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Dissecting metastasis using preclinical models and methods

delete2023-05-03
delete27
PRE
AI
J
Jess D. Hebert
J
Joel W. Neal
M
Monte M. Winslow *
DOI:10.1038/s41568-023-00568-4delete
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摘要

摘要

En 中文
Metastasis has long been understood to lead to the overwhelming majority of cancer-related deaths. However, our understanding of the metastatic process, and thus our ability to prevent or eliminate metastases, remains frustratingly limited. This is largely due to the complexity of metastasis, which is a multistep process that likely differs across cancer types and is greatly influenced by many aspects of the in vivo microenvironment. In this Review, we discuss the key variables to consider when designing assays to study metastasis: which source of metastatic cancer cells to use and where to introduce them into mice to address different questions of metastasis biology. We also examine methods that are being used to interrogate specific steps of the metastatic cascade in mouse models, as well as emerging techniques that may shed new light on previously inscrutable aspects of metastasis. Finally, we explore approaches for developing and using anti-metastatic therapies, and how mouse models can be used to test them. Although metastasis is the leading cause of cancer-related deaths, our understanding of the process is limited. In this Review, Hebert et al. discuss the key features of various models of metastasis, highlighting their advantages and disadvantages for further dissecting mechanisms of metastasis and developing metastasis-targeted therapies.
Keyword:
BREAST-CANCER METASTASIS
CELL LUNG-CANCER
CIRCULATING TUMOR-CELLS
SEROUS OVARIAN-CANCER
MOUSE MODEL
COLORECTAL-CANCER
IN-VIVO
XENOGRAFT MODELS
BONE METASTASIS
ORTHOTOPIC TRANSPLANTATION

期刊

Nature Reviews Cancer 封面图
Nature Reviews Cancer
IF:
66.8
论文数:
3.8K
被引数:
6.0W

机构

S
Stanford University
学者数:
9.6W
论文数: 8.2W
被引数: 17.0W
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