This book reviews how mathematical and computational approaches can be useful to help us understand how killer T-cell responses work to fight viral infections. It also demonstrates, in a writing style that exemplifies the point, that such mathematical and computational approaches are most valuable when coupled with experimental work through interdisciplinary collaborations. Designed to be useful to immunoligists and viroligists without extensive computational background, the book covers a broad variety of topics, including both basic immunological questions and the application of these insights to the understanding and treatment of pathogenic human diseases.

This volume contains collection of Natural Killer Cell methodologies relevant for both basic and translational research. These methodologies present new developments in the natural killer (NK) cell field, such as understanding the influence of NK cells metabolism on its function, identifying complexity of NK cell subsets through mass cytometry, and determining the emergence of memory NK cells in murine model of MCMV infection. Methods that study NK cell migration and cytotoxicity through endpoint analysis or live single cell imaging are also discussed. Chapters also describe methods pertaining to translational application of NK cells, such as ex vivo expansion of NK cells on K562 cell lines genetically modified to express either membrane bound IL-15 or membrane bound IL-21, large scale NK cell culture, current techniques for engineering NK cells to express chimeric antigen receptors or chemokine receptors using retroviral vectors, electroporation of mRNA, and the natural phenomenon of trogocytosis. Written in the highly successful Methods in Molecular Biology series format, these 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 thorough, Natural Killer Cells: Methods and Protocols is a valuable resource for researchers who not only want to understand mechanisms that govern NK cell behavior and diversity, but also for those who want to understand how to systematically evaluate NK cells for adoptive immunotherapy applications.

Natural Killer Cells explains the importance of killer cells and how they are produced. It mentions that the most likely explanation for killer cell production is that they serve as a complementary system for T cells as a primary defense against viruses. However, these cells defend against certain viruses only, such as herpes viruses and influenza viruses. The book also explains the primary functions of killer cells, and it discusses how these cells help recognize damaged tissues, limit further damage to tissues, and regenerate damaged tissues. It discusses how these cells mature and develop, and it covers the different isolation, culture, and propagation methods of these cells. Furthermore, it focuses on the different killer cells that are present in various parts of the human body. The book concludes by explaining that natural killer cells are utilized for clinical therapy of malignancies, and that they have led to positive outcomes in the field of biology and medicine. - Provides a broad, detailed coverage of the biology and interactions of NK cells for students, fellows, scientists, and practitioners - Includes figures, histologic sections, and illustrations of the ontogeny of NK cells

The book shows how mathematical and computational models can be used to study cancer biology. It introduces the concept of mathematical modeling and then applies it to a variety of topics in cancer biology. These include aspects of cancer initiation and progression, such as the somatic evolution of cells, genetic instability, and angiogenesis. The book also discusses the use of mathematical models for the analysis of therapeutic approaches such as chemotherapy, immunotherapy, and the use of oncolytic viruses.

Cancer cell biology research in general, and anti-cancer drug development specifically, still relies on standard cell culture techniques that place the cells in an unnatural environment. As a consequence, growing tumor cells in plastic dishes places a selective pressure that substantially alters their original molecular and phenotypic properties.The emerging field of regenerative medicine has developed bioengineered tissue platforms that can better mimic the structure and cellular heterogeneity of in vivo tissue, and are suitable for tumor bioengineering research. Microengineering technologies have resulted in advanced methods for creating and culturing 3-D human tissue. By encapsulating the respective cell type or combining several cell types to form tissues, these model organs can be viable for longer periods of time and are cultured to develop functional properties similar to native tissues. This approach recapitulates the dynamic role of cell–cell, cell–ECM, and mechanical interactions inside the tumor. Further incorporation of cells representative of the tumor stroma, such as endothelial cells (EC) and tumor fibroblasts, can mimic the in vivo tumor microenvironment. Collectively, bioengineered tumors create an important resource for the in vitro study of tumor growth in 3D including tumor biomechanics and the effects of anti-cancer drugs on 3D tumor tissue. These technologies have the potential to overcome current limitations to genetic and histological tumor classification and development of personalized therapies.

The book aims to provide an introduction to mathematical models that describe the dynamics of tumor growth and the evolution of tumor cells. It can be used as a textbook for advanced undergraduate or graduate courses, and also serves as a reference book for researchers. The book has a strong evolutionary component and reflects the viewpoint that cancer can be understood rationally through a combination of mathematical and biological tools. It can be used both by mathematicians and biologists. Mathematically, the book starts with relatively simple ordinary differential equation models, and subsequently explores more complex stochastic and spatial models. Biologically, the book starts with explorations of the basic dynamics of tumor growth, including competitive interactions among cells, and subsequently moves on to the evolutionary dynamics of cancer cells, including scenarios of cancer initiation, progression, and treatment. The book finishes with a discussion of advanced topics, which describe how some of the mathematical concepts can be used to gain insights into a variety of questions, such as epigenetics, telomeres, gene therapy, and social interactions of cancer cells.