Long Noncoding RNA DANCR in Various Cancers: a Meta-Analysis and Bioinformatics.
Cancer Management and Research(2019)
Zhejiang Univ | Hangzhou Tumor Hosp | 79 Qingchun Rd
Abstract
BACKGROUND:Differentiation antagonizing non-protein-coding RNA (DANCR) is a novel long noncoding RNA. Recent studies have shown that DANCR is aberrantly expressed in several types of cancer and is associated with poor outcomes. However, the clinical diagnostic significance of DANCR in tumors is not completely understood.METHODS:We searched the PubMed, Medline, Web of Science, EMBASE, Cochrane Library, and Ovid databases (up to December 30, 2018) for relevant literature. A total of 11 studies with 945 cancer patients were included in the present meta-analysis. We further validated the results using The Cancer Genome Atlas (TCGA) dataset.RESULTS:High expression of DANCR significantly predicted poor overall survival (low expression group vs high expression group; HR =0.56, 95% CI=[0.43, 0.72], =0.000); this was validated using TCGA. Moreover, DANCR expression was associated with advanced tumor node metastasis stage (I+II:III+IV; OR=0.22, 95% CI=[0.14, 0.35], P=0.001) and lymph node metastasis (no:yes; OR=0.21, 95% CI=[0.13, 0.35], P=0.001).CONCLUSION:Our results suggest that elevated DANCR is related to poor clinical outcomes and could serve as a potential prognostic biomarker of cancer.
MoreTranslated text
Key words
cancer,overall survival,TCGA,long noncoding RNA,DANCR,meta-analysis
PDF
View via Publisher
AI Read Science
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
BMC cancer 2020
被引用18
BMC Cancer 2020
被引用0
BMC Cancer 2020
被引用12
Clinical Laboratory 2020
被引用2
Bioscience reports 2020
被引用11
Cancer Biotherapy and Radiopharmaceuticals 2020
被引用13
The Practical Journal of Cancer 2020
被引用1
Risk Score Model of Autophagy-Related Genes in Osteosarcoma
Annals of Translational Medicine 2022
被引用1
JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH 2021
被引用2
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
去 AI 文献库 对话