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- W4383743072 abstract "To understand the clinical significance of the tumor microenvironment (TME), it is essential to study the interactions between malignant and non-malignant cells in clinical specimens. Here, we established a computational framework for a multiplex imaging system to comprehensively characterize spatial contexts of the TME at multiple scales, including close and long-distance spatial interactions between cell type pairs. We applied this framework to a total of 1,393 multiplex imaging data newly generated from 88 primary central nervous system lymphomas with complete follow-up data and identified significant prognostic subgroups mainly shaped by the spatial context. A supervised analysis confirmed a significant contribution of spatial context in predicting patient survival. In particular, we found an opposite prognostic value of macrophage infiltration depending on its proximity to specific cell types. Altogether, we provide a comprehensive framework to analyze spatial cellular interaction that can be broadly applied to other technologies and tumor contexts." @default.
- W4383743072 created "2023-07-11" @default.
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- W4383743072 date "2023-08-01" @default.
- W4383743072 modified "2023-10-17" @default.
- W4383743072 title "Multi-scale spatial modeling of immune cell distributions enables survival prediction in primary central nervous system lymphoma" @default.
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- W4383743072 doi "https://doi.org/10.1016/j.isci.2023.107331" @default.
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