Christopher R. Clark, Wilaiwan DuRose, and Timothy K. Starr
Part I: Cancer Gene discovery In Silico based on Sequencing Data
2. Identification of Cancer Driver Genes from a Custom Set of Next Generation Sequencing Data
Shu-Hsuan Liu and Wei-Chung Cheng
3. Cancer Gene Discovery by Network Analysis of Somatic Mutations using the MUFFINN Server
Heonjong Han, Ben Lehner, and Insuk Lee
4. Identifying Driver Interfaces Enriched for Somatic Missense Mutations in Tumors
Kivilcim Ozturkand Hannah Carter
5. Identification of Cancer Genes Based on de novo Transposon Insertion Site Analysis using RNA and DNA Sequencing
Aaron Sarver
PartII: Cancer Gene Discovery using Cell and Organoid Systems
6. A Cell-based Method for Identification of Chemotherapy Resistance Cancer Genes
Raffaele Hellweg, Ashley Mooneyham, and Martina Bazzaro
7. Engineering a Bioartificial Human Colon Model through Decellularization and Recellularization
Huanhuan Joyce Chen and Michael L. Shuler
8. Mutagenesis Screens for Prostate Cancer using Replication-Incompetent Lentiviral Vectors
Grant D. Trobridge
9. Arrayed shRNA Screening to Identify Suppressors of Anchorage-independent Growth
Ugur Eskiocak
10. Genome-wide CRISPR/Cas9 Screening for Identification of Cancer Genes in Cell Lines
Charles H. Adelmann, Tim Wang, David M. Sabatini, and Eric S.Lander
11. CRISPR/Cas9 Based Positive Screens for Cancer Related Traits
Nicholas J. Slipek, Jyotika Varshney, and David A. Largaespada
12. Ex vivo Transposon-Mediated Genetic Screens for Cancer Gene Discovery
Kathryn A. O’Donnell, Yabin Guo, Shruthy Suresh, Barrett L. Updegraff, and Xiaorong Zhou
Part III: Cancer Gene Discovery using Animal Models
13. Cancer Gene Discovery Utilizing SleepingBeauty Transposon Mutagenesis
Kelsie L. Becklin, Branden A. Smeester, and Branden S. Moriarity
14. PiggyBac Transposon-based Insertional Mutagenesis in Mice
Mathias J. Friedrich, Iraad F. Bronner, Pentao Liu, Allan Bradley, and Roland Rad
15. Liver-specific Delivery of Sleeping Beauty Transposon System by Hydrodynamic Injection for Cancer Gene Validation
Amy P. Chiu and Vincent W. Keng
16. Engineering Large Genomic Rearrangement in Mouse Embryonic Stem Cell for Cancer Gene Discovery
Yuen-Yi Tsengand Anindya Bagchi
This book presents protocols for identification of genetic drivers of cancer. Chapters guide readers through a brief history of cancer gene discovery, in silico approaches, in vitro approaches, and in vivo approaches using forward genetic screens in mice. 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 cutting-edge, Cancer Driver Genes: Methods and Protocols aims to provide protocols that will be used and adapted by cancer researchers to expand the knowledge base of molecular mechanisms contributing to initiation, progression, and metastasis of cancer.