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Characterization of ovarian cancer cell lines as in vivo models for preclinical studies
Open accessAbstract
Objective The value of cell lines for pre-clinical work lies in choosing those with similar characteristics. Selection of cell lines is typically based on patient history, histological subtype at diagnosis, mutation patterns, or signaling pathways. Although recent studies established consensus regarding molecular characteristics of ovarian cancer cell lines, data on in vivo tumorigenicity remains only sporadically available, impeding translation of in vitro work to xenograft models.Methods We introduced 18 ovarian cancer cell lines into athymic nude mice through subcutaneous, intraperitoneal, and ovary intrabursal routes, and observed tumor development over 6weeks. We also profiled cell line gene expression and identified differentially expressed gene sets based on their ability to form tumors in the subcutaneous or intraperitoneal locations. Representative cell lines were further subjected to proteomic analyses.Results Ovarian cancer cell lines showed variable ability to grow in mice when implanted subcutaneous, intraperitoneal, or intrabursal. While some cell lines grew well in both SC and IP locations, others showed a strong propensity to grow in one location only. Gene expression profiles suggested that cell lines showing preference for IP growth had gene expression patterns more similar to primary tumors.Conclusions We report the tumorigenicity of 17 human ovarian cancer cell lines and one mouse cell line in three distinct anatomical locations, and associated gene networks. Growth patterns and histopathology, linked to molecular characteristics, provide a valuable resource to the research community, and better guide the choice of cell lines for in vitro studies to translate efficiently into xenograft testing.
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“Ovarian cancer cell lines show variable ability to grow in nude mice when implanted either subcutaneously (SC), intraperitoneally (IP) or intrabursally (Hernandez et al., 2016).”
From Three-dimensional modelling of ovarian cancer: from cell lines to organoids for discovery and personalized medicine (2022) · cites this paper as Hernandez et al., 2016
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Metadata
- Authors
- Hernandez, L., Kim, M. K., Lyle, L. T., Bunch, K. P., House, C. D., Ning, F., Noonan, A. M., & Annunziata, C. M.
- Affiliations
- National Cancer Institute (US)
- Corresponding author
- Annunziata, Christina M.
- ORCID
- Venue
- Gynecologic Oncology
- Publisher
- Elsevier BV
- Published
- 2016-08
- Volume
- 142
- Issue
- 2
- Pages
- 332-340
- ISSN
- 0090-8258 (ISSN-L)
- PMC
- PMC4961516
- OpenAlex
- W2399911066
- Cited by
- 121
- References
- 43
- Citations by year
- 2026: 10 · 2025: 10 · 2024: 15 · 2023: 16 · 2022: 17 · 2021: 15 · 2020: 17 · 2019: 14 · 2018: 4 · 2017: 3
- FWCI
- 9.30
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Gynecologic Oncology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute Intramural Research Program (ZIA BC 011054)
- Topics
- Health Sciences › Medicine › Oncology › Ovarian cancer diagnosis and treatment
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Health Sciences › Medicine › Reproductive Medicine › Reproductive Biology and Fertility
- Keywords
- ovarian cancer cell lines, in vivo tumorigenicity, xenograft models, nude mice, subcutaneous implantation, intraperitoneal implantation, gene expression profiling, proteomic profiling, preclinical model selection
- MeSH terms
- Animals, Drug Screening Assays, Antitumor, Female, Humans, Neoplasm Transplantation, Ovarian Neoplasms, Xenograft Model Antitumor Assays, Cell Line, Tumor, Mice, Heterografts
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