Understanding CLL biology through mouse models of human genetics

利用小鼠遗传模型了解慢性淋巴细胞白血病生物学

阅读:1

Abstract

Rapid advances in large-scale next-generation sequencing studies of human samples have progressively defined the highly heterogeneous genetic landscape of chronic lymphocytic leukemia (CLL). At the same time, the numerous challenges posed by the difficulties in rapid manipulation of primary B cells and the paucity of CLL cell lines have limited the ability to interrogate the function of the discovered putative disease "drivers," defined in human sequencing studies through statistical inference. Mouse models represent a powerful tool to study mechanisms of normal and malignant B-cell biology and for preclinical testing of novel therapeutics. Advances in genetic engineering technologies, including the introduction of conditional knockin/knockout strategies, have opened new opportunities to model genetic lesions in a B-cell-restricted context. These new studies build on the experience of generating the MDR mice, the first example of a genetically faithful CLL model, which recapitulates the most common genomic aberration of human CLL: del(13q). In this review, we describe the application of mouse models to the studies of CLL pathogenesis and disease transformation from an indolent to a high-grade malignancy (ie, Richter syndrome [RS]) and treatment, with a focus on newly developed genetically inspired mouse lines modeling recurrent CLL genetic events. We discuss how these novel mouse models, analyzed using new genomic technologies, allow the dissection of mechanisms of disease evolution and response to therapy with greater depth than previously possible and provide important insight into human CLL and RS pathogenesis and therapeutic vulnerabilities. These models thereby provide valuable platforms for functional genomic analyses and treatment studies.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。