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Sample processing obscures cancer-specific alterations in leukemic transcriptomes

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, November 2014
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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 (91st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

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Citations

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127 Mendeley
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1 CiteULike
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Title
Sample processing obscures cancer-specific alterations in leukemic transcriptomes
Published in
Proceedings of the National Academy of Sciences of the United States of America, November 2014
DOI 10.1073/pnas.1413374111
Pubmed ID
Authors

Heidi Dvinge, Rhonda E. Ries, Janine O. Ilagan, Derek L. Stirewalt, Soheil Meshinchi, Robert K. Bradley

Abstract

Substantial effort is currently devoted to identifying cancer-associated alterations using genomics. Here, we show that standard blood collection procedures rapidly change the transcriptional and posttranscriptional landscapes of hematopoietic cells, resulting in biased activation of specific biological pathways; up-regulation of pseudogenes, antisense RNAs, and unannotated coding isoforms; and RNA surveillance inhibition. Affected genes include common mutational targets and thousands of other genes participating in processes such as chromatin modification, RNA splicing, T- and B-cell activation, and NF-κB signaling. The majority of published leukemic transcriptomes exhibit signals of this incubation-induced dysregulation, explaining up to 40% of differences in gene expression and alternative splicing between leukemias and reference normal transcriptomes. The effects of sample processing are particularly evident in pan-cancer analyses. We provide biomarkers that detect prolonged incubation of individual samples and show that keeping blood on ice markedly reduces changes to the transcriptome. In addition to highlighting the potentially confounding effects of technical artifacts in cancer genomics data, our study emphasizes the need to survey the diversity of normal as well as neoplastic cells when characterizing tumors.

X Demographics

X Demographics

The data shown below were collected from the profiles of 35 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 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 5%
Australia 1 <1%
United Kingdom 1 <1%
Sweden 1 <1%
Spain 1 <1%
Denmark 1 <1%
Unknown 116 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 32%
Student > Ph. D. Student 29 23%
Student > Master 11 9%
Student > Bachelor 9 7%
Professor 8 6%
Other 19 15%
Unknown 10 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 42%
Biochemistry, Genetics and Molecular Biology 31 24%
Computer Science 7 6%
Medicine and Dentistry 6 5%
Engineering 6 5%
Other 13 10%
Unknown 11 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 02 April 2023.
All research outputs
#1,969,929
of 25,621,213 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#24,347
of 103,446 outputs
Outputs of similar age
#22,299
of 273,765 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#388
of 967 outputs
Altmetric has tracked 25,621,213 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 103,446 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.6. This one has done well, scoring higher than 76% 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 273,765 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 967 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 59% of its contemporaries.