Recently, thioridazine (10-[2-(1-methyl-2-piperidyl) ethyl]-2-methylthiophenothiazine), a well-known anti-psychotic agent was found to have anti-cancer activity in cancer cells. However, the molecular mechanism of the agent in cellular signal pathways has not been well defined. Thioridazine significantly increased early- and late-stage apoptotic fraction in cervical and endometrial cancer cells, suggesting that suppression of cell growth by thioridazine was due to the induction of apoptosis. Cell cycle analysis indicated thioridazine induced the down-regulation of cyclin D1, cyclin A and CDK4, and the induction of p21 and p27, a cyclin-dependent kinase inhibitor. Additionally, we compared the influence of thioridazine with cisplatin used as a control, and similar patterns between the two drugs were observed in cervical and endometrial cancer cell lines. Furthermore, as expected, thioridazine successfully inhibited phosphorylation of Akt, phosphorylation of 4E-BP1 and phosphorylation of p70S6K, which is one of the best characterized targets of the mTOR complex cascade. These results suggest that thioridazine effectively suppresses tumor growth activity by targeting the PI3K/Akt/mTOR/p70S6K signaling pathway.

Purpose: The aim of this study was to develop a preoperative risk prediction model for lymph node metastasis in patients with endometrial cancer and to identify a low-risk group before surgery. Patients and Methods: The medical records of 360 patients with endometrial cancer who underwent surgical staging were collected from four institutions and were retrospectively reviewed. By using serum CA-125 levels, preoperative biopsy data, and magnetic resonance imaging (MRI) data, a multivariate logistic model was created. Patients whose predicted probability was less than 4% were defined as low risk. The developed model was externally validated in 180 patients from two independent institutions. Results: Serum CA-125 levels and three MRI parameters (deep myometrial invasion, lymph node enlargement, and extension beyond uterine corpus) were found to be independent risk factors for nodal metastasis. The model classified 53% of patients as part of a low-risk group, and the false negative rate was 1.7%. In the validation cohort, the model classified 43% of patients as low-risk, and the false negative rate was 1.4%. The model showed good discrimination (area under the receiver operator characteristic curve = 0.85) and was calibrated well. The negative likelihood ratio of our low-risk criteria was 0.11 (95% CI, 0.04 to 0.29), which was equivalent to the false-negative rate of 1.3% (95% CI, 0.5% to 3.3%) at the assumed prevalence of nodal metastasis of 10%. Conclusion: Using serum CA-125 and MRI as criteria resulted in the accurate identification of a low-risk group for lymph node metastasis among patients with endometrial cancer.