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Biological Basis of Alcohol-Induced Cancer

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Cover of 'Biological Basis of Alcohol-Induced Cancer'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Alcohol and Breast Cancer: Reconciling Epidemiological and Molecular Data.
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    Chapter 3 Genetic-epidemiological evidence for the role of acetaldehyde in cancers related to alcohol drinking.
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    Chapter 4 Alcohol and Cancer: An Overview with Special Emphasis on the Role of Acetaldehyde and Cytochrome P450 2E1
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    Chapter 5 Implications of Acetaldehyde-Derived DNA Adducts for Understanding Alcohol-Related Carcinogenesis.
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    Chapter 6 The Role of Iron in Alcohol-Mediated Hepatocarcinogenesis
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    Chapter 7 Alcoholic Cirrhosis and Hepatocellular Carcinoma
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    Chapter 8 TLR4-Dependent Tumor-Initiating Stem Cell-Like Cells (TICs) in Alcohol-Associated Hepatocellular Carcinogenesis.
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    Chapter 9 Synergistic Toxic Interactions Between CYP2E1, LPS/TNFα, and JNK/p38 MAP Kinase and Their Implications in Alcohol-Induced Liver Injury.
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    Chapter 10 Understanding the Tumor Suppressor PTEN in Chronic Alcoholism and Hepatocellular Carcinoma.
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    Chapter 11 Alcohol Consumption, Wnt/β-Catenin Signaling, and Hepatocarcinogenesis
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    Chapter 12 Alcohol and HCV: Implications for Liver Cancer.
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    Chapter 13 Application of mass spectrometry-based metabolomics in identification of early noninvasive biomarkers of alcohol-induced liver disease using mouse model.
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    Chapter 14 Alcohol metabolism by oral streptococci and interaction with human papillomavirus leads to malignant transformation of oral keratinocytes.
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    Chapter 15 Genetic Polymorphisms of Alcohol Dehydrogense-1B and Aldehyde Dehydrogenase-2, Alcohol Flushing, Mean Corpuscular Volume, and Aerodigestive Tract Neoplasia in Japanese Drinkers
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    Chapter 16 Acetaldehyde and Retinaldehyde-Metabolizing Enzymes in Colon and Pancreatic Cancers
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    Chapter 17 Alcohol, Carcinoembryonic Antigen Processing and Colorectal Liver Metastases.
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    Chapter 18 Alcohol Consumption and Antitumor Immunity: Dynamic Changes from Activation to Accelerated Deterioration of the Immune System.
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    Chapter 19 A Perspective on Chemoprevention by Resveratrol in Head and Neck Squamous Cell Carcinoma
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    Chapter 20 The Effects of Alcohol and Aldehyde Dehydrogenases on Disorders of Hematopoiesis
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    Chapter 21 The Effect of Alcohol on Sirt1 Expression and Function in Animal and Human Models of Hepatocellular Carcinoma (HCC).
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    Chapter 22 Transgenic mouse models for alcohol metabolism, toxicity, and cancer.
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    Chapter 23 Fetal Alcohol Exposure Increases Susceptibility to Carcinogenesis and Promotes Tumor Progression in Prostate Gland
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    Chapter 24 Fetal alcohol exposure and mammary tumorigenesis in offspring: role of the estrogen and insulin-like growth factor systems.
Attention for Chapter 13: Application of mass spectrometry-based metabolomics in identification of early noninvasive biomarkers of alcohol-induced liver disease using mouse model.
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Chapter title
Application of mass spectrometry-based metabolomics in identification of early noninvasive biomarkers of alcohol-induced liver disease using mouse model.
Chapter number 13
Book title
Biological Basis of Alcohol-Induced Cancer
Published in
Advances in experimental medicine and biology, November 2014
DOI 10.1007/978-3-319-09614-8_13
Pubmed ID
Book ISBNs
978-3-31-909613-1, 978-3-31-909614-8
Authors

Manna SK, Thompson MD, Gonzalez FJ, Soumen K. Manna, Matthew D. Thompson, Frank J. Gonzalez, Manna, Soumen K., Thompson, Matthew D., Gonzalez, Frank J.

Abstract

A rapid, non-invasive urine test for early stage alcohol-induced liver disease (ALD) would permit risk stratification and treatment of high-risk individuals before ALD leads to irreversible liver damage and death. Urinary metabolomic studies were carried out to identify ALD-associated metabolic biomarkers using Ppara-null mouse model that is susceptible to ALD development on chronic alcohol consumption. Two successive studies were conducted to evaluate the applicability of mass spectrometry-based metabolomics in identification of ALD-specific signatures and to examine the robustness of these biomarkers against genetic background. Principal components analysis of ultraperformance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOFMS)-generated urinary metabolic fingerprints showed that alcohol-treated wild-type and Ppara-null mice could be distinguished from control animals. It also showed that a combined endogenous biomarker panel helps to identify subjects with ALD as well as those at risk of developing ALD even without any information on alcohol intake or genetics. Quantitative analysis showed that increased excretion of indole-3-lactic acid and phenyllactic acid was a genetic background-independent signature exclusively associated with ALD pathogenesis in Ppara-null mice that showed liver pathologies similar to those observed in early stages of human ALD. These findings demonstrated that mass spectrometry-based metabolomic analysis could help in the identification of ALD-specific signatures, and that metabolites such as indole-3-lactic acid and phenyllactic acid, may serve as robust noninvasive biomarkers for early stages of ALD.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 21%
Student > Doctoral Student 2 11%
Student > Ph. D. Student 2 11%
Student > Bachelor 1 5%
Student > Master 1 5%
Other 3 16%
Unknown 6 32%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 21%
Medicine and Dentistry 3 16%
Biochemistry, Genetics and Molecular Biology 2 11%
Engineering 2 11%
Social Sciences 1 5%
Other 0 0%
Unknown 7 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 December 2014.
All research outputs
#19,631,015
of 24,143,470 outputs
Outputs from Advances in experimental medicine and biology
#3,537
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Outputs of similar age
#272,063
of 370,459 outputs
Outputs of similar age from Advances in experimental medicine and biology
#174
of 299 outputs
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