Triptonide induces apoptosis and inhibits the proliferation of ovarian cancer cells by activating the p38/p53 pathway and autophagy.

Ovarian cancer is a common malignant tumor in women, and 70 % of ovarian cancer patients are diagnosed at an advanced stage. Drug chemotherapy is an important method for treating ovarian cancer, but recurrence and chemotherapy resistance often lead to treatment failure. In this study, we screened 10 extracts of Tripterygium wilfordii, a traditional Chinese herb, and found that triptonide had potent anti-ovarian cancer activity and an IC50 of only 3.803 nM against A2780 cell lines. In addition, we determined that triptonide had a better antitumor effect on A2780 cell lines than platinum chemotherapeutic agents in vitro and that triptonide had no significant side effects in vivo. We found that triptonide induced apoptosis in ovarian cancer cells through activation of the p38/p53 pathway and it also induced cell cycle arrest at the S phase. In addition, we demonstrated that triptonide could activate lethal autophagy, which led to growth inhibition and cell death in ovarian cancer cells, resulting in an anti-ovarian cancer effect. Triptonide exerts its anti-ovarian cancer effect through activation of the p38/p53 pathway and induction of autophagy to promote apoptosis, which provides a new candidate drug and strategy for the treatment of ovarian cancer.

Causes of death in endometrial cancer survivors: A Surveillance, Epidemiology, and End Result-based analysis.

BACKGROUND: Increasing attention has been paid to the survival of endometrial cancer (EC) patients, but the non-cancer causes of death from EC are rarely reported. This study primarily aimed to investigate the non-cancer causes of death in patients with EC. METHODS: The study collected relevant data, including age, tumour stage and treatment mode, on patients diagnosed with endometrial malignancies from 2000 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) Programme. We analysed the standardised mortality ratio (SMR) to determine the cause of death. RESULTS: The study included 135,831 patients with EC. During the follow-up, 46,604 (34.3%) patients died, of whom 42.9%, 15.6% and 41.5% died of EC, other cancers and non-cancer causes, respectively. As the diagnosis time increased, the number of EC-associated mortalities gradually decreased. The most common non-cancer causes of death were heart disease, cerebrovascular disease and diabetes. Regarding the general population of the United States, patients with EC died of heart disease (SMR: 1.06; 95% confidence interval [CI]: 1.03-1.09), diabetes (SMR: 1.56; 95% CI: 1.47-1.65) and septicaemia (SMR: 1.40; 95% CI: 1.28-1.52), which were statistically significant. CONCLUSIONS: For patients with EC, the number of deaths from non-cancer causes (mainly heart disease, cerebrovascular disease and diabetes mellitus) is equivalent to that of EC. In addition, compared with the general population, EC survivors have a higher risk of death from sepsis and diabetes. These discoveries support how survivors can avoid future-related health risks. By doing this, clinicians can improve the quality of life and chances of the survival of patients with EC.

Establishment and validation of a novel nomogram for survival prediction of ovarian carcinosarcoma.

Background: Ovarian carcinosarcoma (OCS) is a rare and aggressive histological type of ovarian cancer. Current prognostic methods for OCS are insufficient. This study was undertaken to establish and validate a novel nomogram for predicting the overall survival (OS) of OCS patients. Methods: We extracted 820 patients with OCS from the Surveillance, Epidemiology, and End Results (SEER) database and further randomly assigned them to a training set (n=574) and a validation set (n=246) at a ratio of 7-to-3. Univariate and multivariate regression analyses were utilized to verity independent prognostic factors, and a prognostic nomogram was constructed based on the results. The performance of the new model was compared with that of the AJCC staging system using the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA). Results: Cox regression analysis suggested that age, grade, tumor size, the American Joint Committee on Cancer (AJCC) stage, surgery, and chemotherapy were the independent prognostic factors. These factors were integrated into a prognostic nomogram to determine the 1-, 3-, and 5-year OS of OCS patients. The AUC, NRI, IDI, calibration curves, and DCA data demonstrated that our nomogram had better discriminative ability than the AJCC staging system alone. The calibration curves indicate that the nomogram was well-calibrated. The DCA verified the clinical applicability of the nomogram. Conclusions: Our current study is the first to establish and internally validate a novel nomogram for predicting the 1-, 3-, and 5-year OS probabilities of OCS patients. Our prognostic nomogram was of good performance and can be an accurate tool to predict individualized survival time of OCS in clinical work.