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RNAi screen identifies essential regulators of human brain metastasis-initiating cells

Overview of attention for article published in Acta Neuropathologica, August 2017
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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
5 news outlets
blogs
1 blog
twitter
4 X users
patent
1 patent
facebook
1 Facebook page
wikipedia
1 Wikipedia page

Citations

dimensions_citation
27 Dimensions

Readers on

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39 Mendeley
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Title
RNAi screen identifies essential regulators of human brain metastasis-initiating cells
Published in
Acta Neuropathologica, August 2017
DOI 10.1007/s00401-017-1757-z
Pubmed ID
Authors

Mohini Singh, Chitra Venugopal, Tomas Tokar, Kevin R. Brown, Nicole McFarlane, David Bakhshinyan, Thusyanth Vijayakumar, Branavan Manoranjan, Sujeivan Mahendram, Parvez Vora, Maleeha Qazi, Manvir Dhillon, Amy Tong, Kathrin Durrer, Naresh Murty, Robin Hallet, John A. Hassell, David R. Kaplan, Jean-Claude Cutz, Igor Jurisica, Jason Moffat, Sheila K. Singh

Abstract

Brain metastases (BM) are the most common brain tumor in adults and are a leading cause of cancer mortality. Metastatic lesions contain subclones derived from their primary lesion, yet their functional characterization is limited by a paucity of preclinical models accurately recapitulating the metastatic cascade, emphasizing the need for a novel approach to BM and their treatment. We identified a unique subset of stem-like cells from primary human patient brain metastases, termed brain metastasis-initiating cells (BMICs). We now establish a BMIC patient-derived xenotransplantation (PDXT) model as an investigative tool to comprehensively interrogate human BM. Using both in vitro and in vivo RNA interference screens of these BMIC models, we identified SPOCK1 and TWIST2 as essential BMIC regulators. SPOCK1 in particular is a novel regulator of BMIC self-renewal, modulating tumor initiation and metastasis from the lung to the brain. A prospective cohort of primary lung cancer specimens showed that SPOCK1 was overexpressed only in patients who ultimately developed BM. Protein-protein interaction network mapping between SPOCK1 and TWIST2 identified novel pathway interactors with significant prognostic value in lung cancer patients. Of these genes, INHBA, a TGF-β ligand found mutated in lung adenocarcinoma, showed reduced expression in BMICs with knockdown of SPOCK1. In conclusion, we have developed a useful preclinical model of BM, which has served to identify novel putative BMIC regulators, presenting potential therapeutic targets that block the metastatic process, and transform a uniformly fatal systemic disease into a locally controlled and eminently more treatable one.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 13%
Student > Bachelor 5 13%
Student > Ph. D. Student 4 10%
Student > Postgraduate 4 10%
Student > Master 3 8%
Other 6 15%
Unknown 12 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 23%
Medicine and Dentistry 7 18%
Agricultural and Biological Sciences 3 8%
Immunology and Microbiology 2 5%
Neuroscience 2 5%
Other 4 10%
Unknown 12 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 51. 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 25 May 2021.
All research outputs
#705,346
of 22,996,001 outputs
Outputs from Acta Neuropathologica
#95
of 2,376 outputs
Outputs of similar age
#16,338
of 317,441 outputs
Outputs of similar age from Acta Neuropathologica
#2
of 31 outputs
Altmetric has tracked 22,996,001 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,376 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one has done particularly well, scoring higher than 96% 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 317,441 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 94% of its contemporaries.
We're also able to compare this research output to 31 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 93% of its contemporaries.