The spatial organisation of Cellular protein expression profiles within tissues determines cellular function and are key to understanding disease pathology. To define molecular phenotypes in the spatial context of tissue, there is a need for unbiased, quantitative technology capable of mapping proteomes within tissue structures. Here, we present a workflow for spatially resolved, quantitative proteomics of tissue that generates maps of protein expression across a tissue slice derived from a human atypical teratoid-rhabdoid tumour (AT/RT). We employ spatially-aware statistical methods that do not require prior knowledge of the fine tissue structure to detect proteins and pathways with varying spatial abundance patterns. We identified PYGL, ASPH and CD45 as spatial markers for tumour boundary and reveal immune response driven, spatially organized protein networks of the extracellular tumour matrix. Overall, this work informs on methods for spatially resolved deep proteo-phenotyping of tissue heterogeneity, which will push the boundaries of understanding tissue biology and pathology at the molecular level.