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The long non-coding RNA HOTAIR promotes the proliferation of serous ovarian cancer cells through the regulation of cell cycle arrest and apoptosis.

Jun-Jun Qiu | Yan Wang | Jing-Xin Ding | Hong-Yan Jin | Gong Yang | Ke-Qin Hua
Experimental cell research | 2015

HOX transcript antisense RNA (HOTAIR) is a well-known long non-coding RNA (lncRNA) whose dysregulation correlates with poor prognosis and malignant progression in many forms of cancer. Here, we investigate the expression pattern, clinical significance, and biological function of HOTAIR in serous ovarian cancer (SOC). Clinically, we found that HOTAIR levels were overexpressed in SOC tissues compared with normal controls and that HOTAIR overexpression was correlated with an advanced FIGO stage and a high histological grade. Multivariate analysis revealed that HOTAIR is an independent prognostic factor for predicting overall survival in SOC patients. We demonstrated that HOTAIR silencing inhibited A2780 and OVCA429 SOC cell proliferation in vitro and that the anti-proliferative effects of HOTAIR silencing also occurred in vivo. Further investigation into the mechanisms responsible for the growth inhibitory effects by HOTAIR silencing revealed that its knockdown resulted in the induction of cell cycle arrest and apoptosis through certain cell cycle-related and apoptosis-related proteins. Together, these results highlight a critical role of HOTAIR in SOC cell proliferation and contribute to a better understanding of the importance of dysregulated lncRNAs in SOC progression.

Pubmed ID: 25796453

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RRID:SCR_005012

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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