Title |
Phase-specific signatures of wound fibroblasts and matrix patterns define cancer-associated fibroblast subtypes
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Published in |
Matrix Biology, March 2023
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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
Geographical breakdown
Country | Count | As % |
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Switzerland | 4 | 31% |
United States | 3 | 23% |
Germany | 1 | 8% |
Unknown | 5 | 38% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 7 | 54% |
Scientists | 4 | 31% |
Practitioners (doctors, other healthcare professionals) | 2 | 15% |
Mendeley readers
Geographical breakdown
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Unknown | 26 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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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% |