News Release

Research validates laboratory model for studying high-grade serous ovarian cancer

“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.”

Peer-Reviewed Publication

Impact Journals LLC

Bridging clinical insight and laboratory model in high-grade serous ovarian carcinoma (HGSOC) using DNA sequencing-based profiling of TP53

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Figure 1: Hemocytometer dead cells count.

Here is the bar graph showing the hemocytometer based dead cell counts for each treatment group across day 1, day 2 and day 4 (24 hours post treatment). The data clearly indicated that dead cells increased in combo with high concentration drug group. The C and L presents clinical and laboratory samples respectively and each group has separate control.

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Credit: Copyright: © 2025 Iqbal. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

“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

Correspondence to: Faisal Iqbal – faisalsaleh59@ymail.comfaisali@uic.edu

Keywords: cancer, ovarian cancer, HGSOC, OVCAR3, TP53

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About Oncoscience

Oncoscience is a peer-reviewed, open-access, traditional journal covering the rapidly growing field of cancer research, especially emergent topics not currently covered by other journals. This journal has a special mission: Freeing oncology from publication costs. It is free for the readers and the authors.

Oncoscience is indexed and archived by PubMed, PubMed Central, Scopus, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

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