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Integrated Functional, Gene Expression and Genomic Analysis for the Identification of Cancer Targets

Overview of attention for article published in PLOS ONE, April 2009
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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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

blogs
1 blog
patent
3 patents
peer_reviews
1 peer review site
wikipedia
1 Wikipedia page

Readers on

mendeley
103 Mendeley
citeulike
5 CiteULike
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Title
Integrated Functional, Gene Expression and Genomic Analysis for the Identification of Cancer Targets
Published in
PLOS ONE, April 2009
DOI 10.1371/journal.pone.0005120
Pubmed ID
Authors

Elizabeth Iorns, Christopher J. Lord, Anita Grigoriadis, Sarah McDonald, Kerry Fenwick, Alan MacKay, Charles A. Mein, Rachael Natrajan, Kay Savage, Narinder Tamber, Jorge S. Reis-Filho, Nicholas C. Turner, Alan Ashworth

Abstract

The majority of new drug approvals for cancer are based on existing therapeutic targets. One approach to the identification of novel targets is to perform high-throughput RNA interference (RNAi) cellular viability screens. We describe a novel approach combining RNAi screening in multiple cell lines with gene expression and genomic profiling to identify novel cancer targets. We performed parallel RNAi screens in multiple cancer cell lines to identify genes that are essential for viability in some cell lines but not others, suggesting that these genes constitute key drivers of cellular survival in specific cancer cells. This approach was verified by the identification of PIK3CA, silencing of which was selectively lethal to the MCF7 cell line, which harbours an activating oncogenic PIK3CA mutation. We combined our functional RNAi approach with gene expression and genomic analysis, allowing the identification of several novel kinases, including WEE1, that are essential for viability only in cell lines that have an elevated level of expression of this kinase. Furthermore, we identified a subset of breast tumours that highly express WEE1 suggesting that WEE1 could be a novel therapeutic target in breast cancer. In conclusion, this strategy represents a novel and effective strategy for the identification of functionally important therapeutic targets in cancer.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Netherlands 1 <1%
Germany 1 <1%
China 1 <1%
United Kingdom 1 <1%
Unknown 95 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 35%
Student > Ph. D. Student 18 17%
Student > Master 9 9%
Student > Bachelor 8 8%
Professor > Associate Professor 8 8%
Other 15 15%
Unknown 9 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 45%
Biochemistry, Genetics and Molecular Biology 22 21%
Medicine and Dentistry 17 17%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Chemistry 2 2%
Other 3 3%
Unknown 11 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 07 December 2020.
All research outputs
#1,984,450
of 22,743,667 outputs
Outputs from PLOS ONE
#25,502
of 194,093 outputs
Outputs of similar age
#6,191
of 93,510 outputs
Outputs of similar age from PLOS ONE
#88
of 521 outputs
Altmetric has tracked 22,743,667 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 194,093 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has done well, scoring higher than 86% 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 93,510 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 93% of its contemporaries.
We're also able to compare this research output to 521 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.