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An RNA editing fingerprint of cancer stem cell reprogramming

Overview of attention for article published in Journal of Translational Medicine, February 2015
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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3 X users
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1 Wikipedia page

Citations

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47 Dimensions

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75 Mendeley
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Title
An RNA editing fingerprint of cancer stem cell reprogramming
Published in
Journal of Translational Medicine, February 2015
DOI 10.1186/s12967-014-0370-3
Pubmed ID
Authors

Leslie A Crews, Qingfei Jiang, Maria A Zipeto, Elisa Lazzari, Angela C Court, Shawn Ali, Christian L Barrett, Kelly A Frazer, Catriona HM Jamieson

Abstract

Deregulation of RNA editing by adenosine deaminases acting on dsRNA (ADARs) has been implicated in the progression of diverse human cancers including hematopoietic malignancies such as chronic myeloid leukemia (CML). Inflammation-associated activation of ADAR1 occurs in leukemia stem cells specifically in the advanced, often drug-resistant stage of CML known as blast crisis. However, detection of cancer stem cell-associated RNA editing by RNA sequencing in these rare cell populations can be technically challenging, costly and requires PCR validation. The objectives of this study were to validate RNA editing of a subset of cancer stem cell-associated transcripts, and to develop a quantitative RNA editing fingerprint assay for rapid detection of aberrant RNA editing in human malignancies. To facilitate quantification of cancer stem cell-associated RNA editing in exons and intronic or 3'UTR primate-specific Alu sequences using a sensitive, cost-effective method, we established an in vitro RNA editing model and developed a sensitive RNA editing fingerprint assay that employs a site-specific quantitative PCR (RESSq-PCR) strategy. This assay was validated in a stably-transduced human leukemia cell line, lentiviral-ADAR1 transduced primary hematopoietic stem and progenitor cells, and in primary human chronic myeloid leukemia stem cells. In lentiviral ADAR1-expressing cells, increased RNA editing of MDM2, APOBEC3D, GLI1 and AZIN1 transcripts was detected by RESSq-PCR with improved sensitivity over sequencing chromatogram analysis. This method accurately detected cancer stem cell-associated RNA editing in primary chronic myeloid leukemia samples, establishing a cancer stem cell-specific RNA editing fingerprint of leukemic transformation that will support clinical development of novel diagnostic tools to predict and prevent cancer progression. RNA editing quantification enables rapid detection of malignant progenitors signifying cancer progression and therapeutic resistance, and will aid future RNA editing inhibitor development efforts.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 1%
Spain 1 1%
Unknown 73 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 20%
Researcher 13 17%
Student > Master 11 15%
Student > Bachelor 10 13%
Other 8 11%
Other 10 13%
Unknown 8 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 33%
Biochemistry, Genetics and Molecular Biology 21 28%
Medicine and Dentistry 6 8%
Chemistry 4 5%
Computer Science 2 3%
Other 7 9%
Unknown 10 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 23 April 2017.
All research outputs
#6,280,124
of 22,789,076 outputs
Outputs from Journal of Translational Medicine
#949
of 3,988 outputs
Outputs of similar age
#88,464
of 357,813 outputs
Outputs of similar age from Journal of Translational Medicine
#26
of 115 outputs
Altmetric has tracked 22,789,076 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 3,988 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 75% 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 357,813 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.