Spatial cell graph analysis reveals skin tissue organization characteristic for cutaneous T cell lymphoma

Abstract

Cutaneous T cell lymphomas (CTCLs) are non-Hodgkin lymphomas caused by malignant T cells which migrate to the skin. The cancerous T cells lead to rash-like lesions which can be difficult to distinguish from inflammatory skin conditions like atopic dermatitis (AD) and psoriasis (PSO). To characterize CTCL in comparison to these differential diagnoses, we carried out multi-antigen imaging on 69 skin tissue samples (21 CTCL, 23 AD, 25 PSO). The resulting spatially resolved protein abundance maps were then analyzed via scoring functions to quantify heterogeneity of the individual cells neighborhoods within spatial graphs inferred from the cells positions in the tissue samples (available as a Python package at https://github.com/bionetslab/SHouT). Our analyses reveal several characteristic patterns of skin tissue organization in CTCL, including a combination of increased local entropy and egophily as characteristic properties of spatial T cell neighborhoods in CTCL as compared to AD and PSO. These results could not only pave the way for high-precision diagnosis of CTCL, but may also facilitate further insights into cellular disease mechanisms.