Starvation‐induced autophagy promotes the invasion and migration of human bladder cancer cells via TGF‐β1/Smad3‐mediated epithelial‐mesenchymal transition activation

Tong, Hang; Yin, Hubin; Hossain, Mohammad Arman; Wang, Yiyang; Wu, Feixiang; Dong, Xiaoyong; Gao, Shun; Zhan, Kai

doi:10.1002/jcb.27788

Cited by 64 publications

(50 citation statements)

References 32 publications

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“…For Bladder Cancer, 3 out of 10 genes have been experimentally verified. Among them, SMAD3 mediates epithelial-mesenchymal transition which affects the invasion and migration of Bladder Cancer (Tong et al, 2018). DMP1 is a tumor suppressor gene of Bladder Cancer (Peng et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

Identifying Disease-Gene Associations With Graph-Regularized Manifold Learning

et al. 2019

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Complex diseases are known to be associated with disease genes. Uncovering disease-gene associations is critical for diagnosis, treatment, and prevention of diseases. Computational algorithms which effectively predict candidate disease-gene associations prior to experimental proof can greatly reduce the associated cost and time. Most existing methods are disease-specific which can only predict genes associated with a specific disease at a time. Similarities among diseases are not used during the prediction. Meanwhile, most methods predict new disease genes based on known associations, making them unable to predict disease genes for diseases without known associated genes.In this study, a manifold learning-based method is proposed for predicting disease-gene associations by assuming that the geodesic distance between any disease and its associated genes should be shorter than that of other non-associated disease-gene pairs. The model maps the diseases and genes into a lower dimensional manifold based on the known disease-gene associations, disease similarity and gene similarity to predict new associations in terms of the geodesic distance between disease-gene pairs. In the 3-fold cross-validation experiments, our method achieves scores of 0.882 and 0.854 in terms of the area under of the receiver operating characteristic (ROC) curve (AUC) for diseases with more than one known associated genes and diseases with only one known associated gene, respectively. Further de novo studies on Lung Cancer and Bladder Cancer also show that our model is capable of identifying new disease-gene associations.

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Section: Resultsmentioning

confidence: 99%

Identifying Disease-Gene Associations With Graph-Regularized Manifold Learning

et al. 2019

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“…The inhibition of FOXK1 in an acidic microenvironment triggers autophagy and reverses EMT in gastric cancer cells (105). However, in bladder cancer cells, it has been demonstrated that starvation conditions promote autophagy, which boosts the EMT process through TGF-β1/Smad3 signaling, enhancing cell invasion and migration (106). Moreover, knockdown of the autophagy-related protein DNA damage-regulated autophagy modulator 1 (DRAM1) reduces the migrative and invasive capabilities of hepatoblastoma cells, inactivating autophagy, and EMT (107).…”

Section: Autophagy and Emtmentioning

confidence: 99%

Autophagy Takes Center Stage as a Possible Cancer Hallmark

et al. 2020

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Cancer remains one of the leading causes of death worldwide, despite significant advances in cancer research and improvements in anticancer therapies. One of the major obstacles to curing cancer is the difficulty of achieving the complete annihilation of resistant cancer cells. The resistance of cancer cells may not only be due to intrinsic factors or factors acquired during the evolution of the tumor but may also be caused by chemotherapeutic treatment failure. Conversely, autophagy is a conserved cellular process in which intracellular components, such as damaged organelles, aggregated or misfolded proteins and macromolecules, are degraded or recycled to maintain cellular homeostasis. Importantly, autophagy is an essential mechanism that plays a key role in tumor initiation and progression. Depending on the cellular context and microenvironmental conditions, autophagy acts as a double-edged sword, playing a role in inducing apoptosis or promoting cell survival. In this review, we propose several scenarios in which autophagy could contribute to cell survival or cell death. Moreover, a special focus on novel promising targets and therapeutic strategies based on autophagic resistant cells is presented.

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“…Hence, regulating EMT by targeting autophagy is a promising potential strategy for cancer therapy. Currently, translational applications of autophagy activators such as rapamycin, and autophagy inhibitors such as chloroquine and 3-methyladenine to regulate the EMT process, have been utilised in anti-cancer therapy [ 67 , 76 , 77 ].…”

Section: Good Guys In the Emt Pathwaymentioning

confidence: 99%

Endogenous Anti-Cancer Candidates in GPCR, ER Stress, and EMT

Gundamaraju

Azimi

et al. 2020

Biomedicines

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The majority of cellular responses to external stimuli are mediated by receptors such as G protein-coupled receptors (GPCRs) and systems including endoplasmic reticulum stress (ER stress). Since GPCR signalling is pivotal in numerous malignancies, they are widely targeted by a number of clinical drugs. Cancer cells often negatively modulate GPCRs in order to survive, proliferate and to disseminate. Similarly, numerous branches of the unfolded protein response (UPR) act as pro-survival mediators and are involved in promoting cancer progression via mechanisms such as epithelial to mesenchymal transition (EMT). However, there are a few proteins among these groups which impede deleterious effects by orchestrating the pro-apoptotic phenomenon and paving a therapeutic pathway. The present review exposes and discusses such critical mechanisms and some of the key processes involved in carcinogenesis.

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Starvation‐induced autophagy promotes the invasion and migration of human bladder cancer cells via TGF‐β1/Smad3‐mediated epithelial‐mesenchymal transition activation

Cited by 64 publications

References 32 publications

Identifying Disease-Gene Associations With Graph-Regularized Manifold Learning

Identifying Disease-Gene Associations With Graph-Regularized Manifold Learning

Autophagy Takes Center Stage as a Possible Cancer Hallmark

Endogenous Anti-Cancer Candidates in GPCR, ER Stress, and EMT

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