Literature DB >> 29390072

Quantification of non-coding RNA target localization diversity and its application in cancers.

Lixin Cheng1, Kwong-Sak Leung1.   

Abstract

Subcellular localization is pivotal for RNAs and proteins to implement biological functions. The localization diversity of protein interactions has been studied as a crucial feature of proteins, considering that the protein-protein interactions take place in various subcellular locations. Nevertheless, the localization diversity of non-coding RNA (ncRNA) target proteins has not been systematically studied, especially its characteristics in cancers. In this study, we provide a new algorithm, non-coding RNA target localization coefficient (ncTALENT), to quantify the target localization diversity of ncRNAs based on the ncRNA-protein interaction and protein subcellular localization data. ncTALENT can be used to calculate the target localization coefficient of ncRNAs and measure how diversely their targets are distributed among the subcellular locations in various scenarios. We focus our study on long non-coding RNAs (lncRNAs), and our observations reveal that the target localization diversity is a primary characteristic of lncRNAs in different biotypes. Moreover, we found that lncRNAs in multiple cancers, differentially expressed cancer lncRNAs, and lncRNAs with multiple cancer target proteins are prone to have high target localization diversity. Furthermore, the analysis of gastric cancer helps us to obtain a better understanding that the target localization diversity of lncRNAs is an important feature closely related to clinical prognosis. Overall, we systematically studied the target localization diversity of the lncRNAs and uncovered its association with cancer.

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Year:  2018        PMID: 29390072     DOI: 10.1093/jmcb/mjy006

Source DB:  PubMed          Journal:  J Mol Cell Biol        ISSN: 1759-4685            Impact factor:   6.216


  18 in total

1.  Knockdown of lncRNA MALAT1 Alleviates LPS-Induced Acute Lung Injury via Inhibiting Apoptosis Through the miR-194-5p/FOXP2 Axis.

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Journal:  Front Cell Dev Biol       Date:  2020-10-07

2.  A novel lincRNA identified in buffalo oocytes with protein binding characteristics could hold the key for oocyte competence.

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3.  PAX8-AS1 knockdown facilitates cell growth and inactivates autophagy in osteoblasts via the miR-1252-5p/GNB1 axis in osteoporosis.

Authors:  Caiqiang Huang; Runguang Li; Changsheng Yang; Rui Ding; Qingchu Li; Denghui Xie; Rongkai Zhang; Yiyan Qiu
Journal:  Exp Mol Med       Date:  2021-05-19       Impact factor: 8.718

4.  Perspectives From Systems Biology to Improve Knowledge of Leishmania Drug Resistance.

Authors:  Elvira Cynthia Alves Horácio; Jéssica Hickson; Silvane Maria Fonseca Murta; Jeronimo Conceição Ruiz; Laila Alves Nahum
Journal:  Front Cell Infect Microbiol       Date:  2021-04-30       Impact factor: 5.293

5.  Whole blood transcriptomic investigation identifies long non-coding RNAs as regulators in sepsis.

Authors:  Lixin Cheng; Chuanchuan Nan; Lin Kang; Ning Zhang; Sheng Liu; Huaisheng Chen; Chengying Hong; Youlian Chen; Zhen Liang; Xueyan Liu
Journal:  J Transl Med       Date:  2020-05-29       Impact factor: 5.531

6.  Weighted correlation network bioinformatics uncovers a key molecular biosignature driving the left-sided heart failure.

Authors:  Jiamin Zhou; Wei Zhang; Chunying Wei; Zhiliang Zhang; Dasong Yi; Xiaoping Peng; Jingtian Peng; Ran Yin; Zeqi Zheng; Hongmei Qi; Yunfeng Wei; Tong Wen
Journal:  BMC Med Genomics       Date:  2020-07-03       Impact factor: 3.063

7.  Overexpression of mechanical sensitive miR-337-3p alleviates ectopic ossification in rat tendinopathy model via targeting IRS1 and Nox4 of tendon-derived stem cells.

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Journal:  J Mol Cell Biol       Date:  2020-05-18       Impact factor: 6.216

Review 8.  Normalization Methods for the Analysis of Unbalanced Transcriptome Data: A Review.

Authors:  Xueyan Liu; Nan Li; Sheng Liu; Jun Wang; Ning Zhang; Xubin Zheng; Kwong-Sak Leung; Lixin Cheng
Journal:  Front Bioeng Biotechnol       Date:  2019-11-26

9.  Computational systems biology for omics data analysis.

Authors:  Luonan Chen
Journal:  J Mol Cell Biol       Date:  2019-08-19       Impact factor: 6.216

10.  LncLocation: Efficient Subcellular Location Prediction of Long Non-Coding RNA-Based Multi-Source Heterogeneous Feature Fusion.

Authors:  Shiyao Feng; Yanchun Liang; Wei Du; Wei Lv; Ying Li
Journal:  Int J Mol Sci       Date:  2020-10-01       Impact factor: 5.923

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