ABSTRACT
Introduction: Epithelial ovarian cancer is a heterogeneous disease classified into five subtypes, each with a different molecular profile. Most cases of ovarian cancer are diagnosed after metastasis of the primary tumor and are resistant to traditional platinum-based chemotherapeutics. Mouse models of ovarian cancer have been utilized to discern ovarian cancer tumorigenesis and the tumor’s response to therapeutics.
Areas covered: The authors provide a review of mouse models currently employed to understand ovarian cancer. This article focuses on advances in the development of orthotopic and patient-derived tumor xenograft (PDX) mouse models of ovarian cancer and discusses current humanized mouse models of ovarian cancer.
Expert opinion: The authors suggest that humanized mouse models of ovarian cancer will provide new insight into the role of the human immune system in combating and augmenting ovarian cancer and aid in the development of novel therapeutics. Development of humanized mouse models will take advantage of the NSG and NSG-SGM3 strains of mice as well as new strains that are actively being derived.
Article highlights
A wide variety of orthotopic, PDX, and humanized mouse models have been developed for ovarian cancer.
Orthotopic mouse models enable recapitulation of the microenvironment of the ovary, allowing for metastasis studies.
PDX models for ovarian cancer have been utilized to determine therapeutic efficacy of novel drugs but may not represent the precise genomic features of patient tumors.
Humanized mouse models provide a platform to investigate the influence of the human immune system on tumorigenesis.
These models may aid in the testing of novel immunotherapeutic anti-cancer drugs.
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Declaration of interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.