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Integrated Analysis of a Competing Endogenous RNA Network Revealing a Prognostic Signature for Cervical Cancer

Overview of attention for article published in Frontiers in oncology, September 2018
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Title
Integrated Analysis of a Competing Endogenous RNA Network Revealing a Prognostic Signature for Cervical Cancer
Published in
Frontiers in oncology, September 2018
DOI 10.3389/fonc.2018.00368
Pubmed ID
Authors

Leilei Xia, Han Wang, Shengyun Cai, Xiaoling Su, Jizi Shen, Qi Meng, Yu Chen, Li Li, Jiuqiong Yan, Caihong Zhang, Mingjuan Xu

Abstract

Given the high morbidity and the trend of younger individuals being affected observed in cervical cancer, it is important to identify sensitive and effective biomarkers for predicting the survival outcome of patients. Based on data from 307 cervical cancer cases acquired from The Cancer Genome Atlas portal, 1920 differentially expressed mRNAs, 70 microRNAs(miRNAs), and 493 long non-coding(lncRNAs) were screened by comparing cervical cancer tissues with paracancerous tissues. A competing endogenous (ceRNA) network containing 50 lncRNAs, 16 miRNAs, and 81 mRNAs was constructed. Eighteen RNAs, comprising 13 mRNAs, 2 miRNAs, and 3 lncRNAs, were identified as significant prognostic factors by univariate Cox proportional hazards regression. ETS-related gene and fatty acid synthase signatures were discovered using a multivariate Cox regression model built to identify independent prognostic factors in cervical cancer patients. Receiver operating characteristic (ROC) analysis was used to determine the optimal cut-off value for distinguishing the risk level of cervical cancer patients. High-risk patients exhibited a poorer prognosis than low-risk patients did. This study focused on ceRNA networks to provide a novel perspective and insight into cervical cancer and suggested that the identified signature can serve as an independent prognostic biomarker in cervical cancer.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 41%
Other 1 6%
Student > Doctoral Student 1 6%
Student > Ph. D. Student 1 6%
Student > Master 1 6%
Other 1 6%
Unknown 5 29%
Readers by discipline Count As %
Medicine and Dentistry 5 29%
Biochemistry, Genetics and Molecular Biology 4 24%
Social Sciences 1 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Unknown 6 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 September 2018.
All research outputs
#22,867,974
of 25,498,750 outputs
Outputs from Frontiers in oncology
#16,070
of 22,603 outputs
Outputs of similar age
#302,939
of 345,956 outputs
Outputs of similar age from Frontiers in oncology
#151
of 185 outputs
Altmetric has tracked 25,498,750 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,603 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 185 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.