linc-UBC1 physically associates with polycomb repressive complex 2 (PRC2) and acts as a negative prognostic factor for lymph node metastasis and survival in bladder cancer

Wang, He; Cai, Qingqing; Sun, Fenyong; Zhong, Guangzheng; Wang, Pei; Liu, Hongyan; Luo, Junpeng; Yu, Hao; Huang, Jian; Lin, Tianxin

doi:10.1016/j.bbadis.2013.05.010

Cited by 109 publications

(115 citation statements)

References 24 publications

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“…In the case of PRC2, binding motifs could not explain the association of the protein complex with thousands of RNA transcripts, as observed by immunoprecipitation-based approaches (Rinn et al 2007;Zhao et al 2008Zhao et al , 2010Guttman et al 2011;Heo and Sung 2011;Kotake et al 2011;Shore et al 2012;He et al 2013;Klattenhoff et al 2013;Sun et al 2014). In vivo CLIP and PAR-CLIP experiments for EZH2 (Guil et al 2012;Kaneko et al 2013) or JARID2 (Kaneko et al 2014a) did not result in well-defined peaks that could, in principle, lead to the discovery of binding motifs.…”

Section: Considering Rna Motifs For Prc2 Bindingmentioning

confidence: 99%

“…In addition to HOTAIR, Xist, RepA, Kcnq1ot1, and Braveheart, as described above, additional PRC2 target transcripts now included the lncRNAs MALAT1 (Guil et al 2012), both sense and antisense transcripts of H19 (Zhao et al 2010), ANRIL (Kotake et al 2011), MEG3 (Zhao et al 2010;Kaneko et al 2014a), PINC (Shore et al 2012), both sense and antisense transcripts of Nespas (Zhao et al 2010), NEAT1 (Guttman et al 2011), Air (Zhao et al 2010), Pint (Marin-Béjar et al 2013), lncRNA-EBIC ), BLACAT1/linc-UBC1 (which was suggested to act in trans) (He et al 2013), and COLDAIR from Arabidopsis thaliana (Heo and Sung 2011).…”

Section: Braveheartmentioning

confidence: 99%

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The recruitment of chromatin modifiers by long noncoding RNAs: lessons from PRC2

Davidovich

Cech

2015

RNA

259

224

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Polycomb repressive complex-2 (PRC2) is a histone methyltransferase required for epigenetic silencing during development and cancer. Among chromatin modifying factors shown to be recruited and regulated by long noncoding RNAs (lncRNAs), PRC2 is one of the most studied. Mammalian PRC2 binds thousands of RNAs in vivo, and it is becoming a model system for the recruitment of chromatin modifying factors by RNA. Yet, well-defined PRC2-binding motifs within target RNAs have been elusive. From the protein side, PRC2 RNA-binding subunits contain no known RNA-binding domains, complicating functional studies. Here we provide a critical review of existing models for the recruitment of PRC2 to chromatin by RNAs. This discussion may also serve researchers who are studying the recruitment of other chromatin modifiers by lncRNAs.

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Section: Considering Rna Motifs For Prc2 Bindingmentioning

confidence: 99%

Section: Braveheartmentioning

confidence: 99%

The recruitment of chromatin modifiers by long noncoding RNAs: lessons from PRC2

Davidovich

Cech

2015

RNA

259

224

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“…RPISeq's performance, using sequence information alone, was comparable to that of Pancaldi and Bähler's [15] method, which uses extensive feature information. An independent experimental validation of RPISeq predictions was published in a recent study [25], in which RPISeq was used to predict that the linc-UBC1 RNA interacts with PRC2 (Polycomb Repressive Complex 2). This prediction was experimentally validated using RNA immunoprecipitation, which confirmed that linc-UBC1 physically interacts with two core protein components of the PRC2 complex, EZH2 and SUZ12.…”

Section: Rna-protein Partner Prediction Methods and Web Serversmentioning

confidence: 99%

Computational Tools for Investigating RNA-Protein Interaction Partners

Muppirala¹,

Lewis

Dobbs

2013

J Comput Sci Syst Biol

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RNA-protein interactions are important in a wide variety of cellular and developmental processes. Recently, high-throughput experiments have begun to provide valuable information about RNA partners and binding sites for many RNA-binding proteins (RBPs), but these experiments are expensive and time consuming. Thus, computational methods for predicting RNA-Protein interactions (RPIs) can be valuable tools for identifying potential interaction partners of a given protein or RNA, and for identifying likely interfacial residues in RNAprotein complexes. This review focuses on the "partner prediction" problem and summarizes available computational methods, web servers and databases that are devoted to it. New computational tools for addressing the related "interface prediction" problem are also discussed. Together, these computational methods for investigating RNA-protein interactions provide the basis for new strategies for integrating RNAprotein interactions into existing genetic and developmental regulatory networks, an important goal of future research.

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“…The 111 LCALs include a lncRNA known to play a role in lung cancer (SCAL1 [16]), cancer-associated lncRNAs not previously implicated in lung cancer (CCAT1 [29], ESC-CAL-1 [30], LINC00261 [31], linc-UBC1 [32], UCA1 [33], ENST00000547963 [34], and PART-1 [35]), a lncRNA implicated in a lethal lung developmental disorder (FENDRR [36]), and three previously unannotated lncRNAs. Interestingly, the remaining 99 lncRNAs were previously annotated in normal human tissues but not implicated in human disease.…”

Section: Characterization Of Novel Lncrnasmentioning

confidence: 99%

Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer

et al. 2014

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Background: Long intergenic non-coding RNAs (lncRNAs) represent an emerging and under-studied class of transcripts that play a significant role in human cancers. Due to the tissue-and cancer-specific expression patterns observed for many lncRNAs it is believed that they could serve as ideal diagnostic biomarkers. However, until each tumor type is examined more closely, many of these lncRNAs will remain elusive. Results: Here we characterize the lncRNA landscape in lung cancer using publicly available transcriptome sequencing data from a cohort of 567 adenocarcinoma and squamous cell carcinoma tumors. Through this compendium we identify over 3,000 unannotated intergenic transcripts representing novel lncRNAs. Through comparison of both adenocarcinoma and squamous cell carcinomas with matched controls we discover 111 differentially expressed lncRNAs, which we term lung cancer-associated lncRNAs (LCALs). A pan-cancer analysis of 324 additional tumor and adjacent normal pairs enable us to identify a subset of lncRNAs that display enriched expression specific to lung cancer as well as a subset that appear to be broadly deregulated across human cancers. Integration of exome sequencing data reveals that expression levels of many LCALs have significant associations with the mutational status of key oncogenes in lung cancer. Functional validation, using both knockdown and overexpression, shows that the most differentially expressed lncRNA, LCAL1, plays a role in cellular proliferation.

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linc-UBC1 physically associates with polycomb repressive complex 2 (PRC2) and acts as a negative prognostic factor for lymph node metastasis and survival in bladder cancer

Abstract: Frequently overexpressed linc-UBC1 physically associates with PRC2 complex, and acts as a negative prognostic factor for lymph node metastasis and survival in bladder cancer.

Cited by 109 publications

References 24 publications

The recruitment of chromatin modifiers by long noncoding RNAs: lessons from PRC2

The recruitment of chromatin modifiers by long noncoding RNAs: lessons from PRC2

Computational Tools for Investigating RNA-Protein Interaction Partners

Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer

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