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Mendeley readers
Attention Score in Context
| Title |
Isoform specific gene expression analysis of KRAS in the prognosis of lung adenocarcinoma patients
|
|---|---|
| Published in |
BMC Bioinformatics, February 2018
|
| DOI | 10.1186/s12859-018-2011-y |
| Pubmed ID | |
| Authors |
In Seok Yang, Sangwoo Kim |
| Abstract |
Aberrant mutations in KRAS play a critical role in tumor initiation and progression, and are a negative prognosis factor in lung adenocarcinoma (LUAD). Using genomic analysis for K-Ras isoforms (K-Ras4A and K-Ras4B) and large-scale multi-omics data, we inspected the overall survival (OS) and disease-free survival (DFS) of LUAD patients based on the abundance of transcript variants by analyzing RNA expression and somatic mutation data from The Cancer Genome Atlas (n = 516). The expression of the minor transcript K-Ras4A and its proportion were positively correlated with the presence of KRAS mutations in LUAD. We found that both K-Ras4A abundance measures (expression and proportion) have a strong association with poor OS (p = 0.0149 and p = 3.18E-3, respectively) and DFS (p = 3.03E-4 and p = 0.0237, respectively), but only in patients harboring KRAS mutations. A Cox regression analysis showed significant results in groups with low expression (hazard ratio (HR) = 2.533, 95% confidence interval (CI) = 1.380-4.651, p = 2.72E-3) and low proportion (HR = 2.549, 95% CI = 1.387-4.684, p = 2.58E-3) of K-Ras4A. Based on the above results, we report the possible use of abundance measures for K-Ras4A for predicting the survival of LUAD patients with KRAS mutations. |
X Demographics
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 32% |
| Student > Doctoral Student | 2 | 11% |
| Student > Bachelor | 2 | 11% |
| Student > Ph. D. Student | 2 | 11% |
| Other | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 6 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 26% |
| Medicine and Dentistry | 3 | 16% |
| Mathematics | 1 | 5% |
| Veterinary Science and Veterinary Medicine | 1 | 5% |
| Computer Science | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 7 | 37% |
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 20 February 2018.
All research outputs
#20,465,050
of 23,023,224 outputs
Outputs from BMC Bioinformatics
#6,891
of 7,316 outputs
Outputs of similar age
#292,330
of 330,824 outputs
Outputs of similar age from BMC Bioinformatics
#86
of 94 outputs
Altmetric has tracked 23,023,224 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 7,316 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. 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 94 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.