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Pan-cancer analysis of TCGA data reveals notable signaling pathways

Overview of attention for article published in BMC Cancer, July 2015
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

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19 X users
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2 patents

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Title
Pan-cancer analysis of TCGA data reveals notable signaling pathways
Published in
BMC Cancer, July 2015
DOI 10.1186/s12885-015-1484-6
Pubmed ID
Authors

Richard Neapolitan, Curt M. Horvath, Xia Jiang

Abstract

A signal transduction pathway (STP) is a network of intercellular information flow initiated when extracellular signaling molecules bind to cell-surface receptors. Many aberrant STPs have been associated with various cancers. To develop optimal treatments for cancer patients, it is important to discover which STPs are implicated in a cancer or cancer-subtype. The Cancer Genome Atlas (TCGA) makes available gene expression level data on cases and controls in ten different types of cancer including breast cancer, colon adenocarcinoma, glioblastoma, kidney renal papillary cell carcinoma, low grade glioma, lung adenocarcinoma, lung squamous cell carcinoma, ovarian carcinoma, rectum adenocarcinoma, and uterine corpus endometriod carcinoma. Signaling Pathway Impact Analysis (SPIA) is a software package that analyzes gene expression data to identify whether a pathway is relevant in a given condition. We present the results of a study that uses SPIA to investigate all 157 signaling pathways in the KEGG PATHWAY database. We analyzed each of the ten cancer types mentioned above separately, and we perform a pan-cancer analysis by grouping the data for all the cancer types. In each analysis several pathways were found to be markedly more significant than all the other pathways. We call them notable. Research has already established a connection between many of these pathways and the corresponding cancer type. However, some of our discovered pathways appear to be new findings. Altogether there were 37 notable findings in the separate analyses, 26 of them occurred in 7 pathways. These 7 pathways included the 4 notable pathways discovered in the pan-cancer analysis. So, our results suggest that these 7 pathways account for much of the mechanisms of cancer. Furthermore, by looking at the overlap among pathways, we identified possible regions on the pathways where the aberrant activity is occurring. We obtained 37 notable findings concerning 18 pathways. Some of them appear to be new discoveries. Furthermore, we identified regions on pathways where the aberrant activity might be occurring. We conclude that our results will prove to be valuable to cancer researchers because they provide many opportunities for laboratory and clinical follow-up studies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
France 1 1%
Norway 1 1%
United Kingdom 1 1%
Spain 1 1%
Unknown 74 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 25%
Student > Ph. D. Student 12 15%
Other 9 11%
Student > Doctoral Student 7 9%
Student > Bachelor 7 9%
Other 17 21%
Unknown 8 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 25%
Biochemistry, Genetics and Molecular Biology 19 24%
Medicine and Dentistry 15 19%
Computer Science 6 8%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Other 5 6%
Unknown 13 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 24 January 2019.
All research outputs
#1,930,732
of 23,344,526 outputs
Outputs from BMC Cancer
#315
of 8,449 outputs
Outputs of similar age
#25,792
of 263,803 outputs
Outputs of similar age from BMC Cancer
#6
of 152 outputs
Altmetric has tracked 23,344,526 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 8,449 research outputs from this source. They receive a mean Attention Score of 4.4. 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 263,803 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 90% of its contemporaries.
We're also able to compare this research output to 152 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 96% of its contemporaries.