Ovarian cancer spreads rapidly through the abdomen because cancer cells recruit and reprogram protective mesothelial cells in ascites fluid to help them invade new tissues, according to new research.
Epithelial ovarian cancer (EOC) is often diagnosed at an advanced stage, in part because it can metastasize within the abdominal cavity soon after it develops. The new study, published in Science Advances, identifies a key mechanism behind this aggressive behavior: the formation of mixed-cell clusters in ascites, the fluid that accumulates in many patients with advanced disease.
The investigators found that nearly all ovarian cancer cells in ascites exist as compact spheroids rather than single cells. About 60 percent of these spheroids contained mesothelial cells, which normally line and protect the abdominal cavity. These aggregated cancer–mesothelial spheroids were highly invasive and capable of penetrating collagen and mesothelial layers.
Importantly, mesothelial cells within these clusters appeared to initiate invasion. The study showed that ovarian cancer cells alter mesothelial cell characteristics through direct contact in spheroids, enabling rapid peritoneal spread without major changes in cancer cell gene expression. In effect, the tumor co-opts surrounding nonmalignant cells to act as “leader” cells that facilitate tissue penetration.
Furthermore, the presence of malignant cells in ascites was associated with significantly shorter progression-free survival, even in early-stage disease. This suggests that ascites is not simply a byproduct of advanced cancer, but an active environment that promotes its spread.
These findings also highlight the tumor microenvironment in ascites as a potential therapeutic target. Disrupting the interaction between cancer cells and mesothelial cells – or blocking key proteins involved in invasion – may reduce metastatic spread and improve outcomes.
The work also points to the biological importance of ascites analysis and the need to consider both malignant and nonmalignant cell populations when evaluating disease progression.
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