Abstract
In the past decades, cancer therapies are evolved from a non-specific approach to a precise and accurate therapy. Precision (or personalized) cancer therapy, in which a patient’s own tumor information is used to help make a diagnosis, a treatment plan, or a prognosis, provides an encouraging solution to overcome the failure of current conventional treatments. Relevant preclinical animal models are critical to translate this concept into clinical application. In this chapter, we overviewed how immunodeficient mouse strains were contributed to the development of personalized immune-oncology therapy, so-called personalized I/O therapy. Patient-derived xenograft (PDX) mice, which are generated by directly engrafting tumor tissues into immunodeficient mice, can largely retain the genetics of the human tumors. PDX models are a versatile platform for the study of tumor biology, and are highly predictive of patients’ responses to many cancer therapies. The human immune-tumor interaction can be further replicated in the PDX-human immune system (HIS) mice after a transplantation of PDX mice with allogeneic or autologous immune cells. This PDX-HIS dual-humanized model represents a valuable avatar of patients in clinical decision-making for I/O therapy. Many novel strategies based on personalized I/O treatment are either under preclinical study or in clinical trials, and represent our hope for fighting the cancer in the future.
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The study was supported by Ministry of Science and Technology, Taiwan MOST-110-2314-B-006-086-MY3, MOST-110-2314-B-048-MY2, and the Center of Applied Nanomedicine, National Cheng Kung University from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan to T.W.W.
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Wang, JL., Ma, WH., Wong, TW., Yu, CK. (2023). Personalized Immuno-Oncology with Immunodeficiency Mouse Models. In: Rezaei, N. (eds) Cancer Research: An Interdisciplinary Approach. Interdisciplinary Cancer Research, vol 1. Springer, Cham. https://doi.org/10.1007/16833_2023_133
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