This heterogeneity often manifests uncontrollably in diseased states at the molecular (genomic and transcriptomic) and the phenotypic level, making progression difficult to predict. Specifically in cancer, spatial cellular heterogeneity has been ascribed to drive tumor development, progression, and treatment resistance. [1][2][3] The last decades have seen tremendous growth in understanding the effect of driving agents (genetic, epigenetic, or external factors) on tumor progression and evolution, with single cell studies [4][5][6] providing a considerable leap in the understanding of tumor heterogeneity. These drivers however manifest at different scales, where a few cells to a whole subpopulation and its microenvironment can act in concert to drive progression, making the context of their spatial location critical in defining their interactions. Context-aware analysis requires an integrated strategy for high spatial resolution recovery of user-defined microscale areas from tissue sections for a) customizable molecular analysis, and b) high resolution molecular profiling of biomolecules that enable biomarker discovery. Current approaches in cancer research utilize analysis of monoclonal cell cultures, tumor models and bulk biopsies, to elucidate roles of biomolecules in cancer progression. These target biomarkers are then used by medical practitioners to execute tests in order to provide a prognosis for disease progression, diagnosis for classification, and prediction of the classified tumor's response to therapy. These processes, however, contain sparse or only rudimentary spatial information and there is a growing need within the research community to elucidate the impact of spatial heterogeneity for clinical evaluation. This necessitates the development of methods for spatial genomic and transcriptomic detection, which can be easily made accessible to the broader cancer research community.Current methods to characterize tumor tissues spatially are mainly based on in situ techniques, visually providing a spatial map of a biomolecule of interest. Traditional in situ approaches (immunohistochemistry, DNA fluorescence in situ