Controlling cancer requires comprehensive understanding of the molecular, cellular, and organizational properties of tumor tissue. While clinical pathology has served as a gold standard for cancer diagnosis for over a century, the field continues to largely rely on visual inspection of sectioned and stained tissue under the microscope by expert pathologists. This work integrates deep learning systems for histopathological image analysis to quantitatively and qualitatively evaluate spatial characteristics of tumor biology to better guide clinical diagnosis and treatment of cancer.