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Biomarkers for Immunotherapy of Cancer

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Cover of 'Biomarkers for Immunotherapy of Cancer'

Table of Contents

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    Book Overview
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    Chapter 1 Status of Immune Oncology: Challenges and Opportunities
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    Chapter 2 Immunological Targets for Immunotherapy: Inhibitory T Cell Receptors
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    Chapter 3 Measuring Tumor Mutational Burden Using Whole-Exome Sequencing
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    Chapter 4 Germline Genetics in Immuno-oncology: From Genome-Wide to Targeted Biomarker Strategies
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    Chapter 5 Detection of Microsatellite Instability Biomarkers via Next-Generation Sequencing
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    Chapter 6 Genetic Instability Markers in Cancer
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    Chapter 7 Validation of Circulating Tumor DNA Assays for Detection of Metastatic Melanoma
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    Chapter 8 Techniques Associated with Exosome Isolation for Biomarker Development: Liquid Biopsies for Ovarian Cancer Detection
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    Chapter 9 Identifying MicroRNA Pathway Variants as Biomarkers of Patient Selection for Immune Therapy
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    Chapter 10 Histone Modifications as Biomarkers for Immunotherapy
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    Chapter 11 Functional Genome Profiling to Understand Cancer Immune Responsiveness
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    Chapter 12 Using RNA Sequencing to Characterize the Tumor Microenvironment
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    Chapter 13 Development of Gene Expression-Based Biomarkers on the nCounter® Platform for Immuno-Oncology Applications
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    Chapter 14 The CRISPR System and Cancer Immunotherapy Biomarkers
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    Chapter 15 HLA Class I Antigen Processing Machinery Defects in Cancer Cells—Frequency, Functional Significance, and Clinical Relevance with Special Emphasis on Their Role in T Cell-Based Immunotherapy of Malignant Disease
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    Chapter 16 High-Parameter Immune Profiling with CyTOF
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    Chapter 17 The Adaptome as Biomarker for Assessing Cancer Immunity and Immunotherapy
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    Chapter 18 Single-Molecule Arrays for Ultrasensitive Detection of Blood-Based Biomarkers for Immunotherapy
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    Chapter 19 Single-Cell Multiplexed Proteomics on the IsoLight Resolves Cellular Functional Heterogeneity to Reveal Clinical Responses of Cancer Patients to Immunotherapies
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    Chapter 20 Methods to Detect Immunogenic Cell Death In Vivo
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    Chapter 21 Overview of Tissue Imaging Methods
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    Chapter 22 Multiplex Immunofluorescence Assays
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    Chapter 23 Multiplexed Immunohistochemical Consecutive Staining on Single Slide (MICSSS): Multiplexed Chromogenic IHC Assay for High-Dimensional Tissue Analysis
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    Chapter 24 Cyclic Multiplexed-Immunofluorescence (cmIF), a Highly Multiplexed Method for Single-Cell Analysis
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    Chapter 25 High-Plex Spatially Resolved RNA and Protein Detection Using Digital Spatial Profiling: A Technology Designed for Immuno-oncology Biomarker Discovery and Translational Research
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    Chapter 26 The InSituPlex® Staining Method for Multiplexed Immunofluorescence Cell Phenotyping and Spatial Profiling of Tumor FFPE Samples
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    Chapter 27 Microbiome as an Immunological Modifier
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    Chapter 28 Systems Biology for Multiplatform Data Integration: An Overview
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    Chapter 29 Bioinformatics Tools and Resources for Cancer Immunotherapy Study
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    Chapter 30 Multiplatform Integrative Analysis of Immunogenomic Data for Biomarker Discovery
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    Chapter 31 Translating Immuno-oncology Biomarkers to Diagnostic Tests: A Regulatory Perspective
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Title
Biomarkers for Immunotherapy of Cancer
Published by
Springer New York, January 2020
DOI 10.1007/978-1-4939-9773-2
ISBNs
978-1-4939-9772-5, 978-1-4939-9773-2
Editors

Magdalena Thurin, Alessandra Cesano, Francesco M. Marincola

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X Demographics

The data shown below were collected from the profiles of 55 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 3%
Student > Master 1 2%
Unknown 56 95%
Readers by discipline Count As %
Medicine and Dentistry 2 3%
Biochemistry, Genetics and Molecular Biology 1 2%
Unknown 56 95%