Long noncoding RNA GAS5 suppresses triple negative breast cancer progression through inhibition of proliferation and invasion by competitively binding miR-196a-5p

2018 ◽  
Vol 104 ◽  
pp. 451-457 ◽  
Author(s):  
Shuqin Li ◽  
Jun Zhou ◽  
Zhaoxin Wang ◽  
Peishun Wang ◽  
Xitao Gao ◽  
...  
2019 ◽  
Vol 5 (3) ◽  
pp. eaat9820 ◽  
Author(s):  
Xi Jin ◽  
Xiao-En Xu ◽  
Yi-Zhou Jiang ◽  
Yi-Rong Liu ◽  
Wei Sun ◽  
...  

Human endogenous retroviruses (HERVs) play pivotal roles in the development of breast cancer. However, the detailed mechanisms of noncoding HERVs remain elusive. Here, our genome-wide transcriptome analysis of HERVs revealed that a primate long noncoding RNA, which we dubbed TROJAN, was highly expressed in human triple-negative breast cancer (TNBC). TROJAN promoted TNBC proliferation and invasion and indicated poor patient outcomes. We further confirmed that TROJAN could bind to ZMYND8, a metastasis-repressing factor, and increase its degradation through the ubiquitin-proteasome pathway by repelling ZNF592. TROJAN also epigenetically up-regulated metastasis-related genes in multiple cell lines. Correlations between TROJAN and ZMYND8 were subsequently confirmed in clinical samples. Furthermore, our study verified that antisense oligonucleotide therapy targeting TROJAN substantially suppressed TNBC progression in vivo. In conclusion, the long noncoding RNA TROJAN promotes TNBC progression and serves as a potential therapeutic target.


2021 ◽  
Vol 15 (1) ◽  
pp. 43-55
Author(s):  
Chao Yuan ◽  
Hongjun Yuan ◽  
Li Chen ◽  
Miaomiao Sheng ◽  
Wenru Tang

Background: Triple-negative breast cancer (TNBC) is characterized by fast tumor increase, rapid recurrence and natural metastasis. We aimed to identify a genetic signature for predicting the prognosis of TNBC. Materials & methods: We conducted a weighted correlation network analysis of datasets from the Gene Expression Omnibus. Multivariate Cox regression was used to construct a risk score model. Results: The multi-factor risk scoring model was meaningfully associated with the prognosis of patients with TBNC. The predictive power of the model was demonstrated by the time-dependent receiver operating characteristic curve and Kaplan–Meier curve, and verified using a validation set. Conclusion: We established a long noncoding RNA-based model for the prognostic prediction of TNBC.


Cancer ◽  
2022 ◽  
Author(s):  
Rama Rao Malla ◽  
Padmaraju Vasudevaraju ◽  
Rahul Kumar Vempati ◽  
Marni Rakshmitha ◽  
Neha Merchant ◽  
...  

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