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An ecological measure of immune-cancer colocalization as a prognostic factor for breast cancer

Overview of attention for article published in Breast Cancer Research, September 2015
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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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
1 blog
twitter
5 tweeters

Citations

dimensions_citation
46 Dimensions

Readers on

mendeley
97 Mendeley
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Title
An ecological measure of immune-cancer colocalization as a prognostic factor for breast cancer
Published in
Breast Cancer Research, September 2015
DOI 10.1186/s13058-015-0638-4
Pubmed ID
Authors

Carlo C. Maley, Konrad Koelble, Rachael Natrajan, Athena Aktipis, Yinyin Yuan

Abstract

Abundance of immune cells has been shown to have prognostic and predictive significance in many tumor types. Beyond abundance, the spatial organization of immune cells in relation to cancer cells may also have significant functional and clinical implications. However there is a lack of systematic methods to quantify spatial associations between immune and cancer cells. We applied ecological measures of species interactions to digital pathology images for investigating the spatial associations of immune and cancer cells in breast cancer. We used the Morisita-Horn similarity index, an ecological measure of community structure and predator-prey interactions, to quantify the extent to which cancer cells and immune cells colocalize in whole-tumor histology sections. We related this index to disease-specific survival of 486 women with breast cancer and validated our findings in a set of 516 patients from different hospitals. Colocalization of immune cells with cancer cells was significantly associated with a disease-specific survival benefit for all breast cancers combined. In HER2-positive subtypes, the prognostic value of immune-cancer cell colocalization was highly significant and exceeded those of known clinical variables. Furthermore, colocalization was a significant predictive factor for long-term outcome following chemotherapy and radiotherapy in HER2 and Luminal A subtypes, independent of and stronger than all known clinical variables. Our study demonstrates how ecological methods applied to the tumor microenvironment using routine histology can provide reproducible, quantitative biomarkers for identifying high-risk breast cancer patients. We found that the clinical value of immune-cancer interaction patterns is highly subtype-specific but substantial and independent to known clinicopathologic variables that mostly focused on cancer itself. Our approach can be developed into computer-assisted prediction based on histology samples that are already routinely collected.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Unknown 95 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 24%
Researcher 16 16%
Student > Master 15 15%
Student > Bachelor 7 7%
Student > Doctoral Student 6 6%
Other 12 12%
Unknown 18 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 21 22%
Agricultural and Biological Sciences 17 18%
Medicine and Dentistry 16 16%
Computer Science 5 5%
Engineering 4 4%
Other 14 14%
Unknown 20 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 17 October 2020.
All research outputs
#2,335,460
of 19,157,212 outputs
Outputs from Breast Cancer Research
#284
of 1,776 outputs
Outputs of similar age
#37,720
of 259,495 outputs
Outputs of similar age from Breast Cancer Research
#2
of 13 outputs
Altmetric has tracked 19,157,212 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,776 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one has done well, scoring higher than 84% 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 259,495 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 85% of its contemporaries.
We're also able to compare this research output to 13 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 92% of its contemporaries.