Related Experiment Video
Updated: Jun 28, 2026
High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids
Published on: June 14, 2021
Low expression of S100P associated with paclitaxel resistance in ovarian cancer cell line
Jian-hua Gao1, Zhi-juan He, Qi Wang
1Department of Obstetrics and Gynecology, First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150010, China.
Background:
Recent studies indicate that S100P expression may be a biomarker that can predict the success of cancer chemotherapy. Whether it is relevant to chemotherapeutics in ovarian cancer is unknown. In this study, we investigated the association of S100P expression with paclitaxel sensitivity in ovarian cancer cell lines.
Methods:
We measured S100P expression and paclitaxel resistance profiles in parent SKOV3 and OVCAR3 cell lines. Then, the two cell lines were transiently transfected with S100P siRNA. We also constructed an OVCAR3 cell clone that stably overexpressed S100P. The effect of S100P expression level on the survival of cells exposed to paclitaxel was measured using the MTT assay. S100P expression was evaluated by semi-quantitative RT-PCR and Western blotting. Significance of differences was calculated using independent samples t-test and one way analysis of variance (ANOVA).
Results:
Lower S100P expression was associated with a survival advantage in OVCAR3 cells exposed to paclitaxel; the survival advantage in SKOV3 cells was smaller (P < 0.05). The survival advantage associated with decreased S100P expression was even greater for SKOV3 and OVCAR3 cells that had been transfected with S100P siRNA before being exposed to paclitaxel (P < 0.05). Consistent with this, the OVCAR3 cell clone that was transfected to overexpress S100P was more sensitive to paclitaxel (P < 0.05).
Conclusions:
Low S100P expression contributes to drug resistance to paclitaxel in ovarian cancer cell lines. S100P expression thus might be a marker that can predict the effectiveness of paclitaxel based chemotherapy. Such a marker could be helpful in improving individual medication regimens for ovarian cancer patients.
