Shifting the focus of zebrafish toward a model of the tumor microenvironment.
Shifting the focus of zebrafish toward a model of the tumor microenvironment.
复制标题
将斑马鱼的重点转移到肿瘤微环境的模型上。
DOI：
10.7554/elife.69703
复制
发表时间：
2022-12-20
期刊：
影响因子：
7.7
通讯作者：
White, Richard M.
中科院分区：
文献类型：
--
作者：
Weiss, Joshua M.;Lumaquin-Yin, Dianne;Montal, Emily;Suresh, Shruthy;Leonhardt, Carl S.;White, Richard M.
癌细胞存在于一个复杂的生态系统中，在肿瘤微环境（TME）中还有许多其他细胞类型。该肿瘤/TME生态系统的组成在每个解剖部位都会有所不同，并影响诸如起始、转移和耐药性等表型。对肿瘤和 TME 之间大量细胞间相互作用的机械理解需要模型，使我们能够表征并从遗传上扰乱这种复杂性。斑马鱼是针对此问题进行优化的模型系统，因为现有大量特定于细胞类型的驱动程序可以标记 TME 中的几乎任何细胞。这些包括基质细胞、免疫细胞和组织驻留正常细胞。这些细胞类型特异性启动子/增强子可用于驱动荧光团以促进成像，也可用于驱动 CRISPR 盒以促进扰动。斑马鱼的一个主要优点是可以轻松地在同一动物内同时研究大量 TME 细胞类型。虽然这些特征使斑马鱼非常适合研究 TME，但该模型具有重要的局限性，我们也对此进行了讨论。在这篇综述中，我们描述了使用斑马鱼癌症模型研究 TME 的现有工具集，并强调了通过利用这一强大资源可以获得的独特生物学见解。
Cancer cells exist in a complex ecosystem with numerous other cell types in the tumor microenvironment (TME). The composition of this tumor/TME ecosystem will vary at each anatomic site and affects phenotypes such as initiation, metastasis, and drug resistance. A mechanistic understanding of the large number of cell-cell interactions between tumor and TME requires models that allow us to both characterize as well as genetically perturb this complexity. Zebrafish are a model system optimized for this problem, because of the large number of existing cell-type-specific drivers that can label nearly any cell in the TME. These include stromal cells, immune cells, and tissue resident normal cells. These cell-type-specific promoters/enhancers can be used to drive fluorophores to facilitate imaging and also CRISPR cassettes to facilitate perturbations. A major advantage of the zebrafish is the ease by which large numbers of TME cell types can be studied at once, within the same animal. While these features make the zebrafish well suited to investigate the TME, the model has important limitations, which we also discuss. In this review, we describe the existing toolset for studying the TME using zebrafish models of cancer and highlight unique biological insights that can be gained by leveraging this powerful resource.
影响因子：
9.8
作者：
van der Weyden L;Karp NA;Swiatkowska A;Adams DJ;Speak AO
通讯作者：
Speak AO