Discriminative analysis of schizophrenia patients using an integrated model combining 3D CNN with 2D CNN: A multimodal MR image and connectomics analysis.

OBJECTIVE: Few studies have applied deep learning to the discriminative analysis of schizophrenia (SZ) patients using the fusional features of multimodal MRI data. Here, we proposed an integrated model combining a 3D convolutional neural network (CNN) with a 2D CNN to classify SZ patients. METHOD: Structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) data were acquired for 140 SZ patients and 205 normal controls. We computed structural connectivity (SC) from the sMRI data as well as functional connectivity (FC), amplitude of low-frequency fluctuation (ALFF), and regional homogeneity (ReHo) from the rs-fMRI data. The 3D images of T1, ReHo, and ALFF were used as the inputs for the 3D CNN model, while the SC and FC matrices were used as the inputs for the 2D CNN model. Moreover, we added squeeze and excitation blocks (SE-blocks) to each layer of the integrated model and used a support vector machine (SVM) to replace the softmax classifier. RESULTS: The integrated model proposed in this study, using the fusional features of the T1 images, and the matrices of FC, showed the best performance. The use of the SE-blocks and SVM classifiers significantly improved the performance of the integrated model, in which the accuracy, sensitivity, specificity, area under the curve, and F1-score were 89.86%, 86.21%, 92.50%, 89.35%, and 87.72%, respectively. CONCLUSIONS: Our findings indicated that an integrated model combining 3D CNN with 2D CNN is a promising method to improve the classification performance of SZ patients and has potential for the clinical diagnosis of psychiatric diseases.

Selectively targeting BCL6 using a small molecule inhibitor is a potential therapeutic strategy for ovarian cancer.

Ovarian cancer is one of the tumors with the highest fatality rate among gynecological tumors. The current 5-year survival rate of ovarian cancer is <35%. Therefore, more novel alternative strategies and drugs are needed to treat ovarian cancer. The transcription factor B-cell lymphoma 6 (BCL6) is critically associated with poor prognosis and cisplatin resistance in ovarian cancer treatment. Therefore, BCL6 may be an attractive therapeutic target for ovarian cancer. However, the role of targeting BCL6 in ovarian cancer remains elusive. Here, we developed a novel BCL6 small molecule inhibitor, WK369, which exhibits excellent anti-ovarian cancer bioactivity, induces cell cycle arrest and causes apoptosis. WK369 effectively inhibits the growth and metastasis of ovarian cancer without obvious toxicity in vitro and in vivo. meanwhile, WK369 can prolong the survival of ovarian cancer-bearing mice. It is worth noting that WK369 also has significant anti-tumor effects on cisplatin-resistant ovarian cancer cell lines. Mechanistic studies have shown that WK369 can directly bind to the BCL6-BTB domain and block the interaction between BCL6 and SMRT, leading to the reactivation of p53, ATR and CDKN1A. BCL6-AKT, BCL6-MEK/ERK crosstalk is suppressed. As a first attempt, our study demonstrates that targeting BCL6 may be an effective approach to treat ovarian cancer and that WK369 has the potential to be used as a candidate therapeutic agent for ovarian cancer.

Combined treatment of disulfiram with PARP inhibitors suppresses ovarian cancer.

Introduction: Due to the difficulty of early diagnosis, nearly 70% of ovarian cancer patients are first diagnosed at an advanced stage. Thus, improving current treatment strategies is of great significance for ovarian cancer patients. Fast-developing poly (ADP-ribose) polymerases inhibitors (PARPis) have been beneficial in the treatment of ovarian cancer at different stages of the disease, but PARPis have serious side effects and can result in drug resistance. Using PARPis in combination with other drug therapies could improve the efficacy of PRAPis.In this study, we identified Disulfiram as a potential therapeutic candidate through drug screening and tested its use in combination with PARPis. Methods: Cytotoxicity tests and colony formation experiments showed that the combination of Disulfiram and PARPis decreased the viability of ovarian cancer cells. Results: The combination of PARPis with Disulfiram also significantly increased the expression of DNA damage index gH2AX and induced more PARP cleavage. In addition, Disulfiram inhibited the expression of genes associated with the DNA damage repair pathway, indicating that Disulfiram functions through the DNA repair pathway. Discussion: Based on these findings, we propose that Disulfiram reinforces PARPis activity in ovarian cancer cells by improving drug sensitivity. The combined use of Disulfiram and PARPis provides a novel treatment strategy for patients with ovarian cancer.

A novel small-molecule activator of unfolded protein response suppresses castration-resistant prostate cancer growth.

Androgen receptor-targeted therapy improves survival in castration-resistant prostate cancer (CRPC). However, almost all patients with CRPC eventually develop secondary resistance to these drugs. Therefore, alternative therapeutic approaches for incurable metastatic CRPC are urgently needed. Unfolded protein response (UPR) is regarded as a cytoprotective mechanism that removes misfolded proteins in rapidly proliferating tumor cells. However, acute activation of the UPR directly leads to tumor cell death. This study has shown that WJ-644A, a novel small molecule activator of UPR, potently inhibited the proliferation of prostate cancer cells and caused tumor regression with a good safety profile in multiple animal models. Mechanistically, we have identified that WJ-644A induced cell methuosis and autophagy upon UPR activation. Our study not only identifies the UPR as an actionable target for CRPC treatment, but also establishes WJ-644A as a novel UPR activator that has potential therapeutic value for CRPC.