Background/Aims: Hepatocellular carcinoma (HCC) is one of the most deadly diseases; metastasis and recurrence are the most important factors that affect the therapy of HCC chronically. Until now, the prognosis for the metastasis of HCC had not improved. Recently, several proteins that are related to metastasis and invasion of HCC were identified, but the effective markers still remain to be elucidated. Methods: In this study, comparative proteomics was used to study the differentially expressed proteins in two HCC cell lines MHCC97L and HCCLM9, which have low and high metastatic potentials, respectively. Results: Our findings indicated that filamin A (FLNA) and phosphoglycerate kinase 1 (PGK1) were two significantly differentially expressed proteins, with high expression in HCCLM9 cells, and may influence the metastasis of HCC cells. Conclusion: Taken together with the confirmation of expression on the mRNA level, we propose the use of FLNA and PGK1 as potential markers for the progression of HCC.

Both retrolinkin and its interaction partner endophilin A1 are required for BDNF-induced dendrite outgrowth of cultured hippocampal neurons. They function sequentially in an early endocytic trafficking pathway for BDNF-activated TrkB, which provides spatiotemporal control of downstream ERK signaling from endosomes.

Cancer is thought to be caused by the accumulation of driver genetic mutations. Therefore, identifying cancer driver genes plays a crucial role in understanding the molecular mechanism of cancer and developing precision therapies and biomarkers. In this work, we propose a Multi-Task learning method, called MTGCN, based on the Graph Convolutional Network to identify cancer driver genes. First, we augment gene features by introducing their features on the protein-protein interaction (PPI) network. After that, the multi-task learning framework propagates and aggregates nodes and graph features from input to next layer to learn node embedding features, simultaneously optimizing the node prediction task and the link prediction task. Finally, we use a Bayesian task weight learner to balance the two tasks automatically. The outputs of MTGCN assign each gene a probability of being a cancer driver gene. Our method and the other four existing methods are applied to predict cancer drivers for pan-cancer and some single cancer types. The experimental results show that our model shows outstanding performance compared with the state-of-the-art methods in terms of the area under the Receiver Operating Characteristic (ROC) curves and the area under the precision-recall curves. The MTGCN is freely available via https://github.com/weiba/MTGCN.

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Abstract. Fibroblast growth factor 21 (FGF21) is a novel metabolic regulator. The present study aimed to investigate the effect of FGF21 on cholesterol efflux and the expression of ATP binding cassette (ABC) A1 and G1 in human THP-1 macrophage-derived foam cells. Furthermore, the present study aimed to investigate the role of the liver X receptor (LXR) α in this process. A model of oxidized low-density lipoprotein-induced foam cells from human THP-1 cells was established. The effect of FGF21 on cholesterol efflux was analyzed using a liquid scintillation counter. The expression of ABCA1 and ABCG1 was determined using quantitative polymerase chain reaction and western blot analyses. FGF21 was found to enhance apolipoprotein A1-and high-density lipoprotein-mediated cholesterol efflux. FGF21 was also observed to increase the mRNA and protein expression of ABCA1 and ABCG1. Furthermore, LXRα-short interfering RNA attenuated the stimulatory effects induced by FGF21. These findings suggest that FGF21 may have a protective effect against atherosclerosis by enhancing cholesterol efflux through the induction of LXRα-dependent ABCA1 and ABCG1 expression. IntroductionAtherosclerosis, one of the leading causes of morbidity and mortality worldwide, is a chronic inflammatory disease and a disorder of lipid metabolism (1). The accumulation of excess cholesterol has been recognized as a crucial event in the development of atherosclerosis (2); therefore, preventing or reversing cholesterol accumulation may be effective protective strategies against atherosclerosis. A growing body of evidence suggests that high density lipoprotein (HDL) has an important role in the removal of cholesterol from atherosclerotic plaques and the transport of the excess cholesterol back to the liver for its subsequent elimination as bile acids and neutral steroids. This process is termed reverse cholesterol transport (RCT) and is one of the major protective mechanisms against the development of atherosclerosis (3-5).Cholesterol efflux from macrophage-derived foam cells is an initial and key step in RCT (6), and serves as an integrated measure of HDL quantity and quality (7). This cholesterol efflux involves numerous genes, including ATP-binding cassette (ABC) A1 and G1 (8). ABCA1 is a member of the ABC superfamily and is the defective gene in Tangier disease. ABCA1 has been reported to have an important role in the prevention of atherosclerosis through facilitating cholesterol efflux from macrophages to lipid-poor apolipoproteinA-Ⅰ (apoA-Ⅰ), and decreasing cholesterol accumulation in macrophages (9). Similar to ABCA1, ABCG1 is capable of promoting cholesterol efflux from macrophages to mature HDL particles, but not to apoA-Ⅰ (10).Liver X receptor (LXR) α, a member of the nuclear hormone receptor superfamily, has a crucial role in cholesterol metabolism (11). Upon activation, LXRα induces numerous genes, which are involved in cholesterol efflux, absorption, transport and excretion. ABCA1 and ABCG1 have been identified as direct targets of LXRα (12).Fibro...