Masahiko Nishiyama

Evaluating the specific STAT3 inhibitor YHO-1701 in ovarian cancer cell lines and patient-derived cell models: efficacy, mechanisms, and therapeutic potential

Signal transducer and activator of transcription 3 (STAT3) plays key roles in regulating cancer cell proliferation, survival, and metastasis. We aimed to determine the effects of YHO-1701, an oral STAT3 inhibitor, in ovarian cancer (OC). We evaluated the impact of YHO-1701 on cell growth in patient-derived cells (PDCs) and OC cell lines using standard cell proliferation assays. Spheroid models derived from PDCs were assessed using three-dimensional (3D) cell viability assays. Antitumor activity was performed in SKOV3 xenograft mice treated orally administrated YHO-1701 with 20 mg/kg. Changes in STAT3 signaling were analyzed by western blotting. The molecular mechanisms of STAT3 inhibition were investigated by sequencing RNA and analyzing pathways in the SKOV3 using a small interfering RNA targeting STAT3 (STAT3 siRNA) and YHO-1701. YHO-1701 inhibited the growth of OC cell lines by preventing STAT3 dimerization and decreasing the expression of its downstream signaling molecule, survivin. The growth of PDCs and spheroids obtained from patients with primary and recurrent OCs was significantly inhibited. Antitumor effect was observed in the SKOV3 xenograft mice with YHO-1701. YHO-1701 induced apoptosis in OC cells. Additionally, p53 and/or MAPK signaling pathways were upregulated in SKOV3 cells incubated with YHO-1701 and in those with STAT3 siRNA. Our results showed that YHO-1701 suppressed cell growth in PDCs of OC, accompanied by survivin inhibition, and a decrease in the number of peritoneal metastasis in the mice by YHO-1701, compared with those treated with control. Therefore, YHO-1701 could be a promising candidate agent for treating OC.

Prediction of response to promising first-line chemotherapy in ovarian cancer patients with residual peritoneal tumors: practical biomarkers and robust multiplex models

Platinum/taxane (TC) chemotherapy with debulking surgery stays the mainstay of the treatment in ovarian cancer patients with peritoneal metastasis, and recently its novel modality, intraperitoneal carboplatin with dose-dense paclitaxel (ddTCip), was shown to have greater therapeutic impact. Nevertheless, the response varies among patients and consequent recurrence, or relapse often occurs. Discovery of therapeutic response predictor to ddTCip and/or TC therapy is eagerly awaited to improve the treatment outcome. Using datasets in 76 participants in our ddTCip study and published databases on patients received TC therapy, we first validated a total of 75 previously suggested markers, sought out more active biomarkers through the association analyses of genome-wide transcriptome and genotyping data with progression-free survival (PFS) and adverse events, and then developed multiplex statistical prediction models for PFS and toxicity by mainly using multiple regression analysis and the classification and regression tree (CART) algorithm. The association analyses revealed that SPINK1 could be a possible biomarker of ddTCip efficacy, while ABCB1 rs1045642 and ERCC1 rs11615 would be a predictor of hematologic toxicity and peripheral neuropathy, respectively. Multiple regression analyses and CART algorithm finally provided a potent efficacy prediction model using 5 gene expression data and robust multiplex toxicity prediction models-CART models using a total of 4 genotype combinations and multiple regression models using 15 polymorphisms on 12 genes. Biomarkers and multiplex models composed here could work well in the response prediction of ddTCip and/or TC therapy, which might contribute to realize optimal selection of the key therapy.