Polysaccharide extracted from the Sargassum fusiforme induces cell cycle arrest and apoptosis of B16F10 melanoma cells through the PI3K/AKT pathway.

BACKGROUND: SARGASSUM FUSIFORME: (S. fusiforme) is a brown alga that has been utilized as a medicine for a long time. Polysaccharides extracted from S. fusiforme demonstrate antitumor activities. METHODS: The impact of S. fusiforme polysaccharides (SFPS 191,212) on the proliferation, apoptosis, and cell cycle kinetics of B16F10 murine melanoma cells were thoroughly investigated in this work. The anticancer activities of the SFPS 191,212 compounds were assayed in the B16F10 cells at both transcriptional and translational levels. RESULTS: The compound exhibited concentration-dependent effects. Moreover, SPFS 191,212 increased the numbers of apoptotic cells and arrested the cell cycle in the S phase of the quantitative real-time PCR. From western blotting, it was verified that the SFPS 191,212 treatment improved the expression of Bax, Caspase-9, and Caspase-3 genes and proteins, while it reduced phosphatidylinositol 3 kinase and Bcl-2 genes and proteins, suggesting the involvement of mitochondria. CONCLUSION: Overall, SFPS 191,212 can be further explored as a potential functional food or adjuvant agent for the prevention or treatment of melanoma.

Potential circRNA-disease association prediction using DeepWalk and network consistency projection.

A growing body of experimental studies have reported that circular RNAs (circRNAs) are of interest in pathogenicity mechanism research and are becoming new diagnostic biomarkers. As experimental techniques for identifying disease-circRNA interactions are costly and laborious, some computational predictors have been advanced on the basis of the integration of biological features about circRNAs and diseases. However, the existing circRNA-disease relationships are not well exploited. To solve this issue, a novel method named DeepWalk and network consistency projection for circRNA-disease association prediction (DWNCPCDA) is proposed. Specifically, our method first reveals features of nodes learned by the deep learning method DeepWalk based on known circRNA-disease associations to calculate circRNA-circRNA similarity and disease-disease similarity, and then these two similarity networks are further employed to feed to the network consistency projection method to predict unobserved circRNA-disease interactions. As a result, DWNCPCDA shows high-accuracy performances for disease-circRNA interaction prediction: an AUC of 0.9647 with leave-one-out cross validation and an average AUC of 0.9599 with five-fold cross validation. We further perform case studies to prioritize latent circRNAs related to complex human diseases. Overall, this proposed method is able to provide a promising solution for disease-circRNA interaction prediction, and is capable of enhancing existing similarity-based prediction methods.

Using Graph Attention Network and Graph Convolutional Network to Explore Human CircRNA-Disease Associations Based on Multi-Source Data.

Cumulative research studies have verified that multiple circRNAs are closely associated with the pathogenic mechanism and cellular level. Exploring human circRNA-disease relationships is significant to decipher pathogenic mechanisms and provide treatment plans. At present, several computational models are designed to infer potential relationships between diseases and circRNAs. However, the majority of existing approaches could not effectively utilize the multisource data and achieve poor performance in sparse networks. In this study, we develop an advanced method, GATGCN, using graph attention network (GAT) and graph convolutional network (GCN) to detect potential circRNA-disease relationships. First, several sources of biomedical information are fused via the centered kernel alignment model (CKA), which calculates the corresponding weight of different kernels. Second, we adopt the graph attention network to learn latent representation of diseases and circRNAs. Third, the graph convolutional network is deployed to effectively extract features of associations by aggregating feature vectors of neighbors. Meanwhile, GATGCN achieves the prominent AUC of 0.951 under leave-one-out cross-validation and AUC of 0.932 under 5-fold cross-validation. Furthermore, case studies on lung cancer, diabetes retinopathy, and prostate cancer verify the reliability of GATGCN for detecting latent circRNA-disease pairs.

The Glutaminase-1 Inhibitor 968 Enhances Dihydroartemisinin-Mediated Antitumor Efficacy in Hepatocellular Carcinoma Cells.

Reprogrammed metabolism and redox homeostasis are potential targets of cancer therapy. Our previous study demonstrated that the kidney form of glutaminase (GLS1) is highly expressed in hepatocellular carcinoma (HCC) cells and can be used as a target for effective anticancer therapy. Dihydroartemisinin (DHA) increases intracellular reactive oxygen species (ROS) levels leading to cytotoxicity in cancer cells. However, the heterogeneity of cancer cells often leads to differing responses to oxidative lesions. For instance, cancer cells with high ratio of GSH/GSSG, a critical ROS scavenger, are resistant to ROS-induced cytotoxicity. We postulate that a combinatorial strategy firstly disrupting redox homeostasis followed by DHA might yield a profound antitumor efficacy. In this study, when HCC cells were treated with a GLS1 inhibitor 968, the ROS elimination capacity was significantly reduced in HCC cells, which rendered HCC cells but not normal endothelial cells more sensitive to DHA-mediated cytotoxicity. We further confirmed that this synergistic antitumor efficacy was mediated by excessive ROS generation in HCC cells. NAC, a ROS inhibitor, partly rescued the combinatorial cytotoxic effect of 968 and DHA. Given that GLS1 is a potential antitumor target and DHA has been safely used in clinic, our findings provide new insight into liver cancer therapy targeting glutamine metabolism combined with the ROS generator DHA, which can be readily translated into cancer clinical trials.

Photoacoustic "nanobombs" fight against undesirable vesicular compartmentalization of anticancer drugs.

Undesirable intracellular vesicular compartmentalization of anticancer drugs in cancer cells is a common cause of chemoresistance. Strategies aimed at circumventing this problem may improve chemotherapeutic efficacy. We report a novel photophysical strategy for controlled-disruption of vesicular sequestration of the anticancer drug doxorubicin (DOX). Single-walled carbon nanotubes (SWCNTs), modified with folate, were trapped in acidic vesicles after entering lung cancer cells. Upon irradiation by near-infrared pulsed laser, these vesicles were massively broken by the resulting photoacoustic shockwave, and the vesicle-sequestered contents were released, leading to redistribution of DOX from cytoplasm to the target-containing nucleus. Redistribution resulted in 12-fold decrease of the EC50 of DOX in lung cancer cells, and enhanced antitumor efficacy of low-dose DOX in tumor-bearing mice. Side effects were not observed. These findings provide insights of using nanotechnology to improve cancer chemotherapy, i.e. not only for drug delivery, but also for overcoming intracellular drug-transport hurdles.

Mitophagy promotes replication of oncolytic Newcastle disease virus by blocking intrinsic apoptosis in lung cancer cells.

Apoptosis contributes to antitumor effect of Newcastle disease virus (NDV). Autophagy is a protective response under cellular stress including viral infection. How autophagy interferes with oncolysis of NDV remains unclear. In this study, we found that NDV La Sota strain induced autophagy and preserved autophagic flux in non-small cell lung cancer cells. NDV-induced autophagy promoted viral replication by blocking cancer cells from caspase-dependent apoptosis. Moreover, we found that NDV recruited SQSTM1-mediated mitophagy to control cytochrome c release, and thus blocked intrinsic pro-apoptotic signaling. Finally, we observed an enhanced oncolysis in NSCLC cells treated with NDV in the presence of an autophagy inhibitor 3-methyladenine (3-MA). Interestingly, a more profound antitumor effect could be achieved when administration of 3-MA was postponed to 24 h after NDV infection. Our findings unveil a novel way that NDV subverts mitophagy to favor its replication by blocking apoptosis, and provide rationale for systemic therapeutic cohort combining NDV with autophagy inhibitors in cancer therapy.