Inhibition of Snail Family Transcriptional Repressor 2 (SNAI2) Enhances Multidrug Resistance of Hepatocellular Carcinoma Cells

Zhao, Xinyu; Li, Lei; Wang, Xiao-Bo; Fu, Rongjie; Lv, Yaping; Jin, Wei; Meng, Chao; Chen, Guoqiang; Huang, Lei; Zhao, Ke-Wen

doi:10.1371/journal.pone.0164752

Cited by 10 publications

(10 citation statements)

References 48 publications

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“…Several drugs, such as Rapamycin, Indomethacin and Cisplatin, target the apoptosis pathway [56,10,58]. Therapeutic targets for gastric cancer have also been found in Calcium and TJ pathways [40,53,60]. These studies show that pathway pairs highlighted by our algorithm have multiple targetable alterations that have been exploited in therapy development.…”

Section: Stca Datasetmentioning

confidence: 80%

Mining Pathway Associations from Networks of Mutual Exclusivity Interactions

Liany

Lin

Jeyasekharan

et al. 2020

Preprint

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Study of pairwise genetic interactions such as mutual exclusivity or synthetic lethality has led to the development of targeted anticancer therapies, and mining the network of such interactions is a common approach used to obtain deeper insights into the mechanism of cancer. A number of useful graph clustering-based tools exist to mine interaction networks. We develop a new network mining algorithm that can provide a pathway-centric view that existing tools cannot. Our approach is based on finding edge-disjoint bipartite subgraphs of highest weights in an input network of genes, where edge weights indicate the significance of the interaction and each set of nodes in every bipartite subgraph is constrained to belong to a single pathway. This problem is NP-hard and we develop an Integer Linear Program to solve this problem. We evaluate our algorithm on breast and stomach cancer data. Our algorithm mines dense between-pathway interactions that are known to play important roles in cancer and are therapeutically actionable. Our algorithm complements existing network mining tools and can be useful to study the mutational landscape of cancer and inform therapy development.

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Section: Stca Datasetmentioning

confidence: 80%

Mining Pathway Associations from Networks of Mutual Exclusivity Interactions

Liany

Lin

Jeyasekharan

et al. 2020

Preprint

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“…Abnormally high expression of SNAI2 has been found in various cancers, including breast cancer [30], colorectal cancer [31] and melanoma [32]. Interestingly, Zhao et al first discovered that SNAI2 could as a tumor suppressor by repressing multidrug resistance via decreasing ABC transporter genes in hepatocellular carcinoma cells [33]. In our study, we found that SNAI2 served as an oncogene and directly targeted by miR-33a-5p in melanoma, and the miR-33a-5p could negatively modulate the expression of SNAI2.…”

Section: Discussionmentioning

confidence: 99%

miR-33a-5p inhibits the growth and metastasis of melanoma cells by targeting SNAI2

Zhang¹,

Yang²

2020

neo

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MicroRNAs have been verified as critical regulators in the development of melanoma. MiR-33a-5p was significantly downregulated in melanoma. However, the specific role and regulatory mechanism of miR-33a-5p in melanoma were still unclear. The present study identified that miR-33a-5p was downregulated in melanoma tissues and cells, while SNAI2 was upregulated. MiR-33a-5p directly targeted SNAI2 and negatively regulated its expression in melanoma cells. Overexpression of miR-33a-5p repressed proliferation, migration, invasion, EMT and promoted apoptosis of melanoma cell in vitro, these effects were partially reversed by SNAI2 overexpression. In addition, miR-33a-5p impaired melanoma growth in vivo by inhibiting SNAI2. Mechanistically, miR-33a-5p repressed activation of the PI3K/AKT/mTOR pathway by targeting SNAI2. In conclusion, miR-33a-5p repressed the progression of melanoma by targeting SNAI2 via inactivation of the PI3K/AKT/mTOR signaling pathway, providing a potential molecular mechanism for the treatment of melanoma.

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“…The induction of EMT by SNAI2 can not only promote the invasion ability in cancer cells, but also lead to drug resistance, pressure, and immune response 29 . In liver cancer, SNAI2 can control multidrug resistance by inhibiting the expression of ABC transporter gene 30 . Moreover, several previous studies demonstrated that expression of CDH2 has a positive correlation with SNAI2 in tumor tissues.…”

Section: Discussionmentioning

confidence: 99%

MYH9 promotes cell metastasis via inducing Angiogenesis and Epithelial Mesenchymal Transition in Esophageal Squamous Cell Carcinoma

Yang¹,

Liu²,

Bi³

et al. 2020

Int. J. Med. Sci.

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Non-muscle myosin heavy chain 9 (MYH9) is one novel low frequency mutated gene identified in esophageal squamous cell carcinoma (ESCC) using next-generation sequencing. However, its clinical relevance, potential function and mechanisms remain elusive. Methods: Genomic sequencing datas from 104 esophageal squamous cell carcinoma (ESCC) cases were screened a series of low frequency mutant genes. MYH9 was selected to further analyze its clinical significance, function and PCR-array was performed to explore its potential mechanism. Results: MHY9 is a low frequency mutant gene with a mutation frequency of 2.88% in ESCC. Immunohistochemical analysis showed that MYH9 expression was significantly higher in ESCC tumor tissues, and the expression levels were associated with lymph node metastasis of ESCC patients. Moreover, we found that MYH9 knock-down led to inhibition of cell migration and invasion. PCR-array showed MYH9 knockdown led to a significant change of genes expression associated with angiogenesis and epithelial-to-mesenchymal transition (EMT). This observation is further confirmed in TCGA database of LUSC (lung squamous cell carcinoma), CESC (cervical squamous cell carcinomas) and HNSC (head and neck squamous cell carcinoma). Conclusions: Collectively, our study identifies a novel role and mechanism of MYH9, highlights a significance of MYH9 as a metastatic biomarker, and offers potential therapeutic targets for ESCC patients harboring MYH9 mutations.

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Inhibition of Snail Family Transcriptional Repressor 2 (SNAI2) Enhances Multidrug Resistance of Hepatocellular Carcinoma Cells

Cited by 10 publications

References 48 publications

Mining Pathway Associations from Networks of Mutual Exclusivity Interactions

Mining Pathway Associations from Networks of Mutual Exclusivity Interactions

miR-33a-5p inhibits the growth and metastasis of melanoma cells by targeting SNAI2

MYH9 promotes cell metastasis via inducing Angiogenesis and Epithelial Mesenchymal Transition in Esophageal Squamous Cell Carcinoma

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