With a computational separation of hundreds of features from the whole slide images of histological tissue sections and a random forest based machine learning approach, we find a combination of tissue features able to distinguish between 1) normal spatial heterogeneity in the prostate tissue, 2) early Pten+/− or Hi-Myc-induced neoplasms from normal tissue, and 3) the two types of neoplasms from each other. The gene discussed is PTEN; the disease is neoplasm.