Revelation
	3.9 Future Recommendation
	References
4: Clinical Proteomics: Diagnostics and Prognostic Markers of Cancer
	4.1 Clinical Proteomics
	4.2 Goals and Need for Proteomics
	4.3 Methods of Protein Measurement and Biomarker Identification
		4.3.1 Bottom-up or Shotgun Proteomics
		4.3.2 Mass Spectrometry-Based Proteomics
		4.3.3 Polyacrylamide Gel Electrophoresis (PAGE)
	4.4 Proteomics and Cancer
	4.5 Early Diagnosis of Cancer
		4.5.1 Diagnostics of Cancer and Proteomic
	4.6 Prognostics of Cancer and Proteomics
	4.7 Recent Advances in Clinical Proteomics Methodologies
	4.8 Conclusions and Future Directions
	References
5: Microbiome as Cancer Biomarkers
	5.1 Introduction: Microbiome as Cancer Biomarkers
		5.1.1 Intestinal Microbiome: Biomarkers of Colorectal Cancer
			5.1.1.1 Colorectal Cancer
			5.1.1.2 Relationship Between Intestinal Microbiota and Colorectal Cancer
				5.1.1.2.1 Bacteroides fragilis
				5.1.1.2.2 Escherichia coli
				5.1.1.2.3 Fusobacterium
		5.1.2 Intestinal Microbiome: Biomarkers of Pancreatic Cancer
		5.1.3 Intestinal Microbiome: Biomarkers of Liver Cancer
		5.1.4 Intestinal Microbiome: Biomarker of Breast Cancer
		5.1.5 Intestinal and Lung Microbiome: Biomarkers of Lung Cancer
		5.1.6 Intestinal and Gastric Microbiome: Biomarkers of Gastric Cancer
	5.2 Oral Microbiome: Biomarker of Oral and Oropharyngeal Cancers
	5.3 Vaginal Microbiome: Biomarker of Cervical Cancer
	5.4 Gut Microbiome: Markers for Modulation of Immune System and Breast Cancer
	5.5 Uterine Microbiome: Biomarkers of Endometrial Cancer
	5.6 Cutaneous Microbiome: Biomarkers of Skin Cancer
	5.7 Gastrointestinal and Urinary Microbiota: Biomarkers of Prostate Cancer
	5.8 Urinary Microbiome: Biomarkers of Bladder Cancer
	5.9 Conclusions
	References
6: Predictive Biomarkers for Anticancer Drugs
	6.1 Introduction
	6.2 Introduction to Predictive Biomarkers
	6.3 Need for Predictive Biomarkers
	6.4 Identification of Predictive Biomarkers for Anticancer Drugs
	6.5 Tools and Techniques for Predictive Biomarker Identification
		6.5.1 Clinical Trial Designs and Analysis Techniques
		6.5.2 In Situ Hybridization and Immunohisto Chemistry Techniques
		6.5.3 PCR-Based Technologies and Multiplexed Gene Analysis
		6.5.4 Microarray Technology
		6.5.5 Massive Parallel Sequencing
		6.5.6 Flow Cytometry
		6.5.7 Molecular Imaging
		6.5.8 Digital and Computational Pathology
		6.5.9 Bioinformatics and Biostatistical Tools
	6.6 Cancer Biomarkers for Predicting the Response Toward the Treatment
		6.6.1 Circulating Tumor Cells (CTCs)
		6.6.2 Mutations and Polymorphisms
		6.6.3 Methylation
		6.6.4 Gene and miRNA Expression
	6.7 Challenges in Identification and Discovery of Predictive Biomarkers
	6.8 Conclusion
	References
7: Biomarkers in Cancer Survival and Drug Resistance
	7.1 Introduction
