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Usage Information

CD47 prevents the elimination of diseased fibroblasts in scleroderma
Tristan Lerbs, Lu Cui, Megan E. King, Tim Chai, Claire Muscat, Lorinda Chung, Ryanne Brown, Kerri Rieger, Tyler Shibata, Gerlinde Wernig
Tristan Lerbs, Lu Cui, Megan E. King, Tim Chai, Claire Muscat, Lorinda Chung, Ryanne Brown, Kerri Rieger, Tyler Shibata, Gerlinde Wernig
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Research Article Dermatology

CD47 prevents the elimination of diseased fibroblasts in scleroderma

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Abstract

Scleroderma is a devastating fibrotic autoimmune disease. Current treatments are partly effective in preventing disease progression but do not remove fibrotic tissue. Here, we evaluated whether scleroderma fibroblasts take advantage of the “don’t-eat-me-signal” CD47 and whether blocking CD47 enables the body’s immune system to get rid of diseased fibroblasts. To test this approach, we used a Jun-inducible scleroderma model. We first demonstrated in patient samples that scleroderma upregulated transcription factor JUN and increased promoter accessibilities of both JUN and CD47. Next, we established our scleroderma model, demonstrating that Jun mediated skin fibrosis through the hedgehog-dependent expansion of CD26+Sca1– fibroblasts in mice. In a niche-independent adaptive transfer model, JUN steered graft survival and conferred increased self-renewal to fibroblasts. In vivo, JUN enhanced the expression of CD47, and inhibiting CD47 eliminated an ectopic fibroblast graft and increased in vitro phagocytosis. In the syngeneic mouse, depleting macrophages ameliorated skin fibrosis. Therapeutically, combined CD47 and IL-6 blockade reversed skin fibrosis in mice and led to the rapid elimination of ectopically transplanted scleroderma cells. Altogether, our study demonstrates the efficiency of combining different immunotherapies in treating scleroderma and provides a rationale for combining CD47 and IL-6 inhibition in clinical trials.

Authors

Tristan Lerbs, Lu Cui, Megan E. King, Tim Chai, Claire Muscat, Lorinda Chung, Ryanne Brown, Kerri Rieger, Tyler Shibata, Gerlinde Wernig

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Usage data is cumulative from June 2025 through June 2026.

Usage JCI PMC
Text version 1,870 253
PDF 395 78
Figure 907 0
Supplemental data 125 16
Citation downloads 258 0
Totals 3,555 347
Total Views 3,902
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Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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