Long Noncoding RNA H19 in Digestive System Cancers: A Meta-Analysis of Its Association with Pathological Features
Joint Authors
Lin, Yang
Xu, Lijian
Wei, Wei
Zhang, Xiaohui
Ying, Rongchao
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-21
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Long noncoding RNA (lncRNA) H19 has been reported to be upregulated in malignant digestive tumors, but its clinical relevance is not yet established.
The meta-analysis was to investigate the association between H19 expression and pathological features of digestive system cancers.
The databases of PubMed, EMBase, Web of Science, CNKI, and WanFang were searched for the related studies.
A total of 478 patients from 6 studies were finally included.
The meta-analysis showed that the patient group of high H19 expression had a higher risk of poorly differentiated grade, deep tumor invasion (T2 stage or more), lymph node metastasis, and advanced TNM stage than the group of low H19 expression, although there was no difference between them in terms of distant metastasis.
Therefore, the high expression of lncRNA H19 might predict poor oncological outcomes of patients with digestive system cancers.
American Psychological Association (APA)
Lin, Yang& Xu, Lijian& Wei, Wei& Zhang, Xiaohui& Ying, Rongchao. 2016. Long Noncoding RNA H19 in Digestive System Cancers: A Meta-Analysis of Its Association with Pathological Features. BioMed Research International،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1097925
Modern Language Association (MLA)
Lin, Yang…[et al.]. Long Noncoding RNA H19 in Digestive System Cancers: A Meta-Analysis of Its Association with Pathological Features. BioMed Research International No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1097925
American Medical Association (AMA)
Lin, Yang& Xu, Lijian& Wei, Wei& Zhang, Xiaohui& Ying, Rongchao. Long Noncoding RNA H19 in Digestive System Cancers: A Meta-Analysis of Its Association with Pathological Features. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1097925
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1097925