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Updated: Jul 21, 2026

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
Microarray analysis of gene expression mirrors the biology of an ovarian cancer model
P N Tonin1, T J Hudson, F Rodier
1Department of Medicine, McGill University, Montréal, Québec, Canada H3G 1A4.
Abstract:
We have previously described an ovarian cancer model based on four independent spontaneously immortalized epithelial ovarian cancer cell lines (TOV-21G, TOV-81D, TOV-112D and OV-90) from patients who were never exposed to chemotherapy or radiation therapy. These cell lines are particularly interesting since they retain characteristics of the original epithelial ovarian cancers (EOC) from which they were derived. Here we report the characterization of this model system using high-density DNA microarrays in order to assess gene expression. Expression profiles were generated from total RNAs extracted from the four EOC cell lines. For comparison, expression profiling is also provided for a primary culture of normal ovarian surface epithelium (NOV-31) and a fresh EOC sample (TOV-578G). Comparison of expression profiles revealed patterns of expression that distinguish NOV-31 from that of all tumor derived samples. The expression pattern of TOV-81D, an EOC cell line that was derived from a patient with indolent disease, most closely resembles NOV-31 while profiles of samples derived from patients with more aggressive disease (TOV-21G, OV-90, TOV-112D and TOV-578G) showed more divergent patterns of expression. The microarray analysis (http://genome.mcgill.ca) results confirm the usefulness of an ovarian cancer model based on the characterization of these EOC cell lines.
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