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Phase-specific signatures of wound fibroblasts and matrix patterns define cancer-associated fibroblast subtypes

Overview of attention for article published in Matrix Biology, March 2023
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 1,114)
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
2 news outlets
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13 X users

Citations

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5 Dimensions

Readers on

mendeley
26 Mendeley
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Title
Phase-specific signatures of wound fibroblasts and matrix patterns define cancer-associated fibroblast subtypes
Published in
Matrix Biology, March 2023
DOI 10.1016/j.matbio.2023.03.003
Pubmed ID
Authors

Mateusz S Wietecha, David Lauenstein, Michael Cangkrama, Sybille Seiler, Juyoung Jin, Andreas Goppelt, Manfred Claassen, Mitchell P Levesque, Reinhard Dummer, Sabine Werner

Abstract

Healing wounds and cancers present remarkable cellular and molecular parallels, but the specific roles of the healing phases are largely unknown. We developed a bioinformatics pipeline to identify genes and pathways that define distinct phases across the time-course of healing. Their comparison to cancer transcriptomes revealed that a resolution phase wound signature is associated with increased severity in skin cancer and enriches for extracellular matrix-related pathways. Comparisons of transcriptomes of early- and late-phase wound fibroblasts vs skin cancer-associated fibroblasts (CAFs) identified an "early wound" CAF subtype, which localizes to the inner tumor stroma and expresses collagen-related genes that are controlled by the RUNX2 transcription factor. A "late wound" CAF subtype localizes to the outer tumor stroma and expresses elastin-related genes. Matrix imaging of primary melanoma tissue microarrays validated these matrix signatures and identified collagen- vs elastin-rich niches within the tumor microenvironment, whose spatial organization predicts survival and recurrence. These results identify wound-regulated genes and matrix patterns with prognostic potential in skin cancer.

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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 15%
Student > Ph. D. Student 3 12%
Researcher 3 12%
Unspecified 2 8%
Student > Master 2 8%
Other 2 8%
Unknown 10 38%
Readers by discipline Count As %
Medicine and Dentistry 6 23%
Biochemistry, Genetics and Molecular Biology 3 12%
Unspecified 2 8%
Mathematics 1 4%
Agricultural and Biological Sciences 1 4%
Other 3 12%
Unknown 10 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 29 March 2023.
All research outputs
#1,429,277
of 25,394,764 outputs
Outputs from Matrix Biology
#16
of 1,114 outputs
Outputs of similar age
#29,868
of 424,461 outputs
Outputs of similar age from Matrix Biology
#1
of 12 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,114 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 98% 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 424,461 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 92% of its contemporaries.
We're also able to compare this research output to 12 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 91% of its contemporaries.