Spatial cell graph analysis reveals skin tissue organization characteristic for cutaneous T cell lymphoma
Suryadipto Sarkar1, Anna Möller1, Anne Hartebrodt1
1Biomedical Network Science Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
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Cutaneous T-cell lymphomas (CTCLs) are non-Hodgkin lymphomas caused by malignant T cells which migrate to the skin and 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 protein abundance maps were then analyzed via scoring functions to quantify the heterogeneity of the individual cells' neighborhoods within spatial graphs inferred from the cells' positions in the tissue samples. Our analyses reveal characteristic patterns of skin tissue organization in CTCL as compared to AD and PSO, including a combination of increased local entropy and egophily in T-cell neighborhoods. These results could not only pave the way for high-precision diagnosis of CTCL, but may also facilitate further insights into cellular disease mechanisms.
