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Colorectal Cancer

Overview of attention for book
Cover of 'Colorectal Cancer'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Cell Line Models of Molecular Subtypes of Colorectal Cancer
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    Chapter 2 Dissecting Oncogenic RTK Pathways in Colorectal Cancer Initiation and Progression
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    Chapter 3 Identification of Response Elements on Promoters Using Site-Directed Mutagenesis and Chromatin Immunoprecipitation
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    Chapter 4 Identification and Functional Analysis of Gene Regulatory Sequences Interacting with Colorectal Tumor Suppressors
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    Chapter 5 Methods for In Vivo Functional Studies of Chromatin-Modifying Enzymes in Early Steps of Colon Carcinogenesis
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    Chapter 6 The Colorectal Cancer Microenvironment: Strategies for Studying the Role of Cancer-Associated Fibroblasts
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    Chapter 7 Methods for Assessing Apoptosis and Anoikis in Normal Intestine/Colon and Colorectal Cancer
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    Chapter 8 Molecular Analysis of the Microbiome in Colorectal Cancer
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    Chapter 9 Proteomics Analysis of Colorectal Cancer Cells
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    Chapter 10 Autophagic Flux Assessment in Colorectal Cancer Cells
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    Chapter 11 Classification of Colorectal Cancer in Molecular Subtypes by Immunohistochemistry
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    Chapter 12 Stool DNA Integrity Method for Colorectal Cancer Detection
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    Chapter 13 RT-qPCR for Fecal Mature MicroRNA Quantification and Validation
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    Chapter 14 A Stool Multitarget mRNA Assay for the Detection of Colorectal Neoplasms
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    Chapter 15 Colorectal Cancer Detection Using Targeted LC-MS Metabolic Profiling
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    Chapter 16 Proteomic Profiling for Colorectal Cancer Biomarker Discovery
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    Chapter 17 Tumor-Derived Microparticles to Monitor Colorectal Cancer Evolution
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    Chapter 18 Molecular Testing for the Treatment of Advanced Colorectal Cancer: An Overview
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    Chapter 19 Testing Cell-Based Immunotherapy for Colorectal Cancer
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    Chapter 20 Patient-Derived Xenograft Models of Colorectal Cancer: Procedures for Engraftment and Propagation
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    Chapter 21 Use of Organoids to Characterize Signaling Pathways in Cancer Initiation
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    Chapter 22 Identification of Novel Molecules Targeting Cancer Stem Cells
Attention for Chapter 11: Classification of Colorectal Cancer in Molecular Subtypes by Immunohistochemistry
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Chapter title
Classification of Colorectal Cancer in Molecular Subtypes by Immunohistochemistry
Chapter number 11
Book title
Colorectal Cancer
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7765-9_11
Pubmed ID
Book ISBNs
978-1-4939-7764-2, 978-1-4939-7765-9
Authors

Sanne ten Hoorn, Anne Trinh, Joan de Jong, Lianne Koens, Louis Vermeulen

Abstract

Colorectal cancer (CRC) is a heterogeneous disease, which can be categorized into distinct consensus molecular subtypes (CMSs). These subtypes differ in both clinical as well as biological properties. The gold-standard classification strategy relies on genome-wide expression data, which hampers widespread implementation. Here we describe an immunohistochemical (IHC) Mini Classifier, a practical tool that, in combination with microsatellite instability testing, delivers objective and accurate scoring to classify CRC patients into the main molecular disease subtypes. It is a robust immunohistochemical-based assay containing four specific stainings (FRMD6, ZEB1, HTR2B, and CDX2) in combination with cytokeratin. We also describe an online tool for classification of individual samples based on scoring parameters of these stainings.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 26%
Student > Bachelor 6 13%
Student > Master 4 9%
Researcher 3 7%
Student > Postgraduate 3 7%
Other 4 9%
Unknown 14 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 26%
Medicine and Dentistry 11 24%
Agricultural and Biological Sciences 3 7%
Neuroscience 2 4%
Computer Science 1 2%
Other 1 2%
Unknown 16 35%