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Single-cell transcriptome analysis of lineage diversity in high-grade glioma

Overview of attention for article published in Genome Medicine, July 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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21 X users

Citations

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177 Dimensions

Readers on

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232 Mendeley
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Title
Single-cell transcriptome analysis of lineage diversity in high-grade glioma
Published in
Genome Medicine, July 2018
DOI 10.1186/s13073-018-0567-9
Pubmed ID
Authors

Jinzhou Yuan, Hanna Mendes Levitin, Veronique Frattini, Erin C. Bush, Deborah M. Boyett, Jorge Samanamud, Michele Ceccarelli, Athanassios Dovas, George Zanazzi, Peter Canoll, Jeffrey N. Bruce, Anna Lasorella, Antonio Iavarone, Peter A. Sims

Abstract

Despite extensive molecular characterization, we lack a comprehensive understanding of lineage identity, differentiation, and proliferation in high-grade gliomas (HGGs). We sampled the cellular milieu of HGGs by profiling dissociated human surgical specimens with a high-density microwell system for massively parallel single-cell RNA-Seq. We analyzed the resulting profiles to identify subpopulations of both HGG and microenvironmental cells and applied graph-based methods to infer structural features of the malignantly transformed populations. While HGG cells can resemble glia or even immature neurons and form branched lineage structures, mesenchymal transformation results in unstructured populations. Glioma cells in a subset of mesenchymal tumors lose their neural lineage identity, express inflammatory genes, and co-exist with marked myeloid infiltration, reminiscent of molecular interactions between glioma and immune cells established in animal models. Additionally, we discovered a tight coupling between lineage resemblance and proliferation among malignantly transformed cells. Glioma cells that resemble oligodendrocyte progenitors, which proliferate in the brain, are often found in the cell cycle. Conversely, glioma cells that resemble astrocytes, neuroblasts, and oligodendrocytes, which are non-proliferative in the brain, are generally non-cycling in tumors. These studies reveal a relationship between cellular identity and proliferation in HGG and distinct population structures that reflects the extent of neural and non-neural lineage resemblance among malignantly transformed cells.

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The data shown below were collected from the profiles of 21 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 232 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 232 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 46 20%
Student > Ph. D. Student 44 19%
Student > Master 24 10%
Student > Bachelor 16 7%
Student > Doctoral Student 16 7%
Other 29 13%
Unknown 57 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 75 32%
Medicine and Dentistry 25 11%
Agricultural and Biological Sciences 21 9%
Neuroscience 12 5%
Immunology and Microbiology 9 4%
Other 25 11%
Unknown 65 28%
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 23 September 2018.
All research outputs
#2,701,033
of 25,225,928 outputs
Outputs from Genome Medicine
#622
of 1,560 outputs
Outputs of similar age
#52,413
of 336,189 outputs
Outputs of similar age from Genome Medicine
#11
of 24 outputs
Altmetric has tracked 25,225,928 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 1,560 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.1. This one has gotten more attention than average, scoring higher than 60% 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 336,189 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 24 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 58% of its contemporaries.