Main description:

This book comprises protocols describing systems biology methodologies and computational tools, offering a variety of ways to analyze different types of high-throughput cancer data. Chapters give an overview over data types available in large-scale data repositories and state-of-the-art methods used in the field of cancer systems biology. 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.

Authoritative and practical, Cancer Systems Biology : Methods and Protocols aims to ensure successful results in the further study of this vital field.

The chapters "Identifying Genetic Dependencies in Cancer by Analyzing siRNA Screens in Tumor Cell Line Panels", "Perseus: A Bioinformatics Platform for Integrative Analysis of Proteomics Data in Cancer Research" and "Phosphoproteomics-based Profiling of Kinase Activities in Cancer Cells" are available open access under a CC BY 4.0 license via link.springer.com.

Contents:

Part I: Systems Biology of the Cancer Genetic and Epigenetic Landscape

1. Detection of Combinatorial Mutational Patterns in Human Cancer Genomes by Exclusivity Analysis

Hua Tan and Xiaobo Zhou

2. Discovering Altered Regulation and Signaling Through Network-based Integration of Transcriptomic, Epigenomic, and Proteomic Tumor Data

Amanda J. Kedaigle and Ernest Fraenkel

3. Analyzing DNA Methylation Patterns during Tumor Evolution

Heng Pan and Olivier Elemento

4. MicroRNA Networks in Breast Cancer CellsAndliena Tahiri, and Miriam R. Aure, and Vessela N. Kristensen

5. Identifying Genetic Dependencies in Cancer by Analyzing siRNA Screens in Tumor Cell Line Panels

James Campbell, Colm J. Ryan, and Christopher J. Lord

Part II: Systems Analyses of Signaling Networks in Cancer Cells

6. Phosphoproteomics-based Profiling of Kinase Activities in Cancer Cells

Jakob Wirbel, Pedro Cutillas, and Julio Saez-Rodriguez

7. Perseus: A Bioinformatics Platform for Integrative Analysis of Proteomics Data in Cancer Research

Stefka Tyanova and Juergen Cox

8. Quantitative Analysis of Tyrosine Kinase Signaling Across Differentially Embedded Human Glioblastoma Tumors

Hannah Johnson and Forest M White

9. Prediction of Clinical Endpoints in Breast Cancer using NMR Metabolic ProfilesLeslie R. Euceda, Tonje H. Haukaas, Tone F. Bathen, and Guro F. Giskeodegard

Part III: Systems Biology of Metastasis and Tumor/ Microenvironment Interactions

10. Stochastic and Deterministic Models for the Metastatic Emission Process: Formalisms and Crosslinks

Christophe Gomez and Niklas Hartung

11. Mechanically Coupled Reaction-Diffusion Model to Predict Glioma Growth: Methodological Details

David A. Hormuth II, Stephanie L. Eldridge, Jared A. Weis, Michael I. Miga, and Thomas E. Yankeelov

12. Profiling Tumor Infiltrating Immune Cells with CIBERSORTBinbin Chen, Michael S. Khodadoust, Chih Long Liu, Aaron M. Newman, and Ash A. Alizadeh

13. Systems Biology Approaches in Cancer Pathology

Aaron DeWard and Rebecca J. Critchley-Thorne

Part IV: Modeling Drug Responses in Cancer Cells

14. Bioinformatics Approaches to Predict Drug Responses from Genomic Sequencing

Neel Madhukar and Olivier Elemento

15. A Robust Optimization Approach to Cancer Treatment under Toxicity Uncertainty

Junfeng Zhu, Hamidreza Badri, and Kevin Leder

16. Modeling of Interactions between Cancer Stem Cells and their Microenvironment: Predicting Clinical Response

Mary E. Sehl and Max S. Wicha

17. Methods for High-throughput Drug Combination Screening and Synergy Scoring

Liye He, Evgeny Kulesskiy, Jani Saarela, Laura Turunen, Krister Wennerberg, Tero Aittokallio, and Jing Tang