This technology is a single-cell-resolution spatiotemporal database of graft-versus-host disease (GVHD) patients from allogeneic hematopoietic stem cell transplantation recipients, along with a multi-omics computational toolkit for its analysis.
Acute graft-versus-host disease (GVHD) remains a leading cause of morbidity and mortality after allogeneic hematopoietic cell transplantation despite current prophylactic strategies. Existing clinical and laboratory approaches do not enable prospective identification or longitudinal tracking of the specific donor T cell clones that drive tissue damage, nor do they provide sufficient resolution to define their functional states or tissue interactions in patients. As a result, clinicians lack reliable biomarkers to predict disease onset, monitor progression, or tailor interventions, which contributes to high mortality and treatment-related toxicity. Addressing these limitations is essential to improve patient outcomes and to advance a broader understanding of human T cell-mediated pathology across immune-driven diseases.
This technology is a multimodal toolkit that enables high-resolution spatiotemporal analysis of human T cell responses in patients with clinical annotations. It combines pre-transplant identification of alloreactive T cells with longitudinal tracking and single-cell profiling, integrating T cell receptor (TCR) sequencing, transcriptional phenotyping, and spatial mapping within affected tissues. Computational modeling enables the identification of pathogenic clones, the characterization of their biophysical and transcriptional features, and the analysis of clonal dynamics over time. By preserving tissue architecture and incorporating spatial transcriptomics, this technology captures localized immune-tissue interactions, revealing how specific T cell populations expand, differentiate, and contribute to tissue injury.
Patent Pending
IR CU25424
Licensing Contact: Joan Martinez
