"The insights gained from this study not only validate OVCAR3 as a representative model for HGSOC, but also provide a foundation for developing targeted therapeutic strategies."
BUFFALO, NY — December 23, 2025 — A new research paper was published in Volume 12 of Oncoscience on October 14, 2025, titled " Bridging clinical insight and laboratory model in high-grade serous ovarian carcinoma (HGSOC) using DNA sequencing-based profiling of TP53 ."
In this study, Faisal Iqbal from the University of Illinois Chicago used genetic sequencing and cell death analysis to demonstrate that the OVCAR3 cell line accurately reflects the biological characteristics of high-grade serous ovarian carcinoma (HGSOC), the most lethal form of ovarian cancer. The findings validate OVCAR3 as a reliable model for HGSOC and provide researchers with a valuable laboratory tool for developing targeted therapeutic strategies.
HGSOC is responsible for the majority of ovarian cancer-related deaths, largely due to its late diagnosis and resistance to standard therapies. To determine whether OVCAR3 can effectively represent clinical cases, the researchers compared its genetic profile to that of clinical ovarian cancer samples. Using Sanger sequencing, a widely used and cost-effective genetic analysis method, they found that both the lab and clinical samples shared the same non-mutated form of the TP53 gene, a key marker often altered in ovarian cancer. This result supports the relevance of OVCAR3 in modeling disease behavior.
"The most prevalent and aggressive subtype of epithelial ovarian cancer is high grade serous ovarian carcinoma (HGSOC) – approximately 70% of all ovarian cancer cases."
The study also explored how two repurposed drugs—metformin and chlorpromazine (CPZ)—affect ovarian cancer cells. These drugs were tested individually and in combination. Cell death measurements and colony formation assays showed that while each drug had moderate effects alone, the combination significantly reduced cancer cell survival. These results were consistent across both clinical and laboratory samples, further validating the model's accuracy in predicting therapeutic responses.
Overall, the study highlights the continued importance of Sanger sequencing in cancer research and emphasizes the need for genetically validated models like OVCAR3. By aligning laboratory experiments with clinical data, the research strengthens the foundation for more accurate preclinical testing, an essential step toward personalized medicine and more effective cancer treatments.
DOI: https://doi.org/10.18632/oncoscience.632
