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In vivo modeling of metastatic human high-grade serous ovarian cancer in mice
- Source :
- PLoS genetics, vol 16, iss 6
- Publication Year :
- 2020
- Publisher :
- eScholarship, University of California, 2020.
-
Abstract
- Metastasis is responsible for 90% of human cancer mortality, yet it remains a challenge to model human cancer metastasis in vivo. Here we describe mouse models of high-grade serous ovarian cancer, also known as high-grade serous carcinoma (HGSC), the most common and deadliest human ovarian cancer type. Mice genetically engineered to harbor Dicer1 and Pten inactivation and mutant p53 robustly replicate the peritoneal metastases of human HGSC with complete penetrance. Arising from the fallopian tube, tumors spread to the ovary and metastasize throughout the pelvic and peritoneal cavities, invariably inducing hemorrhagic ascites. Widespread and abundant peritoneal metastases ultimately cause mouse deaths (100%). Besides the phenotypic and histopathological similarities, mouse HGSCs also display marked chromosomal instability, impaired DNA repair, and chemosensitivity. Faithfully recapitulating the clinical metastases as well as molecular and genomic features of human HGSC, this murine model will be valuable for elucidating the mechanisms underlying the development and progression of metastatic ovarian cancer and also for evaluating potential therapies.
- Subjects :
- Ribonuclease III
DNA Repair
Knockout
Primary Cell Culture
Cystadenocarcinoma
Drug Resistance
Antineoplastic Agents
Drug Screening Assays
Cell Line
DEAD-box RNA Helicases
Mice
Rare Diseases
Chromosomal Instability
Genetics
Animals
Humans
2.1 Biological and endogenous factors
Neoplasm Metastasis
Aetiology
Peritoneal Neoplasms
Cancer
Ovarian Neoplasms
Tumor
Animal
PTEN Phosphohydrolase
Serous
Antitumor
Ovarian Cancer
Disease Models
Mutation
Feasibility Studies
Neoplasm
Female
Tumor Suppressor Protein p53
Neoplasm Grading
Developmental Biology
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- PLoS genetics, vol 16, iss 6
- Accession number :
- edsair.dedup.wf.001..b23038f55a707fc67f90703786e3bae3