This research aims to develop WSI-based deep learning models to proxy spatial expression profiling. Associating these digital expression profiles with clinical outcome in the context of prostate cancer and head and neck cancer will enable to identify spatial interactions between tumor cells and the tumor microenvironment with prognostic and predictive value, without the actual use of sequencing data.