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Beverly A. Teicher and a panel of leading experts comprehensively describe for the first time in many years the state-of-the-art in animal tumor model research. The wide array of models detailed form the basis for the selection of compounds and treatments that go into clinical testing of patients, and include syngeneic models, human tumor xenograft models, orthotopic models, metastatic models, transgenic models, and gene knockout models. Synthesizing many years experience with all the major in vivo models currently available for the study of malignant disease, Tumor Models in Cancer Research provides preclinical and clinical cancer researchers alike with a comprehensive guide to the selection of these models, their effective use, and the optimal interpretation of their results.
Animal Models in Cancer Drug Discovery brings forward the most cutting-edge developments in tumor model systems for translational cancer research. The reader can find under this one volume virtually all types of existing and emerging tumor models in use by the research community. This book provides a deeper insight on how these newer models could de-risk modern drug discovery. Areas covered include up to date information on latest organoid derived models and newer genetic models. Additionally, the book discusses humanized animal tumor models for cancer immunotherapy and how they leverage personalized therapies. The chapter on larger animal, canine models and their use in and their use in pre-investigational new drug (pre-IND) development makes the volume unique. Unlike before, the incorporation of several simplified protocols, breeding methodologies, handling and assessment procedures to study drug intervention makes this book a must read. Animal Models in Cancer Drug Discovery is a valuable resource for basic and translational cancer researchers, drug discovery researchers, contract research organizations, and knowledge seekers at all levels in the biomedical field.
This volume provides a series of review articles that capture the advances in using the fruit fly, Drosophila melanogaster, model system to address a wide range of cancer-related topics. Articles in this book provide case studies that shed light on the intricate cellular and molecular mechanisms underlying tumor formation and progression. Readers will discover the beauty of the fly model’s genetic simplicity and the vast arsenal of powerful genetic tools enabling its efficient and adaptable use. This model organism has provided a unique opportunity to address questions regarding cancer initiation and development that would be extremely challenging in other model systems. This book provides a useful resource for a researcher who wishes to learn about and apply the Drosophila model to tackle fundamental questions in cancer biology, and to find new ways to fight against this devastating disease.
Mathematical modeling, analysis and simulation are set to play crucial roles in explaining tumor behavior, and the uncontrolled growth of cancer cells over multiple time and spatial scales. This book, the first to integrate state-of-the-art numerical techniques with experimental data, provides an in-depth assessment of tumor cell modeling at multiple scales. The first part of the text presents a detailed biological background with an examination of single-phase and multi-phase continuum tumor modeling, discrete cell modeling, and hybrid continuum-discrete modeling. In the final two chapters, the authors guide the reader through problem-based illustrations and case studies of brain and breast cancer, to demonstrate the future potential of modeling in cancer research. This book has wide interdisciplinary appeal and is a valuable resource for mathematical biologists, biomedical engineers and clinical cancer research communities wishing to understand this emerging field.
The laboratory mouse is an important model for addressing questions in cancer biology. In recent years, the questions have become more refined, and mouse models are increasingly being used to develop and test cancer therapeutics. Thus, the need for more sophisticated and clinically relevant mouse models has grown, as has the need for innovative tools to analyze and validate them. This laboratory manual provides cutting-edge methods for generating and characterizing mouse models that accurately recapitulate many features of human cancer. The contributors describe strategies for producing genetic models, including transgenic germline models, gene knockouts and knockins, and conditional and inducible systems, as well as models derived using transposon-based insertional mutagenesis, RNA interference, viral-mediated gene delivery, and chemical carcinogens. Tissue recombination, organ reconstitution, and transplantation methods to develop chimeric, allograft, and xenograft models are covered. Approaches to characterize tumor development, progression, and metastasis in these models using state-of-the-art imaging, histopathological, surgical, and other techniques are also included. Other chapters cover the use of mouse models to test and optimize drugs in pre-, co-, and post-clinical trials. An appendix specifically addresses the use of mouse cancer models in translational studies and the integration of mouse and human clinical investigations. This manual is therefore an indispensable laboratory resource for all researchers, from the graduate level upwards, who study cancer and its treatment.
Cancer is a complex disease process that spans multiple scales in space and time. Driven by cutting-edge mathematical and computational techniques, in silico biology provides powerful tools to investigate the mechanistic relationships of genes, cells, and tissues. It enables the creation of experimentally testable hypotheses, the integration of dat
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.
The onset of cancer presents one of the most fundamental problems in modern biology. In Dynamics of Cancer, Steven Frank produces the first comprehensive analysis of how particular genetic and environmental causes influence the age of onset. The book provides a unique conceptual and historical framework for understanding the causes of cancer and other diseases that increase with age. Using a novel quantitative framework of reliability and multistage breakdown, Frank unifies molecular, demographic, and evolutionary levels of analysis. He interprets a wide variety of observations on the age of cancer onset, the genetic and environmental causes of disease, and the organization of tissues with regard to stem cell biology and somatic mutation. Frank uses new quantitative methods to tackle some of the classic problems in cancer biology and aging: how the rate of increase in the incidence of lung cancer declines after individuals quit smoking, the distinction between the dosage of a chemical carcinogen and the time of exposure, and the role of inherited genetic variation in familial patterns of cancer. This is the only book that presents a full analysis of the age of cancer onset. It is a superb teaching tool and a rich source of ideas for new and experienced researchers. For cancer biologists, population geneticists, evolutionary biologists, and demographers interested in aging, this book provides new insight into disease progression, the inheritance of predisposition to disease, and the evolutionary processes that have shaped organismal design.
This book presents applications of geometric optimal control to real life biomedical problems with an emphasis on cancer treatments. A number of mathematical models for both classical and novel cancer treatments are presented as optimal control problems with the goal of constructing optimal protocols. The power of geometric methods is illustrated with fully worked out complete global solutions to these mathematically challenging problems. Elaborate constructions of optimal controls and corresponding system responses provide great examples of applications of the tools of geometric optimal control and the outcomes aid the design of simpler, practically realizable suboptimal protocols. The book blends mathematical rigor with practically important topics in an easily readable tutorial style. Graduate students and researchers in science and engineering, particularly biomathematics and more mathematical aspects of biomedical engineering, would find this book particularly useful.
Continuous cell lines derived from human cancers are the most widely used resource in laboratory-based cancer research. The first 3 volumes of this series on Human Cell Culture are devoted to these cancer cell lines. The chapters in these first 3 volumes have a common aim. Their purpose is to address 3 questions of fundamental importance to the relevance of human cancer cell lines as model systems of each type of cancer: 1. Do the cell lines available accurately represent the clinical presentation? 2. Do the cell lines accurately represent the histopathology of the original tumors? 3. Do the cell lines accurately represent the molecular genetics of this type of cancer? The cancer cell lines available are derived, in most cases, from the more aggressive and advanced cancers. There are few cell lines derived from low grade organ-confined cancers. This gap can be filled with conditionally immortalized human cancer cell lines. We do not know why the success rate for establishing cell lines is so low for some types of cancer and so high for others. The histopathology of the tumor of origin and the extent to which the derived cell line retains the differentiated features of that tumor are critical. The concept that a single cell line derived from a tumor at a particular site is representative of tumors at that site is naïve and misleading.