Research Papers:

A bibliometric analysis of long non-coding RNA and chemotherapeutic resistance research

Xiaoman Chen, Yulu Shi, Kaiwen Zhou, Sijie Yu, Wei Cai and Muying Ying _

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Oncotarget. 2019; 10:3267-3275. https://doi.org/10.18632/oncotarget.26938

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Xiaoman Chen1, Yulu Shi2, Kaiwen Zhou1, Sijie Yu2, Wei Cai3 and Muying Ying1

1 Department of Molecular Biology and Biochemistry, Basic Medical College of Nanchang University, Nanchang, PR China

2 Queen Mary School of Nanchang University, Nanchang, PR China

3 Department of Medical Genetics and Cell Biology, Basic Medical College of Nanchang University, Nanchang, PR China

Correspondence to:

Muying Ying,email: [email protected]

Keywords: chemotherapeutic resistance; lncRNA; citespace; bibliometric analysis

Received: February 10, 2019     Accepted: May 02, 2019     Published: May 14, 2019


The global outputs of annual publication in long non-coding RNAs (lncRNAs) and chemotherapeutic resistance research exponentially increased from 2 in 2008 to 176 in 2017. Using Java application CiteSpace V and VOSviewer, this study assessed the publication model of lncRNAs and chemoresistance by bibliometric analysis. Totally, 2883 authors contributed 528 publications of lncRNAs and chemoresistance in 215 academic journals in the recent decade (2008-2018). Oncotarget in the 215 academic journals published the highest number of publications (60). China had the highest number of publication outputs (358). The leading institute was Nanjing Medical University. Wang Y was the most influential author (13 counts). Gupta RA had the most cited documents (87 counts). “Gene expression” and “poor prognosis” were identified as the hotspots. “Cancer stem cell”, “HOTAIR” and “UCA1” were the frontiers of the fields in recent years. The increase of publications on lncRNAs and chemotherapeutic resistance will continue in the next years. HOTAIR and UCA1 with multiple roles in drug resistance may offer big opportunities for targeted chemoresistance in cancer therapy. These results may help us discover and explain the possible underlying laws of the subject.

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