American Association for Cancer Research
Browse
can-20-1518_figure_s2_suppsf2.pdf (193.47 kB)

Figure S2 from Modeling High-Grade Serous Ovarian Carcinoma Using a Combination of In Vivo Fallopian Tube Electroporation and CRISPR-Cas9–Mediated Genome Editing

Download (193.47 kB)
journal contribution
posted on 2023-04-04, 02:21 authored by Katie Teng, Matthew J. Ford, Keerthana Harwalkar, YuQi Li, Alain S. Pacis, David Farnell, Nobuko Yamanaka, Yu-Chang Wang, Dunarel Badescu, Tuyet Nhung Ton Nu, Jiannis Ragoussis, David G. Huntsman, Jocelyne Arseneau, Yojiro Yamanaka

Summary of tumour genotyping

Funding

Canadian Cancer Society (Société canadienne du cancer)

Cancer Research Society (CRS)

History

ARTICLE ABSTRACT

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 in vivo electroporation and CRISPR-Cas9–mediated genome editing. Mutation of tumor suppressor genes associated with HGSOC in two different combinations (Brca1, Tp53, Pten with and without Lkb1) 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. This study unveils a new strategy to generate genetic mouse models of ovarian cancer with high flexibility in selecting mutation combinations and targeting areas.

Usage metrics

    Cancer Research

    Categories

    Keywords

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC