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Bioinformatics for Cancer Immunotherapy

Methods and Protocols

  • Book
  • © 2020

Overview

Editors:
  1. Sebastian Boegel

    1. Mainz, Germany

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  • Includes cutting-edge methods and protocols
  • Provides step-by-step detail essential for reproducible results
  • Contains key notes and implementation advice from the experts

Part of the book series: Methods in Molecular Biology (MIMB, volume 2120)

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Table of contents (20 protocols)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Bioinformatics for Cancer Immunotherapy

    • Christoph Holtsträter, Barbara Schrörs, Thomas Bukur, Martin Löwer
    Pages 1-9

  3. An Individualized Approach for Somatic Variant Discovery

    • Minghao Li, Ting He, Chen Cao, Quan Long
    Pages 11-36

  4. Ensemble-Based Somatic Mutation Calling in Cancer Genomes

    • Weitai Huang, Yu Amanda Guo, Mei Mei Chang, Anders Jacobsen Skanderup
    Pages 37-46

  5. SomaticSeq: An Ensemble and Machine Learning Method to Detect Somatic Mutations

    • Li Tai Fang
    Pages 47-70

  6. HLA Typing from RNA Sequencing and Applications to Cancer

    • Rose Orenbuch, Ioan Filip, Raul Rabadan
    Pages 71-92

  7. Rapid High-Resolution Typing of Class I HLA Genes by Nanopore Sequencing

    • Chang Liu, Rick Berry
    Pages 93-99

  8. HLApers: HLA Typing and Quantification of Expression with Personalized Index

    • Vitor R. C. Aguiar, Cibele Masotti, Anamaria A. Camargo, Diogo Meyer
    Pages 101-112

  9. High-Throughput MHC I Ligand Prediction Using MHCflurry

    • Timothy O’Donnell, Alex Rubinsteyn
    Pages 113-127

  10. In Silico Prediction of Tumor Neoantigens with TIminer

    • Alexander Kirchmair, Francesca Finotello
    Pages 129-145

  11. OpenVax: An Open-Source Computational Pipeline for Cancer Neoantigen Prediction

    • Julia Kodysh, Alex Rubinsteyn
    Pages 147-160

  12. Improving MHC-I Ligand Identification by Incorporating Targeted Searches of Mass Spectrometry Data

    • Prathyusha Konda, J. Patrick Murphy, Shashi Gujar
    Pages 161-171

  13. The SysteMHC Atlas: a Computational Pipeline, a Website, and a Data Repository for Immunopeptidomic Analyses

    • Wenguang Shao, Etienne Caron, Patrick Pedrioli, Ruedi Aebersold
    Pages 173-181

  14. Identification of Epitope-Specific T Cells in T-Cell Receptor Repertoires

    • Sofie Gielis, Pieter Moris, Wout Bittremieux, Nicolas De Neuter, Benson Ogunjimi, Kris Laukens et al.
    Pages 183-195

  15. Modeling and Viewing T Cell Receptors Using TCRmodel and TCR3d

    • Ragul Gowthaman, Brian G. Pierce
    Pages 197-212

  16. In Silico Cell-Type Deconvolution Methods in Cancer Immunotherapy

    • Gregor Sturm, Francesca Finotello, Markus List
    Pages 213-222

  17. Immunedeconv: An R Package for Unified Access to Computational Methods for Estimating Immune Cell Fractions from Bulk RNA-Sequencing Data

    • Gregor Sturm, Francesca Finotello, Markus List
    Pages 223-232

  18. EPIC: A Tool to Estimate the Proportions of Different Cell Types from Bulk Gene Expression Data

    • Julien Racle, David Gfeller
    Pages 233-248

  19. Computational Deconvolution of Tumor-Infiltrating Immune Components with Bulk Tumor Gene Expression Data

    • Bo Li, Taiwen Li, Jun S. Liu, X. Shirley Liu
    Pages 249-262

  20. Cell-Type Enrichment Analysis of Bulk Transcriptomes Using xCell

    • Dvir Aran
    Pages 263-276
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Keywords

About this book

This volume focuses on a variety of in silico protocols of the latest bioinformatics tools and computational pipelines developed for neo-antigen identification and immune cell analysis from high-throughput sequencing data for cancer immunotherapy. The chapters in this book cover topics that discuss the two emerging concepts in recognition of tumor cells using endogenous T cells: cancer vaccines against neo-antigens presented on HLA class I and II alleles, and checkpoint inhibitors. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Cutting-edge and authoritative, Bioinformatics for Cancer Immunotherapy: Methods and Protocols is a valuable research tool for any scientist and researcher interested in learning more about this exciting and developing field.


Editors and Affiliations

  • Mainz, Germany

    Sebastian Boegel

Bibliographic Information

  • Book Title: Bioinformatics for Cancer Immunotherapy

  • Book Subtitle: Methods and Protocols

  • Editors: Sebastian Boegel

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-0716-0327-7

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2020

  • Hardcover ISBN: 978-1-0716-0326-0Published: 03 March 2020

  • Softcover ISBN: 978-1-0716-0329-1Published: 03 March 2021

  • eBook ISBN: 978-1-0716-0327-7Published: 02 March 2020

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 1

  • Number of Pages: XII, 304

  • Number of Illustrations: 9 b/w illustrations, 48 illustrations in colour

  • Topics: Cancer Research, Bioinformatics, Immunology

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