Tumor Models in Cancer Research
Progress in a given field is often dependent upon the development of appropriate, accurate models. In modern times, cancer research has been engaged in a focused search for such models for more than 50 years. The foremost problem in developing such models is that cancer is many, many diseases arising from nearly every tissue and metastasizing too many.

The mutual needs for as large an array as possible of tumor types and the expansion of true inbred strains of mice to carry these tumors led to the identification of mutant mice with characteristics of deficient immunity suitable for the growth of human tumors as xenografts. The most frequently used of these mutant mouse strains are nude mice and SCID mice. Human tumor xenograft models were established from the many human tumor cell lines developed in the 1970s and 1980s and from fresh tumor explants. Since techniques for genetic manipulation have become more routine, animals expressing “oncogenes” or missing “tumor suppressor” genes have been developed, allowing a new level of understanding of the process of malignancy and new models for testing anticancer agent efficacy. Through the use of these techniques for some diseases and targets, it has been possible to establish specific animal models.
about the book
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.
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