Encoding functional edges in graphs to model spatially varying relationships in the tumor microenvironment
Ashley Tsang·Arvind Rao·S. R. Anantha Krishnan·Sagnik Bhadury·Reva Kulkarni·Marina Pasca di Magliano·Timothy L. Frankel
Comprehensive characterization of the tumor microenvironment (TME) is essential for understanding cancer progression and developing effective, patient-specific therapies. Spatial context of the TME is particularly important, and exists across multiple scales-from the molecular to cellular to tissue levels. However, current methods are modality-specific and lack flexibility in effectively modeling the TME. We introduce SPIFEE, a flexible graph deep learning framework designed to model the TME and