	7.2 Role and Uses of Biomarkers in Cancer CellSurvival
		7.2.1 Risk Assessment
		7.2.2 Diagnosis
		7.2.3 Prognosis and Treatment Predictions
		7.2.4 Pharmacodynamics and Pharmacokinetics
		7.2.5 Treatment Response Monitoring
		7.2.6 Recurrence
		7.2.7 Developing Drug Targets
		7.2.8 Surrogate Endpoints
	7.3 Drug Resistance
		7.3.1 Types of Drug Resistance
			7.3.1.1 Intrinsic and Acquired Drug Resistance
			7.3.1.2 Intrinsic Resistance
			7.3.1.3 Acquired Resistance
		7.3.2 Role of MiRNAs in CRC Drug Resistance Regulation
			7.3.2.1 MicroRNAs as Drug Response Noninvasive Biomarkers in CRC
	7.4 Biomarker´s Assessment Methods
	7.5 Therapy-Related Biomarkers
		7.5.1 VEGF/VEGFR-Targeted Therapy
		7.5.2 Genetic Determinants as Susceptibility Biomarkers
	7.6 Guidelines for Tumor Biomarkers
		7.6.1 Alpha-Feto Protein
		7.6.2 Cancer Antigen 125 (CA125)
		7.6.3 Carcinoembryonic Antigen (CEA)
		7.6.4 Human Chorionic Gonadotropin (hCG)
		7.6.5 Prostate Specific Antigen (PSA)
		7.6.6 Estrogen and Progesterone receptors (ERs and PRs)
		7.6.7 Human Epididymal Secretory Protein 4 (HE4)
	7.7 MicroRNAs as Potential Biomarkers
	7.8 Additional Factors Contributing to Drug Resistance and Cancer Survival
		7.8.1 Autophagy and Multidrug Resistance in Cancer
	7.9 Challenges in Clinical Applications of Biomarkers
	References
8: Biomarkers in Tumor Recurrence and Metastasis
	8.1 Introduction
	8.2 Cancer Metastasis and Recurrence
		8.2.1 Cancer Metastasis
			8.2.1.1 Mechanism of Metastatic Cascade
				8.2.1.1.1 Invasion
				8.2.1.1.2 Intravasation
				8.2.1.1.3 Extravasation
			8.2.1.2 Changes in Extracellular Matrix (ECM)
			8.2.1.3 Epithelial to Mesenchymal Transition
			8.2.1.4 Angiogenesis and Lymphomagenesis
	8.3 Biomarkers Related to Cancer Metastasis
		8.3.1 Prostate Cancer
		8.3.2 Breast Cancer
		8.3.3 Lung Cancer
		8.3.4 Colorectal Cancer
	8.4 Cancer Recurrence
		8.4.1 Mechanism of Cancer Recurrence
	8.5 Biomarkers Related to Cancer Recurrence
		8.5.1 Breast Cancer
		8.5.2 Prostate Cancer
		8.5.3 Leukemia
	8.6 Applications of Cancer Biomarkers in Most Common Cancers
		8.6.1 Breast Cancer
		8.6.2 Prostate Cancer
		8.6.3 Ovarian Cancer
	8.7 Conclusion
	8.8 Future Perspectives
	References
9: Biomarkers for Cancer Immunotherapy
	9.1 Introduction
	9.2 Programmed Death-Ligand 1 (PD-L1)
	9.3 Tumor Mutational Burden, Mismatch Repair Deficiency, and Neoantigens
		9.3.1 Concerns About TMB
	9.4 Tumor-Infiltrating Lymphocytes (TILs)
		9.4.1 Effect of Chemokines on TILs
	9.5 Neutrophil-Lymphocyte Ratio (NLR)
	9.6 Lactate Dehydrogenase (LDH)
	9.7 MicroRNA (miRNA)
	9.8 Microbiome
	9.9 Conclusion
	References
10: Role of Biomarkers in Personalized Medicine
	10.1 Introduction
	10.2 Discovery and Validation of Biomarkers
	10.3 Biomarker´s Role in Early Detection and Diagnosis
		10.3.1 B-Cell Lymphoma 2
		10.3.2 B-Cell Lymphoma 6
