Yale researchers have discovered that a lupus-related antibody can penetrate tumor cells, trigger an immune response, and significantly extend survival in brain tumor models — a finding with major implications for treating cancers that have long resisted immunotherapy. The study, published in Science Signaling on March 25, 2025, was supported in part by the Colton Center for Autoimmunity at Yale.
The antibody in question is Deoxymab, a re-engineered version of an anti-DNA antibody originally found in lupus patients. Unlike most antibodies, Deoxymab can cross live cell membranes and travel directly into the nucleus — a unique property that researchers have now found can be turned to powerful effect in cancer treatment.
The key insight involves so-called “cold” tumors — immune deserts like glioblastoma that contain few T cells and respond poorly to existing immunotherapies. When Deoxymab enters the cytoplasm of these tumor cells and binds to RNA, it triggers an internal alarm system that recognizes foreign material and activates an immune response. In pre-clinical brain tumor models, this mechanism alone — without radiation or chemotherapy — significantly prolonged survival.
The researchers also found that Deoxymab can deliver functional RNA directly into tumor, brain, and muscle tissue without the need for a viral vector, pointing to potential applications in non-viral gene therapy.
The study was led by Dr. James Hansen and Dr. Xiaoyong Chen of Yale School of Medicine, with contributions from researchers at UCLA and the Veterans Affairs Greater Los Angeles Healthcare System.
Featured Experts

Katsuo Kurabayashi, PhD
Colton Consortium Member
Department Chair, Mechanical and Aerospace Engineering, NYU Tandon School of Engineering
Carla R. Nowosad, PhD
Colton Consortium Member
Assistant Professor, Department of Pathology, NYU Grossman School of Medicine / NYU Langone Health
Jun Wang, PhD
Colton Consortium Member
Associate Professor, Department of Pathology, NYU Grossman School of Medicine / NYU Langone HealthFeatured Projects

Novel Tools to Track and Manipulate Immune Cells in Autoimmunity Models
Developing a cell-labeling tool to map immune cell interactions in living tissue, this project identifies the drivers of skin-resident T cell persistence in psoriasis and potential targets for disease prevention.

Early Detection and Diagnosis of Autoimmune Diseases Using Foundation AI Models
Applying self-supervised AI to multi-modal electronic health records — integrating clinical notes, labs, and imaging — this project builds scalable diagnostic models to detect autoimmune diseases earlier and more precisely.
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