Advances in host genetics and microbiome in colorectal cancer-related phenotypes /

Advances in Host Genetics and Microbiome in Colorectal Cancer-Related Phenotypes, Volume 112 in the Advances in Genetics series, highlights new advances in the field with this new volume presenting interesting chapters on topics such as What we need in colorectal cancer research, and why?, Host Gene...

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Bibliographic Details
Corporate Author:	ScienceDirect (Online service)
Other Authors:	Odriozola Martínez, Adrian (Editor)
Format:	eBook
Language:	English
Published:	[Place of publication not identified] : Academic Press, 2024.
Series:	Advances in Genetics ; volume 112
Subjects:	Colon (Anatomy) > Cancer > Genetic aspects. Rectum > Cancer > Genetic aspects. Colon (Anatomy) > Cancer > Molecular aspects. Rectum > Cancer > Molecular aspects. Gatsrointestinal system > microbiology Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Front Cover
Advances in Genetics
Copyright
Contents
Contributors
Chapter One: What we need in colorectal cancer research, and why?
1 Introduction
2 Key aspects
2.1 Colorectal cancer
2.2 Colorectal cancer classification
2.2.1 -Subtype 1
2.2.2 -Subtype 2
2.2.3 -Subtype 3
2.2.4 -Subtype 4
2.2.5 -Subtype 5
2.2.6 -Subtype 6
2.3 Colorectal cancer epigenetics
2.4 Colorectal cancer metastasis
2.5 Liver metastasis
2.6 Colorectal cancer immunity
2.7 Metabolism
2.8 Colorectal cancer research
2.9 Spatial study of tumor microenvironment
2.10 New era: spatial transcriptomic
2.11 Data mining
2.12 Metabolites in CRC
3 Current limitations
4 Future challenge
5 Conclusion
References
Chapter Two: Host genetics and microbiota data analysis in colorectal cancer research