		10.3.3 Nuclear Factor Kappa-B
		10.3.4 MYC
	10.4 Role of Biomarkers in the Early Detection of Colorectal Cancer (CRC)
	10.5 Potential Biomarkers in Skin Cancer
	10.6 Biomarkers for Asthma
	10.7 Significance of Biomarker Strategies in Drug Development
	10.8 Personalized Medicine in Conventional Therapeutic Approaches
	10.9 Personalized Medicine in Novel Therapeutic Strategies
	10.10 Bioengineering and Personalized Medicine
	10.11 Personalized Cell Therapy and Drug Delivery
	10.12 Concluding Remarks and Future Directions
	References
11: Development of Novel Cancer Biomarkers for Diagnosis and Prognosis
	11.1 Introduction
	11.2 Novel Biomarkers for Diagnosis and Prognosis of Prostate Cancer
		11.2.1 Serum Prostate-Specific Antigen (PSA)
		11.2.2 Field DNA Methylation
		11.2.3 mtDNA Deletion
		11.2.4 Alpha-Methylacyl Coenzyme a Racemase (AMACR)
		11.2.5 Single Nucleotide Polymorphisms (SNPs)
		11.2.6 ERG
		11.2.7 PCA3
		11.2.8 SAP30L-AS1 and SChLAP1
		11.2.9 Multiple Truncated AR Variants (AR-Vs)
		11.2.10 miRNAs
		11.2.11 Circulating Tumor Cells (CTCs)
		11.2.12 Exosomes
	11.3 Novel Biomarkers for Diagnosis and Prognosis of Ovarian Cancer
		11.3.1 CA 125
		11.3.2 Circulating Fetal Protein Alpha-Fetoprotein (RECAF)
		11.3.3 Human Epididymis Protein (HE4)
		11.3.4 Mesothelin
		11.3.5 Kallikrein-Related Peptidases (KLKs)
		11.3.6 Osteopontin
		11.3.7 ApoA1
		11.3.8 Vascular Cell Adhesion Molecules 1 (VCAM-1)
		11.3.9 BRCA1
		11.3.10 P53
		11.3.11 MicroRNAs
	11.4 Novel Biomarkers for Diagnosis and Prognosis of Lungs Cancer
		11.4.1 SAA Proteins
		11.4.2 Epidermal Growth Factor Receptor (EGFR)
		11.4.3 Anaplastic Lymphoma Kinase (ALK)
		11.4.4 Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS)
		11.4.5 Receptor Tyrosine Kinase (ROS1)
		11.4.6 The Human Epidermal Growth Factor Receptor 2 (HER2)
		11.4.7 Phosphatidylinositol-4,5-Bisphosphate 3-Kinase, Catalytic Subunit α (PIK3CA)
		11.4.8 The Neurotrophic Receptor Tyrosine Kinase 1 (NTRK1)
		11.4.9 The Fibroblast Growth Factor Receptor (FGFR)
		11.4.10 The Discoidin Domain Receptor Tyrosine Kinase Two Genes (DDR2)
	11.5 Novel Biomarkers for Diagnosis and Prognosis of Breast Cancer
		11.5.1 Human Epidermal Growth Receptor (HER2)
		11.5.2 ER Expression
		11.5.3 Mib1/Ki-67
		11.5.4 Osteopontin
		11.5.5 Phosphatidylinositol-4,5-Bisphosphate 3-Kinase, Catalytic Subunit α (PIK3CA)
		11.5.6 Tissue Inhibitor of Metalloproteinases-1 (TIMP-1)
		11.5.7 Ferritin Light Chain (FTL)
		11.5.8 Urokinase-Type Plasminogen Activator (uPA)
		11.5.9 Soluble Human Epidermal Growth Factor Receptor 2 (sHER2)
		11.5.10 Mitotic Arrest Deficient Like 1 (MAD1L1)
	11.6 Novel Biomarkers for Diagnosis and Prognosis of Leukemia
		11.6.1 CD123
		11.6.2 Tumor Necrosis Factor Receptor 2 (sTNFR2)
		11.6.3 NPM1 and FLT3 Mutation
		11.6.4 BCR-ABL Tyrosine Kinase Inhibitor (TKI)
