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Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer

Overview of attention for article published in EURASIP Journal on Bioinformatics & Systems Biology, February 2016
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Title
Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer
Published in
EURASIP Journal on Bioinformatics & Systems Biology, February 2016
DOI 10.1186/s13637-015-0034-5
Pubmed ID
Authors

Hiroko K. Solvang, Arnoldo Frigessi, Fateme Kaveh, Margit L. H. Riis, Torben Lüders, Ida R. K. Bukholm, Vessela N. Kristensen, Bettina K. Andreassen

Abstract

Tumor size, as indicated by the T-category, is known as a strong prognostic indicator for breast cancer. It is common practice to distinguish the T1 and T2 groups at a tumor size of 2.0 cm. We investigated the 2.0-cm rule from a new point of view. Here, we try to find the optimal threshold based on the differences between the gene expression profiles of the T1 and T2 groups (as defined by the threshold). We developed a numerical algorithm to measure the overall differential gene expression between patients with smaller tumors and those with larger tumors among multiple expression datasets from different studies. We confirmed the performance of the proposed algorithm by a simulation study and then applied it to three different studies conducted at two Norwegian hospitals. We found that the maximum difference in gene expression is obtained at a threshold of 2.2-2.4 cm, and we confirmed that the optimum threshold was over 2.0 cm, as indicated by a validation study using five publicly available expression datasets. Furthermore, we observed a significant differentiation between the two threshold groups in terms of time to local recurrence for the Norwegian datasets. In addition, we performed an associated network and canonical pathway analyses for the genes differentially expressed between tumors below and above the given thresholds, 2.0 and 2.4 cm, using the Norwegian datasets. The associated network function illustrated a cellular assembly of the genes for the 2.0-cm threshold: an energy production for the 2.4-cm threshold and an enrichment in lipid metabolism based on the genes in the intersection for the 2.0- and 2.4-cm thresholds.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 33%
Student > Master 2 17%
Other 1 8%
Professor 1 8%
Researcher 1 8%
Other 3 25%
Readers by discipline Count As %
Medicine and Dentistry 6 50%
Computer Science 2 17%
Agricultural and Biological Sciences 2 17%
Biochemistry, Genetics and Molecular Biology 1 8%
Mathematics 1 8%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 26 March 2016.
All research outputs
#9,973,304
of 12,457,990 outputs
Outputs from EURASIP Journal on Bioinformatics & Systems Biology
#32
of 51 outputs
Outputs of similar age
#189,117
of 269,576 outputs
Outputs of similar age from EURASIP Journal on Bioinformatics & Systems Biology
#2
of 2 outputs
Altmetric has tracked 12,457,990 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 51 research outputs from this source. They receive a mean Attention Score of 1.7. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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