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Expression levels of long non-coding RNAs are prognostic for AML outcome

Overview of attention for article published in Journal of Hematology & Oncology, April 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

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1 blog
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Title
Expression levels of long non-coding RNAs are prognostic for AML outcome
Published in
Journal of Hematology & Oncology, April 2018
DOI 10.1186/s13045-018-0596-2
Pubmed ID
Authors

Arvind Singh Mer, Johan Lindberg, Christer Nilsson, Daniel Klevebring, Mei Wang, Henrik Grönberg, Soren Lehmann, Mattias Rantalainen

Abstract

Long non-coding RNA (lncRNA) expression has been implicated in a range of molecular mechanisms that are central in cancer. However, lncRNA expression has not yet been comprehensively characterized in acute myeloid leukemia (AML). Here, we assess to what extent lncRNA expression is prognostic of AML patient overall survival (OS) and determine if there are indications of lncRNA-based molecular subtypes of AML. We performed RNA sequencing of 274 intensively treated AML patients in a Swedish cohort and quantified lncRNA expression. Univariate and multivariate time-to-event analysis was applied to determine association between individual lncRNAs with OS. Unsupervised statistical learning was applied to ascertain if lncRNA-based molecular subtypes exist and are prognostic. Thirty-three individual lncRNAs were found to be associated with OS (adjusted p value < 0.05). We established four distinct molecular subtypes based on lncRNA expression using a consensus clustering approach. LncRNA-based subtypes were found to stratify patients into groups with prognostic information (p value < 0.05). Subsequently, lncRNA expression-based subtypes were validated in an independent patient cohort (TCGA-AML). LncRNA subtypes could not be directly explained by any of the recurrent cytogenetic or mutational aberrations, although associations with some of the established genetic and clinical factors were found, including mutations in NPM1, TP53, and FLT3. LncRNA expression-based four subtypes, discovered in this study, are reproducible and can effectively stratify AML patients. LncRNA expression profiling can provide valuable information for improved risk stratification of AML patients.

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X Demographics

The data shown below were collected from the profiles of 11 X users 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 25%
Researcher 9 18%
Student > Master 5 10%
Student > Doctoral Student 2 4%
Student > Postgraduate 2 4%
Other 2 4%
Unknown 18 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 35%
Medicine and Dentistry 6 12%
Agricultural and Biological Sciences 3 6%
Immunology and Microbiology 2 4%
Computer Science 1 2%
Other 2 4%
Unknown 19 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 12 December 2022.
All research outputs
#2,389,042
of 23,322,966 outputs
Outputs from Journal of Hematology & Oncology
#176
of 1,208 outputs
Outputs of similar age
#52,661
of 329,748 outputs
Outputs of similar age from Journal of Hematology & Oncology
#5
of 35 outputs
Altmetric has tracked 23,322,966 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,208 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,748 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.