Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, Canada.
Department of Human Genetics, McGill University, Montreal, Canada.
Cancer Res. 2021 Oct 15;81(20):5147-5160. doi: 10.1158/0008-5472.CAN-20-1518. Epub 2021 Jul 23.
Ovarian cancer is the most lethal gynecologic cancer to date. High-grade serous ovarian carcinoma (HGSOC) accounts for most ovarian cancer cases, and it is most frequently diagnosed at advanced stages. Here, we developed a novel strategy to generate somatic ovarian cancer mouse models using a combination of electroporation and CRISPR-Cas9-mediated genome editing. Mutation of tumor suppressor genes associated with HGSOC in two different combinations ( with and without resulted in successfully generation of HGSOC, albeit with different latencies and pathophysiology. Implementing Cre lineage tracing in this system enabled visualization of peritoneal micrometastases in an immune-competent environment. In addition, these models displayed copy number alterations and phenotypes similar to human HGSOC. Because this strategy is flexible in selecting mutation combinations and targeting areas, it could prove highly useful for generating mouse models to advance the understanding and treatment of ovarian cancer. SIGNIFICANCE: This study unveils a new strategy to generate genetic mouse models of ovarian cancer with high flexibility in selecting mutation combinations and targeting areas.
卵巢癌是迄今为止致死率最高的妇科癌症。高级别浆液性卵巢癌(HGSOC)占大多数卵巢癌病例,并且最常被诊断为晚期。在这里,我们开发了一种新策略,使用电穿孔和 CRISPR-Cas9 介导的基因组编辑的组合来生成体卵巢癌小鼠模型。两种不同组合(有和没有 )中肿瘤抑制基因的突变导致 HGSOC 的成功生成,尽管潜伏期和病理生理学不同。在该系统中实施 Cre 谱系追踪可在免疫相容环境中可视化腹膜微转移。此外,这些模型显示出与人类 HGSOC 相似的拷贝数改变和表型。由于该策略在选择突变组合和靶向区域方面具有灵活性,因此它可能非常有助于生成用于推进卵巢癌理解和治疗的小鼠模型。意义:本研究揭示了一种新的策略,可以生成具有高灵活性的卵巢癌遗传小鼠模型,可灵活选择突变组合和靶向区域。