↓ Skip to main content

The expression pattern of matrix-producing tumor stroma is of prognostic importance in breast cancer

Overview of attention for article published in BMC Cancer, November 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
13 X users

Citations

dimensions_citation
56 Dimensions

Readers on

mendeley
33 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The expression pattern of matrix-producing tumor stroma is of prognostic importance in breast cancer
Published in
BMC Cancer, November 2016
DOI 10.1186/s12885-016-2864-2
Pubmed ID
Authors

Sofia Winslow, Kajsa Ericson Lindquist, Anders Edsjö, Christer Larsson

Abstract

There are several indications that the composition of the tumor stroma can contribute to the malignancy of a tumor. Here we utilized expression data sets to identify metagenes that may serve as surrogate marker for the extent of matrix production and vascularization of a tumor and to characterize prognostic molecular components of the stroma. TCGA data sets from six cancer forms, two breast cancer microarray sets and one mRNA data set of xenografted tumors were downloaded. Using the mean correlation as distance measure compact clusters with genes representing extracellular matrix production (ECM metagene) and vascularization (endothelial metagene) were defined. Explorative Cox modeling was used to identify prognostic stromal gene sets. Clustering of stromal genes in six cancer data sets resulted in metagenes, each containing three genes, representing matrix production and vascularization. The ECM metagene was associated with poor prognosis in renal clear cell carcinoma and in lung adenocarcinoma but not in other cancers investigated. Explorative Cox modeling using gene pairs identified gene sets that in multivariate models were prognostic in breast cancer. This was validated in two microarray sets. Two notable genes are TCF4 and P4HA3 which were included in the sets associated with positive and negative prognosis, respectively. Data from laser-microdissected tumors, a xenografted tumor data set and from correlation analyses demonstrate the stroma specificity of the genes. It is possible to construct ECM and endothelial metagenes common for several cancer forms. The molecular composition of matrix-producing cells, rather than the extent of matrix production seem to be important for breast cancer prognosis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 3%
Germany 1 3%
Unknown 31 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 15%
Student > Ph. D. Student 5 15%
Student > Master 2 6%
Student > Doctoral Student 1 3%
Student > Bachelor 1 3%
Other 4 12%
Unknown 15 45%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 33%
Agricultural and Biological Sciences 4 12%
Medicine and Dentistry 2 6%
Mathematics 1 3%
Engineering 1 3%
Other 1 3%
Unknown 13 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 14 November 2016.
All research outputs
#4,696,521
of 23,505,064 outputs
Outputs from BMC Cancer
#1,184
of 8,494 outputs
Outputs of similar age
#77,027
of 313,109 outputs
Outputs of similar age from BMC Cancer
#17
of 119 outputs
Altmetric has tracked 23,505,064 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,494 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 85% 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 313,109 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 75% of its contemporaries.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.