Yale School of Medicine researchers have published two significant studies advancing the understanding and potential treatment of fibrotic diseases — often autoimmune conditions marked by excessive tissue scarring that currently have no effective therapies. Both studies were supported in part by the Colton Center for Autoimmunity at Yale.
The first study, published in Blood, describes the development of a human anti-epiregulin monoclonal antibody that has shown promise in reversing fibrosis in animal models and patient skin biopsies. Epiregulin is a signaling molecule that activates the epidermal growth factor receptor (EGFR), which when overactivated drives the runaway scar tissue formation characteristic of fibrotic diseases. The team tested their antibody in models of graft-versus-host disease — a condition in which donor immune cells attack the body following stem cell or bone marrow transplants — and found it significantly reduced fibrosis biomarkers. Future studies will test the therapy in lupus and hidradenitis suppurativa.
The second study, published in Nature Communications, identified a previously unknown signaling pathway — EGFR activating STAT1 independently of the JAK pathway — that appears to be specifically required for the onset of fibrosis. This finding helps explain why current JAK inhibitor therapies, which are effective for non-fibrotic skin diseases like psoriasis and atopic dermatitis, have limited efficacy against fibrotic conditions. Crucially, this pathway is only activated under conditions of injury or inflammation, suggesting a favorable safety profile for future therapies targeting it.
Both studies were led by Professor Richard Flavell and Dr. Ian Odell of Yale School of Medicine.
Featured Experts

Richard Flavell, PhD, FRS
Colton Consortium Member
Sterling Professor, Department of Immunobiology, Yale School of Medicine, Yale University
Ian Odell, MD, PhD, FAAD
Colton Consortium Member
Assistant Professor, Department of Dermatology, Yale School of Medicine, Yale UniversityFeatured Projects

Developing a Multi-parameter Prognostic Prediction Model for Disability Ranks and Progression of Patients with Multiple Sclerosis at the Early Stages of the Disease
Integrating clinical, imaging, and biological data from large real-world MS cohorts, this project builds a machine learning model to predict disability progression early and enable personalized treatment decisions.

Immunotherapy-Related Adverse Effects as Models for Fragile Tolerance in Humans
Using cancer patients experiencing immunotherapy-triggered autoimmunity as a unique human model, this project uncovers the molecular and epigenetic mechanisms by which self-reactive T cells escape immune tolerance.
Featured Publications
EGFR-STAT1 pathway drives fibrosis initiation in fibroinflammatory skin diseases
Sclerotic GVHD and scleroderma share dysregulated gene expression that is ameliorated by EREG therapeutic antibody
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