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Updated: Jun 8, 2026

Assessment of Ovarian Cancer Spheroid Attachment and Invasion of Mesothelial Cells in Real Time
Published on: May 20, 2014
Prognostic influence of small leucine-rich proteoglycans on serous ovarian cancer
H Surmann1, A Bartha2, B Győrffy2,3,4
1Department of Gynecology and Obstetrics, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149, Münster, Germany.
Purpose:
Ovarian cancer is one of the most lethal cancers in women worldwide. To be able to offer successful treatment and improve the prognosis, knowledge of factors influencing the tumor microenvironment is indispensable. In this context, the influence of the extracellular matrix on tumor progression is increasingly recognized. Of note, preclinical data in cell line and animal models have suggested that several members of the small leucine-rich proteoglycan (SLRP) family are mechanistically involved in the regulation of tumor progression. We hypothesized that dysregulation of SLRP expression may have a prognostic value in ovarian cancer.
Methods:
To distinguish whether this expression is altered in the cells themselves or in the extracellular matrix, quantitative Real-Time PCR was performed on ovarian cancer cell lines and complemented by analysis of CCLE datasets. We used Kaplan-Meier survival curves to investigate whether a high or low mRNA expression influences the survival of ovarian cancer patients. Finally, the interactions of the SLRPs were investigated using a STRING analysis.
Results:
We demonstrated the potential beneficial effect of a low mRNA expression of most SLRPs on the prognosis of serous ovarian cancer. STRING analysis revealed interactions with other proteins already known to influence tumor behavior and metastasis of various carcinomas.
Conclusion:
These findings suggest that SLRPs may be involved in ovarian cancer biology and could represent candidates for further mechanistic investigation. However, their potential relevance for therapeutic strategies, including treatment response, requires additional functional validation.
