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In this book, Dr. Li and his author team plan to emphasize why mouse models are useful in vivo systems for understanding disease mechanisms and developing therapeutic strategies in blood cancers. The authors do not intend to cover all types of blood cancers; instead, they will focus on some major ones such as leukemias and lymphomas. However, the authors will try to cover as much as they can the cancer types and point out that many blood cancers need to be studied in mouse disease models although they are still not available at present. A major focus in the book will be to show what we can or cannot learn from mouse disease models and to also show the critical contributions of mouse models in therapeutic drug development.
Chapter 1 Mouse models of myeloproliferative disease associated with mutant JAK2 tyrosine kinase: insights into pathophysiology and therapy
Richard A. Van Etten Chapter 2 Genetic modeling of human blood cancers in mice Yiguo Hu and Shaoguang Li Chapter 3 Murine Models of Hematopoietic Disease: Pathologic Analysis and Characterization Benjamin H Lee and Jeffery L. Kutok Chapter 4 Mechanisms of DNA double strand break repair in hematopoietic homeostasis and oncogenesis Sarah A. Maas, Lura Brianna Caddle, and Kevin D. Mills Chapter 5 Modeling human leukemia using immune-compromised mice F Ishikawa, Y Saito, and LD Shultz Chapter 6 Dietary Restriction: A model system probing the cell fate decision between cancer and senescence Robin P. Ertl and David E. Harrison Chapter 7 Modeling human Philadelphia chromosome-positive leukemia in mice Shaoguang Li Chapter 8 Mouse Models of Human Mature B Cell and Plasma Cell Neoplasms Siegfried Janz, Herbert C. Morse III, and Michael A. Teitell Chapter 9 Genetic and Virological Predisposition to Pre-B Lymphomagenesis in SL/Kh Hiroshi Hiai Chapter 10 Animal cancer models in anticancer drug discovery and development Francis Lee and Roberto Weinmann Bristol-Myers Squibb Oncology, Princeton, New Jersey, USA Chapter 11 DGL Global Strategies in DNA Microarray Gene Expression Analysis and Data Mining forHuman Blood Cancers Dongguang Li