1. USP35 is abundant in human lung cancer tissues and cell lines. 2. USP35 modulates iron homeostasis and ferroptosis in lung cancer tissues and cell lines.3. USP35 directly interacts with ferroportin and maintain its protein stability to prevent iron overload and ferroptosis.

Accumulating evidence suggests that autophagy is closely related to the pathogenesis of osteoarthritis (OA). The aim of this study was to determine the changes in autophagy during the progression of OA and to elucidate the specific role of autophagy in OA. For this purpose, a cellular model of OA was generated by stimulating SW1353 cells with interleukin (IL)-1β and a rabbit model of OA was also established by an intra-articular injection of collagenase, followed by treatment with the autophagy specific inhibitor, 3-methyladenine (3-MA). Cell viability was analyzed by MTS assay, and the mRNA expression levels of matrix metalloproteinases (MMP)-13 and tissue inhibitor of metalloproteinase (TIMP)-1 were determined by RT-qPCR. Cartilage degeneration was examined under a light microscope, and autophagosome and chondrocyte degeneration was observed by transmission electron microscopy. The protein expression of Beclin-1 and light chain 3 (LC3)B was evaluated by western blot analysis and immunofluorescence staining. We found that the autophagy was enhanced during the early stages and was weakened during the late stages of experimental OA. The inhibition of autophagy by 3-MA significantly aggravated the degeneration of chondrocytes and cartilage in experimental OA. Our results thus determine the changes in autophagy during different stages of OA, as well as the role of impaired autophagy in the development of OA. Our data suggest that the regulation of autophagy may be a potential therapeutic strategy with which to attenuate OA.

BackgroundRecent studies have shown that autophagy was associated with the development of osteoarthritis (OA), the purpose of this research was to determine the exact role of autophagy in OA and investigate effective therapeutic drugs to inhibit the pathological progression of OA.MethodsIn this study, a cellular OA model was generated by stimulating SW1353 cells with IL-1β and a rabbit OA model was established by intra-articular injection of collagenase, followed by treatment with Torin 1 or 3-Methyladenine (3-MA). The mRNA expression levels of VEGF, MMP-13 and TIMP-1 were determined by quantitative real-time PCR. The caitilage degeneration was examined by histological evaluation, chondrocytes degeneration and autophagosomes were observed by transmission electron microscopy. Expression levels of Beclin-1 and LC3 were evaluated by western blotting and immunofluorescence.ResultsThe degeneration of SW 1353 cells, cartilage and chondrocytes was related to the loss of autophagy in experimental OA. 3-MA increased the severity of degeneration of cells and cartilage by autophagy inhibition, while Torin 1 reduced that by autophagy activation.ConclusionsThe loss of autophagy is linked with the experimental OA and autophagy may play a protective role in the pathogenesis of OA. Treatment of Torin 1 can inhibit the degenerative changes of experimental OA by activating autophagy and it may be a useful therapeutic drug for OA.Electronic supplementary materialThe online version of this article (doi:10.1186/s12891-016-0995-x) contains supplementary material, which is available to authorized users.

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Background: Lung cancer is the cancer with the highest incidence in the world, and there is obvious heterogeneity within its tumor. The emergence of single-cell sequencing technology allows researchers to obtain cell-type-specific expression genes at the single-cell level, thereby obtaining information about the cell status and subpopulation distribution, as well as the communication behavior between cells. Many researchers have applied this technology to lung cancer research, but due to the shortcomings of insufficient sequencing depth, only a small part of the gene expression can be detected. Researchers can only roughly compare whether a few thousand genes are significant in different cell types; Methods: To fully explore the expression of all genes in different cell types, we propose a method to predict cell-type-specific genes. This method infers cell type-specific genes based on the expression levels of genes in different tissues and cells, and gene interactions. At present, biological experiments have discovered a large number of cell-type-specific genes, providing a large number of available samples for the application of deep learning methods; Results: Therefore, we fused Graph Convolutional Network (GCN) with Convolutional Neural Network(CNN) to build, model, and inferred cell-type-specific genes of lung cancer in 8 cell types; Conclusions: This method further analyzes and processes single-cell data and provides a new basis for research on lung cancer tumor heterogeneity, lung cancer tumor microenvironment, lung cancer invasion and metastasis, treatment response and drug resistance, etc.

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