		11.6.5 MicroRNAs
		11.6.6 Exosomes
	11.7 Novel Biomarkers for Diagnosis and Prognosis of Lymphoma
		11.7.1 Imaging-Based Biomarkers
		11.7.2 Peripheral Blood-Based Biomarkers
		11.7.3 Circulating Tumor DNA (ctDNA) Biomarkers
		11.7.4 Identification of Biomarkers Using Gene Expression Profiling
	11.8 Novel Biomarkers for Diagnosis and Prognosis of Adenocarcinoma of the Upper Digestive Tract
		11.8.1 Mammalian Target of Rapamycin (mTOR)
		11.8.2 c-Met
		11.8.3 Vascular Endothelial Growth Factor (VEGF)
		11.8.4 Human Epidermal Growth Factor Receptor 2 (HER2) and Epidermal Growth Factor Receptor (EGFR)
		11.8.5 Germline Alterations (Single Nucleotide Polymorphisms (SNPs))
		11.8.6 Chemotherapy-Associated Metabolism Genes
		11.8.7 NF-κB
		11.8.8 Excision Repair Cross-complementing 1 (ERCC1)
		11.8.9 ATP-Binding Cassette Transporters (ABC Transporters)
	11.9 Novel Biomarkers for Pancreatic Disease Treatment and Diagnosis
		11.9.1 Angiogenesis Factors
		11.9.2 Gene Expression and Potential Factors
		11.9.3 ZIP3 (Zinc/Iron-Regulated Transporter-Related Protein 3)
		11.9.4 Cancer Stem Cell Biomarkers
		11.9.5 Saliva Biomarkers
		11.9.6 Pancreatic Juice Biomarkers
		11.9.7 Plasma Biomarkers
		11.9.8 Metabolomic Biomarkers
	11.10 Novel Biomarkers for Diagnosis and Prognosis of Esophageal Cancer
		11.10.1 Mutations and Polymorphisms
		11.10.2 Genomic Instability
		11.10.3 Proteomics Biomarkers
		11.10.4 Epigenetic Biomarkers
		11.10.5 miRNA
		11.10.6 DNA Methylation
		11.10.7 Exosomes
		11.10.8 Circulating Tumor Cells (CTCs)
		11.10.9 Circulating Tumor DNA (ctDNA)
	11.11 Novel Biomarkers for Diagnosis and Prognosis of Colorectal Cancer
		11.11.1 Caudal Type-Homeobox 2
		11.11.2 Cytokeratins (CKs)
		11.11.3 Cadherin 17
		11.11.4 Special AT-Rich Sequence Binding Protein 2 (SATB2)
		11.11.5 GPA33
		11.11.6 Telomerase
		11.11.7 MicroRNA (miRNAs)
		11.11.8 Insulin-Like Growth Factors Binding Protein 2 (IGFBP-2)
		11.11.9 Long Non-coding RNAs (lncRNAs)
		11.11.10 Circulating Cell-Free DNA (cfDNA)
		11.11.11 Microsatellite Instability
		11.11.12 BRAF
		11.11.13 SMAD4
		11.11.14 p53
		11.11.15 Neutrophil-to-Lymphocyte Ratio
		11.11.16 CEA Levels
	11.12 Conclusion
	References
12: Nanotechnology for Cancer Biomarkers
	12.1 Introduction
	12.2 Nanomaterials-Based Biosensing Platforms
		12.2.1 Nanoparticles
		12.2.2 Targeting Ligand-Conjugated NPs for Detection of Biomarkers
		12.2.3 Protein-Conjugated NPs
		12.2.4 Aptamer-Conjugated NPs
		12.2.5 Carbon Nanotubes (CNTs)
		12.2.6 Quantum Dots (QDs)
	12.3 Nanotechnology-Enhanced Detection of Cancer Biomarkers
		12.3.1 Lab-on-a-Chip Technology
		12.3.2 Mass Spectrometry
		12.3.3 Raman Spectroscopy
		12.3.4 Fluorescence and Luminescence Detection
		12.3.5 Electrical and Electrochemical Detection
	12.4 Conclusion
	References