| Title |
Long non-coding RNA functions in lung cancer
|
|---|---|
| Published in |
Tumor Biology, April 2015
|
| DOI | 10.1007/s13277-015-3449-4 |
| Pubmed ID | |
| Authors |
Haiwei Sang, Haihong Liu, Peng Xiong, Min Zhu |
| Abstract |
Numerous long non-coding RNAs (lncRNAs) have been discovered as a result of advances in sequencing methods in genomic research. Recent evidence indicates that lncRNAs may serve as gene regulators via various mechanisms, such as translational control. Dysregulation of lncRNAs contributes to the development and progression of several human diseases, notably lung cancer, which is one of the leading causes of cancer-associated death. Recent studies have identified key roles for molecules such as p53 and polycomb repressive complex 2 (PRC2) in carcinogenesis and the anti-carcinogenic action of lncRNAs. These findings point to the potential of lncRNAs as prospective diagnostic and prognostic biomarkers in lung cancer. In this review, we consider the functions of lncRNAs in translational control and discuss their involvement in lung cancer via p53, PRC2, and other pathways. We also consider the effects of modulating the levels and functions of lncRNAs. Further characterization of these lung cancer-associated lncRNAs will provide a better understanding of their potential roles as therapeutic targets. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 46 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 24% |
| Student > Ph. D. Student | 9 | 20% |
| Student > Master | 7 | 15% |
| Student > Bachelor | 6 | 13% |
| Lecturer | 2 | 4% |
| Other | 6 | 13% |
| Unknown | 5 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 35% |
| Medicine and Dentistry | 9 | 20% |
| Agricultural and Biological Sciences | 8 | 17% |
| Nursing and Health Professions | 2 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 6 | 13% |
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 25 April 2015.
All research outputs
#15,330,127
of 22,800,560 outputs
Outputs from Tumor Biology
#1,050
of 2,622 outputs
Outputs of similar age
#157,716
of 265,398 outputs
Outputs of similar age from Tumor Biology
#42
of 149 outputs
Altmetric has tracked 22,800,560 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,622 research outputs from this source. They receive a mean Attention Score of 2.2. This one has gotten more attention than average, scoring higher than 53% of its peers.
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We're also able to compare this research output to 149 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.