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The Landscape of Circular RNA in Cancer

Overview of attention for article published in Cell, February 2019
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
9 news outlets
blogs
1 blog
twitter
236 tweeters
facebook
1 Facebook page
Title
The Landscape of Circular RNA in Cancer
Published in
Cell, February 2019
DOI 10.1016/j.cell.2018.12.021
Pubmed ID
Authors

Josh N. Vo, Marcin Cieslik, Yajia Zhang, Sudhanshu Shukla, Lanbo Xiao, Yuping Zhang, Yi-Mi Wu, Saravana M. Dhanasekaran, Carl G. Engelke, Xuhong Cao, Dan R. Robinson, Alexey I. Nesvizhskii, Arul M. Chinnaiyan

Abstract

Circular RNAs (circRNAs) are an intriguing class of RNA due to their covalently closed structure, high stability, and implicated roles in gene regulation. Here, we used an exome capture RNA sequencing protocol to detect and characterize circRNAs across >2,000 cancer samples. When compared against Ribo-Zero and RNase R, capture sequencing significantly enhanced the enrichment of circRNAs and preserved accurate circular-to-linear ratios. Using capture sequencing, we built the most comprehensive catalog of circRNA species to date: MiOncoCirc, the first database to be composed primarily of circRNAs directly detected in tumor tissues. Using MiOncoCirc, we identified candidate circRNAs to serve as biomarkers for prostate cancer and were able to detect circRNAs in urine. We further detected a novel class of circular transcripts, termed read-through circRNAs, that involved exons originating from different genes. MiOncoCirc will serve as a valuable resource for the development of circRNAs as diagnostic or therapeutic targets across cancer types.

Twitter Demographics

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Attention Score in Context

This research output has an Altmetric Attention Score of 199. 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 2019.
All research outputs
#58,540
of 12,533,239 outputs
Outputs from Cell
#363
of 14,555 outputs
Outputs of similar age
#1,409
of 160,039 outputs
Outputs of similar age from Cell
#10
of 102 outputs
Altmetric has tracked 12,533,239 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,555 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.7. This one has done particularly well, scoring higher than 97% 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 160,039 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 99% of its contemporaries.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.