1 Introduction
2 Analyses of host genetics data analysis in colorectal cancer research
2.1 DNA or RNA sequencing data processing
2.2 Identification of relevant genetic variants in colorectal cancer
2.3 Analysis of gene expression profiles for colorectal cancer management
2.3.1 Obtaining gene expression profiling data from colorectal cancer patients
2.3.2 Identification of differentially expressed genes
2.3.3 Functional enrichment analysis of DEGs
2.3.4 Construction of a protein-protein interaction network to identify causative genes for colorectal cancer
2.3.5 Validation of the key genes causing colorectal cancer
2.3.5.1 Validation of key gene expression
2.3.5.2 Relationship between key gene expression and survival in CRC patients
2.3.5.3 Association of key gene expression with other diseases
2.3.5.4 Association of key gene expression with the levels of immune infiltration in CRC
2.3.5.5 Relationship of key genes expression and CRC immune subtypes.
2.3.5.6 DNA methylation at the CpG sites of key genes
2.3.6 Construction of a key gene-regulatory factor interaction network
2.3.7 Identification of potential drugs
3 Microbiome data analysis in colorectal cancer research
3.1 Bioinformatic analyses of microbiome data
3.1.1 16S rRNA gene-based approach
3.1.2 Metagenomics shotgun sequencing approach
3.2 Microbial community diversities measures
3.2.1 Alpha diversity
3.2.2 Beta diversity
3.3 Univariate correlation and association methods of microbiome data
3.3.1 Pearson's product-moment correlation coefficient (or Pearson's correlation coefficient)
3.3.2 Spearman's rank-order correlation coefficient
3.4 Multivariate correlation and association methods in microbiome data
3.5 Exploratory methods
3.5.1 Graphical summary techniques
3.5.2 Clustering and ordination techniques
3.5.2.1 Clustering
3.5.2.2 Ordination
3.6 Discriminatory methods
3.6.1 Linear discriminant analysis
3.6.2 Linear discriminant analysis effect size
3.7 Classification and regression methods
3.8 Statistical analysis of microbiome data
3.9 Comparison of alpha and beta diversities
3.9.1 Alpha diversity
3.9.2 Beta diversity
3.10 Comparison of present or absent taxon
3.11 Differential abundance analysis
3.11.1 Zero inflation
3.11.1.1 Over-dispersed count model
3.11.1.2 Zero-inflated mixture models
3.11.1.3 Zero-inflated hurdle models
3.11.2 Compositional effects
4 Limitations and future perspectives
5 Conclusions
Funding
References
Chapter Three: Host genetics-associated mechanisms in colorectal cancer
1 Introduction
2 Colonic crypt: Components, organisation and oncogenesis
2.1 Differentiated cells
2.2 Intestinal stem cells
2.3 The importance of the acquisition of oncogenic mutations by a cell.
2.4 How can one mutant cell populate the whole colonic crypt?
2.5 What is the cell type that causes colorectal cancer?
3 Colorectal cancer progression
3.1 Polyp to colorectal cancer sequences: Classic and alternative/closed pathway
3.2 Molecular pathways of colorectal cancer progression
3.2.1 Chromosomal instability
3.2.2 Microsatellite instability
3.2.3 The CpG island methylator phenotype
4 Colorectal cancer classification
4.1 The cancer genome atlas (2012)
4.2 Consensus molecular subtypes (2015)
4.3 Colorectal intrinsic subtypes (2016)
4.4 Single-cell intrinsic CMS (2022)
4.5 Pathway derived subtypes (2024)
5 Limitations and future perspectives
6 Conclusions
Funding
References
Chapter Four: Microbiota-associated mechanisms in colorectal cancer
1 Introduction
2 Role of microbiota in colorectal cancer oncogenesis
3 Gut barrier dysfunction
3.1 Mucus layer
4 Inflammation
4.1 Pathogen recognition receptors
4.2 Pathogen recognition receptors and colorectal cancer
4.3 Inflammation and microbiota species
5 Immune system
5.1 Contextualisation
5.2 Immunoediting hypothesis
5.3 The tumour microenvironment
5.4 Main types of immune cells in the tumour microenvironment of colorectal cancer
5.4.1 Innate immune cells
5.4.1.1 Macrophages
5.4.1.2 Innate lymphoid cells
5.4.1.3 Dendritic cells
5.4.2 Adaptive immune cells
5.4.2.1 Cytotoxic T cells
5.4.2.2 B cells
5.5 Microbiota-immune system interaction
5.5.1 Modulation of innate immunity by the microbiota
5.5.1.1 Microbiota as an adjuvant to dendritic cells
5.5.2 Modulation of adaptive immunity by the microbiota
5.5.2.1 Modulation of immune checkpoints and the apoptotic pathway FAS/FASL
5.5.2.2 Microbial antigens that mimic cancer neoantigens
5.5.2.3 Modulation of T cell differentiation.
5.5.2.4 Modulation of B cell immunity
5.5.3 Interaction of microbiota with stromal cells in the tumour microenvironment
5.5.4 Role of microbiota in colorectal cancer metastasis
6 Biofilm
7 Genotoxins
7.1 Cytolethal distending toxin
7.2 Colibactin
8 Pathogenic bacteria and virulence factors
8.1 Fusobacterium nucleatum
8.2 Streptococcus gallolyticus
8.3 Enterotoxigenic Bacteroides fragilis
8.4 Peptostreptococcus anaerobius
8.5 Clostridioides difficile
8.6 Salmonella typhimurium
9 Oxidative stress
9.1 ROS as a colorectal cancer promotor
9.2 ROS as a suppressor of colorectal cancer
9.3 ROS and microbiota species
10 Current limitations and future challenges
11 Conclusions
References
Chapter Five: Construction of an immune gene expression meta signature to assess the prognostic risk of colorectal cancer patients
1 Introduction
2 Materials and Methods
2.1 Data Resources
3 Meta Gene Prioritisation
4 Prognostic Model
5 Analysis of Clinical Parameters according to risk groups
6 Functional Enrichment
7 Gene Set Enrichment Analysis
8 Analysis of the Immune Microenvironment Infiltration
9 Validation Cohort
10 Protein expression patterns of unfavorable prognostic genes
11 Statistical Analysis
12 Results
12.1 Construction of the Immune-Related meta signature with Prognostic Potential in CRC
13 Construction of the prognostic risk score
14 Association Between Immune-Related Gene Signature and Clinical Parameters
14.1 Survival and Clinicopathological Features Associated with Defined Immune Response Risk Scores
14.2 Functional Enrichment Analysis of CRC Patients by their risk score
15 Gene set enrichment analysis GSEA
16 Estimation of the Stromal and Immune Cells Infiltration Analysis
17 Validation of the immune meta-signature.
18 Protein expression patterns of unfavorable prognostic genes
19 Discussion
19.1 Limitations of Using Gene Expression Biomarkers for Diagnosis and Prognosis in Cancer
20 Future Perspectives
21 Conclusions
References
Chapter Six: Microbiota and detrimental protein derived metabolites in colorectal cancer
1 Introduction
2 Red meat and processed meat in colorectal cancer risk
3 Protein fermentation
4 Gut microbiota metabolic pathways involved in protein fermentation
5 Metabolites
5.1 Ammonia
5.1.1 Ammonia and colorectal cancer
5.2 Polyamines
5.2.1 Polyamines and colorectal cancer
5.2.2 Polyamines and gut microbiota
5.3 Trimethylamine N-oxide (TMAO)
5.3.1 Trimethylamine N-oxide (TMAO) and colorectal cancer
5.3.2 Trimethylamine N-oxide (TMAO) and gut microbiota
5.4 N-nitroso compounds (NOC)
5.4.1 N-nitroso compounds and colorectal cancer
5.4.2 Exposure to N-nitroso compounds: Role of gut microbiota
5.4.3 Microbiota and hydrogen sulphide (H2S)
5.5 Phenolic compounds and indole compounds
5.5.1 Phenolic compounds
5.5.2 Indole compounds
6 Limitations and future perspectives
7 Conclusions
References
Chapter Seven: Microbiota and other detrimental metabolites in colorectal cancer
1 Introduction
2 Heterocyclic amines and polycyclic aromatic hydrocarbons
2.1 Heterocyclic amines
2.2 Polycyclic aromatic hydrocarbons
2.3 Heterocyclic amines and polycyclic aromatic hydrocarbons and their interaction with gut microbiota
3 Heme iron
3.1 Heme iron and gut microbiota
4 Secondary bile acids
4.1 Synthesis and circulation of bile acids
4.2 Metabolism of bile acids by gut microbiota
4.2.1 Deconjugation
4.2.2 7-dehydroxylation
4.2.3 Oxidation and epimerisation of hydroxyl groups at C3, C7 and C12
4.2.4 Esterification and desulfatation.